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## **Meet the editor**

Dr Agrawal completed his neurosurgery training from National Institute of Mental Health and Neurosciences, Bangalore (India) in the year 2003. He is extremely enthusiastic, and result oriented professional with over 11 years of rich experience in Research & Development & Teaching & Mentoring in the field of neurosurgery. He has attended and participated in many internation-

al & national level symposiums & conferences and delivered lectures on vivid topics. He has published more than 300 articles in the medical field covering various topics in various national and international journals. He is the Editor-in-Chief of Journal of Neurosciences in Rural Practice (www. ruralneuropractice.com). Presently he is Professor and head, Department of Neurosurgery, MM Institute of Medical Sciences and Research, Mullana (Ambala), India and promoting the concept of Neurosciences in Rural Practice through the Journal of Neurosciences in Rural Practice.

Contents

**Preface IX** 

John T. Weber

**Part 1 Understanding Pathogenesis 1** 

Chapter 1 **Current Understanding and Experimental** 

Chapter 2 **Traumatic Brain Injury and Inflammation:** 

Chapter 3 **Shared Genetic Effects among Measures** 

and Sharon L. R. Kardia

Chapter 5 **The Effects of Melatonin on Brain** 

Bronwen Connor

Aysegul Bayir

**Approaches to the Study of Repetitive Brain Injury 3** 

**Emerging Role of Innate and Adaptive Immunity 23**  Efthimios Dardiotis, Vaios Karanikas, Konstantinos Paterakis,

Jennifer A. Smith, Thomas H. Mosley, Jr., Stephen T. Turner

Kostas Fountas and Georgios M. Hadjigeorgiou

**of Cognitive Function and Leukoaraiosis 39** 

Chapter 4 **Compensatory Neurogenesis in the Injured Adult Brain 63** 

**Injury in Acute Organophosphate Toxicity 87** 

**and Immediate Outcome in Head Injury Patients 139**  Arulselvi Subramanian, Deepak Agrawal, Ravindra Mohan Pandey,

Chapter 6 **Alzheimer's Factors in Ischemic Brain Injury 97**  Ryszard Pluta and Mirosław Jabłoński

Mohita Nimiya and Venencia Albert

Chapter 8 **Animal Models of Retinal Ischemia 153**  Gillipsie Minhas and Akshay Anand

Chapter 7 **The Leukocyte Count, Immature Granulocyte Count** 

### Contents

#### **Preface** XIII


#### X Contents

#### **Part 2 Cerebral Blood Flow and Metabolism 175**

	- **Part 3 Investigative Approaches and Monitoring 189**

Contents VII

**Part 5 Management Approaches 339** 

Stanislaw P. A. Stawicki

Ayotunde Adeagbo

Rivelilson Mendes de Freitas

Chapter 20 **Antioxidant Treatments:**

Chapter 21 **Growth Hormone and** 

Chapter 24 **The Role of Decompressive** 

Chapter 17 **Competing Priorities in the Brain Injured** 

Chapter 18 **Traumatic Brain Injury – Acute Care 355** Angela N. Hays and Abhay K. Varma

**Patient: Dealing with the Unexpected 341**

Chapter 19 **Clinical Neuroprotection Against Tissue Hypoxia During**

**Effect on Behaviour, Histopathological and Oxidative Stress in Epilepsy Model 393**

**Kynesitherapy for Brain Injury Recovery 417**

Chapter 22 **Novel Strategies for Discovery, Validation and FDA Approval of Biomarkers for Acute and Chronic Brain Injury 455**  S. Mondello, F. H. Kobeissy, A. Jeromin, J. D. Guingab-Cagmat,

> **Patients Suffering Severe Closed Head Injuries 487** Haralampos Gatos, Eftychia Z. Kapsalaki, Apostolos Komnos

**in the Metabolic Recovery of Concussed Brain 501**  Giuseppe Lazzarino, Roberto Vagnozzi, Stefano Signoretti, Massimo Manara, Roberto Floris, Angela M. Amorini, Andrea Ludovici, Simone Marziali, Tracy K. McIntosh and Barbara Tavazzi

Konstantinos N. Paterakis and Kostas N. Fountas

Chapter 25 **The Importance of Restriction from Physical Activity** 

Z. Zhiqun, J. Streeter, R. L. Hayes and K. K. Wang

Chapter 23 **Decompressive Craniectomy: Surgical Indications, Clinical Considerations and Rationale 475** 

**Craniectomy in the Management of** 

Dare Adewumi and Austin Colohan

Jesús Devesa, Pablo Devesa, Pedro Reimunde and Víctor Arce

**Brain Injuries; The Challenges and the Targets 383**  Thomas I Nathaniel, Effiong Otukonyong, Sarah Bwint, Katelin Haley, Diane Haleem, Adam Brager and

Jonathan R. Wisler, Paul R. Beery II, Steven M. Steinberg and

	- **Part 4 Protective Mechanisms and Recovery 297**

#### **Part 5 Management Approaches 339**

VI Contents

**Part 2 Cerebral Blood Flow and Metabolism 175** 

Hovhannes M. Manvelyan

Chapter 11 **Neurointensive Care Monitoring** 

Jafri Malin Abdullah

and Hui Zhao

Chapter 13 **The Experimental Technology** 

and Shengxiong Liu

and Keith St. Lawrence

Chapter 15 **Mechanisms of Neuroprotection** 

Chapter 16 **Physiological Neuroprotective** 

Chapter 12 **The Dynamic Visualization Technology** 

**on the Brain Impact Injuries 265** Zhiyong Yin, Hui Zhao, Daiqin Tao

Chapter 14 **Towards Non-Invasive Bedside Monitoring of** 

**Part 4 Protective Mechanisms and Recovery 297**

**Underlying Physical Exercise in Ischemia – Reperfusion Injury 299**  David Dornbos III and Yuchuan Ding

**Mechanisms in Natural Genetic Systems:** 

Leah Dziopa, Julia Glukhoy and Rahul Dani

**Therapeutic Clues for Hypoxia-Induced Brain Injuries 327**  Thomas I Nathaniel, Francis Umesiri, Grace Reifler, Katelin Haley,

Chapter 9 **Cerebral Blood Flow in Experimental and Clinical** 

**Part 3 Investigative Approaches and Monitoring 189** 

**for Severe Traumatic Brain Injury 213** Zamzuri Idris, Muzaimi Mustapha and

**in Brain Deceleration Injury Research 245**  Zhiyong Yin, Shengxiong Liu, Daiqin Tao

**Cerebral Blood Flow and Oxygen Metabolism in Brain-Injured Patients with Near-Infrared Spectroscopy 279**

Mamadou Diop, Jonathan T. Elliott, Ting-Yim Lee

Riikka Immonen and Nick Hayward

**Neurotrauma: Quantitative Assessment 177**

Chapter 10 **MRI Characterization of Progressive Brain Alterations After** 

**Experimental Traumatic Brain Injury: Region Specific Tissue Damage, Hemodynamic Changes and Axonal Injury 191** 


Preface

aspects of traumatic brain injuries.

especially discussed in details.

Brain injury remains one of the most difficult and challenging problems facing many researchers, clinicians and experts involved in care of these patients. The present two volume book "Brain Injury" is distinctive in its presentation and includes a wealth of updated information for professionals on the high quality research on many aspects in the field of brain injury as well as addresses the most difficult and challenging issues in the management and rehabilitation of brain injured patients. The Brain Injury - Pathogenesis, Monitoring, Recovery and Management contains 5 sections and a total 26 chapters devoted to pathogenesis of brain injury, concepts in cerebral blood flow and metabolism, investigative approaches and monitoring of brain injured, different protective mechanisms and recovery and management approach to these individuals and Book Two contains (3 sections) 12 chapters devoted to functional and endocrine aspects of brain injuries, approaches to rehabilitation of brain injured and preventive

Chapters in the book discus current understandings and experimental approaches, emerging role of innate and adaptive immunity, genetic effects among measures of cognitive function, compensatory neurogenesis in injured adult brain. Further the issues discussed include effects of melatonin and Alzheimer's factors on brain injury, lleukocyte response and immediate outcome in traumatic brain injury. Chapters 8 to 10 discuss the experimental models of ischemia, quantitative cerebral blood flow assessment and MRI characterization of progressive brain alterations after experimental traumatic brain injury. Chapters 11-14 address the issues in neurointensive care monitoring, dynamic visualization technology in brain deceleration injury research, experimental technology on the brain impact injuries and non-invasive bedside monitoring of cerebral blood flow and oxygen metabolism with near-infrared spectroscopy respectively. In Section IV protective mechanisms of neuroprotection in ischemia/reperfusion Injury and the issues of recovery have been discussed in details. Section V conservative as well operative management approaches to treat brain injury have been discussed. The role of decompressive craniectomy

I hope that collective contribution from experts in brain injury research area would be successfully conveyed to the readers and readers will find this book to be a valuable guide to further develop their understanding about brain injury. I am grateful to all of

### Preface

Brain injury remains one of the most difficult and challenging problems facing many researchers, clinicians and experts involved in care of these patients. The present two volume book "Brain Injury" is distinctive in its presentation and includes a wealth of updated information for professionals on the high quality research on many aspects in the field of brain injury as well as addresses the most difficult and challenging issues in the management and rehabilitation of brain injured patients. The Brain Injury - Pathogenesis, Monitoring, Recovery and Management contains 5 sections and a total 26 chapters devoted to pathogenesis of brain injury, concepts in cerebral blood flow and metabolism, investigative approaches and monitoring of brain injured, different protective mechanisms and recovery and management approach to these individuals and Book Two contains (3 sections) 12 chapters devoted to functional and endocrine aspects of brain injuries, approaches to rehabilitation of brain injured and preventive aspects of traumatic brain injuries.

Chapters in the book discus current understandings and experimental approaches, emerging role of innate and adaptive immunity, genetic effects among measures of cognitive function, compensatory neurogenesis in injured adult brain. Further the issues discussed include effects of melatonin and Alzheimer's factors on brain injury, lleukocyte response and immediate outcome in traumatic brain injury. Chapters 8 to 10 discuss the experimental models of ischemia, quantitative cerebral blood flow assessment and MRI characterization of progressive brain alterations after experimental traumatic brain injury. Chapters 11-14 address the issues in neurointensive care monitoring, dynamic visualization technology in brain deceleration injury research, experimental technology on the brain impact injuries and non-invasive bedside monitoring of cerebral blood flow and oxygen metabolism with near-infrared spectroscopy respectively. In Section IV protective mechanisms of neuroprotection in ischemia/reperfusion Injury and the issues of recovery have been discussed in details. Section V conservative as well operative management approaches to treat brain injury have been discussed. The role of decompressive craniectomy especially discussed in details.

I hope that collective contribution from experts in brain injury research area would be successfully conveyed to the readers and readers will find this book to be a valuable guide to further develop their understanding about brain injury. I am grateful to all of

#### XIV Preface

the authors who have contributed their tremendous expertise to the present book, my wife and daughter for their passionate support and last but not least I wish to acknowledge the outstanding support from Mr. Bojan Rafaj, Publishing Process manager, InTech Croatia who collaborated tirelessly in crafting this book.

> **Dr Amit Agrawal**  Professor of Neurosurgery MM Institute of Medical Sciences & Research Maharishi Markandeshwar University India

## **Part 1**

**Understanding Pathogenesis** 

**1** 

John T. Weber

*Canada* 

**Current Understanding and** 

*Memorial University of Newfoundland* 

**Experimental Approaches to the** 

**Study of Repetitive Brain Injury** 

Repetitive traumatic brain injury (TBI) occurs in a considerable number of individuals in the general population, such as athletes involved in contact sports (e.g. boxing, football, hockey and soccer), or child abuse victims. Repeated mild injuries, such as concussions, may cause cumulative damage to the brain and result in long-term cognitive dysfunction. The growing field of repetitive TBI research is reflected in the increased media attention given to reporting incidences of athletes suffering multiple blows to the head, and in several recent experimental studies of repeated mild TBI *in vivo*. Experimental reports generally demonstrate cellular and cognitive abnormalities after repetitive injury using rodent TBI models. In some cases, data suggests that the effects of a second mild TBI may be synergistic, rather than additive. In addition, some studies have found increases in cellular markers associated with Alzheimer's disease after repeated mild injuries, which demonstrates a direct experimental link between repetitive TBI and neurodegenerative disease. To complement the findings from humans and *in vivo* experimentation, my laboratory group has investigated the effects of repeated trauma in cultured brain cells using an *in vitro* model of stretch-induced mechanical injury. In these studies, cells exhibit cumulative damage when receiving multiple mild injuries. Interestingly, the extent of damage to the cells is dependent on the time between repeated injuries. Although direct comparisons to the clinical situation are difficult to make, these types of repetitive, low-level, mechanical stresses may be similar to insults received by certain athletes, such as boxers, or hockey and soccer players. As this field of TBI research continues to evolve and expand, it is essential that experimental models of repetitive injury replicate injuries in humans as closely as possible. For example, it is important to appropriately model concussive episodes versus even lower-level injuries (such as those that might occur during boxing matches or by heading a ball repeatedly in soccer). Suitable inter-injury intervals are also important parameters to incorporate into studies. Additionally, it is essential to design and utilize proper controls, which can be more of a challenge than experimental approaches to single mild TBI. These issues, as well as an overview of findings from repeated TBI research, are discussed in

**1. Introduction** 

this chapter.

### **Current Understanding and Experimental Approaches to the Study of Repetitive Brain Injury**

John T. Weber *Memorial University of Newfoundland Canada* 

#### **1. Introduction**

Repetitive traumatic brain injury (TBI) occurs in a considerable number of individuals in the general population, such as athletes involved in contact sports (e.g. boxing, football, hockey and soccer), or child abuse victims. Repeated mild injuries, such as concussions, may cause cumulative damage to the brain and result in long-term cognitive dysfunction. The growing field of repetitive TBI research is reflected in the increased media attention given to reporting incidences of athletes suffering multiple blows to the head, and in several recent experimental studies of repeated mild TBI *in vivo*. Experimental reports generally demonstrate cellular and cognitive abnormalities after repetitive injury using rodent TBI models. In some cases, data suggests that the effects of a second mild TBI may be synergistic, rather than additive. In addition, some studies have found increases in cellular markers associated with Alzheimer's disease after repeated mild injuries, which demonstrates a direct experimental link between repetitive TBI and neurodegenerative disease. To complement the findings from humans and *in vivo* experimentation, my laboratory group has investigated the effects of repeated trauma in cultured brain cells using an *in vitro* model of stretch-induced mechanical injury. In these studies, cells exhibit cumulative damage when receiving multiple mild injuries. Interestingly, the extent of damage to the cells is dependent on the time between repeated injuries. Although direct comparisons to the clinical situation are difficult to make, these types of repetitive, low-level, mechanical stresses may be similar to insults received by certain athletes, such as boxers, or hockey and soccer players. As this field of TBI research continues to evolve and expand, it is essential that experimental models of repetitive injury replicate injuries in humans as closely as possible. For example, it is important to appropriately model concussive episodes versus even lower-level injuries (such as those that might occur during boxing matches or by heading a ball repeatedly in soccer). Suitable inter-injury intervals are also important parameters to incorporate into studies. Additionally, it is essential to design and utilize proper controls, which can be more of a challenge than experimental approaches to single mild TBI. These issues, as well as an overview of findings from repeated TBI research, are discussed in this chapter.

Current Understanding and Experimental Approaches to the Study of Repetitive Brain Injury 5

generally display more cognitive dysfunctions than those who have had a single injury (Wall et al. 2006). An association between repetitive concussions and cognitive impairment, as well as clinical depression, has been demonstrated in professional football players in the United States (Guskiewicz et al., 2005; 2007). In Canada, the occurrence of concussion in ice hockey has been in the press substantially in recent months. The incidence of concussions in hockey appears to be on the rise not only in the National Hockey League, but also at the junior level (Ackery et al., 2009; Echlin et al., 2010). Many of these players have repeated concussions and suffer from post concussion symptoms such as memory impairment, headaches and depression (Ackery et al., 2009). As with boxers, there is evidence that repeated concussions may increase the risk of developing dementia later in life (De Beaumont et al., 2009). Therefore, it is important to understand the processes underlying the

When studying repetitive brain trauma in athletes, we can gain much information about the pathology and progress of such injuries from the injured athletes themselves, e.g. by measuring changes in cognitive and motor performance. However, these injuries are generally at a mild level, and therefore, except in rare cases when athletes die as a result of the insult, we cannot assess the changes that have actually occurred in the brain at the cellular and sub-cellular levels. In order to compile this type of information, we must turn to

When discussing experimental studies of repetitive TBI *in vivo*, this does not include studies of secondary insults, such as a mechanical insult to the head followed by a defined duration of ischemia or glutamate exposure. Repeated TBI experimentation consists of an initial mechanical injury to the head followed by another mechanical insult to the head of the same or different degree. Based on these criteria, there were very few of these types of experiments conducted before the year 2000, with only a handful of repetitive injury studies being published (Kanayama et al., 1996; Olsson et al., 1976; Weitbrecht & Noetzel, 1976). Several additional *in vivo* studies of repeated injuries in rodents have now been conducted over the past decade (Allen et al., 2000; Conte et al., 2004; Creeley et al., 2004; DeFord et al., 2002; Friess et al., 2009; Huh et al., 2007; Laurer et al., 2001; Longhi et al., 2005; Raghupathi et al., 2004; Shitaka et al., 2011; Uryu et al., 2002; Yoshiyama et al., 2005). All of these repeated mild injury studies were conducted using rodent models of TBI with the exception of the studies by Friess et al (2009) and Raghupathi et al (2004), which used a pediatric model of

Repetitive TBI generally occurs at a mild level, therefore experimental models have been used which are minimally invasive and do not require a craniotomy, such as weight drop models or other forms of closed-skull TBI. The models must also be administered at a level that produces minimal, or preferably, no fatality. Individuals who have suffered from a mild TBI often complain of cognitive difficulties post-injury. Therefore, repeated injury studies usually evaluate cognitive function, for example using the Morris water maze (MWM) test, as well as the extent of cellular abnormalities in the cortex and hippocampus. The hippocampus in particular has received significant attention in the study of repeated mild TBI, because it plays a critical role in certain types of learning and aspects of memory

**3. Experimental approaches to the study of repetitive TBI** 

pathology of repetitive TBI.

experimental models of TBI.

**3.1** *In vivo* **studies** 

repeated injury in pigs.

#### **2. Overview of TBI**

#### **2.1 Occurrence and impact of TBI**

Traumatic brain injury (TBI) is an insult to the brain caused by an external physical force, resulting in functional disability. Falls and motor vehicle accidents are the primary causes of TBI, while sports, assaults and gunshot wounds also contribute significantly to these types of injuries (Centre for Disease Control, 2010). TBI is one of the leading causes of death and disability worldwide, including the developing world (Reilly, 2007). In the United Kingdom, an estimated 200-300 per 100,000 people are hospitalized every year due to a TBI (McGregor & Pentland, 1997) and the incidence is reported as even higher in southern Australia and South Africa (Hillier et al., 1997; Nell & Brown, 1991). Although it has been difficult to compile reliable statistics on the prevalence and incidence of TBI in Canada (Tator, 2010), estimates in the United States suggest that between 1.4 and 1.7 million Americans sustain a TBI each year, accounting for 50,000 deaths and 80,000 to 90,000 individuals who suffer from long-term disability (Centre for Disease Control, 2010; Thurman & Guerrero, 1999). In Europe, it is estimated that at least 11.5 million individuals are suffering long-term disabilities related to a TBI (Schouten, 2007). In addition, TBI is considered to be a robust risk factor for the further development of neurodegenerative diseases, such as Alzheimer's disease (Slemmer et al., 2011), leading to additional dysfunction. Financially, the costs of TBI to society are no less distressing. Over two decades ago, an estimated 37.8 billion dollars was spent on direct costs related to hospital care in the U.S., or on indirect costs related to work loss due to disability (Max et al. 1991), and this cost has likely increased substantially. Due to the enormous impact TBI has on human health and health care systems in general throughout the world, understanding the mechanics and pathophysiology involved in TBI is essential for developing successful acute and long-term therapeutic strategies.

#### **2.2 Repetitive mild TBI**

TBI is characterized as mild, moderate or severe. Mild TBI, i.e. concussion, accounts for 70- 90% of all TBI cases and 15-20% of individuals with a mild TBI have long-term dysfunction (Ryu et al, 2009). Although individuals who have experienced a moderate or severe TBI are certainly at risk of a second insult (Saunders et al., 2009), repetitive injuries occur in a considerable portion of individuals who have experienced a mild TBI. Child abuse victims, as well as victims of spousal abuse, are often subjected to multiple injuries to the head (Roberts et al., 1990; Shannon et al., 1998). Many injuries of these types go unreported, and it is difficult to assess how many insults a patient may have suffered. Arguably, athletes represent the largest group of patients that are at risk for experiencing repeated brain injuries, especially concussions (Guskiewicz et al., 2000; Kelly, 1999; Kelly & Rosenberg, 1997; Powell and Barber-Foss, 1999). Also, in comparison to child or spousal abuse victims, there is generally better documentation of how many brain injuries an individual has sustained due to recreational or sports related activities, making this population easier to study.

The idea that multiple head injuries in athletes could lead to clinical problems has long been suggested. For example, many clinicians believe that the development of *dementia pugilistica* in professional boxers is caused by the multiple hits to the head that a boxer endures over the course of their career (Jordan, 2000). Also, studies have shown that the number of concussions is inversely related to performance on several neuropsychological tests in soccer players (Matser et al., 1999; 2001), and jockeys that have experienced multiple concussions generally display more cognitive dysfunctions than those who have had a single injury (Wall et al. 2006). An association between repetitive concussions and cognitive impairment, as well as clinical depression, has been demonstrated in professional football players in the United States (Guskiewicz et al., 2005; 2007). In Canada, the occurrence of concussion in ice hockey has been in the press substantially in recent months. The incidence of concussions in hockey appears to be on the rise not only in the National Hockey League, but also at the junior level (Ackery et al., 2009; Echlin et al., 2010). Many of these players have repeated concussions and suffer from post concussion symptoms such as memory impairment, headaches and depression (Ackery et al., 2009). As with boxers, there is evidence that repeated concussions may increase the risk of developing dementia later in life (De Beaumont et al., 2009). Therefore, it is important to understand the processes underlying the pathology of repetitive TBI.

#### **3. Experimental approaches to the study of repetitive TBI**

When studying repetitive brain trauma in athletes, we can gain much information about the pathology and progress of such injuries from the injured athletes themselves, e.g. by measuring changes in cognitive and motor performance. However, these injuries are generally at a mild level, and therefore, except in rare cases when athletes die as a result of the insult, we cannot assess the changes that have actually occurred in the brain at the cellular and sub-cellular levels. In order to compile this type of information, we must turn to experimental models of TBI.

#### **3.1** *In vivo* **studies**

4 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Traumatic brain injury (TBI) is an insult to the brain caused by an external physical force, resulting in functional disability. Falls and motor vehicle accidents are the primary causes of TBI, while sports, assaults and gunshot wounds also contribute significantly to these types of injuries (Centre for Disease Control, 2010). TBI is one of the leading causes of death and disability worldwide, including the developing world (Reilly, 2007). In the United Kingdom, an estimated 200-300 per 100,000 people are hospitalized every year due to a TBI (McGregor & Pentland, 1997) and the incidence is reported as even higher in southern Australia and South Africa (Hillier et al., 1997; Nell & Brown, 1991). Although it has been difficult to compile reliable statistics on the prevalence and incidence of TBI in Canada (Tator, 2010), estimates in the United States suggest that between 1.4 and 1.7 million Americans sustain a TBI each year, accounting for 50,000 deaths and 80,000 to 90,000 individuals who suffer from long-term disability (Centre for Disease Control, 2010; Thurman & Guerrero, 1999). In Europe, it is estimated that at least 11.5 million individuals are suffering long-term disabilities related to a TBI (Schouten, 2007). In addition, TBI is considered to be a robust risk factor for the further development of neurodegenerative diseases, such as Alzheimer's disease (Slemmer et al., 2011), leading to additional dysfunction. Financially, the costs of TBI to society are no less distressing. Over two decades ago, an estimated 37.8 billion dollars was spent on direct costs related to hospital care in the U.S., or on indirect costs related to work loss due to disability (Max et al. 1991), and this cost has likely increased substantially. Due to the enormous impact TBI has on human health and health care systems in general throughout the world, understanding the mechanics and pathophysiology involved in TBI

is essential for developing successful acute and long-term therapeutic strategies.

TBI is characterized as mild, moderate or severe. Mild TBI, i.e. concussion, accounts for 70- 90% of all TBI cases and 15-20% of individuals with a mild TBI have long-term dysfunction (Ryu et al, 2009). Although individuals who have experienced a moderate or severe TBI are certainly at risk of a second insult (Saunders et al., 2009), repetitive injuries occur in a considerable portion of individuals who have experienced a mild TBI. Child abuse victims, as well as victims of spousal abuse, are often subjected to multiple injuries to the head (Roberts et al., 1990; Shannon et al., 1998). Many injuries of these types go unreported, and it is difficult to assess how many insults a patient may have suffered. Arguably, athletes represent the largest group of patients that are at risk for experiencing repeated brain injuries, especially concussions (Guskiewicz et al., 2000; Kelly, 1999; Kelly & Rosenberg, 1997; Powell and Barber-Foss, 1999). Also, in comparison to child or spousal abuse victims, there is generally better documentation of how many brain injuries an individual has sustained due to recreational or sports related activities, making this population easier to

The idea that multiple head injuries in athletes could lead to clinical problems has long been suggested. For example, many clinicians believe that the development of *dementia pugilistica* in professional boxers is caused by the multiple hits to the head that a boxer endures over the course of their career (Jordan, 2000). Also, studies have shown that the number of concussions is inversely related to performance on several neuropsychological tests in soccer players (Matser et al., 1999; 2001), and jockeys that have experienced multiple concussions

**2. Overview of TBI** 

**2.2 Repetitive mild TBI** 

study.

**2.1 Occurrence and impact of TBI** 

When discussing experimental studies of repetitive TBI *in vivo*, this does not include studies of secondary insults, such as a mechanical insult to the head followed by a defined duration of ischemia or glutamate exposure. Repeated TBI experimentation consists of an initial mechanical injury to the head followed by another mechanical insult to the head of the same or different degree. Based on these criteria, there were very few of these types of experiments conducted before the year 2000, with only a handful of repetitive injury studies being published (Kanayama et al., 1996; Olsson et al., 1976; Weitbrecht & Noetzel, 1976). Several additional *in vivo* studies of repeated injuries in rodents have now been conducted over the past decade (Allen et al., 2000; Conte et al., 2004; Creeley et al., 2004; DeFord et al., 2002; Friess et al., 2009; Huh et al., 2007; Laurer et al., 2001; Longhi et al., 2005; Raghupathi et al., 2004; Shitaka et al., 2011; Uryu et al., 2002; Yoshiyama et al., 2005). All of these repeated mild injury studies were conducted using rodent models of TBI with the exception of the studies by Friess et al (2009) and Raghupathi et al (2004), which used a pediatric model of repeated injury in pigs.

Repetitive TBI generally occurs at a mild level, therefore experimental models have been used which are minimally invasive and do not require a craniotomy, such as weight drop models or other forms of closed-skull TBI. The models must also be administered at a level that produces minimal, or preferably, no fatality. Individuals who have suffered from a mild TBI often complain of cognitive difficulties post-injury. Therefore, repeated injury studies usually evaluate cognitive function, for example using the Morris water maze (MWM) test, as well as the extent of cellular abnormalities in the cortex and hippocampus. The hippocampus in particular has received significant attention in the study of repeated mild TBI, because it plays a critical role in certain types of learning and aspects of memory

Current Understanding and Experimental Approaches to the Study of Repetitive Brain Injury 7

Several *in vitro* approaches have now been developed to study traumatic injury, which utilize dissociated brain cells or slices grown in culture (LaPlaca et al., 2005; Morrison et al., 1998; Noraberg et al., 2005; Spaethling et al., 2007; Weber, 2004). For many years, my laboratory group has utilized an *in vitro* model of stretch-induced mechanical injury originally developed by Ellis et al. (1995). We have characterized this stretch injury model in cell cultures composed of neurons and glia from murine hippocampus (Slemmer *et al.*, 2002; Slemmer & Weber, 2005), cortex (Engel et al., 2005), and cerebellum (Slemmer *et al.*, 2004),

We have previously conducted studies investigating the effects of repeated trauma on cultured hippocampal cells (Slemmer *et al*., 2002; Slemmer & Weber, 2005), which were intended to complement the findings from humans and *in vivo* experimentation. In these studies, we utilized a mild level of stretch injury that produces some measurable damage to cells when administered a single time. When mild stretch injuries were repeated at either 1-hr or 24-hr intervals, cells exhibited cumulative damage. For example, cultures that received a second insult displayed a significant loss of neurons not evident in cultures that received only one injury (see Figure 1). Additionally, cultures injured twice released a significant level of neuron specific enolase (NSE), which was not observed in cultures injured a single time. Interestingly, the extent of damage to the cells was dependent on the time between repeated injuries. For example, cultures that received a second insult 1 hr after the first injury released more S-100B protein (a biomarker of injury commonly employed in the clinic) than cultures that received a second injury at 24 hr. Cultures injured 24 hr apart also exhibited less staining with the intravital dye, propidium iodide, than those injured 1 hr apart. As demonstrated in some *in vivo* studies, these findings suggest that a level of injury producing measurable damage or dysfunction on its own, may cause cumulative damage if repeated within a certain time frame (Laurer et al.,

We also investigated the effects of a very low level of stretch, which produces no overt cell damage (Slemmer and Weber, 2005). This "subthreshold" level of stretch did not cause significant damage or death, even when it was repeated at a 1 hr interval. However, this low level of stretch did induce cell damage when it was repeated several times at a short interval (every 2 min), indicated by increased propidium iodide staining (a marker of cellular injury), neuronal loss, and an increase in NSE release. Although direct comparisons to the clinical situation are difficult to make, these types of repetitive, low-level, mechanical stresses may be similar to the insults received by certain athletes, such as boxers, and hockey and soccer players (Jordan, 2000; Matser et al., 1998; Matser et al., 1999; Webbe & Ochs, 2003; Wennberg & Tator, 2003). This type of *in vitro* model may provide a reliable system in which to study the mechanisms underlying cellular dysfunction following repeated injuries. In addition, this approach could provide a means for rapid screening of potential therapeutic

Another study of repeated injury *in vitro* used a model of axonal injury (Yuen et al., 2009). Low levels of strain to cortical axons in culture resulted in no obvious pathological changes. By 24 hr however, these axons exhibited increased sodium channel expression. When axons were stretched again at 24 hr, there was a significant increase in intracellular calcium, which led to degeneration of the axons. This finding suggests a possible mechanism underlying the susceptibility of the brain to a second impact within a certain

**3.2 Studies conducted** *in vitro*

2001; Longhi et al., 2005).

temporal window.

and currently in cortical cultures from rat pups.

strategies for both single and repeated mild TBI.

storage. Experimental and clinical data have demonstrated not only the importance of this brain region in learning and memory, but also that the hippocampus is uniquely vulnerable to injury, even after mild brain trauma (Lowenstein et al., 1992; Lyeth et al., 1990). In a study by DeFord et al. (2002), repeated mild injuries were administered to mice (four times every 24 hr), followed by MWM testing and histological analysis. Significant learning deficits were found after repeated injuries, which were not evident after a single injury. These deficits occurred even in the absence of cell death within the cortex and hippocampus. Cognitive deficits after multiple mild TBIs (using MWM analysis) were demonstrated in a similar study using a weight drop model (Creeley et al., 2004). In a recent study, Shitaka et al. (2011) used a controlled cortical impact model in mice and found that animals receiving two injuries 24 hr apart displayed MWM deficits for several weeks. In addition, although no gross histological abnormalities were noted, mice that received two insults had damaged axons in various brain areas, which could underlie the cognitive abnormalities.

In one of the early studies of repeated injury *in vivo*, Laurer et al. (2001) used an injury regimen that they described as "concussive". This model was meant to mimic the type of insult that athletes may receive, and was also used for many subsequent studies (Conte et al., 2004; Longhi et al., 2005; Uryu et al., 2002). In an assessment of cognitive and motor function after repeated injury in mice, Laurer et al. (2001) found that the brain was more vulnerable to a second insult if the second injury occurred 24 hr after the first. Even though no cognitive deficits were demonstrated in mice receiving repeated injuries, there was a decrease in motor function and neuronal loss. The authors also stated that the effects of a second mTBI could be synergistic, rather than additive. To further analyze the effects of lengthening the inter-injury interval, Longhi et al. (2005) investigated repetitive injuries three, five and seven days apart. Animals that received repeated injuries three or five days apart exhibited cognitive dysfunction not evident in sham animals or those injured only once. However, no deficits were observed when the injury interval was extended to seven days. This experimental evidence demonstrating that the brain can recover from a first injury, given sufficient amount of time, is certainly alluring, especially in relation to establishing "return-to-play" guidelines for athletes. Overall, the evidence from these *in vivo* experimental models suggests that repetitive mild TBI causes more cognitive and cellular dysfunction than a single injury, if the brain is not given a sufficient amount of time to recover.

Other *in vivo* studies have been conducted with a primary interest in discovering more about the pathology of inflicted repetitive brain injury in the pediatric population, such as 'shaken impact syndrome' (Friess et al., 2009; Huh et al., 2007; Raghupathi et al., 2004). In a study by Raghupathi et al. (2004), neonatal pigs were subjected to rapid axial rotations of the head, either once, or twice within 15 minutes. Brains were analyzed at 6 hr post-injury and animals that had received double insults exhibited a wider distribution of injured axons than animals that were injured once. In another study in piglets (Friess et al., 2009), animals were injured (by axial head rotation) either once, twice one day apart, or twice one week apart. Animals injured one day apart had the highest mortality rate. Also, animals receiving two injuries had worse neuropathology and neurobehavioral outcome than those injured only once. Huh et al. (2007) conducted experiments in young rats (11 days old) and administered one, two or three injuries spaced only 5 minutes apart. Animals receiving multiple injuries generally displayed increased axonal damage, which was evident earlier after injury than a single impact. Overall, these studies suggest a graded response to repeated injury in the pediatric brain.

#### **3.2 Studies conducted** *in vitro*

6 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

storage. Experimental and clinical data have demonstrated not only the importance of this brain region in learning and memory, but also that the hippocampus is uniquely vulnerable to injury, even after mild brain trauma (Lowenstein et al., 1992; Lyeth et al., 1990). In a study by DeFord et al. (2002), repeated mild injuries were administered to mice (four times every 24 hr), followed by MWM testing and histological analysis. Significant learning deficits were found after repeated injuries, which were not evident after a single injury. These deficits occurred even in the absence of cell death within the cortex and hippocampus. Cognitive deficits after multiple mild TBIs (using MWM analysis) were demonstrated in a similar study using a weight drop model (Creeley et al., 2004). In a recent study, Shitaka et al. (2011) used a controlled cortical impact model in mice and found that animals receiving two injuries 24 hr apart displayed MWM deficits for several weeks. In addition, although no gross histological abnormalities were noted, mice that received two insults had damaged

axons in various brain areas, which could underlie the cognitive abnormalities.

recover.

repeated injury in the pediatric brain.

In one of the early studies of repeated injury *in vivo*, Laurer et al. (2001) used an injury regimen that they described as "concussive". This model was meant to mimic the type of insult that athletes may receive, and was also used for many subsequent studies (Conte et al., 2004; Longhi et al., 2005; Uryu et al., 2002). In an assessment of cognitive and motor function after repeated injury in mice, Laurer et al. (2001) found that the brain was more vulnerable to a second insult if the second injury occurred 24 hr after the first. Even though no cognitive deficits were demonstrated in mice receiving repeated injuries, there was a decrease in motor function and neuronal loss. The authors also stated that the effects of a second mTBI could be synergistic, rather than additive. To further analyze the effects of lengthening the inter-injury interval, Longhi et al. (2005) investigated repetitive injuries three, five and seven days apart. Animals that received repeated injuries three or five days apart exhibited cognitive dysfunction not evident in sham animals or those injured only once. However, no deficits were observed when the injury interval was extended to seven days. This experimental evidence demonstrating that the brain can recover from a first injury, given sufficient amount of time, is certainly alluring, especially in relation to establishing "return-to-play" guidelines for athletes. Overall, the evidence from these *in vivo* experimental models suggests that repetitive mild TBI causes more cognitive and cellular dysfunction than a single injury, if the brain is not given a sufficient amount of time to

Other *in vivo* studies have been conducted with a primary interest in discovering more about the pathology of inflicted repetitive brain injury in the pediatric population, such as 'shaken impact syndrome' (Friess et al., 2009; Huh et al., 2007; Raghupathi et al., 2004). In a study by Raghupathi et al. (2004), neonatal pigs were subjected to rapid axial rotations of the head, either once, or twice within 15 minutes. Brains were analyzed at 6 hr post-injury and animals that had received double insults exhibited a wider distribution of injured axons than animals that were injured once. In another study in piglets (Friess et al., 2009), animals were injured (by axial head rotation) either once, twice one day apart, or twice one week apart. Animals injured one day apart had the highest mortality rate. Also, animals receiving two injuries had worse neuropathology and neurobehavioral outcome than those injured only once. Huh et al. (2007) conducted experiments in young rats (11 days old) and administered one, two or three injuries spaced only 5 minutes apart. Animals receiving multiple injuries generally displayed increased axonal damage, which was evident earlier after injury than a single impact. Overall, these studies suggest a graded response to Several *in vitro* approaches have now been developed to study traumatic injury, which utilize dissociated brain cells or slices grown in culture (LaPlaca et al., 2005; Morrison et al., 1998; Noraberg et al., 2005; Spaethling et al., 2007; Weber, 2004). For many years, my laboratory group has utilized an *in vitro* model of stretch-induced mechanical injury originally developed by Ellis et al. (1995). We have characterized this stretch injury model in cell cultures composed of neurons and glia from murine hippocampus (Slemmer *et al.*, 2002; Slemmer & Weber, 2005), cortex (Engel et al., 2005), and cerebellum (Slemmer *et al.*, 2004), and currently in cortical cultures from rat pups.

We have previously conducted studies investigating the effects of repeated trauma on cultured hippocampal cells (Slemmer *et al*., 2002; Slemmer & Weber, 2005), which were intended to complement the findings from humans and *in vivo* experimentation. In these studies, we utilized a mild level of stretch injury that produces some measurable damage to cells when administered a single time. When mild stretch injuries were repeated at either 1-hr or 24-hr intervals, cells exhibited cumulative damage. For example, cultures that received a second insult displayed a significant loss of neurons not evident in cultures that received only one injury (see Figure 1). Additionally, cultures injured twice released a significant level of neuron specific enolase (NSE), which was not observed in cultures injured a single time. Interestingly, the extent of damage to the cells was dependent on the time between repeated injuries. For example, cultures that received a second insult 1 hr after the first injury released more S-100B protein (a biomarker of injury commonly employed in the clinic) than cultures that received a second injury at 24 hr. Cultures injured 24 hr apart also exhibited less staining with the intravital dye, propidium iodide, than those injured 1 hr apart. As demonstrated in some *in vivo* studies, these findings suggest that a level of injury producing measurable damage or dysfunction on its own, may cause cumulative damage if repeated within a certain time frame (Laurer et al., 2001; Longhi et al., 2005).

We also investigated the effects of a very low level of stretch, which produces no overt cell damage (Slemmer and Weber, 2005). This "subthreshold" level of stretch did not cause significant damage or death, even when it was repeated at a 1 hr interval. However, this low level of stretch did induce cell damage when it was repeated several times at a short interval (every 2 min), indicated by increased propidium iodide staining (a marker of cellular injury), neuronal loss, and an increase in NSE release. Although direct comparisons to the clinical situation are difficult to make, these types of repetitive, low-level, mechanical stresses may be similar to the insults received by certain athletes, such as boxers, and hockey and soccer players (Jordan, 2000; Matser et al., 1998; Matser et al., 1999; Webbe & Ochs, 2003; Wennberg & Tator, 2003). This type of *in vitro* model may provide a reliable system in which to study the mechanisms underlying cellular dysfunction following repeated injuries. In addition, this approach could provide a means for rapid screening of potential therapeutic strategies for both single and repeated mild TBI.

Another study of repeated injury *in vitro* used a model of axonal injury (Yuen et al., 2009). Low levels of strain to cortical axons in culture resulted in no obvious pathological changes. By 24 hr however, these axons exhibited increased sodium channel expression. When axons were stretched again at 24 hr, there was a significant increase in intracellular calcium, which led to degeneration of the axons. This finding suggests a possible mechanism underlying the susceptibility of the brain to a second impact within a certain temporal window.

Current Understanding and Experimental Approaches to the Study of Repetitive Brain Injury 9

Another interesting phenomenon is that heat acclimation (chronic exposure to moderate heat) can also provide resistance to subsequent TBI (Shein et al. 2007; 2008; Umschwief et al.,

In our *in vitro* studies using mechanical stretch, we observed a novel form of mechanical preconditioning. When hippocampal cultures were administered a subthreshold level of stretch 24 hr prior to a mild stretch, there was a significant decrease in released S-100B protein compared to cultures that were injured at a mild level alone (Slemmer & Weber, 2005). This observation suggests some form of protection initiated by this low level of stretch. A similar finding *in vivo* was reported by Allen et al. (2000). In their study, rats received a series of mild injuries spaced three days apart using a weight drop model. Some of these animals received a severe injury after the repetitive mild injuries. Motor function deficits were evident in severely injured animals, but not in animals that received repeated mild injuries or repeated mild injuries followed by a severe injury. This last observation

An important question is how do we utilize this information for beneficial means? One can imagine the ethical implications of suggesting to people that a mild insult to their brains may in fact protect them from worse insults in the future. We still have much to learn about preconditioning. For example, what is the threshold for mechanical insults between initiating protective versus damaging mechanisms in the brain? A clear understanding of the mechanisms by which this protection is elicited holds potential for the management of mild TBI. The fact that a wide variety of stressors can protect the brain from TBI (i.e. crosstolerance) suggests that the same, or similar mechanisms are responsible for the endogenous protection. Increasing the expression of these protective systems could not only be a reliable way for managing mild TBI, but could also provide resistance in individuals who may be at risk of sustaining an additional head injury, such as athletes. Both *in vivo* and *in vitro* models could provide reliable systems in which to study the mechanisms underlying the

A correlation between the occurrence of TBI and the further development of neurodegenerative disease later in life has been recognized for several years, and TBI is considered to be one of the most robust risk factors for developing Alzheimer's disease (AD; Szczygielski, et al., 2005; Slemmer et al., 2011). There is also evidence that genetic predisposition may increase one's risk of developing AD, such as possession of the apolipoprotein E 4 allele (Isoniemi et al., 2006). A phenomenon known as chronic TBI occurs in a significant amount of professional boxers (Jordan, 2000), with the most serious form, the neurodegenerative disorder *dementia pugilistica*, resulting in severe cognitive and motor dysfunctions. A potential link between TBI and Parkinson's disease has also been suggested (Masel and DeWitt, 2010). It is generally accepted that the pathology of AD and *dementia pugilistica* are quite similar (Geddes et al., 1999; Schmidt et al., 2001). Although epidemiological data linking TBI and neurogenerative diseases are quite strong, only a modest amount of experimental work has been conducted in order to achieve a mechanistic link between repeated mild TBI and the development of either AD or *dementia* 

In addition to cognitive symptoms, dementias such as *dementia pugilistica* and AD are associated with specific types of neuropathological markers. In fact, AD in humans can only

2010).

suggests a preconditioning effect.

preconditioning phenomenon.

*pugilistica.* 

**4. Repetitive injury and neurodegenerative disease** 

Fig. 1. Effect of repeated stretch injury on hippocampal cells in culture. Cell injury was assessed using the two dyes fluorescein diacetate (FDA) and propidium iodide (PrI). FDA stains healthy, viable cells and fluoresces green, while PrI does not pass through intact cellular membranes. If membranes are damaged, however, cells lose their ability to retain FDA and PrI will enter the cell and bind to the nucleus, fluorescing red. (A) PrI uptake following mild stretch injury at 1 h post‐injury (B) A double mild insult increased PrI uptake when evaluated immediately after the second injury. Note that many cells also have beaded neurites. (A and B) Magnification: 100X. (C and D) Enlargements of A and B, respectively. Magnification: 200X. Modified from Slemmer et al. (2002). Reprinted with permission from Oxford Press, 2002.

#### **3.3 The preconditioning phenomenon**

Several studies have indicated that an initial, very mild insult to either cultured cells or to the brain itself, may provide some protection from a second, more severe insult, a finding that has been termed "preconditioning". Ischemic preconditioning, in which a brief exposure to ischemia renders the brain more resistant to subsequent longer periods of ischemia, has been well described (for review, see Schaller & Graf, 2002). There is also evidence of preconditioning cross-tolerance. For example, brief ischemia lessens damage following TBI *in vivo* (Perez-Pinzon et al., 1999). More recently, several other types of pretreatments have been demonstrated to improve outcome and pathology after experimental TBI, such as a low dose of *N*-methyl-D-aspartate (Costa et al., 2010), exposure to lipopolysaccharide (Longhi et al., 2011) or glucagon (Fanne et al., 2011), hypothermia (Lotocki et al., 2006), as well as exposure to hyperbaric oxygen (Hu et al., 2008; 2010).

Fig. 1. Effect of repeated stretch injury on hippocampal cells in culture. Cell injury was assessed using the two dyes fluorescein diacetate (FDA) and propidium iodide (PrI). FDA stains healthy, viable cells and fluoresces green, while PrI does not pass through intact cellular membranes. If membranes are damaged, however, cells lose their ability to retain FDA and PrI will enter the cell and bind to the nucleus, fluorescing red. (A) PrI uptake following mild stretch injury at 1 h post‐injury (B) A double mild insult increased PrI uptake when evaluated immediately after the second injury. Note that many cells also have beaded neurites. (A and B) Magnification: 100X. (C and D) Enlargements of A and B, respectively. Magnification: 200X. Modified from Slemmer et al. (2002). Reprinted with permission from

Several studies have indicated that an initial, very mild insult to either cultured cells or to the brain itself, may provide some protection from a second, more severe insult, a finding that has been termed "preconditioning". Ischemic preconditioning, in which a brief exposure to ischemia renders the brain more resistant to subsequent longer periods of ischemia, has been well described (for review, see Schaller & Graf, 2002). There is also evidence of preconditioning cross-tolerance. For example, brief ischemia lessens damage following TBI *in vivo* (Perez-Pinzon et al., 1999). More recently, several other types of pretreatments have been demonstrated to improve outcome and pathology after experimental TBI, such as a low dose of *N*-methyl-D-aspartate (Costa et al., 2010), exposure to lipopolysaccharide (Longhi et al., 2011) or glucagon (Fanne et al., 2011), hypothermia (Lotocki et al., 2006), as well as exposure to hyperbaric oxygen (Hu et al., 2008; 2010).

Oxford Press, 2002.

**3.3 The preconditioning phenomenon** 

Another interesting phenomenon is that heat acclimation (chronic exposure to moderate heat) can also provide resistance to subsequent TBI (Shein et al. 2007; 2008; Umschwief et al., 2010).

In our *in vitro* studies using mechanical stretch, we observed a novel form of mechanical preconditioning. When hippocampal cultures were administered a subthreshold level of stretch 24 hr prior to a mild stretch, there was a significant decrease in released S-100B protein compared to cultures that were injured at a mild level alone (Slemmer & Weber, 2005). This observation suggests some form of protection initiated by this low level of stretch. A similar finding *in vivo* was reported by Allen et al. (2000). In their study, rats received a series of mild injuries spaced three days apart using a weight drop model. Some of these animals received a severe injury after the repetitive mild injuries. Motor function deficits were evident in severely injured animals, but not in animals that received repeated mild injuries or repeated mild injuries followed by a severe injury. This last observation suggests a preconditioning effect.

An important question is how do we utilize this information for beneficial means? One can imagine the ethical implications of suggesting to people that a mild insult to their brains may in fact protect them from worse insults in the future. We still have much to learn about preconditioning. For example, what is the threshold for mechanical insults between initiating protective versus damaging mechanisms in the brain? A clear understanding of the mechanisms by which this protection is elicited holds potential for the management of mild TBI. The fact that a wide variety of stressors can protect the brain from TBI (i.e. crosstolerance) suggests that the same, or similar mechanisms are responsible for the endogenous protection. Increasing the expression of these protective systems could not only be a reliable way for managing mild TBI, but could also provide resistance in individuals who may be at risk of sustaining an additional head injury, such as athletes. Both *in vivo* and *in vitro* models could provide reliable systems in which to study the mechanisms underlying the preconditioning phenomenon.

#### **4. Repetitive injury and neurodegenerative disease**

A correlation between the occurrence of TBI and the further development of neurodegenerative disease later in life has been recognized for several years, and TBI is considered to be one of the most robust risk factors for developing Alzheimer's disease (AD; Szczygielski, et al., 2005; Slemmer et al., 2011). There is also evidence that genetic predisposition may increase one's risk of developing AD, such as possession of the apolipoprotein E 4 allele (Isoniemi et al., 2006). A phenomenon known as chronic TBI occurs in a significant amount of professional boxers (Jordan, 2000), with the most serious form, the neurodegenerative disorder *dementia pugilistica*, resulting in severe cognitive and motor dysfunctions. A potential link between TBI and Parkinson's disease has also been suggested (Masel and DeWitt, 2010). It is generally accepted that the pathology of AD and *dementia pugilistica* are quite similar (Geddes et al., 1999; Schmidt et al., 2001). Although epidemiological data linking TBI and neurogenerative diseases are quite strong, only a modest amount of experimental work has been conducted in order to achieve a mechanistic link between repeated mild TBI and the development of either AD or *dementia pugilistica.* 

In addition to cognitive symptoms, dementias such as *dementia pugilistica* and AD are associated with specific types of neuropathological markers. In fact, AD in humans can only

Current Understanding and Experimental Approaches to the Study of Repetitive Brain Injury 11

Fig. 2. Amyloid deposition in Tg2576 mice with sham (A, B) or repetitive mild TBI (C, D) with 4G8 immunohistochemistry at 9 (A, C) and 16 (B, D) weeks after mild TBI. Senile plaques increased in an age-dependent manner in both sham and injured mice, but the largest number of Aβ-positive plaques are evident in the 16-week repetitive mild TBI mice (D). Modified from Uryu et al. (2002). Reprinted with permission from the Society for

The overall findings of these *in vivo* studies are quite significant, because they can demonstrate a direct experimental link between repeated mild TBI and the development of AD-like pathology, as well as other forms of dementia. Generally, it takes many years before the onset of symptoms of neurodegenerative disorders is evident, after an individual has experienced a TBI. Therefore, it requires an exceedingly long amount of time to gather this type of epidemiological data from the human population. This area of research, in particular, is where experimental models could truly help decipher the mechanisms by which neurodegenerative disease may be triggered by repetitive brain injury, and to

The current lines of research in repetitive TBI should certainly be continued, such as attempting to firmly establish the link to neurodegenerative disease, as well as demonstrating appropriate recovery times after a mild injury. However, new avenues also need to be explored. For example, much experimental evidence suggests that animals demonstrate cognitive deficits and cellular dysfunction after repetitive mild TBI, even though the injury may not necessarily lead to cell death (DeFord et al., 2002; Kanayama et al., 1996). Therefore, rather than trying to prevent cells from dying after repeated injuries, it may be more useful to learn how to restore normal cellular physiology after a traumatic episode*.* Combining studies

Neuroscience, 2002.

**5. Future directions** 

identify potential therapeutic strategies.

**5.1 Potential new experimental directions** 

be fully confirmed post-mortem via the presence of extracellular senile plaques, which are abnormal amyloid β (Aβ) protein deposits, and abnormal tau protein aggregation in specific brain regions (Price et al., 1991). The tau protein is an important functional component of the cytoskeleton in healthy neurons, but it is also a predominant component of neurofibrillary plaques found in AD and *dementia pugilistica* (Schmidt et al., 2001). Therefore, the development of abnormal tau protein pathology is a potential molecular link between TBI and dementia. In a study by Kanayama et al (1996), rats were injured with a mild impact once a day for seven days. Analysis showed an increase in abnormal tau protein deposits by one month after injury. Yoshiyama et al. (2005) used a robust injury paradigm in an attempt to model human *dementia pugilistica* in transgenic mice expressing the shortest human tau isoform (T44). Mice were subjected to four injuries a day, once a week, for four weeks, resulting in each mouse receiving a total of 16 injuries, and surprisingly, they could find only one mouse that displayed pathology of *dementia pugilistica* at nine months of age. Partly for this reason, the vast majority of animal studies have focused on the deposition of Aβ, or the intracellular processing of amyloid precursor protein (APP), from which Aβ is derived. Although high levels of Aβ have clearly been demonstrated in AD patients, the exact function of amyloid protein has not been established. Interestingly, deposition of Aβ has not been observed in the majority of nontransgenic animal studies after trauma (Laurer et al., 2001; Szczygielski, et al., 2005), and as a result, many of the current models used to investigate traumatic dementia are derived from transgenic rodents that were originally created to investigate AD. For example, the transgenic mouse Tg2576, which is characterized by AD-like amyloidosis by nine months of age, has been used in several investigations of repetitive mild TBI, and has become a popular animal model for traumatically-induced dementia.

In a study by Uryu et al. (2002), Tg2576 transgenic mice subjected to repeated, but not to single mild TBI, displayed cognitive deficits and Aβ deposition. As shown in Figure 2, Aβ deposition did not occur in these mice at either 9 or 16 weeks post-sham injury. In contrast, brain slices from Tg2576 mice that underwent repeated mild TBI displayed evident Aβ deposition (in the form of senile plaques) at 16 weeks post-injury. The appearance of senile plaques followed a delayed time-scale, which is not surprising, as dementia is often manifested in humans long after TBI. This study also demonstrated that the transgenic background alone was not sufficient to induce marked amounts of Aβ deposition in these aged mice, which is in line with a "two-hit" hypothesis proposed by Nakagawa et al. (1999). In this case, the first-hit is the genetic predisposition, which enables an individual to produce high amounts of abnormal proteins such as Aβ, and the second-hit is the TBI. However, a single mild injury alone was not enough to produce AD-like pathology. It is therefore possible that more than one mild TBI is necessary to lead to dementia later in life, whereas a single moderate or severe TBI on its own may lead to dementia. Increased incidence of dementia in humans is obviously associated with increased age, and recent evidence links aging with the overproduction of free radicals via oxidative stress (Slemmer et al., 2008). TBI is also known to dramatically increase free radicals and reactive oxygen species (Slemmer et al., 2008, Weber, 2004). Repetitive, but not single mild TBI, has been previously shown to increase oxidative stress in Tg2576 mice (Uryu et al., 2002), which could be reduced by supplementing the rodent chow with vitamin E, a known antioxidant (Conte et al., 2004). Therefore, oxidative stress may be a major contributing factor leading to the development of neurodegenerative disease following TBI.

Fig. 2. Amyloid deposition in Tg2576 mice with sham (A, B) or repetitive mild TBI (C, D) with 4G8 immunohistochemistry at 9 (A, C) and 16 (B, D) weeks after mild TBI. Senile plaques increased in an age-dependent manner in both sham and injured mice, but the largest number of Aβ-positive plaques are evident in the 16-week repetitive mild TBI mice (D). Modified from Uryu et al. (2002). Reprinted with permission from the Society for Neuroscience, 2002.

The overall findings of these *in vivo* studies are quite significant, because they can demonstrate a direct experimental link between repeated mild TBI and the development of AD-like pathology, as well as other forms of dementia. Generally, it takes many years before the onset of symptoms of neurodegenerative disorders is evident, after an individual has experienced a TBI. Therefore, it requires an exceedingly long amount of time to gather this type of epidemiological data from the human population. This area of research, in particular, is where experimental models could truly help decipher the mechanisms by which neurodegenerative disease may be triggered by repetitive brain injury, and to identify potential therapeutic strategies.

#### **5. Future directions**

10 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

be fully confirmed post-mortem via the presence of extracellular senile plaques, which are abnormal amyloid β (Aβ) protein deposits, and abnormal tau protein aggregation in specific brain regions (Price et al., 1991). The tau protein is an important functional component of the cytoskeleton in healthy neurons, but it is also a predominant component of neurofibrillary plaques found in AD and *dementia pugilistica* (Schmidt et al., 2001). Therefore, the development of abnormal tau protein pathology is a potential molecular link between TBI and dementia. In a study by Kanayama et al (1996), rats were injured with a mild impact once a day for seven days. Analysis showed an increase in abnormal tau protein deposits by one month after injury. Yoshiyama et al. (2005) used a robust injury paradigm in an attempt to model human *dementia pugilistica* in transgenic mice expressing the shortest human tau isoform (T44). Mice were subjected to four injuries a day, once a week, for four weeks, resulting in each mouse receiving a total of 16 injuries, and surprisingly, they could find only one mouse that displayed pathology of *dementia pugilistica* at nine months of age. Partly for this reason, the vast majority of animal studies have focused on the deposition of Aβ, or the intracellular processing of amyloid precursor protein (APP), from which Aβ is derived. Although high levels of Aβ have clearly been demonstrated in AD patients, the exact function of amyloid protein has not been established. Interestingly, deposition of Aβ has not been observed in the majority of nontransgenic animal studies after trauma (Laurer et al., 2001; Szczygielski, et al., 2005), and as a result, many of the current models used to investigate traumatic dementia are derived from transgenic rodents that were originally created to investigate AD. For example, the transgenic mouse Tg2576, which is characterized by AD-like amyloidosis by nine months of age, has been used in several investigations of repetitive mild TBI, and has become a popular animal model for traumatically-induced

In a study by Uryu et al. (2002), Tg2576 transgenic mice subjected to repeated, but not to single mild TBI, displayed cognitive deficits and Aβ deposition. As shown in Figure 2, Aβ deposition did not occur in these mice at either 9 or 16 weeks post-sham injury. In contrast, brain slices from Tg2576 mice that underwent repeated mild TBI displayed evident Aβ deposition (in the form of senile plaques) at 16 weeks post-injury. The appearance of senile plaques followed a delayed time-scale, which is not surprising, as dementia is often manifested in humans long after TBI. This study also demonstrated that the transgenic background alone was not sufficient to induce marked amounts of Aβ deposition in these aged mice, which is in line with a "two-hit" hypothesis proposed by Nakagawa et al. (1999). In this case, the first-hit is the genetic predisposition, which enables an individual to produce high amounts of abnormal proteins such as Aβ, and the second-hit is the TBI. However, a single mild injury alone was not enough to produce AD-like pathology. It is therefore possible that more than one mild TBI is necessary to lead to dementia later in life, whereas a single moderate or severe TBI on its own may lead to dementia. Increased incidence of dementia in humans is obviously associated with increased age, and recent evidence links aging with the overproduction of free radicals via oxidative stress (Slemmer et al., 2008). TBI is also known to dramatically increase free radicals and reactive oxygen species (Slemmer et al., 2008, Weber, 2004). Repetitive, but not single mild TBI, has been previously shown to increase oxidative stress in Tg2576 mice (Uryu et al., 2002), which could be reduced by supplementing the rodent chow with vitamin E, a known antioxidant (Conte et al., 2004). Therefore, oxidative stress may be a major contributing factor leading to

the development of neurodegenerative disease following TBI.

dementia.

#### **5.1 Potential new experimental directions**

The current lines of research in repetitive TBI should certainly be continued, such as attempting to firmly establish the link to neurodegenerative disease, as well as demonstrating appropriate recovery times after a mild injury. However, new avenues also need to be explored. For example, much experimental evidence suggests that animals demonstrate cognitive deficits and cellular dysfunction after repetitive mild TBI, even though the injury may not necessarily lead to cell death (DeFord et al., 2002; Kanayama et al., 1996). Therefore, rather than trying to prevent cells from dying after repeated injuries, it may be more useful to learn how to restore normal cellular physiology after a traumatic episode*.* Combining studies

Current Understanding and Experimental Approaches to the Study of Repetitive Brain Injury 13

For example, if animals or tissue are analyzed one day after the fourth injury, then four days will have passed for the single injury group if those animals were injured on day one. This difference in time could affect the observations. One could argue that if a long enough period of time passes after the injuries, such as weeks or months, then the effect of when the single insult animals were injured will be negligible. Admittedly, this would be more proper for comparison to the human situation in which the effects of mild TBI can be manifested for weeks, months, or even years. However, this is often not practical for many laboratories, as the costs of housing animals for months can at times be prohibitive. Also, conducting long-term experiments *in vitro* is limited, since the cells generally remain viable for only a few weeks. This raises a critical point as to the relevance of repeated injury studies *in vitro*. I strongly believe that *in vitro* experiments can deliver information about the cellular mechanisms of repeated injury that are difficult to obtain *in vivo*, and that it is essential to combine data derived from *in vitro* experiments with those conducted with animals *in vivo.* However, I am unsure how to directly compare the data*.* For example, is a 24 hr injury interval *in vitro* equivalent to 24 hr *in vivo*? The greater consensus that exists on these issues with individuals who conduct repeated injury studies, the easier it will be to compare the data, and the stronger a case can be made for showing unequivocally, that repeated mild TBI could lead to long-term

Fig. 3. Issues for consideration when designing repeated TBI experiments (i.e. choosing

proper timepoints for controls and behavioral/tissue analysis). T = time. From Weber (2007). Reprinted with permission from Elsevier, 2007.

dysfunction in humans.

at the cellular and behavioral levels is crucial for attaining this goal, and one area of potential interest is the evaluation of the effects of repeated TBI on synaptic plasticity in the cortex and hippocampus. The ability of neurons to undergo changes in synaptic strength, such as longterm potentiation (LTP), is postulated to be a cellular correlate of learning and memory (Bliss & Collingridge, 1993; Malenka & Nicoll, 1999). Several studies have reported impaired hippocampal LTP after TBI *in vivo* (see Albensi, 2001; Weber, 2004). One area of future research could focus on restoring mechanisms of synaptic plasticity after injury (such as LTP), as well as correlated hippocampal-mediated behavioral tasks.

The hippocampus shares neuronal projections with areas of the cerebral cortex, which undoubtedly also contributes to memory formation and storage. Indeed, alterations in synaptic plasticity may also occur directly in the cortex after repeated mild TBI. Therefore, although the hippocampus may play a central role in the cognitive dysfunction observed after mild TBI, it is important not to overlook contributions from other brain areas as well. Since some repeated injury studies demonstrate motor impairment, it may also be appropriate to investigate cellular physiology and synaptic plasticity in the cerebellum (see Hansel et al., 2001; Weber et al., 2003; Slemmer et al., 2005) after repetitive TBI. These types of investigations could involve electrophysiology measurements as well as analysis of intracellular calcium dynamics. Intracellular calcium is extremely important to the normal function of neurons and can be considerably altered even in cells that do not go on to die (Weber, 2004; Yuen et al., 2009).

#### **5.2 Experimental design considerations**

Although deciding on appropriate research directions is of paramount importance to developing potential therapeutic strategies for repetitive TBI, the utilization of proper parameters for repeated injury studies may be just as crucial. For example, what are the best inter-injury interval, or intervals, to use? Although 24 hr between injuries is the most common (and perhaps practical) interval in the laboratory (Conte et al., 2004; Creeley et al., 2004; DeFord et al., 2002; Friess et al., 2009; Kanayama et al., 1996; Laurer et al., 2001; Shitaka et al., 2011; Uryu et al., 2002; Weitbrecht & Noetzel, 1976; Yoshiyama et al., 2005), is it the most appropriate in mimicking what occurs in humans? Also, how many injuries should a researcher administer? If one is attempting to model concussive episodes, then two or three may be enough, as this may closely mimic a true situation, especially with athletes. However, when attempting to recreate *dementia pugilistica* (Yoshiyama et al., 2005), the number of injuries should certainly be increased, and perhaps be 'subthreshold' levels of injury, i.e. a level of injury which produces no overt damage on its own.

The proper controls and endpoints to use for repeated injury studies also need to be carefully considered. For *in vivo* studies analyzing the effects of a single TBI, the issue of controls is fairly straightforward. Sham animals are treated at an equivalent time as injured animals, and the analysis, cellular or behavioral, is also performed at the same time-point. However, when comparing uninjured animals to animals that have received more than one injury, what is the proper comparison? For example, if an animal receives an injury on day one, and an additional injury on day two, and analysis takes place on day three, does one compare the data with sham animals from day one, or from day two (or both, see figure 3A)? The issue is further complicated when comparing repeatedly injured animals to animals that have received a single TBI. If the comparison concerns animals that undergo four injuries or a single injury, are the single insult animals injured at the same time as injury one in the repeated group, or at the same time as the fourth injury (see figure 3B)? This decision will affect the endpoint as well.

at the cellular and behavioral levels is crucial for attaining this goal, and one area of potential interest is the evaluation of the effects of repeated TBI on synaptic plasticity in the cortex and hippocampus. The ability of neurons to undergo changes in synaptic strength, such as longterm potentiation (LTP), is postulated to be a cellular correlate of learning and memory (Bliss & Collingridge, 1993; Malenka & Nicoll, 1999). Several studies have reported impaired hippocampal LTP after TBI *in vivo* (see Albensi, 2001; Weber, 2004). One area of future research could focus on restoring mechanisms of synaptic plasticity after injury (such as LTP), as well as

The hippocampus shares neuronal projections with areas of the cerebral cortex, which undoubtedly also contributes to memory formation and storage. Indeed, alterations in synaptic plasticity may also occur directly in the cortex after repeated mild TBI. Therefore, although the hippocampus may play a central role in the cognitive dysfunction observed after mild TBI, it is important not to overlook contributions from other brain areas as well. Since some repeated injury studies demonstrate motor impairment, it may also be appropriate to investigate cellular physiology and synaptic plasticity in the cerebellum (see Hansel et al., 2001; Weber et al., 2003; Slemmer et al., 2005) after repetitive TBI. These types of investigations could involve electrophysiology measurements as well as analysis of intracellular calcium dynamics. Intracellular calcium is extremely important to the normal function of neurons and can be considerably altered even in cells that do not go on to die (Weber, 2004; Yuen et al., 2009).

Although deciding on appropriate research directions is of paramount importance to developing potential therapeutic strategies for repetitive TBI, the utilization of proper parameters for repeated injury studies may be just as crucial. For example, what are the best inter-injury interval, or intervals, to use? Although 24 hr between injuries is the most common (and perhaps practical) interval in the laboratory (Conte et al., 2004; Creeley et al., 2004; DeFord et al., 2002; Friess et al., 2009; Kanayama et al., 1996; Laurer et al., 2001; Shitaka et al., 2011; Uryu et al., 2002; Weitbrecht & Noetzel, 1976; Yoshiyama et al., 2005), is it the most appropriate in mimicking what occurs in humans? Also, how many injuries should a researcher administer? If one is attempting to model concussive episodes, then two or three may be enough, as this may closely mimic a true situation, especially with athletes. However, when attempting to recreate *dementia pugilistica* (Yoshiyama et al., 2005), the number of injuries should certainly be increased, and perhaps be 'subthreshold' levels of

The proper controls and endpoints to use for repeated injury studies also need to be carefully considered. For *in vivo* studies analyzing the effects of a single TBI, the issue of controls is fairly straightforward. Sham animals are treated at an equivalent time as injured animals, and the analysis, cellular or behavioral, is also performed at the same time-point. However, when comparing uninjured animals to animals that have received more than one injury, what is the proper comparison? For example, if an animal receives an injury on day one, and an additional injury on day two, and analysis takes place on day three, does one compare the data with sham animals from day one, or from day two (or both, see figure 3A)? The issue is further complicated when comparing repeatedly injured animals to animals that have received a single TBI. If the comparison concerns animals that undergo four injuries or a single injury, are the single insult animals injured at the same time as injury one in the repeated group, or at the same time as the fourth injury (see figure 3B)? This decision will affect the endpoint as well.

injury, i.e. a level of injury which produces no overt damage on its own.

correlated hippocampal-mediated behavioral tasks.

**5.2 Experimental design considerations** 

For example, if animals or tissue are analyzed one day after the fourth injury, then four days will have passed for the single injury group if those animals were injured on day one. This difference in time could affect the observations. One could argue that if a long enough period of time passes after the injuries, such as weeks or months, then the effect of when the single insult animals were injured will be negligible. Admittedly, this would be more proper for comparison to the human situation in which the effects of mild TBI can be manifested for weeks, months, or even years. However, this is often not practical for many laboratories, as the costs of housing animals for months can at times be prohibitive. Also, conducting long-term experiments *in vitro* is limited, since the cells generally remain viable for only a few weeks. This raises a critical point as to the relevance of repeated injury studies *in vitro*. I strongly believe that *in vitro* experiments can deliver information about the cellular mechanisms of repeated injury that are difficult to obtain *in vivo*, and that it is essential to combine data derived from *in vitro* experiments with those conducted with animals *in vivo.* However, I am unsure how to directly compare the data*.* For example, is a 24 hr injury interval *in vitro* equivalent to 24 hr *in vivo*? The greater consensus that exists on these issues with individuals who conduct repeated injury studies, the easier it will be to compare the data, and the stronger a case can be made for showing unequivocally, that repeated mild TBI could lead to long-term dysfunction in humans.

Fig. 3. Issues for consideration when designing repeated TBI experiments (i.e. choosing proper timepoints for controls and behavioral/tissue analysis). T = time. From Weber (2007). Reprinted with permission from Elsevier, 2007.

Current Understanding and Experimental Approaches to the Study of Repetitive Brain Injury 15

healthy individuals. Ampakines positively modulate the AMPA-type of glutamate receptors in the brain (Lynch & Gall, 2006). Glutamate receptors are known to be involved in a wide variety of processes in the nervous system, one of which is memory. Their activation appears to be imperative for memory consolidation. For example, the activation of AMPA receptors is known to facilitate LTP in the hippocampus. Ampakines are peripherally administered drugs known to cross the blood-brain barrier and can potently facilitate LTP, as demonstrated in rodents (Staubli et al., 1994). These drugs also improve

Ampakines have now been evaluated in clinical trials in humans. One of these drugs in particular (CX516) has demonstrated enhanced memory and cognitive performance in healthy young adults (Ingvar et al., 1997; Lynch et al., 1996). Similar positive cognitive effects were found with CX516 in healthy elderly subjects (Lynch et al., 1997). In these studies, no changes in heart rate, mood or motor performance were found. Another study in healthy elderly volunteer subjects with another ampakine (farampator) showed improvements with short-term memory (Wezenberg et al., 2007). At higher doses, farampator caused side effects such as nausea, headache and drowsiness. Overall, these drugs produce cognitive enhancement with either no, or very mild side effects. This raises the possibility of treating athletes with these drugs after they have sustained a concussion,

Repetitive mild TBI constitutes a significant portion of all TBI cases and the incidence of repeated TBI appears to be on the rise. Overall, there has been surprisingly little attention given to experimental repetitive TBI studies. However, more researchers have conducted studies in this field in recent years. Research involving both *in vivo* and *in vitro* experimentation holds promise for unraveling the pathology of repetitive mild TBI, which may differ from that of single TBI at various levels. A greater understanding of how long the brain takes to recover after a mild injury will aid in determining return to play guidelines for athletes. In addition, further experimentation and monitoring of mild TBI sufferers will assist in developing treatment strategies for decreasing damage should a second injury

The author would like to recognize current funding from the Natural Sciences and Engineering Research Council (NSERC) and the Canada Foundation for Innovation (CFI).

Ackery, A., Provvidenza, C. & Tator, C.H. (2009) Concussion in hockey: compliance with

Albensi, B.C. (2001) Models of brain injury and alterations in synaptic plasticity. *Journal of* 

*Neuroscience Research*, vol.65, no.4, pp. 279-283, ISSN 0360-4012

Vol.36, No. 2, pp. 207-12, ISSN 0317-1671

return to play advice and follow-up status. *Canadian Journal of Neurological Sciences*,

memory performance in rodents and humans (Lynch, 1998; Lynch & Gall, 2006).

as well as treating child and spousal abuse victims who have repetitive injuries.

**6. Conclusions** 

occur.

**7. Acknowledgements** 

**8. References** 

#### **5.3 Possible therapeutic interventions**

Perhaps one of the best, and most logical, therapeutic interventions that physicians can make especially when athletes are concerned is to not allow these individuals to return to play until they seem to have fully recovered from a mild injury/concussion. This would obviously stop the individual from being in a position of acquiring a second injury in a vulnerable period. Return to play and treatment guidelines have been established by a consensus statement on concussion in sport at the 3rd International Conference on concussion in sport in Zurich in November of 2008 (McCrory et al., 2009). Diagnosis of concussion and recovery involves a wide assessment of an individual including physical signs, behavioral abnormalities, balance, sleep and cognition (Echlin et al., 2010; McCrory et al., 2009). Neuropsychological assessments and tests such as the Sideline Concussion Assessment Tool 2 (SCAT2) and the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT) should also be routinely used (Echlin et al., 2010; McCrory et al., 2009), and players should have no signs of neurological deficits or syndromes before returning to play (Ackery et al. 2009). There will likely still be players that will not comply with return to play advice, but these individuals need to be made aware that lack of compliance may put them at higher risk for experiencing another concussion as well as suffering potential permanent brain damage and disability (Ackery et al., 2009).

Another potential type of intervention is genetic screening. As previously mentioned, individuals with the apolipoprotein E 4 allele generally show poorer outcome after injury than others without this genetic polymorphism (Isoniemi et al., 2006). Also, individuals with a genetic alteration in neprilysin, which is the enzyme that degrades Aβ protein, may be at greater risk of Aβ plaque formation after TBI as well as the development of AD (Johnson et al, 2009). At present, there are no specific therapeutic interventions that are routinely used for these individuals. However, these persons could at least be advised that they may be at a much higher risk of developing AD if they sustain a TBI or repetitive mild TBIs. Therefore, they could make an informed decision about whether they would participate in activities where they may be at high risk of experience a TBI, such as specific types of sports.

TBI is known to increase free radicals and reactive oxygen species, leading to oxidative stress (Slemmer et al., 2008, Weber, 2004), and this may be a prevalent means of damage even after mild TBI. Therefore, specific agents that could be useful for treating mild TBI are antioxidants. In a study mentioned earlier (Conte et al., 2004), vitamin E, a known antioxidant, increased cognitive function and decreased Aβ deposition after repetitive concussive injury. In addition to supplementation, individuals could potentially increase the amount of antioxidant species in their body through diet, as several foods have high amounts of antioxidants (Ferrari & Torres, 2003). Of course, these compounds would have to cross the blood-brain barrier in order to provide protection from TBI. In fact, many of these species do cross into the brain. For example, Andres-Lacueva et al. (2005) demonstrated that compounds present in blueberries were found in rat brain cells after feeding them a diet with blueberry extract. In addition, Sweeney et al. (2002) showed that rats fed blueberries for six weeks were protected from stroke. This raises the possibility that an individual on a diet high in antioxidant species may be somewhat protected from a mild trauma and may have better outcome following a second mild TBI should it occur.

Another interesting prospect in the field of treating repetitive mild TBI is the potential use of cognitive enhancers, such as ampakines, which were and still are touted as therapeutic agents for neurodegenerative conditions such as Alzheimer's disease (Lynch and Gall, 2006). They are now gaining popularity as safe drugs to improve memory and concentration in healthy individuals. Ampakines positively modulate the AMPA-type of glutamate receptors in the brain (Lynch & Gall, 2006). Glutamate receptors are known to be involved in a wide variety of processes in the nervous system, one of which is memory. Their activation appears to be imperative for memory consolidation. For example, the activation of AMPA receptors is known to facilitate LTP in the hippocampus. Ampakines are peripherally administered drugs known to cross the blood-brain barrier and can potently facilitate LTP, as demonstrated in rodents (Staubli et al., 1994). These drugs also improve memory performance in rodents and humans (Lynch, 1998; Lynch & Gall, 2006).

Ampakines have now been evaluated in clinical trials in humans. One of these drugs in particular (CX516) has demonstrated enhanced memory and cognitive performance in healthy young adults (Ingvar et al., 1997; Lynch et al., 1996). Similar positive cognitive effects were found with CX516 in healthy elderly subjects (Lynch et al., 1997). In these studies, no changes in heart rate, mood or motor performance were found. Another study in healthy elderly volunteer subjects with another ampakine (farampator) showed improvements with short-term memory (Wezenberg et al., 2007). At higher doses, farampator caused side effects such as nausea, headache and drowsiness. Overall, these drugs produce cognitive enhancement with either no, or very mild side effects. This raises the possibility of treating athletes with these drugs after they have sustained a concussion, as well as treating child and spousal abuse victims who have repetitive injuries.

#### **6. Conclusions**

14 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Perhaps one of the best, and most logical, therapeutic interventions that physicians can make especially when athletes are concerned is to not allow these individuals to return to play until they seem to have fully recovered from a mild injury/concussion. This would obviously stop the individual from being in a position of acquiring a second injury in a vulnerable period. Return to play and treatment guidelines have been established by a consensus statement on concussion in sport at the 3rd International Conference on concussion in sport in Zurich in November of 2008 (McCrory et al., 2009). Diagnosis of concussion and recovery involves a wide assessment of an individual including physical signs, behavioral abnormalities, balance, sleep and cognition (Echlin et al., 2010; McCrory et al., 2009). Neuropsychological assessments and tests such as the Sideline Concussion Assessment Tool 2 (SCAT2) and the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT) should also be routinely used (Echlin et al., 2010; McCrory et al., 2009), and players should have no signs of neurological deficits or syndromes before returning to play (Ackery et al. 2009). There will likely still be players that will not comply with return to play advice, but these individuals need to be made aware that lack of compliance may put them at higher risk for experiencing another concussion as well as suffering potential permanent

Another potential type of intervention is genetic screening. As previously mentioned, individuals with the apolipoprotein E 4 allele generally show poorer outcome after injury than others without this genetic polymorphism (Isoniemi et al., 2006). Also, individuals with a genetic alteration in neprilysin, which is the enzyme that degrades Aβ protein, may be at greater risk of Aβ plaque formation after TBI as well as the development of AD (Johnson et al, 2009). At present, there are no specific therapeutic interventions that are routinely used for these individuals. However, these persons could at least be advised that they may be at a much higher risk of developing AD if they sustain a TBI or repetitive mild TBIs. Therefore, they could make an informed decision about whether they would participate in activities

where they may be at high risk of experience a TBI, such as specific types of sports.

trauma and may have better outcome following a second mild TBI should it occur.

Another interesting prospect in the field of treating repetitive mild TBI is the potential use of cognitive enhancers, such as ampakines, which were and still are touted as therapeutic agents for neurodegenerative conditions such as Alzheimer's disease (Lynch and Gall, 2006). They are now gaining popularity as safe drugs to improve memory and concentration in

TBI is known to increase free radicals and reactive oxygen species, leading to oxidative stress (Slemmer et al., 2008, Weber, 2004), and this may be a prevalent means of damage even after mild TBI. Therefore, specific agents that could be useful for treating mild TBI are antioxidants. In a study mentioned earlier (Conte et al., 2004), vitamin E, a known antioxidant, increased cognitive function and decreased Aβ deposition after repetitive concussive injury. In addition to supplementation, individuals could potentially increase the amount of antioxidant species in their body through diet, as several foods have high amounts of antioxidants (Ferrari & Torres, 2003). Of course, these compounds would have to cross the blood-brain barrier in order to provide protection from TBI. In fact, many of these species do cross into the brain. For example, Andres-Lacueva et al. (2005) demonstrated that compounds present in blueberries were found in rat brain cells after feeding them a diet with blueberry extract. In addition, Sweeney et al. (2002) showed that rats fed blueberries for six weeks were protected from stroke. This raises the possibility that an individual on a diet high in antioxidant species may be somewhat protected from a mild

**5.3 Possible therapeutic interventions** 

brain damage and disability (Ackery et al., 2009).

Repetitive mild TBI constitutes a significant portion of all TBI cases and the incidence of repeated TBI appears to be on the rise. Overall, there has been surprisingly little attention given to experimental repetitive TBI studies. However, more researchers have conducted studies in this field in recent years. Research involving both *in vivo* and *in vitro* experimentation holds promise for unraveling the pathology of repetitive mild TBI, which may differ from that of single TBI at various levels. A greater understanding of how long the brain takes to recover after a mild injury will aid in determining return to play guidelines for athletes. In addition, further experimentation and monitoring of mild TBI sufferers will assist in developing treatment strategies for decreasing damage should a second injury occur.

#### **7. Acknowledgements**

The author would like to recognize current funding from the Natural Sciences and Engineering Research Council (NSERC) and the Canada Foundation for Innovation (CFI).

#### **8. References**


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**2** 

*Greece* 

**Traumatic Brain Injury and Inflammation:** 

Efthimios Dardiotis1,2, Vaios Karanikas3, Konstantinos Paterakis4,

*3Department of Immunology, Faculty of Medicine, University of Thessaly, Larissa* 

Traumatic brain injury (TBI) has long been recognized as a leading cause of mortality and permanent neurological disability worldwide and has been described as a silent epidemic of modern societies. It is most common amongst young individuals, in their productive years of life, thereby causing a significant social and financial burden for them, their families and

The pathophysiology of TBI is complex and multifactorial with several pathways involved in the damage of the brain. TBI has been classified into primary and secondary injury. The primary injury is the result of the external mechanical force at the moment of trauma leading to skull fractures, brain contusions, lacerations, diffuse axonal injuries, vascular tearing and intracranial hemorrhages (Maas et al., 2008). The initial impact damages directly the neuronal tissue via excitatory amino acids release and massive ionic influx referred to as

Secondary neuronal damage is induced immediately after primary injury and is mediated through several pathophysiologic mechanisms including raised intracranial pressure, disruption of blood brain barrier, brain edema, decreased cerebral blood flow, altered tissue perfusion, cerebral hypoxia, ischemia and reperfusion injury (Graham et al., 2000). Furthermore, a cascade of molecular, neurochemical, cellular and immune processes contribute to secondary damage such as disruption of calcium homeostasis, oxidative stress, excitatory mediators release, cytoskeletal and mitochondrial dysfunction, Ab-peptide deposition, inflammatory cell infiltration and neuronal cell apoptosis and death (Greve & Zink, 2009). Gene expression studies have demonstrated that several genes are implicated in the pathophysiology of secondary brain damage (Lei et al., 2009). Secondary cascade of events were found to dramatically aggregate primary neuronal damage and given that primary injury is unavoidable and irreversible, secondary processes are the targets of

current therapeutic strategies and trials on neuroprotective agents (Jain, 2008).

**1. Introduction**

the public health system (Maas et al., 2008).

traumatic depolarization (Katayama et al., 1995).

Kostas Fountas2,4 and Georgios M. Hadjigeorgiou1,2 *1Department of Neurology, University Hospital of Larissa Faculty of Medicine, University of Thessaly, Larissa* 

*2Institute of Biomedical Research and Technology (BIOMED)* 

*4Department of Neurosurgery, University Hospital of Larissa* 

 *Faculty of Medicine, University of Thessaly, Larissa* 

*Center for Research and Technology, Thessaly (CERETETH), Larissa* 

**Emerging Role of Innate and Adaptive Immunity** 

lipid peroxidation, and cognitive impairment in a transgenic mouse model of Alzheimer amyloidosis. *Journal of Neuroscience*, vol.22, no.2, pp. 446-454, ISSN: 0270- 6474


### **Traumatic Brain Injury and Inflammation: Emerging Role of Innate and Adaptive Immunity**

Efthimios Dardiotis1,2, Vaios Karanikas3, Konstantinos Paterakis4,

Kostas Fountas2,4 and Georgios M. Hadjigeorgiou1,2 *1Department of Neurology, University Hospital of Larissa Faculty of Medicine, University of Thessaly, Larissa 2Institute of Biomedical Research and Technology (BIOMED) Center for Research and Technology, Thessaly (CERETETH), Larissa 3Department of Immunology, Faculty of Medicine, University of Thessaly, Larissa 4Department of Neurosurgery, University Hospital of Larissa Faculty of Medicine, University of Thessaly, Larissa Greece* 

#### **1. Introduction**

22 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

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Traumatic brain injury (TBI) has long been recognized as a leading cause of mortality and permanent neurological disability worldwide and has been described as a silent epidemic of modern societies. It is most common amongst young individuals, in their productive years of life, thereby causing a significant social and financial burden for them, their families and the public health system (Maas et al., 2008).

The pathophysiology of TBI is complex and multifactorial with several pathways involved in the damage of the brain. TBI has been classified into primary and secondary injury. The primary injury is the result of the external mechanical force at the moment of trauma leading to skull fractures, brain contusions, lacerations, diffuse axonal injuries, vascular tearing and intracranial hemorrhages (Maas et al., 2008). The initial impact damages directly the neuronal tissue via excitatory amino acids release and massive ionic influx referred to as traumatic depolarization (Katayama et al., 1995).

Secondary neuronal damage is induced immediately after primary injury and is mediated through several pathophysiologic mechanisms including raised intracranial pressure, disruption of blood brain barrier, brain edema, decreased cerebral blood flow, altered tissue perfusion, cerebral hypoxia, ischemia and reperfusion injury (Graham et al., 2000). Furthermore, a cascade of molecular, neurochemical, cellular and immune processes contribute to secondary damage such as disruption of calcium homeostasis, oxidative stress, excitatory mediators release, cytoskeletal and mitochondrial dysfunction, Ab-peptide deposition, inflammatory cell infiltration and neuronal cell apoptosis and death (Greve & Zink, 2009). Gene expression studies have demonstrated that several genes are implicated in the pathophysiology of secondary brain damage (Lei et al., 2009). Secondary cascade of events were found to dramatically aggregate primary neuronal damage and given that primary injury is unavoidable and irreversible, secondary processes are the targets of current therapeutic strategies and trials on neuroprotective agents (Jain, 2008).

Traumatic Brain Injury and Inflammation: Emerging Role of Innate and Adaptive Immunity 25

leukocytes between endothelial cells. Finally, these leukocytes migrate along the concentration gradient of chemokines to the site of TBI. Neutrophil accumulation peaks

Leukocytes are believed to be important in the initiation and progression of inflammation following TBI because they contain and release a significant number of inflammatory mediators that injure neurons. Increased leukocyte infiltration has been linked to increased brain damage. Leukocytes release pro-inflammatory cytokines, proteases, prostaglandins, complement factors, free oxygen and nitrogen species which damage neuronal population and brain microvasculature and contribute to the disruption of BBB and formation of vasogenic edema (Nguyen et al., 2007). Studies in vitro have shown that mixed cultures of hippocampal neurons and neutrophils contributed to increased neuronal loss and excitotoxic damage (Dinkel et al., 2004). Also, leukocyte accumulation seemed to mediate the detrimental effects of chemokines. It was shown that increased intrathecal levels of CXCL8 were correlated to the extent of posttraumatic BBB dysfunction and mortality (Kossmann et al., 1997; Whalen et al., 2000). However, these effects were attenuated by prior depletion of the circulating leukocytes (Bell et al., 1996). Leukocytes also contribute to oxidative damage in the injured brain tissue. Free oxygen radicals released by leukocytes induce lipid and protein peroxidation,

It has been hypothesized that inhibition of neutrophil function or migration would reduce the injury size and improve the functional outcome after TBI. This notion has already been proved in experimental models of ischemic brain injury. However, the beneficial role of leukocyte inhibition is less convincing in TBI experiments. Studies in animal models and humans with severe TBI have shown increased expression of the adhesion molecules selectin E and ICAM-1 in the early period following TBI (Carlos et al., 1997; McKeating et al., 1998; Pleines et al., 1998) indicating that these molecules are important in the neutrophil recruitment in the injured brain. Administration of monoclonal antibodies directed against the leukocyte adhesion molecules CD11b (aM subunit of integrin CR3) and ICAM-1 resulted in decreased neutrophil migration (Carlos et al., 1997; Weaver et al., 2000; Knoblach & Faden, 2002) and better clinical recovery (Knoblach & Faden, 2002) after experimental brain trauma. However, in the latter study the beneficial effect of anti-ICAM-1 treatment was also achieved, although to a lesser extent, with the administration of a nonspecific IgG, indicating that part of the effects may be attributed to the general properties of the antibodies. Moreover, ICAM-1 gene deficient mice with TBI did not demonstrate evidence of improved neurological function, reduced lesion volume or neutrophil accumulation compared to wild type control mice (Whalen et al., 1999), suggesting that other adhesion molecules may also play a significant role in the recruitment of neutrophils. Inhibition of neutrophil infiltration was also tested by blocking chemokine expression. Mice deficient in CXC receptor 2 which interacts with chemokines CXCL8, CXCL1 and CXCL2 and mediates the neutrophil transmigration across the BBB were reported to demonstrate significant attenuation of neutrophil infiltration, reduced tissue damage and neuronal loss, especially in the delayed phase post injury (Semple et al., 2010a). In a similar study, deletion of monocyte chemokine CCL2 gene resulted in improved neurological function, delayed reduction in lesion volume and macrophage accumulation (Semple et al., 2010b). Both the latter studies support the notion that late inhibition of leukocyte recruitment in TBI may be beneficial for the extent of brain trauma and the clinical outcome. These results were not achieved when neutrophil depletion was applied early in the course of TBI (Whalen et al., 1999), indicating that leukocyte infiltration in the early phase post injury may mediate some beneficial

within 2 days after TBI whereas monocytes accumulate slightly later (Rhodes, 2011).

mitochondrial and DNA damage and neuronal apoptosis (Tyurin et al., 2000).

Extensive research has indicated that cellular and humoral inflammation after TBI play a key role in the extent of brain injury and repair processes. The initiation, progression and resolution of inflammation in TBI is multifaceted involving leukocyte infiltration, activation of resident immune cells and secretion of inflammatory mediators such as pro- and antiinflammatory cytokines, chemokines, adhesion molecules, complement factors, reactive oxygen species and other factors. Several lines of evidence support a dual role for the neuroinflammation either detrimental or beneficial depending on the extent, time and site of induction. Elucidation of the inflammatory cascade in the injured brain would offer the possibility of novel therapies.

The present article will focus on the TBI induced neuroinflammation and on the current knowledge regarding the involvement of innate and adaptive immune system in the inflammation and repair following TBI.

#### **2. Neuroinflammation**

The normal central nervous system (CNS) limits the entry of immune components and is traditionally regarded as an immune privileged organ separated from the peripheral immune system by the blood-brain-barrier (BBB). However, this concept of limited immune intervention in the CNS has been questioned, since under physiological conditions, resident brain cells are capable of immune surveillance and expression of immune mediators within the CNS. In addition, T-lymphocytes are known to enter the healthy brain parenchyma to perform surveillance in the absence of inflammatory stimulus (Hickey, 1999; Becher et al., 2000). During inflammatory brain insults the immune privileged status is compromised with an activation of innate immune cells and mobilization of specific adaptive immune responses.

A growing body of evidence suggests a pivotal role of TBI induced cerebral inflammation, including activation of resident cells, migration and recruitment of leukocytes and release of inflammatory mediators, in the extent of neuronal injury and repair. Inflammation after TBI is believed to be triggered by several factors such as extravasated blood products, tissue debris, intracellular components, complement fragments, prostaglandins, reactive oxygen and nitrogen species. The BBB is disrupted after TBI resulting in invasion of neutrophils, monocytes and lymphocytes from the periphery and activation of microglia and other resident cells and thus initiating a potent inflammatory response. A biphasic BBB breakdown after TBI has been reported with a first opening occurring immediately after the primary impact reaching a maximum permeability within a few hours and then being declined. A second-delayed opening as a result of secondary injury cascades was found to peak around 3-7 days following TBI and can last from days to years (Baskaya et al., 1997; Shlosberg et al., 2010).

The accumulation of leukocytes into the injured brain area is crucial to the extent of inflammation and secondary brain damage. Leukocytes migrate out of blood vessels into the injured brain parenchyma via binding to the endothelial selectins P and E and the intercellular adhesion molecules (ICAMs). Chemokines from the injured brain tissue contribute to the expression of these endothelial molecules in the local vasculature. Chemokines are produced by resident cells including microglia, astrocytes and neurons in response to local inflammation (Ransohoff, 2002). For instance, the chemokine CXCL8 (IL8) interacts with leukocytes, triggering the activation of the integrins LFA-1 and CR3 (Mac-1) in the surface of leukocytes. These integrins consequently interact with endothelial ICAM-1 and ICAM-2 leading to a firm adhesion, conformational changes and extravasation of

Extensive research has indicated that cellular and humoral inflammation after TBI play a key role in the extent of brain injury and repair processes. The initiation, progression and resolution of inflammation in TBI is multifaceted involving leukocyte infiltration, activation of resident immune cells and secretion of inflammatory mediators such as pro- and antiinflammatory cytokines, chemokines, adhesion molecules, complement factors, reactive oxygen species and other factors. Several lines of evidence support a dual role for the neuroinflammation either detrimental or beneficial depending on the extent, time and site of induction. Elucidation of the inflammatory cascade in the injured brain would offer the

The present article will focus on the TBI induced neuroinflammation and on the current knowledge regarding the involvement of innate and adaptive immune system in the

The normal central nervous system (CNS) limits the entry of immune components and is traditionally regarded as an immune privileged organ separated from the peripheral immune system by the blood-brain-barrier (BBB). However, this concept of limited immune intervention in the CNS has been questioned, since under physiological conditions, resident brain cells are capable of immune surveillance and expression of immune mediators within the CNS. In addition, T-lymphocytes are known to enter the healthy brain parenchyma to perform surveillance in the absence of inflammatory stimulus (Hickey, 1999; Becher et al., 2000). During inflammatory brain insults the immune privileged status is compromised with an activation of

A growing body of evidence suggests a pivotal role of TBI induced cerebral inflammation, including activation of resident cells, migration and recruitment of leukocytes and release of inflammatory mediators, in the extent of neuronal injury and repair. Inflammation after TBI is believed to be triggered by several factors such as extravasated blood products, tissue debris, intracellular components, complement fragments, prostaglandins, reactive oxygen and nitrogen species. The BBB is disrupted after TBI resulting in invasion of neutrophils, monocytes and lymphocytes from the periphery and activation of microglia and other resident cells and thus initiating a potent inflammatory response. A biphasic BBB breakdown after TBI has been reported with a first opening occurring immediately after the primary impact reaching a maximum permeability within a few hours and then being declined. A second-delayed opening as a result of secondary injury cascades was found to peak around 3-7 days following TBI and can last from days to years (Baskaya et al., 1997;

The accumulation of leukocytes into the injured brain area is crucial to the extent of inflammation and secondary brain damage. Leukocytes migrate out of blood vessels into the injured brain parenchyma via binding to the endothelial selectins P and E and the intercellular adhesion molecules (ICAMs). Chemokines from the injured brain tissue contribute to the expression of these endothelial molecules in the local vasculature. Chemokines are produced by resident cells including microglia, astrocytes and neurons in response to local inflammation (Ransohoff, 2002). For instance, the chemokine CXCL8 (IL8) interacts with leukocytes, triggering the activation of the integrins LFA-1 and CR3 (Mac-1) in the surface of leukocytes. These integrins consequently interact with endothelial ICAM-1 and ICAM-2 leading to a firm adhesion, conformational changes and extravasation of

innate immune cells and mobilization of specific adaptive immune responses.

possibility of novel therapies.

**2. Neuroinflammation** 

Shlosberg et al., 2010).

inflammation and repair following TBI.

leukocytes between endothelial cells. Finally, these leukocytes migrate along the concentration gradient of chemokines to the site of TBI. Neutrophil accumulation peaks within 2 days after TBI whereas monocytes accumulate slightly later (Rhodes, 2011).

Leukocytes are believed to be important in the initiation and progression of inflammation following TBI because they contain and release a significant number of inflammatory mediators that injure neurons. Increased leukocyte infiltration has been linked to increased brain damage. Leukocytes release pro-inflammatory cytokines, proteases, prostaglandins, complement factors, free oxygen and nitrogen species which damage neuronal population and brain microvasculature and contribute to the disruption of BBB and formation of vasogenic edema (Nguyen et al., 2007). Studies in vitro have shown that mixed cultures of hippocampal neurons and neutrophils contributed to increased neuronal loss and excitotoxic damage (Dinkel et al., 2004). Also, leukocyte accumulation seemed to mediate the detrimental effects of chemokines. It was shown that increased intrathecal levels of CXCL8 were correlated to the extent of posttraumatic BBB dysfunction and mortality (Kossmann et al., 1997; Whalen et al., 2000). However, these effects were attenuated by prior depletion of the circulating leukocytes (Bell et al., 1996). Leukocytes also contribute to oxidative damage in the injured brain tissue. Free oxygen radicals released by leukocytes induce lipid and protein peroxidation, mitochondrial and DNA damage and neuronal apoptosis (Tyurin et al., 2000).

It has been hypothesized that inhibition of neutrophil function or migration would reduce the injury size and improve the functional outcome after TBI. This notion has already been proved in experimental models of ischemic brain injury. However, the beneficial role of leukocyte inhibition is less convincing in TBI experiments. Studies in animal models and humans with severe TBI have shown increased expression of the adhesion molecules selectin E and ICAM-1 in the early period following TBI (Carlos et al., 1997; McKeating et al., 1998; Pleines et al., 1998) indicating that these molecules are important in the neutrophil recruitment in the injured brain. Administration of monoclonal antibodies directed against the leukocyte adhesion molecules CD11b (aM subunit of integrin CR3) and ICAM-1 resulted in decreased neutrophil migration (Carlos et al., 1997; Weaver et al., 2000; Knoblach & Faden, 2002) and better clinical recovery (Knoblach & Faden, 2002) after experimental brain trauma. However, in the latter study the beneficial effect of anti-ICAM-1 treatment was also achieved, although to a lesser extent, with the administration of a nonspecific IgG, indicating that part of the effects may be attributed to the general properties of the antibodies. Moreover, ICAM-1 gene deficient mice with TBI did not demonstrate evidence of improved neurological function, reduced lesion volume or neutrophil accumulation compared to wild type control mice (Whalen et al., 1999), suggesting that other adhesion molecules may also play a significant role in the recruitment of neutrophils. Inhibition of neutrophil infiltration was also tested by blocking chemokine expression. Mice deficient in CXC receptor 2 which interacts with chemokines CXCL8, CXCL1 and CXCL2 and mediates the neutrophil transmigration across the BBB were reported to demonstrate significant attenuation of neutrophil infiltration, reduced tissue damage and neuronal loss, especially in the delayed phase post injury (Semple et al., 2010a). In a similar study, deletion of monocyte chemokine CCL2 gene resulted in improved neurological function, delayed reduction in lesion volume and macrophage accumulation (Semple et al., 2010b). Both the latter studies support the notion that late inhibition of leukocyte recruitment in TBI may be beneficial for the extent of brain trauma and the clinical outcome. These results were not achieved when neutrophil depletion was applied early in the course of TBI (Whalen et al., 1999), indicating that leukocyte infiltration in the early phase post injury may mediate some beneficial

Traumatic Brain Injury and Inflammation: Emerging Role of Innate and Adaptive Immunity 27

inflammatory processes, the lack of meaningful effects after blocking a single inflammatory mediator and the duality of inflammation which means that inflammation may have either detrimental or beneficial effects depending on the site, the time of induction, the concentration of mediators and the microenvironment (Morganti-Kossmann et al., 2002). This duality was demonstrated for IL-1 which aside from its pro-inflammatory effects also seems to participate in tissue repair processes, especially when induced at later stages, via stimulation of neurotrophic factors synthesis (Spranger et al., 1990; DeKosky et al., 1994; Herx et al., 2000), astrocyte proliferation (Appel et al., 1997) and involvement in synaptic

IL-6 is another cytokine that has been studied in TBI. IL-6 was found to have also a dual role in inflammation with either regulatory, anti-inflammatory or inflammatory effects depending on the time course and extent of expression (Allan & Rothwell, 2001; Morganti-Kossmann et al., 2002). The neurotrophic properties of IL-6 are mediated by inhibition of TNFa synthesis, induction of IL-1ra and nerve growth factor and attenuation of oxidative stress (Morganti-Kossmann et al., 2001). On the contrary, IL-6 promotes inflammatory processes by stimulating the production of chemokines and adhesion molecules and the recruitment of leukocytes (Romano et al., 1997). Elevated levels of IL-6 were observed in the cerebrospinal fluid (CSF) and in the serum of patients with TBI and this increase was correlated with a favorable neurological outcome (Singhal et al., 2002; Chiaretti et al., 2008). In contrast, other studies demonstrated that IL-6 levels were correlated to the clinical severity of TBI patients (Arand et al., 2001; Minambres et al., 2003). Studies in animal models provide evidence for a neuroprotective effect of IL-6. IL-6 was found at elevated levels in experimental TBI (Shohami et al., 1994). Mice deficient for IL-6 had increased numbers of apoptotic neurons, increased oxidative stress and delayed healing of the tissue (Penkowa et al., 2000), whereas the same group demonstrated that IL-6 transgenic mice exhibited increased reduction of oxidative stress

plasticity (Fagan & Gage, 1990; Bellinger et al., 1993; Ide et al., 1996).

and apoptotic cell death after a cryogenic brain injury (Penkowa et al., 2003).

Tumor necrosis factor-a (TNFa) is another cytokine with a well-documented role in TBI. TNFa mRNA and protein is elevated in the early period after experimental TBI and before the infiltration of leukocytes suggesting that the early source of TNFa production are the resident cells (Riva-Depaty et al., 1994). Elevated levels were also observed in the clinical setting of TBI patients (Goodman et al., 1990; Csuka et al., 1999). TNFa has proinflammatory properties similar to that of IL-1 and exacerbates inflammation and secondary brain damage after TBI (Allan & Rothwell, 2001). Early upregulation of neuronal TNFa expression after TBI was found to contribute to subsequent neurological dysfunction (Knoblach et al., 1999). Inhibition of TNFa by the HU-211 compound (a novel TNFa production inhibitor), pentoxyfilline and TNF-binding protein resulted in improved neurological outcome after closed head injury (Shohami et al., 1997). However, in a phase III clinical trial, administration of the HU-211 compound in patients with TBI failed to show improved outcome 6 months after the injury, compared to the placebo group (Maas et al., 2006). These data indicate that neurodegeneration is mediated through various pathological pathways and neuroprotection cannot be achieved by blocking a single mediator as other alternative pathways may be activated leading to neuronal loss. Furthermore, as reported with IL-1, TNFa also has neuroprotective effects and can enhance recovery processes. In a very interesting study, knockout mice for the TNFa gene exhibited milder behavioral deficits compared to the wild-type mice during the acute period post-injury. However, in the long term period (4 weeks post-injury) knockout mice did not recover as well as the wild-type mice, had persistent motor deficits and greater cortical tissue loss (Scherbel et al.,

physiologic processes and only delayed and prolonged leukocyte recruitment may be deleterious to the neuronal survival.

Apart from leukocyte infiltration, the humoral components of neuroinflammation were also found to play an important role in the initiation, maintenance and resolution of inflammation following TBI. The primary traumatic impact and the ensuing injury triggers the release of several cytokines which facilitate the migration of inflammatory cells, the activation of resident cells, the expression of vascular endothelial molecules and chemokines. Cellular sources of cytokines include leukocytes, lymphocytes, microglia, astrocytes, endothelial cells and neurons. Cytokines are induced shortly after primary insult and this early increase is mediated by resident brain cells. Cytokines have multiple actions and targets, and often overlapping biological effects. Cytokines exert their function either through binding to their receptors, which are expressed by both glial and neuronal cells, or through diverse pathways such as modulation of neurotransmitter receptor function, induction of nitric oxide synthase, secretion of chemokines and proteolytic enzymes (Allan & Rothwell, 2001).

Interleukin-1 (IL-1) is a pro-inflammatory cytokine that has been identified as an important mediator of the inflammation following TBI. The IL-1 family has three main members: the proinflammatory cytokines IL-1a and IL-1b, which exert their action by binding to the cell surface receptor IL-1RI, and the anti-inflammatory cytokine IL-1 receptor antagonist (IL-1ra) (Rothwell & Luheshi, 2000). The pro-inflammatory cytokines IL-1a and IL-1b have pleiotropic effects which are mediated by binding to the IL-1RI. IL-1 triggers inflammatory reactions, leads to recruitment of leukocytes, disruption of BBB and formation of edema, induces other interleukins, prostagladins, histamine, thromboxane, chemokines and adhesion molecules and exerts multiple effects in neuronal, glial and endothelial cells (Hopkins & Rothwell, 1995; Rothwell & Hopkins, 1995). IL-1ra is a naturally occurring competitive and highly selective inhibitor of IL-1a and IL-1b which binds to the IL-1RI without initiating signal transduction. IL-1ra plays an important role in the regulation of the inflammatory response and the balance between proinflammatory and anti-inflammatory cytokines (Arend, 1991; Dinarello, 1991).

In experimental TBI a rapid induction of IL-1b (mRNA expression and protein levels) was observed in the very early period following TBI (Fan et al., 1995; Wang & Shuaib, 2002). Similarly, IL-1ra was upregulated in response to head injury but shortly after the induction of IL-1b (Gabellec et al., 1999). Elevated levels of IL-1b were also detected intrathecally in patients with head injury (Winter et al., 2002). Moreover, these elevated levels were correlated to poorer clinical outcome (Chiaretti et al., 2005; Shiozaki et al., 2005). The proinflammatory cytokines IL-1a and IL-1b are believed to initiate inflammation and to contribute to neurodegeneration after various brain insults including TBI, whereas IL-1ra seemed to be neuroprotective. In experimental animal models, intracerebral or intraventricular administration of exogenous IL-1b markedly exacerbates brain injury (Patel et al., 2003). In contrast, administration or overexpression of IL-1ra significantly attenuates neuronal damage and inflammation (Toulmond & Rothwell, 1995; Sanderson et al., 1999; Tehranian et al., 2002). Apart from acute neuroinflammation, TBI induces long-term and persistent inflammation with elevation of IL-1 and other cytokines and increased expression of beta-amyloid protein and phosphorylated tau protein. This long-term inflammation may be the causative link between TBI and traumatic dementia (Hoshino et al., 1998; Holmin & Mathiesen, 1999). These data highlight the important role of IL-1 in the acute and chronic neuroinflammation following TBI and the possibility of beneficial effects that may ensue after its therapeutic inhibition. However, many studies have underlined the complexity of

physiologic processes and only delayed and prolonged leukocyte recruitment may be

Apart from leukocyte infiltration, the humoral components of neuroinflammation were also found to play an important role in the initiation, maintenance and resolution of inflammation following TBI. The primary traumatic impact and the ensuing injury triggers the release of several cytokines which facilitate the migration of inflammatory cells, the activation of resident cells, the expression of vascular endothelial molecules and chemokines. Cellular sources of cytokines include leukocytes, lymphocytes, microglia, astrocytes, endothelial cells and neurons. Cytokines are induced shortly after primary insult and this early increase is mediated by resident brain cells. Cytokines have multiple actions and targets, and often overlapping biological effects. Cytokines exert their function either through binding to their receptors, which are expressed by both glial and neuronal cells, or through diverse pathways such as modulation of neurotransmitter receptor function, induction of nitric oxide synthase, secretion of chemokines and proteolytic enzymes (Allan

Interleukin-1 (IL-1) is a pro-inflammatory cytokine that has been identified as an important mediator of the inflammation following TBI. The IL-1 family has three main members: the proinflammatory cytokines IL-1a and IL-1b, which exert their action by binding to the cell surface receptor IL-1RI, and the anti-inflammatory cytokine IL-1 receptor antagonist (IL-1ra) (Rothwell & Luheshi, 2000). The pro-inflammatory cytokines IL-1a and IL-1b have pleiotropic effects which are mediated by binding to the IL-1RI. IL-1 triggers inflammatory reactions, leads to recruitment of leukocytes, disruption of BBB and formation of edema, induces other interleukins, prostagladins, histamine, thromboxane, chemokines and adhesion molecules and exerts multiple effects in neuronal, glial and endothelial cells (Hopkins & Rothwell, 1995; Rothwell & Hopkins, 1995). IL-1ra is a naturally occurring competitive and highly selective inhibitor of IL-1a and IL-1b which binds to the IL-1RI without initiating signal transduction. IL-1ra plays an important role in the regulation of the inflammatory response and the balance between proinflammatory and anti-inflammatory cytokines (Arend, 1991; Dinarello, 1991). In experimental TBI a rapid induction of IL-1b (mRNA expression and protein levels) was observed in the very early period following TBI (Fan et al., 1995; Wang & Shuaib, 2002). Similarly, IL-1ra was upregulated in response to head injury but shortly after the induction of IL-1b (Gabellec et al., 1999). Elevated levels of IL-1b were also detected intrathecally in patients with head injury (Winter et al., 2002). Moreover, these elevated levels were correlated to poorer clinical outcome (Chiaretti et al., 2005; Shiozaki et al., 2005). The proinflammatory cytokines IL-1a and IL-1b are believed to initiate inflammation and to contribute to neurodegeneration after various brain insults including TBI, whereas IL-1ra seemed to be neuroprotective. In experimental animal models, intracerebral or intraventricular administration of exogenous IL-1b markedly exacerbates brain injury (Patel et al., 2003). In contrast, administration or overexpression of IL-1ra significantly attenuates neuronal damage and inflammation (Toulmond & Rothwell, 1995; Sanderson et al., 1999; Tehranian et al., 2002). Apart from acute neuroinflammation, TBI induces long-term and persistent inflammation with elevation of IL-1 and other cytokines and increased expression of beta-amyloid protein and phosphorylated tau protein. This long-term inflammation may be the causative link between TBI and traumatic dementia (Hoshino et al., 1998; Holmin & Mathiesen, 1999). These data highlight the important role of IL-1 in the acute and chronic neuroinflammation following TBI and the possibility of beneficial effects that may ensue after its therapeutic inhibition. However, many studies have underlined the complexity of

deleterious to the neuronal survival.

& Rothwell, 2001).

inflammatory processes, the lack of meaningful effects after blocking a single inflammatory mediator and the duality of inflammation which means that inflammation may have either detrimental or beneficial effects depending on the site, the time of induction, the concentration of mediators and the microenvironment (Morganti-Kossmann et al., 2002). This duality was demonstrated for IL-1 which aside from its pro-inflammatory effects also seems to participate in tissue repair processes, especially when induced at later stages, via stimulation of neurotrophic factors synthesis (Spranger et al., 1990; DeKosky et al., 1994; Herx et al., 2000), astrocyte proliferation (Appel et al., 1997) and involvement in synaptic plasticity (Fagan & Gage, 1990; Bellinger et al., 1993; Ide et al., 1996).

IL-6 is another cytokine that has been studied in TBI. IL-6 was found to have also a dual role in inflammation with either regulatory, anti-inflammatory or inflammatory effects depending on the time course and extent of expression (Allan & Rothwell, 2001; Morganti-Kossmann et al., 2002). The neurotrophic properties of IL-6 are mediated by inhibition of TNFa synthesis, induction of IL-1ra and nerve growth factor and attenuation of oxidative stress (Morganti-Kossmann et al., 2001). On the contrary, IL-6 promotes inflammatory processes by stimulating the production of chemokines and adhesion molecules and the recruitment of leukocytes (Romano et al., 1997). Elevated levels of IL-6 were observed in the cerebrospinal fluid (CSF) and in the serum of patients with TBI and this increase was correlated with a favorable neurological outcome (Singhal et al., 2002; Chiaretti et al., 2008). In contrast, other studies demonstrated that IL-6 levels were correlated to the clinical severity of TBI patients (Arand et al., 2001; Minambres et al., 2003). Studies in animal models provide evidence for a neuroprotective effect of IL-6. IL-6 was found at elevated levels in experimental TBI (Shohami et al., 1994). Mice deficient for IL-6 had increased numbers of apoptotic neurons, increased oxidative stress and delayed healing of the tissue (Penkowa et al., 2000), whereas the same group demonstrated that IL-6 transgenic mice exhibited increased reduction of oxidative stress and apoptotic cell death after a cryogenic brain injury (Penkowa et al., 2003).

Tumor necrosis factor-a (TNFa) is another cytokine with a well-documented role in TBI. TNFa mRNA and protein is elevated in the early period after experimental TBI and before the infiltration of leukocytes suggesting that the early source of TNFa production are the resident cells (Riva-Depaty et al., 1994). Elevated levels were also observed in the clinical setting of TBI patients (Goodman et al., 1990; Csuka et al., 1999). TNFa has proinflammatory properties similar to that of IL-1 and exacerbates inflammation and secondary brain damage after TBI (Allan & Rothwell, 2001). Early upregulation of neuronal TNFa expression after TBI was found to contribute to subsequent neurological dysfunction (Knoblach et al., 1999). Inhibition of TNFa by the HU-211 compound (a novel TNFa production inhibitor), pentoxyfilline and TNF-binding protein resulted in improved neurological outcome after closed head injury (Shohami et al., 1997). However, in a phase III clinical trial, administration of the HU-211 compound in patients with TBI failed to show improved outcome 6 months after the injury, compared to the placebo group (Maas et al., 2006). These data indicate that neurodegeneration is mediated through various pathological pathways and neuroprotection cannot be achieved by blocking a single mediator as other alternative pathways may be activated leading to neuronal loss. Furthermore, as reported with IL-1, TNFa also has neuroprotective effects and can enhance recovery processes. In a very interesting study, knockout mice for the TNFa gene exhibited milder behavioral deficits compared to the wild-type mice during the acute period post-injury. However, in the long term period (4 weeks post-injury) knockout mice did not recover as well as the wild-type mice, had persistent motor deficits and greater cortical tissue loss (Scherbel et al.,

Traumatic Brain Injury and Inflammation: Emerging Role of Innate and Adaptive Immunity 29

enhance neuronal survival (M2) through the release of anti-inflammatory cytokines and neurotrophic factors. However, it is possible that M1 and M2 phenotypes may represent the two extremes of a wide spectrum of phenotypes that microglia can have in response to the type, intensity, persistence of the stimuli and the microenvironment interactions (Mantovani et al., 2004). In fact, microglia have plastic properties and at different stages of the disease can acquire diverse phenotypes and functions that can be either detrimental or beneficial. The activation process begins when resting microglia detect the noxious stimuli or the subproducts of tissue damage. Microglia become activated, release inflammatory mediators, express surface molecules and remove cellular debris by phagocytosis. Once the toxic factors are eliminated and under the influences of the invading immune cells and the normal CNS cells activated microglia acquire a neurotrophic phenotype and release anti-inflammatory cytokines and neurotrophic factors. After a certain period of time inflammation is resolved and the activating microglia return to a resting-surveying state retaining some kind of memory of the processes. However, under not fully elucidated conditions, this delicate balance between activation-termination and neurotoxic-neurotrophic phenotype can be disrupted leading to excessive, uncontrolled or prolonged activation of microglia with destructive consequences in neuronal survival. Excessive and dysregulated microglia activation were elicited after intense and severe CNS insults. Moreover, insufficient recruitment of systemic immune cells to the CNS site of lesion may result in an inability to suppress and terminate the microglia activation or to turn them into a neuroprotective phenotype (Kempermann & Neumann, 2003; Hanisch & Kettenmann, 2007; Popovich & Longbrake, 2008; Rivest, 2009; Schwartz & Shechter, 2010). Thus, dysregulation of the innate or adaptive immune system may mediate excessive inflammatory damage following brain insults. It is obvious that a better understanding of the interaction mechanisms between

Several studies have investigated the microglia function after TBI. The release of various mediators in the extracellular space after the injured site alters the expression profile of local microglia. In a very interesting imaging study of fluorescent labeled microglia it was shown that microglia from the intact brain that are nearby the injured site extend their processes which reach the damaged site. There the processes and without cell body movement, converge and fuse together to form a spherical area of containment that separate the healthy from the injured tissue. In other words fused microglial processes act as a barrier that contains the tissue debris. This highly dynamic movement of microglial processes is under

The time of induction and the duration of microglia activation after TBI were found to be different from other brain insults such as cerebral ischemia. Studies in humans with TBI have revealed a striking delay of microglial activation and proliferation. Markers of microglial activation and proliferation were not detected until 3 days post TBI (Beschorner et al., 2000; Engel et al., 2000) whereas the same markers were expressed early in cerebral ischemia (Postler et al., 1997). This observation although in line with some findings in experimental models (Aihara et al., 1995; Holmin et al., 1997) cannot be fully understood. It is possible to reflect different activation cascades of microglia after TBI compared to other brain insults. However this window delay of microglial activation after TBI may provide a

Several studies in TBI have also demonstrated that inflammation can persist for long period of time after the primary traumatic brain insult. Studies in rodents have revealed reactive astrocytosis for over a year following brain injury resulting in chronic progressive neuronal

immune cells may facilitate the introduction of novel therapies.

the chemotactic influence of extracellular ATP (Davalos et al., 2005).

therapeutic opportunity when the target would be the microglial activation.

1999). These results suggest that the time, concentration and the site of TNFa induction may determine the driving of inflammatory processes towards neurodegeneration or neuroprotection.

#### **3. Innate immunity**

Microglia, the brain's resident macrophages, are the main cell type of the innate immune system of the brain. Microglia, although debatable, seem to originate from bone marrow monocytic cells which invade the CNS during embryonic development (Chan et al., 2007). Microglia provide a first line of regional defense in the CNS against various pathological insults. They are scattered throughout the CNS although some regional differences in their localization have been reported as they are more densely distributed in the gray than in the white matter and in structures like hippocampus, basal ganglia and substantia nigra (Block et al., 2007).

While resting, microglia have a highly ramified morphology with symmetrically extended, motile processes that form a network, which continuously monitor the local microenvironment of the brain parenchyma being the most susceptible sensors of brain pathology (Nimmerjahn et al., 2005; Kettenmann et al., 2011). In physiological conditions they provide surveillance of the CNS homeostasis and they sense neuronal and astrocytic activity and other physiological changes such as pH shifts, ion currents and neurotransmitter release (Farber & Kettenmann, 2005). This is achieved by the expression of numerous receptors by the microglia establishing a delicate neuron-microglia communication (McCluskey & Lampson, 2000). In an in vitro study the normal neuronal activity was found to inhibit the effects of microglia activators such as interferon-γ signifying the importance of cell to cell interactions (Neumann et al., 1996).

Various brain insults including bacterial lipopolysaccharide (LPS), cytokines, b-amyloid peptide and damaged tissue can result in activation of microglia (Nakamura, 2002). Upon activation, the cell size increases and the morphology dramatically changes to an amoeboid structure which facilitates the migration of microglial cells towards the lesion site and the phagocytosis of cellular debris and toxic substances (Raivich, 2005). In response to noxious stimuli microglia also proliferate and migrate to the lesion site. The rapidly chemotactic convergence to the site of injury is mediated by ATP, glutamate and other chemotactic agents released by the injured cells (Davalos et al., 2005; Liu et al., 2009). At this point the morphology of activated microglia cannot be discriminated from that of infiltrating macrophages using standard immunohistochemical techniques (Streit et al., 1999; Loane & Byrnes, 2010).

A significant part in the activation of microglia after inflammatory stimuli is the expression of constitutive and inducible surface receptors. Activated microglia express pattern recognition receptors, cytokine and chemokine receptors, phagocytic receptors, Fc and complement receptors, receptors for glutamate, growth factors and several other molecules (Gebicke-Haerter et al., 1996; Cho et al., 2006; Kettenmann et al., 2011). Activated microglia also express on their surface MHC class I and II molecules, making them able to present antigenic peptides and thus modulating T cell responses (Aloisi, 2001).

The specific profile of the surface receptors determine the phenotype of microglia and their functional properties. In line with macrophages phenotype, activated microglia may be neurotoxic (M1) due to the secretion of pro-inflammatory cytokines and reactive oxygen and nitrogen species. In contrast, activation of microglia may enable them to maintain and

1999). These results suggest that the time, concentration and the site of TNFa induction may determine the driving of inflammatory processes towards neurodegeneration or

Microglia, the brain's resident macrophages, are the main cell type of the innate immune system of the brain. Microglia, although debatable, seem to originate from bone marrow monocytic cells which invade the CNS during embryonic development (Chan et al., 2007). Microglia provide a first line of regional defense in the CNS against various pathological insults. They are scattered throughout the CNS although some regional differences in their localization have been reported as they are more densely distributed in the gray than in the white matter and in structures like hippocampus, basal ganglia and substantia nigra (Block

While resting, microglia have a highly ramified morphology with symmetrically extended, motile processes that form a network, which continuously monitor the local microenvironment of the brain parenchyma being the most susceptible sensors of brain pathology (Nimmerjahn et al., 2005; Kettenmann et al., 2011). In physiological conditions they provide surveillance of the CNS homeostasis and they sense neuronal and astrocytic activity and other physiological changes such as pH shifts, ion currents and neurotransmitter release (Farber & Kettenmann, 2005). This is achieved by the expression of numerous receptors by the microglia establishing a delicate neuron-microglia communication (McCluskey & Lampson, 2000). In an in vitro study the normal neuronal activity was found to inhibit the effects of microglia activators such as interferon-γ signifying the importance of cell to cell interactions

Various brain insults including bacterial lipopolysaccharide (LPS), cytokines, b-amyloid peptide and damaged tissue can result in activation of microglia (Nakamura, 2002). Upon activation, the cell size increases and the morphology dramatically changes to an amoeboid structure which facilitates the migration of microglial cells towards the lesion site and the phagocytosis of cellular debris and toxic substances (Raivich, 2005). In response to noxious stimuli microglia also proliferate and migrate to the lesion site. The rapidly chemotactic convergence to the site of injury is mediated by ATP, glutamate and other chemotactic agents released by the injured cells (Davalos et al., 2005; Liu et al., 2009). At this point the morphology of activated microglia cannot be discriminated from that of infiltrating macrophages using

standard immunohistochemical techniques (Streit et al., 1999; Loane & Byrnes, 2010).

antigenic peptides and thus modulating T cell responses (Aloisi, 2001).

A significant part in the activation of microglia after inflammatory stimuli is the expression of constitutive and inducible surface receptors. Activated microglia express pattern recognition receptors, cytokine and chemokine receptors, phagocytic receptors, Fc and complement receptors, receptors for glutamate, growth factors and several other molecules (Gebicke-Haerter et al., 1996; Cho et al., 2006; Kettenmann et al., 2011). Activated microglia also express on their surface MHC class I and II molecules, making them able to present

The specific profile of the surface receptors determine the phenotype of microglia and their functional properties. In line with macrophages phenotype, activated microglia may be neurotoxic (M1) due to the secretion of pro-inflammatory cytokines and reactive oxygen and nitrogen species. In contrast, activation of microglia may enable them to maintain and

neuroprotection.

et al., 2007).

**3. Innate immunity** 

(Neumann et al., 1996).

enhance neuronal survival (M2) through the release of anti-inflammatory cytokines and neurotrophic factors. However, it is possible that M1 and M2 phenotypes may represent the two extremes of a wide spectrum of phenotypes that microglia can have in response to the type, intensity, persistence of the stimuli and the microenvironment interactions (Mantovani et al., 2004). In fact, microglia have plastic properties and at different stages of the disease can acquire diverse phenotypes and functions that can be either detrimental or beneficial. The activation process begins when resting microglia detect the noxious stimuli or the subproducts of tissue damage. Microglia become activated, release inflammatory mediators, express surface molecules and remove cellular debris by phagocytosis. Once the toxic factors are eliminated and under the influences of the invading immune cells and the normal CNS cells activated microglia acquire a neurotrophic phenotype and release anti-inflammatory cytokines and neurotrophic factors. After a certain period of time inflammation is resolved and the activating microglia return to a resting-surveying state retaining some kind of memory of the processes. However, under not fully elucidated conditions, this delicate balance between activation-termination and neurotoxic-neurotrophic phenotype can be disrupted leading to excessive, uncontrolled or prolonged activation of microglia with destructive consequences in neuronal survival. Excessive and dysregulated microglia activation were elicited after intense and severe CNS insults. Moreover, insufficient recruitment of systemic immune cells to the CNS site of lesion may result in an inability to suppress and terminate the microglia activation or to turn them into a neuroprotective phenotype (Kempermann & Neumann, 2003; Hanisch & Kettenmann, 2007; Popovich & Longbrake, 2008; Rivest, 2009; Schwartz & Shechter, 2010). Thus, dysregulation of the innate or adaptive immune system may mediate excessive inflammatory damage following brain insults. It is obvious that a better understanding of the interaction mechanisms between immune cells may facilitate the introduction of novel therapies.

Several studies have investigated the microglia function after TBI. The release of various mediators in the extracellular space after the injured site alters the expression profile of local microglia. In a very interesting imaging study of fluorescent labeled microglia it was shown that microglia from the intact brain that are nearby the injured site extend their processes which reach the damaged site. There the processes and without cell body movement, converge and fuse together to form a spherical area of containment that separate the healthy from the injured tissue. In other words fused microglial processes act as a barrier that contains the tissue debris. This highly dynamic movement of microglial processes is under the chemotactic influence of extracellular ATP (Davalos et al., 2005).

The time of induction and the duration of microglia activation after TBI were found to be different from other brain insults such as cerebral ischemia. Studies in humans with TBI have revealed a striking delay of microglial activation and proliferation. Markers of microglial activation and proliferation were not detected until 3 days post TBI (Beschorner et al., 2000; Engel et al., 2000) whereas the same markers were expressed early in cerebral ischemia (Postler et al., 1997). This observation although in line with some findings in experimental models (Aihara et al., 1995; Holmin et al., 1997) cannot be fully understood. It is possible to reflect different activation cascades of microglia after TBI compared to other brain insults. However this window delay of microglial activation after TBI may provide a therapeutic opportunity when the target would be the microglial activation.

Several studies in TBI have also demonstrated that inflammation can persist for long period of time after the primary traumatic brain insult. Studies in rodents have revealed reactive astrocytosis for over a year following brain injury resulting in chronic progressive neuronal

Traumatic Brain Injury and Inflammation: Emerging Role of Innate and Adaptive Immunity 31

processing of the relevant antigen and its subsequent presentation on class I or class II

Another hypothesis that has been introduced is that the initial activation of T cells takes place within CNS. However, data have shown that the interaction between microglia and T cells is incomplete and insufficient to support a full activation and proliferation of T cells. In an ex vivo study this interaction resulted in increased T cell apoptosis which may reflect a regulatory function of microglia upon T cell responses (Ford et al., 1996). It seems possible that activated microglia may influence the function and maintenance of auto-reactive T cells in the CNS either directly by presenting the antigen causing re-activation of the T cells or indirectly by determining the local inflammatory/anti-inflammatory microenvironment and

The peripheral activation of T cells against cerebral antigens is supported by a number of studies. Several studies have provided evidence for a traveling of the antigen from the CNS to the peripheral lymph nodes. Fluorescent substances injected into the CNS of animal models were detected in the cervical lymph nodes in a few hours after the injection. In addition, intracerebrally infused protein antigen was found to elicit the accumulation of antigen-specific CD8+ T cells 3 days after the injection (Ling et al., 2003). Moreover, experimental and human studies of CNS trauma have revealed the presence of auto-reactive T cells against cerebral antigens. Isolated T cells from an animal model of spinal cord injury when injected intravenously into naive recipients were found to induce spinal cord neuroinflammation and transient hind limb paralysis and ataxic gait (Popovich et al., 1996). Additionally auto-reactive T cells against myelin basic protein were found in increased frequencies in patients with spinal cord injury compared to multiple sclerosis patients and

Adaptive immunity may mediate either pathogenic or reparative processes based of the inflammatory conditions of the microenvironment during activation of T-cells. It has been hypothesized that Th1 immune response may aggravate brain damage by pro-inflammatory actions whereas Th2 response may alleviate brain damage by anti-inflammatory and neurotrophic effects. In a study of freeze cerebral injury activated T cells were found to exacerbate brain damage when transferred to rats 24h before the injury (Fee et al., 2003). In contrast, in an very intriguing study in animals with injury in the optic nerve it was shown that intraperitoneally injected anti-myelin basic protein specific T cells prevented the secondary degeneration of retinal ganglion cells (Moalem et al., 1999). These significant data were also replicated in an animal model of spinal cord injury. It was shown that autoreactive T cells against myelin basic protein or active immunization with myelin basic protein improved the recovery by promoting neuroprotective and regenerative processes (Hauben et al., 2000). Furthermore, it was showed that Th2 cells specific for myelin basic protein had protective effects on neuronal survival. This neuroprotective effect of the antigen-specific T cells was influenced by the extent of non-specific activation of the T cells (Wolf et al., 2002). In another study of peripheral facial nerve injury CD4+ T cells were found

These observations of beneficial effects of autoreactive T cells led to the introduction of the term "protective autoimmunity" implying that the recognition of an exposed self antigen by T cells can result in protection, repair and maintenance of the functional integrity of a tissue rather than the initiation of an autoimmune process. (Schwartz et al., 2003; Schwartz & Shechter, 2010). Regulatory T cells (CD4+CD25+Foxp3+) that suppress autoimmune activity seem to play a central role in protective autoimmunity. The concept of protective

MHC (Ankeny et al., 2006).

the recruitment of T cells.

normal controls (Kil et al., 1999).

to mediate facial motor neurons survival (Serpe et al., 2003).

tissue loss (Smith et al., 1997; Holmin & Mathiesen, 1999). In primates, microglia activation was found to persist for at least 12 months (Nagamoto-Combs et al., 2007). Post-mortem studies in humans have shown persistent elevated microglial activity several years after TBI (Gentleman et al., 2004). In addition, a recent PET imaging study in humans using a ligand that binds to activated microglia revealed increased microglial activation for up to 17 years after TBI (Ramlackhansingh et al., 2011). Persistent microglial activation is believed to underline both chronic neuroprotective and destructive processes. The precise mechanisms for the persistence of inflammatory processes after TBI are not fully understood. It is believed that a severe initial neuronal injury with excessive cytokine signals may lead to enhanced activation of microglia that further aggravate brain damage feeding a selfsustaining and self-propelling prolonged vicious circle of neurotoxicity and progressive degeneration (Gao & Hong, 2008). This dysregulated and uncontrolled microglial activation may be the key for chronic, long-lived and destructive inflammatory processes. The longterm microglia activation may also provide insights into a potential causative link between head injury and Alzheimer's disease.

#### **4. Adaptive immunity**

Adaptive immunity refers to an antigen-specific response either cell-mediated or humoral aiming at elimination of pathogenic factors. Adaptive immunity is mediated by B and T lymphocytes. In experiment TBI, T cells were found to infiltrate the brain parenchyma in a biphasic manner: immediately after the primary impact as a result of disruption of BBB and in a delayed phage with increased numbers of T cells which represents an active infiltration of specific targeting T-cells (Czigner et al., 2007). In other studies it was shown that T cell infiltration in the damaged tissue occurred 3-14 days after CNS trauma and persisted for 6 months (Kigerl et al., 2006; Beck et al., 2010). In post-mortem human studies CD4+ and CD8+ were identified in the injured tissue after spinal cord injury (Fleming et al., 2006).

It is known that the transformation of naive T cells into effector T cells requires an initial antigen presentation in secondary lymphoid organs and a re-activation after re-exposure to their antigen. However, the exact mechanics of adaptive immune response after brain injury have not been fully elucidated and some aspects remain obscure. It is known that naive T cells against CNS antigens are circulating in the periphery. After brain insults the cerebral auto-antigens are exposed to the peripheral blood cells. The activation of naive T cells can take place in the peripheral lymph nodes as a result of BBB disruption and release of cerebral antigens into the bloodstream alone or in conjunction with the brain APCs (Lenzlinger et al., 2001; Ling et al., 2003; Karman et al., 2004). After activation, T cells traffic to the CNS under the influence of chemokine gradient. Microglia are already activated as a result of brain tissue damage and release of inflammatory mediators. Activated microlgia release at the site of injury cytokines and chemokines, express various surface molecules including complement components and induce the expression of adhesion molecules by the endothelial cells. These alterations induce the recruitment of the T cells into the injury site. Within the CNS, T cells become re-activated against their antigen which is presented to them by local microglia and macrophages.

As already mentioned MHC expression is almost absent in normal brain parenchyma. After brain trauma activated microglia upregulate the expression of MHC class I and class II and the expression of adhesion molecules and costimulatory factors. Activated microglia can act as antigen-presenting cells to T cells by phagocytosis of the tissue debris,

tissue loss (Smith et al., 1997; Holmin & Mathiesen, 1999). In primates, microglia activation was found to persist for at least 12 months (Nagamoto-Combs et al., 2007). Post-mortem studies in humans have shown persistent elevated microglial activity several years after TBI (Gentleman et al., 2004). In addition, a recent PET imaging study in humans using a ligand that binds to activated microglia revealed increased microglial activation for up to 17 years after TBI (Ramlackhansingh et al., 2011). Persistent microglial activation is believed to underline both chronic neuroprotective and destructive processes. The precise mechanisms for the persistence of inflammatory processes after TBI are not fully understood. It is believed that a severe initial neuronal injury with excessive cytokine signals may lead to enhanced activation of microglia that further aggravate brain damage feeding a selfsustaining and self-propelling prolonged vicious circle of neurotoxicity and progressive degeneration (Gao & Hong, 2008). This dysregulated and uncontrolled microglial activation may be the key for chronic, long-lived and destructive inflammatory processes. The longterm microglia activation may also provide insights into a potential causative link between

Adaptive immunity refers to an antigen-specific response either cell-mediated or humoral aiming at elimination of pathogenic factors. Adaptive immunity is mediated by B and T lymphocytes. In experiment TBI, T cells were found to infiltrate the brain parenchyma in a biphasic manner: immediately after the primary impact as a result of disruption of BBB and in a delayed phage with increased numbers of T cells which represents an active infiltration of specific targeting T-cells (Czigner et al., 2007). In other studies it was shown that T cell infiltration in the damaged tissue occurred 3-14 days after CNS trauma and persisted for 6 months (Kigerl et al., 2006; Beck et al., 2010). In post-mortem human studies CD4+ and CD8+

It is known that the transformation of naive T cells into effector T cells requires an initial antigen presentation in secondary lymphoid organs and a re-activation after re-exposure to their antigen. However, the exact mechanics of adaptive immune response after brain injury have not been fully elucidated and some aspects remain obscure. It is known that naive T cells against CNS antigens are circulating in the periphery. After brain insults the cerebral auto-antigens are exposed to the peripheral blood cells. The activation of naive T cells can take place in the peripheral lymph nodes as a result of BBB disruption and release of cerebral antigens into the bloodstream alone or in conjunction with the brain APCs (Lenzlinger et al., 2001; Ling et al., 2003; Karman et al., 2004). After activation, T cells traffic to the CNS under the influence of chemokine gradient. Microglia are already activated as a result of brain tissue damage and release of inflammatory mediators. Activated microlgia release at the site of injury cytokines and chemokines, express various surface molecules including complement components and induce the expression of adhesion molecules by the endothelial cells. These alterations induce the recruitment of the T cells into the injury site. Within the CNS, T cells become re-activated against their antigen which is presented to

As already mentioned MHC expression is almost absent in normal brain parenchyma. After brain trauma activated microglia upregulate the expression of MHC class I and class II and the expression of adhesion molecules and costimulatory factors. Activated microglia can act as antigen-presenting cells to T cells by phagocytosis of the tissue debris,

were identified in the injured tissue after spinal cord injury (Fleming et al., 2006).

head injury and Alzheimer's disease.

them by local microglia and macrophages.

**4. Adaptive immunity** 

processing of the relevant antigen and its subsequent presentation on class I or class II MHC (Ankeny et al., 2006).

Another hypothesis that has been introduced is that the initial activation of T cells takes place within CNS. However, data have shown that the interaction between microglia and T cells is incomplete and insufficient to support a full activation and proliferation of T cells. In an ex vivo study this interaction resulted in increased T cell apoptosis which may reflect a regulatory function of microglia upon T cell responses (Ford et al., 1996). It seems possible that activated microglia may influence the function and maintenance of auto-reactive T cells in the CNS either directly by presenting the antigen causing re-activation of the T cells or indirectly by determining the local inflammatory/anti-inflammatory microenvironment and the recruitment of T cells.

The peripheral activation of T cells against cerebral antigens is supported by a number of studies. Several studies have provided evidence for a traveling of the antigen from the CNS to the peripheral lymph nodes. Fluorescent substances injected into the CNS of animal models were detected in the cervical lymph nodes in a few hours after the injection. In addition, intracerebrally infused protein antigen was found to elicit the accumulation of antigen-specific CD8+ T cells 3 days after the injection (Ling et al., 2003). Moreover, experimental and human studies of CNS trauma have revealed the presence of auto-reactive T cells against cerebral antigens. Isolated T cells from an animal model of spinal cord injury when injected intravenously into naive recipients were found to induce spinal cord neuroinflammation and transient hind limb paralysis and ataxic gait (Popovich et al., 1996). Additionally auto-reactive T cells against myelin basic protein were found in increased frequencies in patients with spinal cord injury compared to multiple sclerosis patients and normal controls (Kil et al., 1999).

Adaptive immunity may mediate either pathogenic or reparative processes based of the inflammatory conditions of the microenvironment during activation of T-cells. It has been hypothesized that Th1 immune response may aggravate brain damage by pro-inflammatory actions whereas Th2 response may alleviate brain damage by anti-inflammatory and neurotrophic effects. In a study of freeze cerebral injury activated T cells were found to exacerbate brain damage when transferred to rats 24h before the injury (Fee et al., 2003). In contrast, in an very intriguing study in animals with injury in the optic nerve it was shown that intraperitoneally injected anti-myelin basic protein specific T cells prevented the secondary degeneration of retinal ganglion cells (Moalem et al., 1999). These significant data were also replicated in an animal model of spinal cord injury. It was shown that autoreactive T cells against myelin basic protein or active immunization with myelin basic protein improved the recovery by promoting neuroprotective and regenerative processes (Hauben et al., 2000). Furthermore, it was showed that Th2 cells specific for myelin basic protein had protective effects on neuronal survival. This neuroprotective effect of the antigen-specific T cells was influenced by the extent of non-specific activation of the T cells (Wolf et al., 2002). In another study of peripheral facial nerve injury CD4+ T cells were found to mediate facial motor neurons survival (Serpe et al., 2003).

These observations of beneficial effects of autoreactive T cells led to the introduction of the term "protective autoimmunity" implying that the recognition of an exposed self antigen by T cells can result in protection, repair and maintenance of the functional integrity of a tissue rather than the initiation of an autoimmune process. (Schwartz et al., 2003; Schwartz & Shechter, 2010). Regulatory T cells (CD4+CD25+Foxp3+) that suppress autoimmune activity seem to play a central role in protective autoimmunity. The concept of protective

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In conclusion, neuroinflammation seems to play a key role in the pathophysiology of brain damage following TBI. A complex interaction between several components and mediators of the innate and adaptive immunity appear to determine the extent of inflammation and its nature, either destructive or reparative. A better understanding of these mechanisms that are implicated in the initiation, progression and termination of the inflammation and the communication between immune cells is required for the development of new and effective therapeutic strategies.

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**3** 

*USA* 

**Shared Genetic Effects among Measures of** 

*2Department of Medicine, University of Mississippi Medical Center, Jackson, MS* 

The aging process influences cognitive and physical functioning through a variety of biological mechanisms. Multiple facets of cognitive function decline with age, including executive function, memory, language, visuomotor coordination, and information processing speed. Strong epidemiological trends show that areas of brain injury due to ischemic damage also increase with age. Areas of ischemic damage known as leukoaraiosis appear as hyperintense spots on MRI of the white matter of the brain. Leukoaraiosis is a strong predictor of ischemic stroke and vascular dementia, independent of other known risk factors (Markus et al., 2005). It is also strongly associated with cognitive impairment and cognitive decline in individuals who have not yet progressed to dementia (Pantoni et al.,

Few studies have examined the genetic contribution to later-age cognitive changes in relationship to markers of subclinical ischemic brain injury such as leukoaraiosis. After increasing age, the main risk factors for leukoaraiosis are elevated blood pressure and lack of hypertension control (van Dijk et al., 2004). However, there is a significant amount of inter-individual variation in leukoaraiosis among subjects with similar duration and severity of hypertension (Schmidt et al., 2004; Szolnoki & Melegh, 2006). Cognitive functioning is also highly variable, and it is likely that genetic variability accounts for a significant portion of the variation in both structural characteristics of the brain such as

In this chapter, we present a review of the biological mechanisms that influence leukoaraiosis and cognitive function, discuss the public health implications of the clinical manifestations of cerebrovascular disease, and explore the broad genetic attributes that explain inter-individual variation and covaraition (i.e., pleiotropy) among these brain traits.

The human brain is composed of gray matter (the cerebral cortex) that is responsible for consciousness, movement, and cognition and white matter that consists of nerve fibers that

**1.1 Biological mechanisms that influence leukoaraiosis and cognitive function 1.1.1 Physiology and pathology of cerebrovascular disease and leukoaraiosis** 

leukoaraiosis and measures of cognitive function (Deary et al., 2004).

**1. Introduction**

2007; Schmidt et al., 2007).

**Cognitive Function and Leukoaraiosis** 

*1Department of Epidemiology, University of Michigan, Ann Arbor, MI* 

*3Department of Internal Medicine, Mayo Clinic, Rochester, MN* 

Jennifer A. Smith1, Thomas H. Mosley, Jr.2, Stephen T. Turner3 and Sharon L. R. Kardia1


### **Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis**

Jennifer A. Smith1, Thomas H. Mosley, Jr.2, Stephen T. Turner3 and Sharon L. R. Kardia1

*1Department of Epidemiology, University of Michigan, Ann Arbor, MI 2Department of Medicine, University of Mississippi Medical Center, Jackson, MS 3Department of Internal Medicine, Mayo Clinic, Rochester, MN USA* 

#### **1. Introduction**

38 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Wang, C. X. and Shuaib, A. (2002). Involvement of inflammatory cytokines in central

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nervous system injury. *Prog Neurobiol*, 67, 2, pp. 161-72.

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state. *J Neuroimmunol*, 133, 1-2, pp. 72-80.

pp. 1081-90.

*Neurotrauma*, 16, 4, pp. 299-309.

The aging process influences cognitive and physical functioning through a variety of biological mechanisms. Multiple facets of cognitive function decline with age, including executive function, memory, language, visuomotor coordination, and information processing speed. Strong epidemiological trends show that areas of brain injury due to ischemic damage also increase with age. Areas of ischemic damage known as leukoaraiosis appear as hyperintense spots on MRI of the white matter of the brain. Leukoaraiosis is a strong predictor of ischemic stroke and vascular dementia, independent of other known risk factors (Markus et al., 2005). It is also strongly associated with cognitive impairment and cognitive decline in individuals who have not yet progressed to dementia (Pantoni et al., 2007; Schmidt et al., 2007).

Few studies have examined the genetic contribution to later-age cognitive changes in relationship to markers of subclinical ischemic brain injury such as leukoaraiosis. After increasing age, the main risk factors for leukoaraiosis are elevated blood pressure and lack of hypertension control (van Dijk et al., 2004). However, there is a significant amount of inter-individual variation in leukoaraiosis among subjects with similar duration and severity of hypertension (Schmidt et al., 2004; Szolnoki & Melegh, 2006). Cognitive functioning is also highly variable, and it is likely that genetic variability accounts for a significant portion of the variation in both structural characteristics of the brain such as leukoaraiosis and measures of cognitive function (Deary et al., 2004).

In this chapter, we present a review of the biological mechanisms that influence leukoaraiosis and cognitive function, discuss the public health implications of the clinical manifestations of cerebrovascular disease, and explore the broad genetic attributes that explain inter-individual variation and covaraition (i.e., pleiotropy) among these brain traits.

#### **1.1 Biological mechanisms that influence leukoaraiosis and cognitive function 1.1.1 Physiology and pathology of cerebrovascular disease and leukoaraiosis**

The human brain is composed of gray matter (the cerebral cortex) that is responsible for consciousness, movement, and cognition and white matter that consists of nerve fibers that

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 41

an effect of leukoaraiosis on cognition. In particular, leukoaraiosis is more strongly associated with decreasing executive function than memory and is also associated with a decline in motor performance such as gait disturbances (Pantoni et al., 2007; Schmidt et al., 2007). The rate of progression of leukoaraiosis over time is also related to cognitive decline, and the severity of leukoaraiosis at baseline is a significant predictor of progression (Schmidt et al., 2007). It is also important to keep in mind, however, that other factors may affect the association between leukoaraiosis and cognitive decline such as brain atrophy and

Dementia is a heterogeneous group of disorders with variable etiology that involves impairment in cognitive domains such as memory, executive function, and language as well as specific physical impairments such as gait abnormalities that cause significant impairment in social or occupational function and represent a decline from a previous level of functioning (American Psychiatric Association, 2000). The differential diagnosis of vascular dementia (VaD), incorporates the underlying vascular cause as well as the cognitive and physical symptomology (Pohjasvaara et al., 2000), specifically "focal neurological signs and symptoms or laboratory evidence indicative of cerebrovascular disease (multiple infarctions involving cortex and underlying white matter) that are judged to be etiologically related to the disturbance" (American Psychiatric Association, 2000). Leukoaraiosis and multiple lacunar (small vessel) strokes, both caused by cerebrovascular disease, are the primary markers of VaD (Geldmacher & Whitehouse, 1997) and are thought to be contributors to cognitive impairment in individuals who have not yet progressed to dementia (Pantoni et al., 2007; Schmidt et al., 2007). Several studies have also shown that

**1.1.5 Complexity in the inter-relationships among clinical outcomes and sub-clinical** 

relationships among these clinical outcomes and subclinical measures, including:

Leukoaraiosis is a risk factor for cognitive decline and ischemic stroke.

A complex relationship exists among hypertension, leukoaraiosis, cognitive decline, dementia, and stroke. The figure below illustrates what is currently known about the inter-

Leukoaraiosis is thought to be a manifestation (sub-clinical marker) of cerebrovascular

Leukoaraiosis, ischemic stroke, and cognitive decline are included in the clinical criteria

Ischemic stroke (without additional evidence of leukoaraiosis) is a risk factor for

The clinical outcomes that are associated with cerebrovascular disease have large public health implications. Ischemic stroke accounts for 87% of all strokes, a leading cause of morbidity, mortality, and economic burden in the US (Roger et al., 2011). Stroke is the second most common cause of death and disability-adjusted life-years in industrialized

**1.2 Public health implications of the clinical manifestations of cerebrovascular** 

stroke (Pantoni et al., 2007; Schmidt et al., 2007).

**1.1.4 Cognitive decline and vascular dementia** 

leukoaraiosis is predictive of incident VaD (Prins et al., 2004).

Hypertension is a primary risk factor for leukoaraiosis.

for the diagnosis of vascular dementia.

**measures** 

**disease** 

disease.

cognitive decline.

transmit impulses among cerebral areas and to the central nervous system. Leukoaraiosis is visible as bright spots in the white matter on T2-weighted MRIs (Markus, 2008; O'Sullivan, 2008). Leukoaraiosis ranges in severity from small, distinct areas of white matter hyperintensity (punctuate lesions) to large regions of white matter hyperintensity (early confluent or confluent lesions) (O'Sullivan, 2008). Leukoaraiosis is thought to be a marker of cerebral small vessel disease (cerebrovascular disease) in the long, narrow penetrating arterioles that supply the white matter with blood (Markus, 2008). This type of small vessel disease is defined by areas of diffuse arteriolosclerosis with deposits of a proteinaceous substance that includes fibrin, amyloid, and collagen, which results in thickening of the vessel and chronic ischemia that leads to demyelination, axonal loss, and gliosis (Markus, 2008; O'Sullivan, 2008). It occurs in regions of the brain that have low perfusion pressure, such as the deep white matter, and results in chronic ischemia and multiple diffuse infarctions due to small vessel occlusions (lacunar infarctions), both of which are visible as hyperintensity on MRIs (Markus, 2008). In regions of leukoaraiosis, there appears to be decreased blood flow (hypoperfusion) and impaired ability to regulate blood flow (autoregulation) (Markus, 2008).

Recently, it has been suggested that endothelial dysfunction, characterized by the inability of endothelial cells to perform tasks such as mediation of coagulation, platelet adhesion, and immune response, may be the intermediate process between hypertension and the alterations in blood flow observed in areas of leukoaraiosis (Hassan et al., 2003; Markus, 2008). Circulating endothelial markers may show a pro-coagulant pattern of endothelial function (e.g. higher circulating levels of thrombomodulin (*TM*) and lower circulating levels of tissue factor pathway inhibitor (*TFPI*)) that is specific to leukoaraiosis (Hassan et al., 2003) and may be related to progression of leukoaraiosis (Markus et al., 2005). Further support for endothelial dysfunction comes from the strong association between leukoaraiosis and elevated homocysteine level, which is hypothesized to be a mediator of endothelial damage (Hassan et al., 2004).

#### **1.1.2 Hypertension as a predictor of leukoaraiosis**

Development of leukoaraiosis is thought to be a marker of one of the major mechanistic pathways between hypertension and clinical endpoints such as ischemic stroke and vascular dementia, and is a known risk factor for both of these endpoints (Markus et al., 2005; O'Sullivan, 2008). Inadequately controlled hypertension gives rise to ischemic damage of the brain that is thought to be the manifestation of underlying cerebrovascular disease (Turner & Boerwinkle, 2000). Several studies have also demonstrated an association between hypertension in midlife and cognitive decline in later life (Launer et al., 2000), and it has been hypothesized that this is due to the cumulative effects of subclinical damage due to small vessel disease (Knopman et al., 2001) with leukoaraiosis as a detectable sign of one of the main mechanistic pathways implicated (Sierra & Coca, 2006). Hypertension is a leading risk factor for ischemic stroke (Roger et al., 2011) and for cognitive decline leading to vascular dementia (Launer et al., 2000). Hypertension affects approximately 1 in 3 American adults (76.4 million people), and accounts for \$43.5 billion in yearly direct and indirect costs in the United States (Roger et al., 2011).

#### **1.1.3 The relationship between leukoaraiosis and cognitive function**

In a review of studies pertaining to leukoaraiosis and cognition, Pantoni et al. (2007) conclude that despite different study characteristics, there is almost invariably evidence of an effect of leukoaraiosis on cognition. In particular, leukoaraiosis is more strongly associated with decreasing executive function than memory and is also associated with a decline in motor performance such as gait disturbances (Pantoni et al., 2007; Schmidt et al., 2007). The rate of progression of leukoaraiosis over time is also related to cognitive decline, and the severity of leukoaraiosis at baseline is a significant predictor of progression (Schmidt et al., 2007). It is also important to keep in mind, however, that other factors may affect the association between leukoaraiosis and cognitive decline such as brain atrophy and stroke (Pantoni et al., 2007; Schmidt et al., 2007).

#### **1.1.4 Cognitive decline and vascular dementia**

40 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

transmit impulses among cerebral areas and to the central nervous system. Leukoaraiosis is visible as bright spots in the white matter on T2-weighted MRIs (Markus, 2008; O'Sullivan, 2008). Leukoaraiosis ranges in severity from small, distinct areas of white matter hyperintensity (punctuate lesions) to large regions of white matter hyperintensity (early confluent or confluent lesions) (O'Sullivan, 2008). Leukoaraiosis is thought to be a marker of cerebral small vessel disease (cerebrovascular disease) in the long, narrow penetrating arterioles that supply the white matter with blood (Markus, 2008). This type of small vessel disease is defined by areas of diffuse arteriolosclerosis with deposits of a proteinaceous substance that includes fibrin, amyloid, and collagen, which results in thickening of the vessel and chronic ischemia that leads to demyelination, axonal loss, and gliosis (Markus, 2008; O'Sullivan, 2008). It occurs in regions of the brain that have low perfusion pressure, such as the deep white matter, and results in chronic ischemia and multiple diffuse infarctions due to small vessel occlusions (lacunar infarctions), both of which are visible as hyperintensity on MRIs (Markus, 2008). In regions of leukoaraiosis, there appears to be decreased blood flow (hypoperfusion) and impaired ability to regulate blood flow

Recently, it has been suggested that endothelial dysfunction, characterized by the inability of endothelial cells to perform tasks such as mediation of coagulation, platelet adhesion, and immune response, may be the intermediate process between hypertension and the alterations in blood flow observed in areas of leukoaraiosis (Hassan et al., 2003; Markus, 2008). Circulating endothelial markers may show a pro-coagulant pattern of endothelial function (e.g. higher circulating levels of thrombomodulin (*TM*) and lower circulating levels of tissue factor pathway inhibitor (*TFPI*)) that is specific to leukoaraiosis (Hassan et al., 2003) and may be related to progression of leukoaraiosis (Markus et al., 2005). Further support for endothelial dysfunction comes from the strong association between leukoaraiosis and elevated homocysteine level, which is hypothesized to be a mediator of endothelial damage

Development of leukoaraiosis is thought to be a marker of one of the major mechanistic pathways between hypertension and clinical endpoints such as ischemic stroke and vascular dementia, and is a known risk factor for both of these endpoints (Markus et al., 2005; O'Sullivan, 2008). Inadequately controlled hypertension gives rise to ischemic damage of the brain that is thought to be the manifestation of underlying cerebrovascular disease (Turner & Boerwinkle, 2000). Several studies have also demonstrated an association between hypertension in midlife and cognitive decline in later life (Launer et al., 2000), and it has been hypothesized that this is due to the cumulative effects of subclinical damage due to small vessel disease (Knopman et al., 2001) with leukoaraiosis as a detectable sign of one of the main mechanistic pathways implicated (Sierra & Coca, 2006). Hypertension is a leading risk factor for ischemic stroke (Roger et al., 2011) and for cognitive decline leading to vascular dementia (Launer et al., 2000). Hypertension affects approximately 1 in 3 American adults (76.4 million people), and accounts for \$43.5 billion in yearly direct and indirect costs

In a review of studies pertaining to leukoaraiosis and cognition, Pantoni et al. (2007) conclude that despite different study characteristics, there is almost invariably evidence of

(autoregulation) (Markus, 2008).

(Hassan et al., 2004).

**1.1.2 Hypertension as a predictor of leukoaraiosis** 

in the United States (Roger et al., 2011).

**1.1.3 The relationship between leukoaraiosis and cognitive function** 

Dementia is a heterogeneous group of disorders with variable etiology that involves impairment in cognitive domains such as memory, executive function, and language as well as specific physical impairments such as gait abnormalities that cause significant impairment in social or occupational function and represent a decline from a previous level of functioning (American Psychiatric Association, 2000). The differential diagnosis of vascular dementia (VaD), incorporates the underlying vascular cause as well as the cognitive and physical symptomology (Pohjasvaara et al., 2000), specifically "focal neurological signs and symptoms or laboratory evidence indicative of cerebrovascular disease (multiple infarctions involving cortex and underlying white matter) that are judged to be etiologically related to the disturbance" (American Psychiatric Association, 2000). Leukoaraiosis and multiple lacunar (small vessel) strokes, both caused by cerebrovascular disease, are the primary markers of VaD (Geldmacher & Whitehouse, 1997) and are thought to be contributors to cognitive impairment in individuals who have not yet progressed to dementia (Pantoni et al., 2007; Schmidt et al., 2007). Several studies have also shown that leukoaraiosis is predictive of incident VaD (Prins et al., 2004).

#### **1.1.5 Complexity in the inter-relationships among clinical outcomes and sub-clinical measures**

A complex relationship exists among hypertension, leukoaraiosis, cognitive decline, dementia, and stroke. The figure below illustrates what is currently known about the interrelationships among these clinical outcomes and subclinical measures, including:


#### **1.2 Public health implications of the clinical manifestations of cerebrovascular disease**

The clinical outcomes that are associated with cerebrovascular disease have large public health implications. Ischemic stroke accounts for 87% of all strokes, a leading cause of morbidity, mortality, and economic burden in the US (Roger et al., 2011). Stroke is the second most common cause of death and disability-adjusted life-years in industrialized

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 43

leukoaraiosis have primarily concentrated on genes in pathways known to be involved in hypertension, vasculature, and endothelial damage. Although initial findings have been encouraging, no specific genetic factors have been unequivocally shown to be associated with this trait (Paternoster et al., 2009). Genome-wide association studies (GWAS) for this trait have also been limited, but are currently being conducted in several ethnic groups. To date, the most promising evidence for association is with a region on chromosome 17q25 in

For cognitive decline, the most promising candidate genes include those that are associated with hypertension, leukoaraiosis, Alzheimer's Disease (AD), normal cognitive functioning, cardiovascular function, oxidative stress, and inflammation (Deary et al., 2004), though candidate gene studies have not yet established any specific genetic factors that definitively affect cognitive decline. GWAS for a variety of cognitive traits are currently underway. GWASs that examine the change of cognitive traits over time in multiple cohorts will be

Pleiotropy is most simply defined as the condition in which variation in a single gene affects multiple traits (Hodgkin, 1998). Defined in this manner, pleiotropic genes range from those that encode proteins involved in a single biological pathway that influences multiple disease processes and/or organ systems to those that play entirely different roles in multiple biological pathways. In some instances, pleiotropy is "the phenomenon in which a single gene controls several distinct, seemingly unrelated, phenotypic effects" (Zou et al., 2008). A well-known example of pleiotropy in humans is the 4 allele of the apolioprotein E (*APOE*) gene (Dickstein et al., 2010). *APOE* is a plasma cholesterol transport molecule that resides primarily on very low density lipoproteins, and the 4 allele has been shown to be a risk factor for coronary heart disease and stroke through mechanisms related directly to lipid transport. However, the 4 alelle is also a risk factor for AD and cognitive decline, with those carrying the allele having a younger age of onset as well as an accelerated pace of cognitive decline. Though the precise mechanism by which 4 leads to cognitive decline is not known, the main hypotheses are through pathways not directly related or only tangentially related to lipid transport. *APOE* appears to affect brain traits through its role as a chaperone for the amyloid beta protein

The study of pleiotropy in model organisms and humans serves several functions. In model organisms, it serves to further the understanding and elucidation of the complex biological pathways that regulate the development of traits, providing information about normal cellular function, normal development and function at the organismal level, connections between previously unrecognized biological processes, and increased predictive ability in breeding programs (Hodgkin, 1998). It also it provides insight into the mechanisms of evolution, as effects on multiple traits due to a single genetic variant may pose severe evolutionary constraints (Cheverud et al., 2004). The findings from pleiotropy studies in model organisms, particularly the high degree of connectivity among transcriptional modules, have strong implications for understanding the pleiotropic genetic mechanisms that are also operating in humans. A greater understanding of the underlying pleiotropic mechanisms contributing to human health and disease has the potential to allow for earlier identification of individuals at increased risk for disease, the development of more efficacious treatments, and the tailoring of particular treatments to people most likely to

particularly useful for identifying genetic factors associated with cognitive decline.

European Americans (Fornage et al., 2011).

and/or mediation of the phosphorylation of the tau protein.

**1.3.2 Role of pleiotropy** 

respond positively.

countries (Lopez et al., 2001) and the third most common cause of death in the US, accounting for approximately 1 in 18 deaths in 2007 (Roger et al., 2011). Over 7 million Americans currently living with the cognitive and physical consequences of stroke (Roger et al., 2011), and it has been estimated that stroke account for approximately 4% of all direct health care costs in the US (Donnan et al., 2008). The risk of first-ever stroke is almost twice as high for African Americans as for white Americans, which may in part be due to the higher prevalence of hypertension in this group (Roger et al., 2011).

Fig. 1. Relationship between subclinical measures and clinical outcomes. Dark blue arrows represent risk factor relationships, and dashed blue lines represent clinical criteria.

Dementia is also an important public health burden in the U.S. and abroad (Haan & Wallace, 2004), and the World Health Organization predicts that there will be approximately 29 million people affected by all forms of dementia by the year 2020 (Essink-Bot et al., 2002). Alzheimer's disease (AD) and other dementias affect over 5.2 million Americans, including between 200,000 and 500,000 people under the age of 65. Dementias place a heavy economic burden on the health care system, with each Medicare patient with dementia accounting for more than three times as much spending than the average beneficiary (Alzheimer's Association, 2008). The aging population of the U.S. is expected to dramatically increase the prevalence of dementia, which is thought to affect 3%-11% of people older than 65 and 25%- 47% of people older than 85 (Boustani et al., 2003). Older African Americans are about twice as likely to develop AD and other dementias as older white Americans, which may in part be due to the higher prevalences of hypertension and diabetes and lower average socioeconomic status of this group (Alzheimer's Association, 2010).

#### **1.3 Role of genetics in leukoaraiosis and cognitive function**

Genetic factors are likely to account for a significant amount of the inter-individual variation in cognitive functioning and brain structure (Deary et al., 2004). Heritability studies, candidate gene studies, and genome-wide association studies are beginning to shed light on the biological processes involved in the progression from hypertension to the development of leukoaraiosis and cognitive decline that are indicators of increased risk of stroke and dementia.

#### **1.3.1 Genetics of leukoaraiosis and cognitive function**

Estimates of heritability for leukoaraiosis range from 0.45-0.71, indicating that genetic factors account for a large proportion of the inter-individual variation in this trait (Atwood et al., 2004; Carmelli et al., 1998; Turner et al., 2004). Candidate gene studies for leukoaraiosis have primarily concentrated on genes in pathways known to be involved in hypertension, vasculature, and endothelial damage. Although initial findings have been encouraging, no specific genetic factors have been unequivocally shown to be associated with this trait (Paternoster et al., 2009). Genome-wide association studies (GWAS) for this trait have also been limited, but are currently being conducted in several ethnic groups. To date, the most promising evidence for association is with a region on chromosome 17q25 in European Americans (Fornage et al., 2011).

For cognitive decline, the most promising candidate genes include those that are associated with hypertension, leukoaraiosis, Alzheimer's Disease (AD), normal cognitive functioning, cardiovascular function, oxidative stress, and inflammation (Deary et al., 2004), though candidate gene studies have not yet established any specific genetic factors that definitively affect cognitive decline. GWAS for a variety of cognitive traits are currently underway. GWASs that examine the change of cognitive traits over time in multiple cohorts will be particularly useful for identifying genetic factors associated with cognitive decline.

#### **1.3.2 Role of pleiotropy**

42 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

countries (Lopez et al., 2001) and the third most common cause of death in the US, accounting for approximately 1 in 18 deaths in 2007 (Roger et al., 2011). Over 7 million Americans currently living with the cognitive and physical consequences of stroke (Roger et al., 2011), and it has been estimated that stroke account for approximately 4% of all direct health care costs in the US (Donnan et al., 2008). The risk of first-ever stroke is almost twice as high for African Americans as for white Americans, which may in part be due to the

Fig. 1. Relationship between subclinical measures and clinical outcomes. Dark blue arrows

Dementia is also an important public health burden in the U.S. and abroad (Haan & Wallace, 2004), and the World Health Organization predicts that there will be approximately 29 million people affected by all forms of dementia by the year 2020 (Essink-Bot et al., 2002). Alzheimer's disease (AD) and other dementias affect over 5.2 million Americans, including between 200,000 and 500,000 people under the age of 65. Dementias place a heavy economic burden on the health care system, with each Medicare patient with dementia accounting for more than three times as much spending than the average beneficiary (Alzheimer's Association, 2008). The aging population of the U.S. is expected to dramatically increase the prevalence of dementia, which is thought to affect 3%-11% of people older than 65 and 25%- 47% of people older than 85 (Boustani et al., 2003). Older African Americans are about twice as likely to develop AD and other dementias as older white Americans, which may in part be due to the higher prevalences of hypertension and diabetes and lower average

Genetic factors are likely to account for a significant amount of the inter-individual variation in cognitive functioning and brain structure (Deary et al., 2004). Heritability studies, candidate gene studies, and genome-wide association studies are beginning to shed light on the biological processes involved in the progression from hypertension to the development of leukoaraiosis and cognitive decline that are indicators of increased risk of stroke and

Estimates of heritability for leukoaraiosis range from 0.45-0.71, indicating that genetic factors account for a large proportion of the inter-individual variation in this trait (Atwood et al., 2004; Carmelli et al., 1998; Turner et al., 2004). Candidate gene studies for

represent risk factor relationships, and dashed blue lines represent clinical criteria.

higher prevalence of hypertension in this group (Roger et al., 2011).

socioeconomic status of this group (Alzheimer's Association, 2010).

**1.3 Role of genetics in leukoaraiosis and cognitive function** 

**1.3.1 Genetics of leukoaraiosis and cognitive function** 

dementia.

Pleiotropy is most simply defined as the condition in which variation in a single gene affects multiple traits (Hodgkin, 1998). Defined in this manner, pleiotropic genes range from those that encode proteins involved in a single biological pathway that influences multiple disease processes and/or organ systems to those that play entirely different roles in multiple biological pathways. In some instances, pleiotropy is "the phenomenon in which a single gene controls several distinct, seemingly unrelated, phenotypic effects" (Zou et al., 2008). A well-known example of pleiotropy in humans is the 4 allele of the apolioprotein E (*APOE*) gene (Dickstein et al., 2010). *APOE* is a plasma cholesterol transport molecule that resides primarily on very low density lipoproteins, and the 4 allele has been shown to be a risk factor for coronary heart disease and stroke through mechanisms related directly to lipid transport. However, the 4 alelle is also a risk factor for AD and cognitive decline, with those carrying the allele having a younger age of onset as well as an accelerated pace of cognitive decline. Though the precise mechanism by which 4 leads to cognitive decline is not known, the main hypotheses are through pathways not directly related or only tangentially related to lipid transport. *APOE* appears to affect brain traits through its role as a chaperone for the amyloid beta protein and/or mediation of the phosphorylation of the tau protein.

The study of pleiotropy in model organisms and humans serves several functions. In model organisms, it serves to further the understanding and elucidation of the complex biological pathways that regulate the development of traits, providing information about normal cellular function, normal development and function at the organismal level, connections between previously unrecognized biological processes, and increased predictive ability in breeding programs (Hodgkin, 1998). It also it provides insight into the mechanisms of evolution, as effects on multiple traits due to a single genetic variant may pose severe evolutionary constraints (Cheverud et al., 2004). The findings from pleiotropy studies in model organisms, particularly the high degree of connectivity among transcriptional modules, have strong implications for understanding the pleiotropic genetic mechanisms that are also operating in humans. A greater understanding of the underlying pleiotropic mechanisms contributing to human health and disease has the potential to allow for earlier identification of individuals at increased risk for disease, the development of more efficacious treatments, and the tailoring of particular treatments to people most likely to respond positively.

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 45

non-Hispanic whites and 1,841 African Americans). The diagnosis of essential hypertension was established based on blood pressure levels measured at the study visit (>140 mmHg average systolic BP or >90 mmHg average diastolic BP) or a prior diagnosis of hypertension and current treatment with antihypertensive medications. Exclusion criteria were secondary hypertension, alcoholism or drug abuse, pregnancy, insulin-dependent diabetes mellitus, or active malignancy. In the second phase of the GENOA study (Phase II: 2000-2004), 1,241 white and 1,482 African American participants were successfully re-recruited to measure potential target organ damage due to hypertension. Phase I and II GENOA data consist of demographic information, medical history, clinical characteristics, lifestyle factors, and blood samples for genotyping and biomarker assays. Written informed consent was obtained from all subjects and approval was granted by participating institutional review boards. All reported phenotype and covariate data used for this analysis was collected

The Genetics of Microangiopathic Brain Injury (GMBI) study (2001-2006) is an ancillary study of GENOA undertaken to investigate susceptibility genes for ischemic brain injury. Phase II GENOA participants that had a sibling willing and eligible to participate in the GMBI study underwent a neurocognitive testing battery to assess several domains of cognitive function including learning, memory, attention, concentration, and language. Ischemic brain damage to the subcortical and periventricular white matter (leukoaraiosis) was quantified by magnetic resonance imaging (MRI) in subjects who had no history of stroke or neurological disease and no implanted metal devices. Participants were excluded from this analysis if they were less than 45 years of age or had evidence of silent stroke (transient ischemic attack) upon examination of their MRI. The analysis sample was comprised of 762 whites in 378 sibships and 720 African Americans in

Leukoaraiosis volume (cm3) was obtained via MRI in a separate clinical visit. All MRI scans were performed on identically equipped Signa 1.5 T MRI scanners (GE Medical Systems, Waukesha, WI, USA) and images were centrally processed at the Mayo Clinic. Symmetric head positioning with respect to orthogonal axes was verified by a series of short scout scans. Total intracranial volume (head size) was measured from T1-weighted spin echo sagittal images, each set consisting of 32 contiguous 5 mm thick slices with no interslice gap, field of view = 24 cm, matrix = 256 x 192, obtained with the following sequence: scan time = 2.5 min, echo time = 14 ms, repetitions = 2, replication time = 500 ms (Jack et al., 1989). Total brain and leukoaraiosis volumes were determined from axial fluid-attenuated inversion recovery (FLAIR) images, each set consisting of 48 contiguous 3-mm interleaved slices with no interslice gap, field of view = 22 cm, matrix = 256 x 160, obtained with the following sequence: scan time = 9 min, echo time = 144.8 ms, inversion time = 2,600 ms, repetition time = 26,002 ms, bandwidth = +/- 15.6 kHz, one signal average. A FLAIR image is a T2-weighted image with the signal of the cerebrospinal fluid nulled, such that brain pathology appears as the brightest intracranial tissue. Interactive imaging processing steps were performed by a research associate who had no knowledge of the subjects' personal or medical histories or biological relationships. A fully automated algorithm was used to segment each slice of the edited multi-slice FLAIR sequence into voxels assigned to one of three categories: brain, cerebrospinal fluid, or leukoaraiosis. The mean absolute error of this method is 1.4% for brain volume and 6.6% for leukoaraiosis volume, and the mean test-

during the Phase II exam.

413 sibships.

**2.2 Leukoaraiosis** 

#### **1.3.3 Bivariate variance component analysis to assess pleiotropy**

Studies of pleiotropy in humans have generally consisted of bivariate genetic analysis using variance decomposition techniques and linkage analysis in biologically related groups of traits. Variance decomposition techniques are used to parse the total phenotypic correlation in a pair of traits into the correlation due to genetic influences (genetic correlation) and the correlation due to environmental influences (environmental correlation) using family relationships.

Bivariate variance decomposition techniques have been used to study pleiotropy in humans for a variety of purposes. Comuzzie et al. (1994) estimated the genetic and environmental correlations among eight measures of skinfolds in order to inform epidemiologic studies that examine these measures as risk factors for heart disease and diabetes. The authors argue that studying pleiotropy in risk factors is important because shared genetic or environmental effects may confound analyses using these traits if these effects are unrecognized. Bivariate genetic analysis is has also been used to identify measureable endophenotypes that can be used to study the genetic underpinnings of complex diseases with multiple etiologies. For example, Charlesworth et al. (2010) examined the genetic correlations between several quantitative characteristics of the eye and primary open-angle glaucoma in order to determine the most appropriate endophenotypes to focus on in genetic association studies.

#### **1.4 Motivation for studying pleiotropy of leukoaraiosis and cognitive function**

In this chapter, we focus on estimating the heritabilities, genetic correlations, and environmental correlations between leukoaraiosis and seven measures of neurocognitive function. In a sample of 759 whites and 720 African Americans, we examine patterns of pleiotropy using a bivariate variance components approach. Findings of this work help inform the understanding of the genetic relationships among leukoaraiosis and measures of cognitive function. A deeper understanding the genetics of leukoaraiosis development and its impact on cognitive decline in individuals free of overt neurocognitive disorders may help to inform pharmacogenomic drug development and preventive strategies for identifying individuals at increased risk of stroke and dementia. Research into the genetic architecture of leukoaraiosis and cognitive function in samples that are presymptomatic is particularly important because preventive interventions for dementia would need to start early, preferably before any brain damage occurs (DeKosky & Marek, 2003).

#### **2. Methods**

#### **2.1 Sample**

The National Heart, Lung and Blood Institute established the Family Blood Pressure Program (FBPP) in 1996 from four existing research networks that were investigating the genetics of hypertension and its sequelae (FBPP Investigators, 2002), including The Genetic Epidemiology Network of Arteriopathy (GENOA). GENOA recruited hypertensive sibships from Rochester, Minnesota and Jackson, Mississippi for linkage and association studies to investigate the genetic underpinnings of hypertension and target organ damage related to hypertension (Daniels et al., 2004).

In the initial phase of the GENOA study (Phase I: 1996-2001), all members of sibships containing ≥ 2 individuals with essential hypertension clinically diagnosed before age 60 were invited to participate, including both hypertensive and normotensive siblings (1,583 non-Hispanic whites and 1,841 African Americans). The diagnosis of essential hypertension was established based on blood pressure levels measured at the study visit (>140 mmHg average systolic BP or >90 mmHg average diastolic BP) or a prior diagnosis of hypertension and current treatment with antihypertensive medications. Exclusion criteria were secondary hypertension, alcoholism or drug abuse, pregnancy, insulin-dependent diabetes mellitus, or active malignancy. In the second phase of the GENOA study (Phase II: 2000-2004), 1,241 white and 1,482 African American participants were successfully re-recruited to measure potential target organ damage due to hypertension. Phase I and II GENOA data consist of demographic information, medical history, clinical characteristics, lifestyle factors, and blood samples for genotyping and biomarker assays. Written informed consent was obtained from all subjects and approval was granted by participating institutional review boards. All reported phenotype and covariate data used for this analysis was collected during the Phase II exam.

The Genetics of Microangiopathic Brain Injury (GMBI) study (2001-2006) is an ancillary study of GENOA undertaken to investigate susceptibility genes for ischemic brain injury. Phase II GENOA participants that had a sibling willing and eligible to participate in the GMBI study underwent a neurocognitive testing battery to assess several domains of cognitive function including learning, memory, attention, concentration, and language. Ischemic brain damage to the subcortical and periventricular white matter (leukoaraiosis) was quantified by magnetic resonance imaging (MRI) in subjects who had no history of stroke or neurological disease and no implanted metal devices. Participants were excluded from this analysis if they were less than 45 years of age or had evidence of silent stroke (transient ischemic attack) upon examination of their MRI. The analysis sample was comprised of 762 whites in 378 sibships and 720 African Americans in 413 sibships.

#### **2.2 Leukoaraiosis**

44 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Studies of pleiotropy in humans have generally consisted of bivariate genetic analysis using variance decomposition techniques and linkage analysis in biologically related groups of traits. Variance decomposition techniques are used to parse the total phenotypic correlation in a pair of traits into the correlation due to genetic influences (genetic correlation) and the correlation due to environmental influences (environmental correlation) using family

Bivariate variance decomposition techniques have been used to study pleiotropy in humans for a variety of purposes. Comuzzie et al. (1994) estimated the genetic and environmental correlations among eight measures of skinfolds in order to inform epidemiologic studies that examine these measures as risk factors for heart disease and diabetes. The authors argue that studying pleiotropy in risk factors is important because shared genetic or environmental effects may confound analyses using these traits if these effects are unrecognized. Bivariate genetic analysis is has also been used to identify measureable endophenotypes that can be used to study the genetic underpinnings of complex diseases with multiple etiologies. For example, Charlesworth et al. (2010) examined the genetic correlations between several quantitative characteristics of the eye and primary open-angle glaucoma in order to determine the most appropriate endophenotypes to focus on in genetic

**1.4 Motivation for studying pleiotropy of leukoaraiosis and cognitive function** 

early, preferably before any brain damage occurs (DeKosky & Marek, 2003).

In this chapter, we focus on estimating the heritabilities, genetic correlations, and environmental correlations between leukoaraiosis and seven measures of neurocognitive function. In a sample of 759 whites and 720 African Americans, we examine patterns of pleiotropy using a bivariate variance components approach. Findings of this work help inform the understanding of the genetic relationships among leukoaraiosis and measures of cognitive function. A deeper understanding the genetics of leukoaraiosis development and its impact on cognitive decline in individuals free of overt neurocognitive disorders may help to inform pharmacogenomic drug development and preventive strategies for identifying individuals at increased risk of stroke and dementia. Research into the genetic architecture of leukoaraiosis and cognitive function in samples that are presymptomatic is particularly important because preventive interventions for dementia would need to start

The National Heart, Lung and Blood Institute established the Family Blood Pressure Program (FBPP) in 1996 from four existing research networks that were investigating the genetics of hypertension and its sequelae (FBPP Investigators, 2002), including The Genetic Epidemiology Network of Arteriopathy (GENOA). GENOA recruited hypertensive sibships from Rochester, Minnesota and Jackson, Mississippi for linkage and association studies to investigate the genetic underpinnings of hypertension and target organ damage related to

In the initial phase of the GENOA study (Phase I: 1996-2001), all members of sibships containing ≥ 2 individuals with essential hypertension clinically diagnosed before age 60 were invited to participate, including both hypertensive and normotensive siblings (1,583

**1.3.3 Bivariate variance component analysis to assess pleiotropy** 

relationships.

association studies.

**2. Methods 2.1 Sample** 

hypertension (Daniels et al., 2004).

Leukoaraiosis volume (cm3) was obtained via MRI in a separate clinical visit. All MRI scans were performed on identically equipped Signa 1.5 T MRI scanners (GE Medical Systems, Waukesha, WI, USA) and images were centrally processed at the Mayo Clinic. Symmetric head positioning with respect to orthogonal axes was verified by a series of short scout scans. Total intracranial volume (head size) was measured from T1-weighted spin echo sagittal images, each set consisting of 32 contiguous 5 mm thick slices with no interslice gap, field of view = 24 cm, matrix = 256 x 192, obtained with the following sequence: scan time = 2.5 min, echo time = 14 ms, repetitions = 2, replication time = 500 ms (Jack et al., 1989). Total brain and leukoaraiosis volumes were determined from axial fluid-attenuated inversion recovery (FLAIR) images, each set consisting of 48 contiguous 3-mm interleaved slices with no interslice gap, field of view = 22 cm, matrix = 256 x 160, obtained with the following sequence: scan time = 9 min, echo time = 144.8 ms, inversion time = 2,600 ms, repetition time = 26,002 ms, bandwidth = +/- 15.6 kHz, one signal average. A FLAIR image is a T2-weighted image with the signal of the cerebrospinal fluid nulled, such that brain pathology appears as the brightest intracranial tissue. Interactive imaging processing steps were performed by a research associate who had no knowledge of the subjects' personal or medical histories or biological relationships. A fully automated algorithm was used to segment each slice of the edited multi-slice FLAIR sequence into voxels assigned to one of three categories: brain, cerebrospinal fluid, or leukoaraiosis. The mean absolute error of this method is 1.4% for brain volume and 6.6% for leukoaraiosis volume, and the mean test-

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 47

The examiner begins by reading a list of 15 common words aloud, and participants are asked to recall as many of the words as possible in any order. The same procedure is repeated four more times using the same list of 15 words. The total number of words that the participant remembers correctly over the five trials is recorded and forms the basis of the RAVLT total learning outcome measure for this analysis, which assesses immediate memory. Delayed recall is assessed by asking the participant to again name as many words as he/she remembers after a 30-minute delay, forming the basis of the RAVLT delayed learning outcome measure for this analysis. During the 30-minute interim, an interference task is performed in which the interviewer reads another set of words aloud, and the participant is asked to recall them. Thus, the delayed learning outcome assesses both

The Digit Symbol Substitution task (DSS) from the Wechsler Adult Intelligence Scale Revised (WAIS-R) (Wechsler, 1981) is a timed translation test designed to measure complex visual attention, sustained and focused concentration, response speed, and visuomotor coordination (Lezak, 1995). In this test, participants are given a key in which each number corresponds to a special symbol. The task consists of filling in empty boxes below a series of random numbers with the symbol corresponding to the appropriate number (translating the numbers to symbols). After a practice session to ensure that the participant understands the task, participants were given a 90 second time limit to complete as many items as possible. The DSST outcome measure for this analysis was the number of correct symbols completed

**2.3.3 Controlled Oral Word Association Test (COWA) of the Multilingual Aphasia** 

The Multilingual Aphasia Examination was developed to diagnose the presence of aphasic disorders (any type of acquired language impairment), and the Controlled Oral Word Association Test (COWA) is a subset of this examination designed to measure verbal fluency (Lezak, 1995). Two measures of verbal fluency were used as outcomes for the present study, one of letter fluency (Word Fluency Test (WFT)) and one of category fluency (Animal Naming). The Word Fluency Test of the COWA assesses letter fluency (phonetic association) by asking subjects to generate words orally that begin with a specific letter of the alphabet ("F", "A", and "S") for a period of 60 seconds. These letters were chosen because they have been demonstrated to allow more vocabulary choices overall than other letters. Scoring of this test consisted of adding the total number of admissible words generated for each of the three letters. Inadmissable words include proper nouns as well as variations, plurals, and

The Animal Naming portion of the COWA assesses category fluency (semantic association) by asking subjects to name as many animals as possible in a period of 60 seconds (Lezak, 1995). Scoring of this test is the sum of all admissible animals. Inadmissable animals include extinct, imaginary, or magical animals, proper names, and variations of previously stated animals.

The Stroop Color Word (CW) Test is primarily a measure of concentration effectiveness, specifically the ability to shift perceptual sets to correspond with changing demands and the

delayed memory as well as vulnerability to interference.

**Substitution Task (DSST)** 

in 90 seconds.

**Examination** 

repetitions of previously stated words.

**2.3.4 Stroop Color Word (CW) Test** 

**2.3.2 Wechsler Adult Intelligence Scale Revised (WAIS-R) Digit Symbol** 

retest coefficient of variation is 0.3% for brain volume and 1.4% for leukoaraiosis volume (Jack et al., 2001). White matter hyperintensities in the corona-radiata and periventricular zone, as well as central gray infarcts (ie, lacunes) were included in the global leukoaraiosis measurements. Brain scans with cortical infarctions were excluded from the analyses because of the distortion of the leukoaraiosis volume estimates that would be introduced in the automated segmentation algorithm.

#### **2.3 Neuropsychological testing battery**

Neuropsychological tests were conducted in a private room that was free of noise and other distractions by trained interviewers. In order to assure accuracy and comparability in test administrator performance, a portion (approximately 5%) of all interviews were tape recorded and evaluated for accuracy to provide feedback to test administrators. The neuropsychological outcome measures used for this analysis are presented in Table 1 along with the cognitive functions assessed.


Table 1. Measures of cognitive function

#### **2.3.1 Rey's Auditory Verbal Learning Test (RAVLT)**

Rey's Auditory Verbal Learning Test (RAVLT) is a brief test that assesses learning and memory through multiple learning trials and a 30-minute delayed recall (Rey, 1964). Specifically, the measure assesses immediate memory span, new learning, vulnerability to interference in learning, and recognition memory. RAVLT testing norms for individuals aged 55 and older were developed through Mayo's Older Americans Normative Studies (MOANS), and the testing procedure followed in GMBI was identical to that used in MOANS (Ivnik et al., 1992).

retest coefficient of variation is 0.3% for brain volume and 1.4% for leukoaraiosis volume (Jack et al., 2001). White matter hyperintensities in the corona-radiata and periventricular zone, as well as central gray infarcts (ie, lacunes) were included in the global leukoaraiosis measurements. Brain scans with cortical infarctions were excluded from the analyses because of the distortion of the leukoaraiosis volume estimates that would be introduced in

Neuropsychological tests were conducted in a private room that was free of noise and other distractions by trained interviewers. In order to assure accuracy and comparability in test administrator performance, a portion (approximately 5%) of all interviews were tape recorded and evaluated for accuracy to provide feedback to test administrators. The neuropsychological outcome measures used for this analysis are presented in Table 1 along

> RAVLT delayed recall

COWA animals

word

interference

Rey's Auditory Verbal Learning Test (RAVLT) is a brief test that assesses learning and memory through multiple learning trials and a 30-minute delayed recall (Rey, 1964). Specifically, the measure assesses immediate memory span, new learning, vulnerability to interference in learning, and recognition memory. RAVLT testing norms for individuals aged 55 and older were developed through Mayo's Older Americans Normative Studies (MOANS), and the testing procedure followed in GMBI was identical to that used in

Association Test (COWA) COWA FAS Language

RAVLT total learning

*Measure Cognitive Functions* 

Learning

Learning

Language

Delayed memory

Immediate memory

Psychomotor speed Visual attention Concentration

Vulnerability to interference

Verbal fluency (phonetic association)

Concentration effectiveness Ability to shift perceptual sets in response to novel stimuli

Ability to shift perceptual sets in response to novel stimuli

Category fluency (semantic association)

the automated segmentation algorithm.

**2.3 Neuropsychological testing battery** 

with the cognitive functions assessed.

Rey's Auditory Verbal Learning Test (RAVLT)

Rey's Auditory Verbal Learning Test (RAVLT)

Controlled Oral Word

Controlled Oral Word Association Test (COWA)

Digit Symbol Substitution

Test (DSST) DSST

Stroop Color Word Test Stroop color

**2.3.1 Rey's Auditory Verbal Learning Test (RAVLT)** 

Stroop Color Word Test Stroop

Table 1. Measures of cognitive function

MOANS (Ivnik et al., 1992).

*Neurocognitive Test Outcome*

The examiner begins by reading a list of 15 common words aloud, and participants are asked to recall as many of the words as possible in any order. The same procedure is repeated four more times using the same list of 15 words. The total number of words that the participant remembers correctly over the five trials is recorded and forms the basis of the RAVLT total learning outcome measure for this analysis, which assesses immediate memory. Delayed recall is assessed by asking the participant to again name as many words as he/she remembers after a 30-minute delay, forming the basis of the RAVLT delayed learning outcome measure for this analysis. During the 30-minute interim, an interference task is performed in which the interviewer reads another set of words aloud, and the participant is asked to recall them. Thus, the delayed learning outcome assesses both delayed memory as well as vulnerability to interference.

#### **2.3.2 Wechsler Adult Intelligence Scale Revised (WAIS-R) Digit Symbol Substitution Task (DSST)**

The Digit Symbol Substitution task (DSS) from the Wechsler Adult Intelligence Scale Revised (WAIS-R) (Wechsler, 1981) is a timed translation test designed to measure complex visual attention, sustained and focused concentration, response speed, and visuomotor coordination (Lezak, 1995). In this test, participants are given a key in which each number corresponds to a special symbol. The task consists of filling in empty boxes below a series of random numbers with the symbol corresponding to the appropriate number (translating the numbers to symbols). After a practice session to ensure that the participant understands the task, participants were given a 90 second time limit to complete as many items as possible. The DSST outcome measure for this analysis was the number of correct symbols completed in 90 seconds.

#### **2.3.3 Controlled Oral Word Association Test (COWA) of the Multilingual Aphasia Examination**

The Multilingual Aphasia Examination was developed to diagnose the presence of aphasic disorders (any type of acquired language impairment), and the Controlled Oral Word Association Test (COWA) is a subset of this examination designed to measure verbal fluency (Lezak, 1995). Two measures of verbal fluency were used as outcomes for the present study, one of letter fluency (Word Fluency Test (WFT)) and one of category fluency (Animal Naming).

The Word Fluency Test of the COWA assesses letter fluency (phonetic association) by asking subjects to generate words orally that begin with a specific letter of the alphabet ("F", "A", and "S") for a period of 60 seconds. These letters were chosen because they have been demonstrated to allow more vocabulary choices overall than other letters. Scoring of this test consisted of adding the total number of admissible words generated for each of the three letters. Inadmissable words include proper nouns as well as variations, plurals, and repetitions of previously stated words.

The Animal Naming portion of the COWA assesses category fluency (semantic association) by asking subjects to name as many animals as possible in a period of 60 seconds (Lezak, 1995). Scoring of this test is the sum of all admissible animals. Inadmissable animals include extinct, imaginary, or magical animals, proper names, and variations of previously stated animals.

#### **2.3.4 Stroop Color Word (CW) Test**

The Stroop Color Word (CW) Test is primarily a measure of concentration effectiveness, specifically the ability to shift perceptual sets to correspond with changing demands and the

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 49

for genetic effects, based on family relationships (Sing et al., 1987). In this study, SOLAR (Sequential Oligogenic Linkage Analysis Routines) (Almasy & Blangero, 1998) was used to implement a variance component regression based on maximum likelihood estimation to estimate the proportion of phenotypic variance that is due to additive genetic effects, giving an estimate of heritability. Shared residual (non-genetic) effects are assumed to be zero because the siblings in this study are all adults and have reported living in separate

Heritabilities were estimated for the outcome variables (all cognitive traits and ln(leukoaraiosis+1)) both with and without covariates (age, sex, education, and TIV) included in the biometric models. When covariates are included in the model, the heritability estimate is given by [(1-proportion of variance explained by covariates)\*h2]\*100, and represents the hertiability the residual variance of the trait that is not accounted for by

The heritability of the traits were tested for significance by comparing the log-likelihood of the model in which heritability is estimated to that of the model in which heritability is fixed to 0. The null distribution of the likelihood ratio test statistic is a 50:50 mixture of a Chi-

The phenotypic, genetic, and environmental correlations among all pairs of traits in both ethnic groups were estimated in SOLAR, both with and without covariates included in the biometric models. The estimated genetic and environmental correlations, *ρg* and *ρe*, were tested for significance by comparing the log-likelihood of the model in which the parameter

The test for pleiotropy, or evidence of shared genetic influences, is as follows: **Ho**: *ρg* = 0 vs. **Ha**: *ρg* ≠ 0. The null distribution of the likelihood ratio test statistic statistic is a Chi-square distribution with one degree of freedom. Rejection of the null hypothesis provides evidence

The presence of shared environmental influences (non-genetic influences beyond the covariates included in the model) is tested similarly: **Ho**: *ρe* = 0 vs. **Ha**: *ρe* ≠ 0. The null distribution of the likelihood ratio test statistic statistic is a Chi-square distribution with one degree of freedom. Rejection of the null hypothesis provides evidence that there are shared

Descriptive statistics of the outcome measures and covariates for the 762 white and 720 African American participants, as well as T-tests comparing the samples, are presented in Tables 2 and 3. GENOA whites are 58.1% female, have a mean age at the time of cognitive testing of 61.3 years (range= 45-84 years), and have a mean leukoaraiosis volume of 8.11cm3 (range=1.2-62 cm3). GENOA African Americans have a much larger percentage of females (72.6%), have a higher mean age of cognitive testing (63.3 years, range = 45-91 years)), and have a higher mean volume of leukoaraiosis with greater variability (9.56cm3, range=2.0-126 cm3). Approximately half of both whites and African Americans attended at least some college; however, only 5.2% of white participants did not graduate from high school or obtain a GED while this was true for 28.3% of African American participants. The mean

square distribution with one degree of freedom and a point mass at zero.

of interest is estimated to that of the model in which the parameter is fixed to 0.

**2.4.4 Phenotypic, genetic, and environmental correlations** 

households.

the covariates.

of pleiotropy.

**3. Results** 

**3.1 Descriptive statistics** 

environmental influences on the traits.

ability to inhibit a customary response to stimulus in favor of a more novel one (Lezak, 1995; Stroop, 1935). Administration and scoring of the test to GMBI participants followed procedures outlined in the standardized version of the CW test developed by Golden (Golden, 1978).

This test consists of three pages: the word page, the color page, and the color-word page. The word page consists of the words "RED", "GREEN", and "BLUE" arranged randomly and printed in black ink. The color page consists of sets of "XXXX" printed in red, green, or blue ink. The color-word page consists of the words from the word page printed in the colors on the color page, but no word matches the color in which it is printed (for example, the word "RED" is printed in either green or blue ink). For this study, the participant was first asked to read the word page as fast as he/she could for 45 seconds, and the total number of correct words was recorded. If the participant stated an incorrect word, the interviewer said, "No," and the participant was instructed to read the same word again to correct their error. The same procedure was followed for naming the colors on the color page. The participant was then asked to state the colors of the words on the color-word page as fast as he/she could in 45 seconds, and the total number of correctly stated colors were recorded.

Two measures from this test are used as outcomes in the present study. The color-word (CW) score is the total number of correctly stated colors out of 100 from the color-word page. The Stroop interference score is the difference in scores between the color page and the color-word page.

#### **2.4 Statistical analysis**

#### **2.4.1 Descriptive statistics**

Data management and statistical analyses were conducted primarily in R version 2.8.0 (R Core Development Team, 2008). Distributional plots indicated that the measures of leukoaraiosis volume are severely right-skewed, so this variable was transformed by taking the natural log of (leukoaraiosis + 1). The cognitive traits appeared to have relatively normal distributions; thus, no variable transformations were applied to these variables. T-tests were conducted for the outcome measures to test whether there were significant differences in the white and African American study participants.

#### **2.4.2 Covariates**

Biometrical modeling of leukoaraiosis and cognitive function included age at cognitive testing, gender, and education as covariates. Relative performance on cognitive tests is determined using age- and gender-specific population-based norms, since both of these variables are known to affect cognitive function. Age is also a very strong independent predictor for leukoaraiosis. Education affects performance on some cognitive tests, as people with higher educational attainment tend to perform better (Valenzuela & Sachdev, 2006). For this analysis, education was categorized as follows: 0) less than high school, 1) completed high school (GED), 2) some college, and 3) completed college (4+ years). To account for differences in brain size, intracranial volume was also included in models of leukoaraiosis. We conducted multivariable linear mixed models with covariates as predictor variables for each outcome measure to explore the relationships between these variables and each outcome of interest in GENOA whites and African Americans.

#### **2.4.3 Biometrical genetic modeling**

The expected covariance of a trait between a pair of individuals can be modeled as a function of the variance parameters and the expected correlation between the individuals for genetic effects, based on family relationships (Sing et al., 1987). In this study, SOLAR (Sequential Oligogenic Linkage Analysis Routines) (Almasy & Blangero, 1998) was used to implement a variance component regression based on maximum likelihood estimation to estimate the proportion of phenotypic variance that is due to additive genetic effects, giving an estimate of heritability. Shared residual (non-genetic) effects are assumed to be zero because the siblings in this study are all adults and have reported living in separate households.

Heritabilities were estimated for the outcome variables (all cognitive traits and ln(leukoaraiosis+1)) both with and without covariates (age, sex, education, and TIV) included in the biometric models. When covariates are included in the model, the heritability estimate is given by [(1-proportion of variance explained by covariates)\*h2]\*100, and represents the hertiability the residual variance of the trait that is not accounted for by the covariates.

The heritability of the traits were tested for significance by comparing the log-likelihood of the model in which heritability is estimated to that of the model in which heritability is fixed to 0. The null distribution of the likelihood ratio test statistic is a 50:50 mixture of a Chisquare distribution with one degree of freedom and a point mass at zero.

#### **2.4.4 Phenotypic, genetic, and environmental correlations**

The phenotypic, genetic, and environmental correlations among all pairs of traits in both ethnic groups were estimated in SOLAR, both with and without covariates included in the biometric models. The estimated genetic and environmental correlations, *ρg* and *ρe*, were tested for significance by comparing the log-likelihood of the model in which the parameter of interest is estimated to that of the model in which the parameter is fixed to 0.

The test for pleiotropy, or evidence of shared genetic influences, is as follows: **Ho**: *ρg* = 0 vs. **Ha**: *ρg* ≠ 0. The null distribution of the likelihood ratio test statistic statistic is a Chi-square distribution with one degree of freedom. Rejection of the null hypothesis provides evidence of pleiotropy.

The presence of shared environmental influences (non-genetic influences beyond the covariates included in the model) is tested similarly: **Ho**: *ρe* = 0 vs. **Ha**: *ρe* ≠ 0. The null distribution of the likelihood ratio test statistic statistic is a Chi-square distribution with one degree of freedom. Rejection of the null hypothesis provides evidence that there are shared environmental influences on the traits.

#### **3. Results**

48 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

ability to inhibit a customary response to stimulus in favor of a more novel one (Lezak, 1995; Stroop, 1935). Administration and scoring of the test to GMBI participants followed procedures outlined in the standardized version of the CW test developed by Golden

This test consists of three pages: the word page, the color page, and the color-word page. The word page consists of the words "RED", "GREEN", and "BLUE" arranged randomly and printed in black ink. The color page consists of sets of "XXXX" printed in red, green, or blue ink. The color-word page consists of the words from the word page printed in the colors on the color page, but no word matches the color in which it is printed (for example, the word "RED" is printed in either green or blue ink). For this study, the participant was first asked to read the word page as fast as he/she could for 45 seconds, and the total number of correct words was recorded. If the participant stated an incorrect word, the interviewer said, "No," and the participant was instructed to read the same word again to correct their error. The same procedure was followed for naming the colors on the color page. The participant was then asked to state the colors of the words on the color-word page as fast as he/she could in 45

Two measures from this test are used as outcomes in the present study. The color-word (CW) score is the total number of correctly stated colors out of 100 from the color-word page. The Stroop interference score is the difference in scores between the color page and

Data management and statistical analyses were conducted primarily in R version 2.8.0 (R Core Development Team, 2008). Distributional plots indicated that the measures of leukoaraiosis volume are severely right-skewed, so this variable was transformed by taking the natural log of (leukoaraiosis + 1). The cognitive traits appeared to have relatively normal distributions; thus, no variable transformations were applied to these variables. T-tests were conducted for the outcome measures to test whether there were significant differences in the

Biometrical modeling of leukoaraiosis and cognitive function included age at cognitive testing, gender, and education as covariates. Relative performance on cognitive tests is determined using age- and gender-specific population-based norms, since both of these variables are known to affect cognitive function. Age is also a very strong independent predictor for leukoaraiosis. Education affects performance on some cognitive tests, as people with higher educational attainment tend to perform better (Valenzuela & Sachdev, 2006). For this analysis, education was categorized as follows: 0) less than high school, 1) completed high school (GED), 2) some college, and 3) completed college (4+ years). To account for differences in brain size, intracranial volume was also included in models of leukoaraiosis. We conducted multivariable linear mixed models with covariates as predictor variables for each outcome measure to explore the relationships between these variables and

The expected covariance of a trait between a pair of individuals can be modeled as a function of the variance parameters and the expected correlation between the individuals

seconds, and the total number of correctly stated colors were recorded.

each outcome of interest in GENOA whites and African Americans.

(Golden, 1978).

the color-word page.

**2.4.2 Covariates** 

**2.4 Statistical analysis 2.4.1 Descriptive statistics** 

white and African American study participants.

**2.4.3 Biometrical genetic modeling** 

#### **3.1 Descriptive statistics**

Descriptive statistics of the outcome measures and covariates for the 762 white and 720 African American participants, as well as T-tests comparing the samples, are presented in Tables 2 and 3. GENOA whites are 58.1% female, have a mean age at the time of cognitive testing of 61.3 years (range= 45-84 years), and have a mean leukoaraiosis volume of 8.11cm3 (range=1.2-62 cm3). GENOA African Americans have a much larger percentage of females (72.6%), have a higher mean age of cognitive testing (63.3 years, range = 45-91 years)), and have a higher mean volume of leukoaraiosis with greater variability (9.56cm3, range=2.0-126 cm3). Approximately half of both whites and African Americans attended at least some college; however, only 5.2% of white participants did not graduate from high school or obtain a GED while this was true for 28.3% of African American participants. The mean

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 51

0.074 in African Americans) and highest for DSST (0.411 in whites and 0.529 in African Americans). The amount of variance explained by covariates in the remainder of the cognitive measures ranged from 0.122 to 0.309 in whites and from 0.207 to 0.294 in African Americans. Variance of ln(leukoaraiosis+1) explained by covariates was higher in whites

In order to examine the contribution of genetic factors to the observed variation in the traits, we used a biometrical approach to estimate the proportion of variance in the traits explained by genetic factors (heritabilities) both with and without inclusion of covariates in the models (Table 4). Heritabilities of all traits were highly significant in both whites and African Americans (p-value<0.001) with the exception of Stroop interference in African Americans that showed only a marginally significant heritability, illustrating that all of the traits under study are influenced by genetic factors. Similar patterns of heritability were observed between the two groups, though African Americans tended to have lower heritabilities than

> **h2 for Trait Modeled with Covariates**

**Ln(leukoaraiosis+1)** 0.656\*\*\* 0.529\*\*\* 0.311 36.45 **RAVLT delayed recall** 0.602\*\*\* 0.526\*\*\* 0.222 40.92 **RAVLT total learning** 0.627\*\*\* 0.516\*\*\* 0.308 35.71 **DSST** 0.774\*\*\* 0.843\*\*\* 0.403 50.33 **COWA FAS** 0.441\*\*\* 0.366\*\*\* 0.139 31.51 **COWA animals** 0.503\*\*\* 0.349\*\*\* 0.152 29.60 **Stroop color word** 0.586\*\*\* 0.429\*\*\* 0.276 31.06 **Stroop interference** 0.302\*\*\* 0.275\*\*\* 0.023 26.87

**Ln(leukoaraiosis+1)** 0.485\*\*\* 0.432\*\*\* 0.217 33.83 **RAVLT delayed recall** 0.494\*\*\* 0.390\*\*\* 0.203 31.08 **RAVLT total learning** 0.560\*\*\* 0.440\*\*\* 0.279 31.72 **DSST** 0.810\*\*\* 0.556\*\*\* 0.525 26.41 **COWA FAS** 0.710\*\*\* 0.536\*\*\* 0.300 37.52 **COWA animals** 0.551\*\*\* 0.329\*\*\* 0.260 24.35 **Stroop color word** 0.532\*\*\* 0.440\*\*\* 0.232 33.79 **Stroop interference** 0.135\*\*\* 0.154\* 0.075 14.25

For all traits modeled with covariates, biometric models included age, sex, and education. The biometric

a [(1 – Proportion of variance explained by adjustment covariates)\*h2]\*100

\* 0.01 < p-value < 0.05, \*\* 0.001 < p-value < 0.01, \*\*\* p-value < 0.001

model for ln(leukoaraiosis+1) also included TIV.

Null hypothesis of tests: h2 = 0

Table 4. Trait heritabilities

**Proportion of Variance Explained by Covariates** 

**Percent Variation Due to Genetic Factors After Accounting for Covariatesa** 

**h2 for Trait Modeled without Covariates** 

(0.309) than in African Americans (0.213).

**3.3 Genetic variance (heritability)** 

whites for most traits.

*African Americans* 

**Trait** 

*Whites* 

*Whites African Americans*  **Trait Category N Percentage N Percentage Education** 0 (Less than HS) 40 5.2% 204 28.3% 1 (HS/GED) 329 43.2% 205 28.5% 2 (Some College) 246 32.3% 127 17.6% 3 (Grad/Professional) 147 19.3% 184 25.6% **Gender** Male 319 41.9% 197 27.4% Female 443 58.1% 523 72.6%

values for all outcome measures were significantly different in whites and African Americans except for Stroop interference. Leukoaraiosis was strongly right skewed in both populations, but had a relatively normal distribution after taking the natural logarithm.

Table 2. Descriptive characteristics of the samples


**<sup>a</sup>**T-test p-value for a test of equality of trait means in whites and African Americans.

Table 3. Comparison of outcome measures

#### **3.2 Associations between covariates and outcome measures**

In order to explore the relationship between covariates and each outcome of interest, we conducted multivariable linear mixed models with covariates as predictor variables for each outcome measure. In both whites and African Americans, age, gender, and education were significant predictors for all cognitive measures except that education was not a significant predictor of Stroop interference in whites and gender was not a significant predictor of Stroop color word in African Americans after accounting for the other covariates. As expected, increasing age was associated with lower cognitive scores, while increasing education was associated with higher cognitive scores. Female gender also showed a trend of being associated with higher cognitive scores. In both groups, increasing age and total intracranial volume were associated with increasing leukoaraiosis volume, while gender and education were not associated with this measure.

The amount of variance explained by the covariates, as measured by R2, showed a consistent pattern between the two groups. R2 was lowest for Stroop interference (0.018 in whites and 0.074 in African Americans) and highest for DSST (0.411 in whites and 0.529 in African Americans). The amount of variance explained by covariates in the remainder of the cognitive measures ranged from 0.122 to 0.309 in whites and from 0.207 to 0.294 in African Americans. Variance of ln(leukoaraiosis+1) explained by covariates was higher in whites (0.309) than in African Americans (0.213).

#### **3.3 Genetic variance (heritability)**

50 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

values for all outcome measures were significantly different in whites and African Americans except for Stroop interference. Leukoaraiosis was strongly right skewed in both populations, but had a relatively normal distribution after taking the natural logarithm.

**Gender** Male 319 41.9% 197 27.4%

**Leukoaraiosis volume, cm3** 714 8.11 (6.83) 574 9.56 (9.89) 0.0028 **Ln (leukoaraiosis+1)** 714 2.06 (0.05) 574 2.16 (0.55) 0.0002 **RAVLT delayed recall** 758 9.08 (3.27) 708 6.80 (3.36) <2.2E-16 **RAVLT total learning** 759 47.7 (9.8) 712 40.1 (9.4) <2.2E-16 **DSST** 758 50.2 (12.4) 697 32.9 (13.6) <2.2E-16 **COWA FAS** 760 32.4 (13.6) 687 28.6 (11.7) 1.96E-08 **COWA animals** 762 19.3 (4.9) 716 14.9 (4.5) <2.2E-16 **Stroop color word** 740 34.5 (9.3) 648 22.3 (10.1) <2.2E-16 **Stroop interference** 740 32.8 (9.3) 648 33.6 (11.8) 0.4450

In order to explore the relationship between covariates and each outcome of interest, we conducted multivariable linear mixed models with covariates as predictor variables for each outcome measure. In both whites and African Americans, age, gender, and education were significant predictors for all cognitive measures except that education was not a significant predictor of Stroop interference in whites and gender was not a significant predictor of Stroop color word in African Americans after accounting for the other covariates. As expected, increasing age was associated with lower cognitive scores, while increasing education was associated with higher cognitive scores. Female gender also showed a trend of being associated with higher cognitive scores. In both groups, increasing age and total intracranial volume were associated with increasing leukoaraiosis volume, while gender

The amount of variance explained by the covariates, as measured by R2, showed a consistent pattern between the two groups. R2 was lowest for Stroop interference (0.018 in whites and

**Trait N Mean (±SD) N** 

**<sup>a</sup>**T-test p-value for a test of equality of trait means in whites and African Americans.

**3.2 Associations between covariates and outcome measures** 

and education were not associated with this measure.

Table 2. Descriptive characteristics of the samples

Table 3. Comparison of outcome measures

*Whites African Americans*  **Trait Category N Percentage N Percentage Education** 0 (Less than HS) 40 5.2% 204 28.3%

> 1 (HS/GED) 329 43.2% 205 28.5% 2 (Some College) 246 32.3% 127 17.6% 3 (Grad/Professional) 147 19.3% 184 25.6%

> Female 443 58.1% 523 72.6%

*Whites African Americans* 

**Mean (±SD)**

**T-test P-valuea** In order to examine the contribution of genetic factors to the observed variation in the traits, we used a biometrical approach to estimate the proportion of variance in the traits explained by genetic factors (heritabilities) both with and without inclusion of covariates in the models (Table 4). Heritabilities of all traits were highly significant in both whites and African Americans (p-value<0.001) with the exception of Stroop interference in African Americans that showed only a marginally significant heritability, illustrating that all of the traits under study are influenced by genetic factors. Similar patterns of heritability were observed between the two groups, though African Americans tended to have lower heritabilities than whites for most traits.


a [(1 – Proportion of variance explained by adjustment covariates)\*h2]\*100

For all traits modeled with covariates, biometric models included age, sex, and education. The biometric model for ln(leukoaraiosis+1) also included TIV.

Null hypothesis of tests: h2 = 0

\* 0.01 < p-value < 0.05, \*\* 0.001 < p-value < 0.01, \*\*\* p-value < 0.001

Table 4. Trait heritabilities

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 53

**Leuko** 0.529\*\*\* -0.253 -0.295 -0.294 -0.072 -0.174 -0.232 -0.110 **RAV-DR** -0.083 0.526\*\*\* 0.816 0.442 0.274 0.373 0.376 0.052 **RAV-TL** -0.063 0.755 0.516\*\*\* 0.523 0.346 0.429 0.441 0.147 **DSST** -0.064 0.213 0.269 0.843\*\*\* 0.376 0.334 0.600 0.268 **C-FAS** -0.023 0.163 0.234 0.265 0.366\*\*\* 0.440 0.345 0.160 **C-AN** -0.039 0.261 0.311 0.175 0.367 0.349\*\*\* 0.309 0.134 **Str-CW** 0.003 0.186 0.226 0.424 0.262 0.160 0.429\*\*\* -0.134 **Str-Int** -0.071 -0.010 0.089 0.228 0.128 0.107 -0.233 0.275\*\*\*

**Leuko** 0.432\*\*\* -2.10 -0.281 -0.270 -0.213 -0.172 -0.197 -0.108 **RAV-DR** -0.007 0.390\*\*\* 0.790 0.416 0.307 0.285 0.275 0.153 **RAV-TL** -0.079 0.729 0.440\*\*\* 0.492 0.401 0.358 0.308 0.257 **DSST** -0.075 0.188 0.220 0.556\*\*\* 0.557 0.489 0.534 0.311 **C-FAS** -0.081 0.136 0.020 0.298 0.536\*\*\* 0.540 0.347 0.311 **C-AN** -0.031 0.143 0.188 0.245 0.395 0.329\*\*\* 0.357 0.204 **Str-CW** -0.056 0.145 0.132 0.332 0.170 0.161 0.440\*\*\* -0.189 **Str-Int** -0.021 0.046 0.139 0.194 0.219 0.129 -0.339 0.154\* Leuko = Ln(leukoaraios+1), RAV-DR = RAVLT delayed recall, RAV-TL = RAVLT total learning, C-FAS = COWA FAS, C-AN = COWA animals, Str-CW = Stroop color word, Str-Int = Stroop interference

For all traits modeled with covariates, biometric models included age, sex, and education. The biometric

environmental effects. For all estimates of genetic and environmental correlations,

The majority of significant genetic correlations observed were in whites. In whites, significant genetic correlations ranged from 0.263 (RAVLT total learning and DSST) to 0.918 (RAVLT total learning and RAVLT delayed recall). Other highly significant genetic correlations (p-value<0.001) were between DSST and Stroop color word (0.7) and between RAVLT total learning and COWA animals (0.55). Many of the pairs involving RAVLT, COWA, and DSST also showed significant genetic correlations, ranging from 0.263 to 0.476. Leukoaraiosis and RAVLT had a marginally significant negative genetic correlation (-0.28), indicating that genes shared between these two traits have opposite effects on the traits (for example, a certain genetic variation may increase leukoaraiosis volume while decreasing learning scores). No other evidence of pleiotropic effects was found between leukoaraiosis

In contrast to the relative abundance of genetic correlations between these measures, there were very few significant environmental correlations in whites. The most significant

Above diagonal: phenotypic correlations, p, for traits modeled without covariates Below diagonal: phenotypic correlations, p, for traits modeled with covariates Diagonal: heritabilities from polygenic analysis, h2, for traits modeled with covariates

model for ln(leukoaraiosis+1) also included TIV. Null hypothesis of tests: h2 = 0 (diagonal) \*

and cognitive measures.

0.01 < p-value < 0.05, \*\* 0.001 < p-value < 0.01, \*\*\* p-value < 0.001

adjustment covariates were included in the biometric models.

Table 5. Biometrically derived phenotypic correlations among traits

**TL DSST C-FAS C-AN** 

**Str-CW**  **Str-Int** 

**RAV-**

**Leuko**

*Whites*

*African Americans*

**RAV-DR** 

Heritabilities in traits modeled without covariates were lowest for Stroop interference (0.302 in whites, 0.135 in African Americans) and highest for DSST (0.774 in whites, 0.81 in African Americans), with the majority of heritabilities in the range of 0.45 to 0.6. Leukoaraiosis had a higher heritability in whites (0.656) than in African Americans (0.485). After including covariates in the biometric models, heritabilities for the traits were generally lower but remained highly significant. Again, Stroop interference had the lowest heritability in both groups (0.275 in whites, 0.154 in African Americans) and DSST had the highest (0.843 in whites, 0.556 in African Americans), with the remaining traits ranging between 0.33 and 0.54. Leukoaraiosis still showed higher heritability in whites (0.529) than in African Americans (0.432).

The proportion of the observed trait variance accounted for by covariates estimated with biometric modeling mirrored the relationships we observed in multivariate linear mixed modeling, described above. The lowest proportion of variance explained was for Stroop interference (0.023 in whites, 0.075 in African Americans) and the highest was for DSST (0.403 in whites, 0.525 in African Americans). For the remainder of the traits, the proportion of variance explained by covariates ranged from 0.139 (COWA FAS) to 0.311 (leukoaraiosis) in whites and from 0.203 (RAVLT delayed recall) to 0.3 (COWA FAS) in African Americans. In order to determine the proportion of variation in the traits explained by genetic factors, we multiplied the proportion of variation not explained by the covariates by the heritability. Expressed as a percentage of total variation, genetic factors explain the lowest amount of variation in Stroop interference in both groups (26.87% in whites, 14.25% in African Americans). The largest amount of variation explained by genetic factors in whites was for DSST (50.33%) followed by RAVLT delayed recall (40.92%) and leukoaraiosis (36.45%). In African Americans, genetic factors explained the largest percentage of variation in COWA FAS (37.52%) followed by leukoaraiosis (33.83%) and Stroop color word (33.79%). For the majority of traits, the amount of variation explained by genetic factors was lower in African Americans than in whites, but most traits in both groups had at least 25% of variation explained by genetic factors, showing that genetics has an important influence on these traits.

#### **3.4 Phenotypic correlations between trait pairs**

The patterns observed in the correlations estimated biometrically in SOLAR are presented in Table 5. The strongest correlation in the traits modeled with covariates was between the two RAVLT measures (0.755 in whites, 0.729 in African Americans), and the weakest correlations were between leukoaraiosis and all cognitive traits (ranging from -0.001 to -0.083). In general, multiple measures from the same test exhibited stronger correlations than measures across tests, which is intuitive since measures from the same test are assessing different but closely related cognitive functions. Patterns of correlation in whites and African Americans were very similar, though whites generally tended to exhibit somewhat stronger correlations.

#### **3.5 Genetic and environmental correlations between trait pairs**

In order to begin to understand the extent to which pleiotropic genetic effects may be contributing to each pair of traits, we used a biometrical approach to estimate genetic and environmental correlations (Table 6). Overall, there were far more significant genetic correlations (pleiotropic effects) between trait pairs than environmental correlations, indicating that shared genetic effects were more common in these pairs of traits than shared


Leuko = Ln(leukoaraios+1), RAV-DR = RAVLT delayed recall, RAV-TL = RAVLT total learning, C-FAS = COWA FAS, C-AN = COWA animals, Str-CW = Stroop color word, Str-Int = Stroop interference Above diagonal: phenotypic correlations, p, for traits modeled without covariates

Below diagonal: phenotypic correlations, p, for traits modeled with covariates

Diagonal: heritabilities from polygenic analysis, h2, for traits modeled with covariates

For all traits modeled with covariates, biometric models included age, sex, and education. The biometric model for ln(leukoaraiosis+1) also included TIV.

Null hypothesis of tests: h2 = 0 (diagonal) \*

52 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Heritabilities in traits modeled without covariates were lowest for Stroop interference (0.302 in whites, 0.135 in African Americans) and highest for DSST (0.774 in whites, 0.81 in African Americans), with the majority of heritabilities in the range of 0.45 to 0.6. Leukoaraiosis had a higher heritability in whites (0.656) than in African Americans (0.485). After including covariates in the biometric models, heritabilities for the traits were generally lower but remained highly significant. Again, Stroop interference had the lowest heritability in both groups (0.275 in whites, 0.154 in African Americans) and DSST had the highest (0.843 in whites, 0.556 in African Americans), with the remaining traits ranging between 0.33 and 0.54. Leukoaraiosis still showed higher heritability in whites (0.529) than in African

The proportion of the observed trait variance accounted for by covariates estimated with biometric modeling mirrored the relationships we observed in multivariate linear mixed modeling, described above. The lowest proportion of variance explained was for Stroop interference (0.023 in whites, 0.075 in African Americans) and the highest was for DSST (0.403 in whites, 0.525 in African Americans). For the remainder of the traits, the proportion of variance explained by covariates ranged from 0.139 (COWA FAS) to 0.311 (leukoaraiosis) in whites and from 0.203 (RAVLT delayed recall) to 0.3 (COWA FAS) in African Americans. In order to determine the proportion of variation in the traits explained by genetic factors, we multiplied the proportion of variation not explained by the covariates by the heritability. Expressed as a percentage of total variation, genetic factors explain the lowest amount of variation in Stroop interference in both groups (26.87% in whites, 14.25% in African Americans). The largest amount of variation explained by genetic factors in whites was for DSST (50.33%) followed by RAVLT delayed recall (40.92%) and leukoaraiosis (36.45%). In African Americans, genetic factors explained the largest percentage of variation in COWA FAS (37.52%) followed by leukoaraiosis (33.83%) and Stroop color word (33.79%). For the majority of traits, the amount of variation explained by genetic factors was lower in African Americans than in whites, but most traits in both groups had at least 25% of variation explained by genetic factors, showing that genetics has an important influence on

The patterns observed in the correlations estimated biometrically in SOLAR are presented in Table 5. The strongest correlation in the traits modeled with covariates was between the two RAVLT measures (0.755 in whites, 0.729 in African Americans), and the weakest correlations were between leukoaraiosis and all cognitive traits (ranging from -0.001 to -0.083). In general, multiple measures from the same test exhibited stronger correlations than measures across tests, which is intuitive since measures from the same test are assessing different but closely related cognitive functions. Patterns of correlation in whites and African Americans were very

In order to begin to understand the extent to which pleiotropic genetic effects may be contributing to each pair of traits, we used a biometrical approach to estimate genetic and environmental correlations (Table 6). Overall, there were far more significant genetic correlations (pleiotropic effects) between trait pairs than environmental correlations, indicating that shared genetic effects were more common in these pairs of traits than shared

similar, though whites generally tended to exhibit somewhat stronger correlations.

**3.5 Genetic and environmental correlations between trait pairs** 

Americans (0.432).

these traits.

**3.4 Phenotypic correlations between trait pairs** 

0.01 < p-value < 0.05, \*\* 0.001 < p-value < 0.01, \*\*\* p-value < 0.001

Table 5. Biometrically derived phenotypic correlations among traits

environmental effects. For all estimates of genetic and environmental correlations, adjustment covariates were included in the biometric models.

The majority of significant genetic correlations observed were in whites. In whites, significant genetic correlations ranged from 0.263 (RAVLT total learning and DSST) to 0.918 (RAVLT total learning and RAVLT delayed recall). Other highly significant genetic correlations (p-value<0.001) were between DSST and Stroop color word (0.7) and between RAVLT total learning and COWA animals (0.55). Many of the pairs involving RAVLT, COWA, and DSST also showed significant genetic correlations, ranging from 0.263 to 0.476. Leukoaraiosis and RAVLT had a marginally significant negative genetic correlation (-0.28), indicating that genes shared between these two traits have opposite effects on the traits (for example, a certain genetic variation may increase leukoaraiosis volume while decreasing learning scores). No other evidence of pleiotropic effects was found between leukoaraiosis and cognitive measures.

In contrast to the relative abundance of genetic correlations between these measures, there were very few significant environmental correlations in whites. The most significant

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 55

The overall patterns of genetic and environmental correlations in African Americans were strikingly similar to the patterns observed in whites. However, many of the genetic correlations in African Americans did not reach statistical significance due to larger standard errors in their estimates, and there was slightly more evidence of shared environmental effects. Two of the four highly significant genetic correlations observed in whites were also observed in African Americans. RAVLT total learning and RAVLT delayed recall were the most strongly genetically correlated (0.915) followed by DSST and Stroop color word (0.698). The only other significant genetic correlations were between the two measures of COWA (0.533) and between COWA FAS and Stroop color word (0.363). There were no significant genetic

As with whites, the most highly significant environmental correlation was between the two measures of RAVLT (0.596) and between Stroop color word and Stroop interference (-0.541). The direction and magnitudes of the correlations for these traits were also the same in African Americans as they were in whites. The other strongly significant environmental correlations observed in African Americans were between DSST and RAVLT total learning (0.401) and DSST and COWA FAS (0.442). Four additional pairs of traits also exhibited marginally significant environmental correlations, including the two COWA measures (0.313) that also showed a marginally significant environmental correlation in whites.

In our study, the heritability of leukoaraiosis was 0.529 in whites and 0.432 in African Americans, after adjustment for age, sex, and total intracranial volume. This finding is consistent with heritability estimates from comparable studies. Heritability was estimated to be 0.71 in study of white male twins (mean age 73 years) after adjustment for age and head size (Carmelli et al., 1998) and 0.55 in a sample of stroke- and dementia-free subjects (mean age 61.0 years) after adjustment for sex, age, age2, and total cranial volume (Atwood et el., 2004). Turner et al. (2004) showed that leukoaraiosis has a consistently high heritability even after adjustment for blood pressure. These high heritabilities imply that much of the inter-individual differences in variation of leukoaraiosis are due to differences

Our study estimates that the majority of heritabilities of seven measures of cognitive function in whites and African Americans are between ~0.35 and ~0.55. Previous studies of the heritability of cognitive functioning has been conducted primarily in twin studies that use factor analysis to identify a common factor to act as a proxy for overall cognitive function, and the findings point to a higher heritability for this measure than was estimated in our study. For example, McGue and Christensen (2002) estimated the heritability of general cognitive function as measured by five cognitive tasks comprised of fluency, digit span, and recall to be 0.70. Finkel et al. (1995) peformed quantitative genetic analysis on four measures of cognitive function (verbal, spatial, perceptual speed, and memory) and showed that heritability for a general cognitive factor was between 0.54 and 0.81 in two samples

Our results show that there are differences in heritability across cognitive measures, with processing speed having the highest heritability in whites (0.843) and African Americans

correlations between leukoaraiosis and any of the cognitive traits.

**4. Discussion** 

in genetics.

**4.1 Heritability of leukoaraiosis**

**4.2 Heritability of cognitive function** 

across several age groups of adults (from young to elderly).

environmental correlation was between the trait pair that also had the highest genetic correlation, RAVLT total learning and RAVLT delayed recall (0.586), although the environmental correlation was substantially less than the genetic correlation. This indicates that for this trait pair, shared genetic effects have a stronger influence than shared environmental effects, though both contribute to the observed strong phenotypic correlation. The only other highly significant environmental correlation was between Stroop color word and Stroop interference (-0.427). This correlation is negative since poor cognitive performance is indicated by a low score on Stroop color word but by a high score on Stroop interference. Only two other trait pairs exhibited even marginally significant environmental correlations in whites. Leukoaraiosis had a negative environmental correlation with Stroop interference (-0.274) and the two measures from the COWA had a positive environmental correlation (0.293).


Leuko = Ln(leukoaraios+1), RAV-DR = RAVLT delayed recall, RAV-TL = RAVLT total learning, C-FAS = COWA FAS, C-AN = COWA animals, Str-CW = Stroop color word, Str-Int = Stroop interference Above diagonal: environmental correlations, <sup>e</sup>

Below diagonal: genetic correlations, <sup>g</sup>

Diagonal: heritabilities from univariate polygenic analysis, h2, for adjusted traits

For all adjusted traits, biometric models included age, sex, and education. The biometric model for ln(leukoaraiosis+1) also included TIV.

Null hypothesis of tests: e = 0 (above diagonal)

Null hypothesis of tests: g = 0 (below diagonal)

Null hypothesis of tests: h2 = 0 (diagonal) \*

0.01 < p-value < 0.05, \*\* 0.001 < p-value < 0.01, \*\*\* p-value < 0.001

Table 6. Genetic and enviromental correlations among traits

The overall patterns of genetic and environmental correlations in African Americans were strikingly similar to the patterns observed in whites. However, many of the genetic correlations in African Americans did not reach statistical significance due to larger standard errors in their estimates, and there was slightly more evidence of shared environmental effects. Two of the four highly significant genetic correlations observed in whites were also observed in African Americans. RAVLT total learning and RAVLT delayed recall were the most strongly genetically correlated (0.915) followed by DSST and Stroop color word (0.698). The only other significant genetic correlations were between the two measures of COWA (0.533) and between COWA FAS and Stroop color word (0.363). There were no significant genetic correlations between leukoaraiosis and any of the cognitive traits.

As with whites, the most highly significant environmental correlation was between the two measures of RAVLT (0.596) and between Stroop color word and Stroop interference (-0.541). The direction and magnitudes of the correlations for these traits were also the same in African Americans as they were in whites. The other strongly significant environmental correlations observed in African Americans were between DSST and RAVLT total learning (0.401) and DSST and COWA FAS (0.442). Four additional pairs of traits also exhibited marginally significant environmental correlations, including the two COWA measures (0.313) that also showed a marginally significant environmental correlation in whites.

#### **4. Discussion**

54 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

environmental correlation was between the trait pair that also had the highest genetic correlation, RAVLT total learning and RAVLT delayed recall (0.586), although the environmental correlation was substantially less than the genetic correlation. This indicates that for this trait pair, shared genetic effects have a stronger influence than shared environmental effects, though both contribute to the observed strong phenotypic correlation. The only other highly significant environmental correlation was between Stroop color word and Stroop interference (-0.427). This correlation is negative since poor cognitive performance is indicated by a low score on Stroop color word but by a high score on Stroop interference. Only two other trait pairs exhibited even marginally significant environmental correlations in whites. Leukoaraiosis had a negative environmental correlation with Stroop interference (-0.274) and the two measures from the COWA had a positive environmental

correlation (0.293).

*Whites*

*African Americans*

**Leuko**

Above diagonal: environmental correlations, <sup>e</sup> Below diagonal: genetic correlations, <sup>g</sup>

Null hypothesis of tests: e = 0 (above diagonal) Null hypothesis of tests: g = 0 (below diagonal) Null hypothesis of tests: h2 = 0 (diagonal) \*

ln(leukoaraiosis+1) also included TIV.

Diagonal: heritabilities from univariate polygenic analysis, h2, for adjusted traits

 0.01 < p-value < 0.05, \*\* 0.001 < p-value < 0.01, \*\*\* p-value < 0.001 Table 6. Genetic and enviromental correlations among traits

**RAV-DR** 

**RAV-**

**Leuko** 0.529\*\*\* 0.078 0.178 -0.008 -0.092 -0.136 -0.066 -0.274\* **RAV-DR** -0.233 0.526\*\*\* 0.586\*\*\* -0.015 -0.072 0.185 0.087 -0.024 **RAV-TL** -0.280\* 0.918\*\*\* 0.516\*\*\* 0.354 0.149 0.142 0.128 0.092 **DSST** -0.092 0.329\*\* 0.263\* 0.843\*\*\* 0.107 0.015 0.021 0.276 **C-FAS** 0.062 0.476\*\* 0.350\* 0.418\*\* 0.366\*\*\* 0.293\* 0.163 0.185 **C-AN** 0.084 0.372\* 0.550\*\* 0.310\* 0.495\* 0.349\*\*\* 0.023 0.157 **Str-CW** 0.078 0.296 0.336\* 0.700\*\*\* 0.413\* 0.371\* 0.429\*\*\* -0.427\*\*\* **Str-Int** 0.230 0.010 0.091 0.280 0.007 -0.004 0.146 0.275\*\*\*

**Leuko** 0.432\*\*\* -0.161 -0.261 -0.232 -0.169 -0.127 -0.194 0.130 **RAV-DR** 0.215 0.390\*\*\* 0.596\*\*\* 0.327\* 0.167 0.166 0.040 0.035 **RAV-TL** 0.158 0.915\*\*\* 0.440\*\*\* 0.401\*\* 0.322\* 0.128 0.017 0.035 **DSST** 0.078 0.036 0.045 0.556\*\*\* 0.442\*\* 0.270\* -0.005 0.237 **C-FAS** 0.010 0.102 0.075 0.179 0.536\*\*\* 0.313\* -0.019 0.113 **C-AN** 0.124 0.101 0.286 0.228 0.533\*\* 0.329\*\*\* 0.158 0.020 **Str-CW** 0.128 0.293 0.278 0.698\*\*\* 0.363\* 0.167 0.440\*\*\* -0.541\*\*\* **Str-Int** -0.422 0.010 0.432 0.164 0.507 0.522 0.099 0.154\* Leuko = Ln(leukoaraios+1), RAV-DR = RAVLT delayed recall, RAV-TL = RAVLT total learning, C-FAS = COWA FAS, C-AN = COWA animals, Str-CW = Stroop color word, Str-Int = Stroop interference

For all adjusted traits, biometric models included age, sex, and education. The biometric model for

**TL DSST C-FAS C-AN** 

**Str-CW**  **Str-Int** 

#### **4.1 Heritability of leukoaraiosis**

In our study, the heritability of leukoaraiosis was 0.529 in whites and 0.432 in African Americans, after adjustment for age, sex, and total intracranial volume. This finding is consistent with heritability estimates from comparable studies. Heritability was estimated to be 0.71 in study of white male twins (mean age 73 years) after adjustment for age and head size (Carmelli et al., 1998) and 0.55 in a sample of stroke- and dementia-free subjects (mean age 61.0 years) after adjustment for sex, age, age2, and total cranial volume (Atwood et el., 2004). Turner et al. (2004) showed that leukoaraiosis has a consistently high heritability even after adjustment for blood pressure. These high heritabilities imply that much of the inter-individual differences in variation of leukoaraiosis are due to differences in genetics.

#### **4.2 Heritability of cognitive function**

Our study estimates that the majority of heritabilities of seven measures of cognitive function in whites and African Americans are between ~0.35 and ~0.55. Previous studies of the heritability of cognitive functioning has been conducted primarily in twin studies that use factor analysis to identify a common factor to act as a proxy for overall cognitive function, and the findings point to a higher heritability for this measure than was estimated in our study. For example, McGue and Christensen (2002) estimated the heritability of general cognitive function as measured by five cognitive tasks comprised of fluency, digit span, and recall to be 0.70. Finkel et al. (1995) peformed quantitative genetic analysis on four measures of cognitive function (verbal, spatial, perceptual speed, and memory) and showed that heritability for a general cognitive factor was between 0.54 and 0.81 in two samples across several age groups of adults (from young to elderly).

Our results show that there are differences in heritability across cognitive measures, with processing speed having the highest heritability in whites (0.843) and African Americans

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 57

African Americans showed little evidence for genetic correlation among cognitive traits, a

Heritabilities of leukoaraiosis and cognitive measures showed a consistent pattern in whites and African Americans. DSST had the highest heritability (0.883 in whites, 0.556 in African Americans), Stroop interference had the lowest heritability (0.275 in whites, 0.154 in African Americans), and leukoaraiosis and the other cognitive measures had mid-range heritabilities (0.35-0.53 in whites, 0.33-0.54 in African Americans). However, heritabilities showed a clear trend of being lower in African Americans, with COWA FAS being the only notable exception (heritability = 0.366 in whites, 0.536 in African Americans). A similar trend was observed for overall phenotypic correlations and genetic correlations, with African

There are several reasons that could account for the lower observed heritabilities in African Americans. Since heritability is the fraction of the total variability of the trait accounted for by additive genetic factors, lower heritabilities could result from greater trait variation (a larger denominator) or from a smaller contribution from additive genetic effects (a smaller numerator). Differences in either the numerator or the demoninator could be due to true population differences between whites and African Americans, or they could simply be artefacts of the GENOA samples, such as differences in age or family structure. We examined the possibility that age or family structure may be responsible for the differences in heritability by re-estimating heritabilities in sub-samples of each ethnic group that were of equivalent age or had equivalent family compositions (data not shown). Trends in the heritabilities remained consistent across sub-samples, so we concluded that the lower heritabilities observed in the African American GENOA sample reflect a true difference in the population parameters of the groups studied and is not an artefact of the GENOA sample structure. However, it is possible that the same factors hypothesized to contribute to variability in test scores among ethnic groups (e.g., cultural variability in familiarity with testing response sets, motivation and attitudes toward test-taking) may have increased the measurement error of the cognitive function tests in the African American sample, resulting

Lower heritabilities of leukoaraiosis and the seven cognitive traits as well as differences in the genetic and environmental correlations between GENOA whites and African Americans suggest that non-genetic factors have a greater effect in African Americans than in whites for all of the brain traits studied. Though similar patterns were observed in whites and African Americans, genetic correlations (evidence of shared genetic effects) among cognitive traits tended to be higher and more significant in whites. While very little evidence of environmental correlation (shared environmental effects) between cognitive traits was observed in whites, eight of the 21 pairs of cognitive traits (38%) had evidence of significant environmental correlation in African Americans. Therefore, it is likely that non-genetic factors are indeed playing a larger role in affecting variation in brain traits in African

Most studies of the genetic and environmental factors associated with leukoaraiosis have had samples composed of individuals who have already experienced clinical endpoints such

significant genetic correlation was found for DSST and Stroop color word.

Americans showing a similar but weaker correlational structure.

in lower heritability estimates for this group.

**4.5 The effect of age on genetic parameter estimation** 

American GENOA sample.

**4.4 Differences in the genetic parameters for whites and African Americans** 

(0.556). Other studies have also shown that processing speed has the strongest genetic influence among measures of executive function (Carmelli et al., 2002). The heritability of executive function generally tends to be higher than that of memory, with heritabilities for executive functions between 0.34-0.70 (Carmelli et al., 2002; Sleegers et al., 2007) and heritabilities for memory function closer to 0.2-0.4 (McGue & Christensen, 2001; Plomin et al., 1994; Sleegers et al., 2007). In GENOA whites, memory measures (RAVLT) had slightly higher heritabilities than most of the executive function tests except for DSST. However, in African Americans, heritability of memory measures tended to be similar to those of executive funtion.

While existing research supports true differences in the heritabilities of cognitive domains, a portion of the observed differences may be due to the nature of the tests and scoring procedures. More complex tests such as Stroop may be more susceptible to measurement error than less complex tests such as DSST, and test scores that are mathematically manipulated (e.g., Stroop interference) are particularly susceptible to this type of error. Increased measurement error may lead to lower heritability estimations as well as weaker genetic and environmental correlations among trait pairs.

#### **4.3 Bivariate variance component analysis in leukoaraiosis and cognitive traits**

We found that in GENOA whites, measures of cognitive function exhibit substantial evidence of genetic correlation (pleiotropy), with measures of similar tests showing stronger genetic correlation. Evidence of phenotypic correlation due to shared environment was largely limited to a smaller number of cognitive trait pairs in African Americans. However, we detected no evidence of genetic or environmental correlations between measures of cognitive function and leukoaraiosis.

The lack of evidence of genetic correlation between leukoaraiosis and cognitive function in this study stands in contrast to a study conducted by Carmelli, et al. (2002), which used maximum likelihood nested modeling techniques to estimate the proportion of variance in leukoaraiosis and executive control function due to genetic, shared environmental, and non-shared environmental effects in 142 pairs of elderly twins (mean age = 73 years). The total phenotypic correlation between leukoaraiosis and executive function was -0.20, and they found that 70% of the total phenotypic correlation was accounted for by shared genes while 30% was accounted for by shared environments. While this is substantial, the contribution of overlapping genes (genes shared between the executive control factor and leukoaraiosis) to the genetic variance in executive function was only 8% due to the relatively low phenotypic correlation. The lack of detecting shared genetic or enviornmental effects between leukoaraiosis and measures of cognitive function in the GENOA study was partially due to the very low phenotypic correlations among leukoaraiosis and the measures of cognitive function, which may be a function of the younger average age of GENOA participants.

Other studies of the shared genetic components of cognitive traits tend to focus on change in cognition over time. Variance components analysis of the relationship between cognitive change and perception speed in a study of 292 twins aged 40-84 revealed that 90% of the age-related variance and 70% of the genetic variance in cognitive function was shared with perception speed, demonstrating that there is a genetic component to processing speed which also influences general cognitive functioning (Finkel & Pedersen, 2000). This finding was supported by the GENOA study, as processing speed (DSST) exhibited genetic correlation with nearly all of the other cognitive measures in whites. Although GENOA

(0.556). Other studies have also shown that processing speed has the strongest genetic influence among measures of executive function (Carmelli et al., 2002). The heritability of executive function generally tends to be higher than that of memory, with heritabilities for executive functions between 0.34-0.70 (Carmelli et al., 2002; Sleegers et al., 2007) and heritabilities for memory function closer to 0.2-0.4 (McGue & Christensen, 2001; Plomin et al., 1994; Sleegers et al., 2007). In GENOA whites, memory measures (RAVLT) had slightly higher heritabilities than most of the executive function tests except for DSST. However, in African Americans, heritability of memory measures tended to be similar to those of

While existing research supports true differences in the heritabilities of cognitive domains, a portion of the observed differences may be due to the nature of the tests and scoring procedures. More complex tests such as Stroop may be more susceptible to measurement error than less complex tests such as DSST, and test scores that are mathematically manipulated (e.g., Stroop interference) are particularly susceptible to this type of error. Increased measurement error may lead to lower heritability estimations as well as weaker

**4.3 Bivariate variance component analysis in leukoaraiosis and cognitive traits** 

We found that in GENOA whites, measures of cognitive function exhibit substantial evidence of genetic correlation (pleiotropy), with measures of similar tests showing stronger genetic correlation. Evidence of phenotypic correlation due to shared environment was largely limited to a smaller number of cognitive trait pairs in African Americans. However, we detected no evidence of genetic or environmental correlations between measures of

The lack of evidence of genetic correlation between leukoaraiosis and cognitive function in this study stands in contrast to a study conducted by Carmelli, et al. (2002), which used maximum likelihood nested modeling techniques to estimate the proportion of variance in leukoaraiosis and executive control function due to genetic, shared environmental, and non-shared environmental effects in 142 pairs of elderly twins (mean age = 73 years). The total phenotypic correlation between leukoaraiosis and executive function was -0.20, and they found that 70% of the total phenotypic correlation was accounted for by shared genes while 30% was accounted for by shared environments. While this is substantial, the contribution of overlapping genes (genes shared between the executive control factor and leukoaraiosis) to the genetic variance in executive function was only 8% due to the relatively low phenotypic correlation. The lack of detecting shared genetic or enviornmental effects between leukoaraiosis and measures of cognitive function in the GENOA study was partially due to the very low phenotypic correlations among leukoaraiosis and the measures of cognitive function, which may be a function of the

Other studies of the shared genetic components of cognitive traits tend to focus on change in cognition over time. Variance components analysis of the relationship between cognitive change and perception speed in a study of 292 twins aged 40-84 revealed that 90% of the age-related variance and 70% of the genetic variance in cognitive function was shared with perception speed, demonstrating that there is a genetic component to processing speed which also influences general cognitive functioning (Finkel & Pedersen, 2000). This finding was supported by the GENOA study, as processing speed (DSST) exhibited genetic correlation with nearly all of the other cognitive measures in whites. Although GENOA

genetic and environmental correlations among trait pairs.

cognitive function and leukoaraiosis.

younger average age of GENOA participants.

executive funtion.

African Americans showed little evidence for genetic correlation among cognitive traits, a significant genetic correlation was found for DSST and Stroop color word.

#### **4.4 Differences in the genetic parameters for whites and African Americans**

Heritabilities of leukoaraiosis and cognitive measures showed a consistent pattern in whites and African Americans. DSST had the highest heritability (0.883 in whites, 0.556 in African Americans), Stroop interference had the lowest heritability (0.275 in whites, 0.154 in African Americans), and leukoaraiosis and the other cognitive measures had mid-range heritabilities (0.35-0.53 in whites, 0.33-0.54 in African Americans). However, heritabilities showed a clear trend of being lower in African Americans, with COWA FAS being the only notable exception (heritability = 0.366 in whites, 0.536 in African Americans). A similar trend was observed for overall phenotypic correlations and genetic correlations, with African Americans showing a similar but weaker correlational structure.

There are several reasons that could account for the lower observed heritabilities in African Americans. Since heritability is the fraction of the total variability of the trait accounted for by additive genetic factors, lower heritabilities could result from greater trait variation (a larger denominator) or from a smaller contribution from additive genetic effects (a smaller numerator). Differences in either the numerator or the demoninator could be due to true population differences between whites and African Americans, or they could simply be artefacts of the GENOA samples, such as differences in age or family structure. We examined the possibility that age or family structure may be responsible for the differences in heritability by re-estimating heritabilities in sub-samples of each ethnic group that were of equivalent age or had equivalent family compositions (data not shown). Trends in the heritabilities remained consistent across sub-samples, so we concluded that the lower heritabilities observed in the African American GENOA sample reflect a true difference in the population parameters of the groups studied and is not an artefact of the GENOA sample structure. However, it is possible that the same factors hypothesized to contribute to variability in test scores among ethnic groups (e.g., cultural variability in familiarity with testing response sets, motivation and attitudes toward test-taking) may have increased the measurement error of the cognitive function tests in the African American sample, resulting in lower heritability estimates for this group.

Lower heritabilities of leukoaraiosis and the seven cognitive traits as well as differences in the genetic and environmental correlations between GENOA whites and African Americans suggest that non-genetic factors have a greater effect in African Americans than in whites for all of the brain traits studied. Though similar patterns were observed in whites and African Americans, genetic correlations (evidence of shared genetic effects) among cognitive traits tended to be higher and more significant in whites. While very little evidence of environmental correlation (shared environmental effects) between cognitive traits was observed in whites, eight of the 21 pairs of cognitive traits (38%) had evidence of significant environmental correlation in African Americans. Therefore, it is likely that non-genetic factors are indeed playing a larger role in affecting variation in brain traits in African American GENOA sample.

#### **4.5 The effect of age on genetic parameter estimation**

Most studies of the genetic and environmental factors associated with leukoaraiosis have had samples composed of individuals who have already experienced clinical endpoints such

Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 59

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as stroke or severe cognitive decline. The relatively young age range of our sample provided the unique opportunity to examine the relationships between leukoaraiosis and cognitive phenotypes in asymptomatic individuals, at a time when preventive treatment would be most effective. However, the young age of our sample also imposed constraints, including the limited variability in the leukoaraiosis phenotype. In addition, it has been shown that heritabilities of cognitive traits tend to vary with age (Knopman et al., 2001; Mattay, 2008). Since this study was cross-sectional, we did not have the ability to examine how heritabilities and genetic correlations change over time. Differential heritabilities across age groups also implies that there may be genetic factors that show age-related changes in penetrance with respect to cognitive traits. It is therefore plausible that the genetic correlations between leukoaraiosis and cognitive traits may also change with age.

#### **5. Conclusion**

The complex relationship between subclinical measures and clinical outcomes underscores the importance of studying leukoaraiosis and cognitive decline as the predecessors of stroke and dementia in order to better elucide the shared and unique contributions of genetic factors to the disease pathologies that result from hypertension and other risk factors. This study illustrates that the genetic and environmental influences on the subclinical measures of stroke and dementia vary substantially between measures of structural injury (leukoaraiosis) and performance on cognitive tests, and that unique patterns of genetic and environmental correlation exist across cognitive domains (memory vs. executive function).

All of the traits studied demonstrate significant heritability, indicating that genetic factors account for a substantial portion of the variability in leukoaraiosis as well as multiple measures of cognitive function. Some of the cognitive measures, particularly those that assessed similar cognitive domains, demonstrated a significant degree of shared genetic effects, while others demonstrated a greater degree of shared environmental effects. Leukoaraiosis, while heritable, does not share any genetic or environmental influences with the cognitive measures. Patterning of heritability and genetic/environmental correlations showed definitive trends that were consistent across ethic groups, but one clear difference was that cognitive measures tended to have more shared genetic effects in whites and more shared enviornmental effects in African Americans. These results indicate that the environmental and genetic factors that predispose individuals to leukoaraiosis and cognitive decline are likely to be best understood and studied at the family and community levels. Integrating genetic information with family history and cultural or socio-economic stressors and supports is likely to contribute to new knowledge of the unique and shared risk factors for these traits, and thus lead to more effective preventive strategies.

#### **6. Acknowledgements**

Data collection and statistical analysis was supported by the National Institutes of Health research grants U10 HL54457, U01 HL054481, and R01 NS041558. We would like to thank Eric Boerwinkle and Myriam Fornage (University of Texas Health Science Center), Clifford Jack, Jr. (Mayo Clinic), Wei Zhao and Patricia Peyser (University of Michigan), Reagan Kelly (Z-Tech at National Center for Toxological Research), the research staff at the Mayo Clinic and University of Mississippi field centers, and the families that participated in the GENOA study.

#### **7. References**

58 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

as stroke or severe cognitive decline. The relatively young age range of our sample provided the unique opportunity to examine the relationships between leukoaraiosis and cognitive phenotypes in asymptomatic individuals, at a time when preventive treatment would be most effective. However, the young age of our sample also imposed constraints, including the limited variability in the leukoaraiosis phenotype. In addition, it has been shown that heritabilities of cognitive traits tend to vary with age (Knopman et al., 2001; Mattay, 2008). Since this study was cross-sectional, we did not have the ability to examine how heritabilities and genetic correlations change over time. Differential heritabilities across age groups also implies that there may be genetic factors that show age-related changes in penetrance with respect to cognitive traits. It is therefore plausible that the genetic

correlations between leukoaraiosis and cognitive traits may also change with age.

risk factors for these traits, and thus lead to more effective preventive strategies.

Data collection and statistical analysis was supported by the National Institutes of Health research grants U10 HL54457, U01 HL054481, and R01 NS041558. We would like to thank Eric Boerwinkle and Myriam Fornage (University of Texas Health Science Center), Clifford Jack, Jr. (Mayo Clinic), Wei Zhao and Patricia Peyser (University of Michigan), Reagan Kelly (Z-Tech at National Center for Toxological Research), the research staff at the Mayo Clinic and University of Mississippi field centers, and the families that participated in the GENOA

The complex relationship between subclinical measures and clinical outcomes underscores the importance of studying leukoaraiosis and cognitive decline as the predecessors of stroke and dementia in order to better elucide the shared and unique contributions of genetic factors to the disease pathologies that result from hypertension and other risk factors. This study illustrates that the genetic and environmental influences on the subclinical measures of stroke and dementia vary substantially between measures of structural injury (leukoaraiosis) and performance on cognitive tests, and that unique patterns of genetic and environmental correlation exist across cognitive domains (memory vs. executive function). All of the traits studied demonstrate significant heritability, indicating that genetic factors account for a substantial portion of the variability in leukoaraiosis as well as multiple measures of cognitive function. Some of the cognitive measures, particularly those that assessed similar cognitive domains, demonstrated a significant degree of shared genetic effects, while others demonstrated a greater degree of shared environmental effects. Leukoaraiosis, while heritable, does not share any genetic or environmental influences with the cognitive measures. Patterning of heritability and genetic/environmental correlations showed definitive trends that were consistent across ethic groups, but one clear difference was that cognitive measures tended to have more shared genetic effects in whites and more shared enviornmental effects in African Americans. These results indicate that the environmental and genetic factors that predispose individuals to leukoaraiosis and cognitive decline are likely to be best understood and studied at the family and community levels. Integrating genetic information with family history and cultural or socio-economic stressors and supports is likely to contribute to new knowledge of the unique and shared

**5. Conclusion** 

**6. Acknowledgements** 

study.


Shared Genetic Effects among Measures of Cognitive Function and Leukoaraiosis 61

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**4** 

Bronwen Connor

*New Zealand* 

**Compensatory Neurogenesis** 

*Department of Pharmacology and Clinical Pharmacology, Centre for Brain Research* 

The occurrence of neurogenesis, defined as the generation of new neurons, has become well established in the adult mammalian brain, including the human brain over the last two decades. Neurogenesis in the adult brain can be divided into four phases: (a) progenitor cell proliferation; (b) migration of progenitor cells towards a target area; (c) terminal differentiation into a specific phenotype, and; (d) integration into established networks. Neural stem/progenitor cells generate neurons throughout life in the mammalian forebrain subventricular zone (SVZ)–olfactory bulb (OB) pathway and the hippocampal dentate gyrus [for review see (Whitman*, et al.*, 2009)]. Neural progenitor cells can be isolated from these two regions and cultured *in vitro* as self-renewable neurospheres in epidermal growth factor (EGF) and fibroblast growth factor-2 (FGF2) containing media (Reynolds*, et al.*, 1992, Reynolds*, et al.*, 1996). Upon withdrawal of growth factors, they differentiate into the three main neural lineages; neurons, astrocytes and oligodendrocytes (Reynolds & Weiss, 1996). There are four major cell types within the adult SVZ-OB pathway; ependymal cells, Type B, Type C and Type A cells (Doetsch*, et al.*, 1997). The true neural stem cells in this region are the Type B cells which have the characteristics of radial glial cells, including the expression of GFAP (Doetsch*, et al.*, 1997, Doetsch*, et al.*, 1999). Type B cells proliferate slowly to generate Type C cells, which are the most rapidly proliferating cell type in the SVZ. The bipotent Type C cells are able to divide either symmetrically or asymmetrically to generate glial or neural precursor cells. The SVZ-OB pathway is organized as an extensive network of chains of migrating neural precursor cells (neuroblasts; Type A cells) that travel through glial tubes formed by GFAP positive radial glial-like cells (Lois*, et al.*, 1994, Doetsch*, et al.*, 1996, Lois*, et al.*, 1996, Doetsch*, et al.*, 1997). SVZ- derived neuroblasts migrate long distances via a restricted forebrain pathway known as the rostral migratory stream (RMS) to their final destination in the olfactory bulb. This is achieved through a unique form of tangential chain migration. Migrating neuroblasts (Type A cells) in the SVZ – OB pathway can be identified by their expression of characteristic markers such as the polysialylated form of neural cell adhesion molecule (PSA-NCAM), neuron-specific βIII-tubulin and doublecortin (Dcx). Once the neuroblasts reach the subependymal region of the olfactory bulb, they disperse radially and differentiate into granule and periglomerular neurons (Luskin, 1993, Lois&Alvarez-Buylla, 1994, Lois*, et al.*, 1996, Thomas*, et al.*, 1996, Curtis*, et al.*,

**1. Introduction** 

 *Faculty of Medical and Health Sciences, The University of Auckland* 

**in the Injured Adult Brain**


### **Compensatory Neurogenesis in the Injured Adult Brain**

Bronwen Connor

*Department of Pharmacology and Clinical Pharmacology, Centre for Brain Research Faculty of Medical and Health Sciences, The University of Auckland New Zealand* 

#### **1. Introduction**

62 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Roger, V.L., Go, A.S., Lloyd-Jones, D.M., Adams, R.J., Berry, J.D., Brown, T.M., Carnethon,

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Specific Susceptibility for Different Types of Ischaemic Stroke and Leukoaraiosis.

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Pleiotropy in C. Elegans Early Embryogenesis. *PLoS Computational Biology*, Vol. 4,

The occurrence of neurogenesis, defined as the generation of new neurons, has become well established in the adult mammalian brain, including the human brain over the last two decades. Neurogenesis in the adult brain can be divided into four phases: (a) progenitor cell proliferation; (b) migration of progenitor cells towards a target area; (c) terminal differentiation into a specific phenotype, and; (d) integration into established networks. Neural stem/progenitor cells generate neurons throughout life in the mammalian forebrain subventricular zone (SVZ)–olfactory bulb (OB) pathway and the hippocampal dentate gyrus [for review see (Whitman*, et al.*, 2009)]. Neural progenitor cells can be isolated from these two regions and cultured *in vitro* as self-renewable neurospheres in epidermal growth factor (EGF) and fibroblast growth factor-2 (FGF2) containing media (Reynolds*, et al.*, 1992, Reynolds*, et al.*, 1996). Upon withdrawal of growth factors, they differentiate into the three main neural lineages; neurons, astrocytes and oligodendrocytes (Reynolds & Weiss, 1996). There are four major cell types within the adult SVZ-OB pathway; ependymal cells, Type B, Type C and Type A cells (Doetsch*, et al.*, 1997). The true neural stem cells in this region are the Type B cells which have the characteristics of radial glial cells, including the expression of GFAP (Doetsch*, et al.*, 1997, Doetsch*, et al.*, 1999). Type B cells proliferate slowly to generate Type C cells, which are the most rapidly proliferating cell type in the SVZ. The bipotent Type C cells are able to divide either symmetrically or asymmetrically to generate glial or neural precursor cells. The SVZ-OB pathway is organized as an extensive network of chains of migrating neural precursor cells (neuroblasts; Type A cells) that travel through glial tubes formed by GFAP positive radial glial-like cells (Lois*, et al.*, 1994, Doetsch*, et al.*, 1996, Lois*, et al.*, 1996, Doetsch*, et al.*, 1997). SVZ- derived neuroblasts migrate long distances via a restricted forebrain pathway known as the rostral migratory stream (RMS) to their final destination in the olfactory bulb. This is achieved through a unique form of tangential chain migration. Migrating neuroblasts (Type A cells) in the SVZ – OB pathway can be identified by their expression of characteristic markers such as the polysialylated form of neural cell adhesion molecule (PSA-NCAM), neuron-specific βIII-tubulin and doublecortin (Dcx). Once the neuroblasts reach the subependymal region of the olfactory bulb, they disperse radially and differentiate into granule and periglomerular neurons (Luskin, 1993, Lois&Alvarez-Buylla, 1994, Lois*, et al.*, 1996, Thomas*, et al.*, 1996, Curtis*, et al.*,

Compensatory Neurogenesis in the Injured Adult Brain 65

Epilepsy, characterized by periodic and unpredictable occurrence of seizure activity, affects ~50 million people worldwide and temporal lobe epilepsy (TLE) is among the most frequent types of intractable epilepsy. Abnormal hippocampal neurogenesis has emerged as an important pathophysiology of TLE over the past decade [for review see (Kuruba*, et al.*, 2009)]. Initial studies on neurogenesis in animal models of TLE by Parent and colleagues (Parent*, et al.*, 1997, Parent*, et al.*, 1998) and Bengzon and colleagues (Bengzon*, et al.*, 1997) provided the first evidence for increased hippocampal neurogenesis following acute seizures. In these studies, an increase in the production of new cells was observed in the SGZ of the dentate gyrus following pilocarpine-induced status epilepticus (SE) (Parent*, et al.*, 1997, Gray*, et al.*, 1998) or kindling stimulations (Bengzon*, et al.*, 1997, Parent*, et al.*, 1998). However, by 3-4 weeks after seizure induction, neurogenesis returned to baseline levels. In normal animals, proliferating cells labeled with the mitotic marker bromodeoxyuridine (BrdU) are restricted to the SGZ of the hippocampus. In contrast, following seizure activity BrdU+ cells were found extensively in the dentate hilus and/or dentate molecular layer of the hippocampus, indicating aberrant migration of dividing cells in response to seizure-induced cell loss (Parent*, et al.*, 1997, Scharfman*, et al.*, 2000, Scharfman*, et al.*, 2002, Scharfman*, et al.*, 2003, Parent*, et al.*, 2006). Similarly, displaced granule cells have been observed in hippocampal tissues obtained from patients with TLE (Houser, 1990, Thom*, et al.*, 2002, Liu*, et al.*, 2008). This suggests that acute seizure-induced dentate gyrus neurogenesis promotes aberrant circuitry development, which likely contributes to the evolution of initial seizure-induced hippocampal injury

In addition to the neurogenic response observed in the hippocampus, progenitor cells in the SVZ also respond to seizure activity in the adult rodent brain. Within 1-2 weeks following pilocarpine-induced seizure activity, Parent and colleagues (Parent*, et al.*, 2002) observed an increase in BrdU labeling and Nissl staining in the RMS. These changes were associated with an increase in expression of the Type A neuroblast marker Dcx 2 – 3 weeks following prolonged seizures. At these same time points the RMS expanded and contained more proliferating cells and immature neurons. BrdU labeling and retroviral tracing showed that prolonged seizures also increased neuroblast migration to the olfactory bulb. Importantly, a large number of labeled cells were found adjacent to the RMS instead of within its realms (most prominent at 14 days following seizure induction), indicating that seizure activity induces aberrant migration of SVZ-derived progenitor cells into surrounding regions of the

Increased neurogenesis observed following acute seizure activity returns to baseline by about 2 months after the initial seizure episode in rats. The extent of neurogenesis has then been shown to decline significantly in the chronic phase of epilepsy when significant numbers of spontaneous seizures manifest [for review see (Hattiangady*, et al.*, 2008)]. A 64- 81% decrease in neurogenesis was reported at 5 months post-SE with an inverse relationship evident between the frequency of spontaneous seizures and the extent of neurogenesis (Hattiangady*, et al.*, 2004). The severe reduction in hippocampal neurogenesis observed in chronic TLE is not however associated with either decreased production of new cells or reduced survival of newly born cells in the dentate gyrus. Rather, it is due to a decline in the neuronal fate-choice decision of newly generated cells with the majority of newly born

**2. The response of progenitor cells to the injured brain** 

**2.1 Temporal lobe epilepsy** 

into chronic epilepsy (Kuruba*, et al.*, 2009).

brain (Parent*, et al.*, 2002).

2007). Studies have shown that olfactory granule and periglomerular cells are continuously added to the olfactory bulb to both increase total cell number over time in these layers as well as replace pre-existing cells (Lagace*, et al.*, 2007, Imayoshi*, et al.*, 2008). The function of persistent olfactory bulb neurogenesis is largely unknown, but increasing evidence supports a role for the new neurons in olfactory memory and odour discrimination (Gheusi*, et al.*, 2000, Petreanu*, et al.*, 2002, Rochefort*, et al.*, 2002).

In contrast to the extensive migration undertaken by neurons destined for the olfactory bulb, dentate gyrus granule neurons are born locally in the subgranular zone (SGZ), a germinal layer between the dentate gyrus and the hilus (Altman*, et al.*, 1965, Kaplan*, et al.*, 1977, Eriksson*, et al.*, 1998, Kornack*, et al.*, 1999, Gould*, et al.*, 2001). Within the SGZ, GFAP positive cells (Type B cells) divide to give rise to immature Type D cells, which then generate granule neurons (Palmer*, et al.*, 2000, Seri*, et al.*, 2001). Interestingly, Type D cells divide less frequently and are more differentiated than the transit amplifying Type C cells in the SVZ. SGZ-derived neural progenitor cells generate new neurons that make and receive functional synapses (Palmer*, et al.*, 2000, Song*, et al.*, 2002, Van Praag*, et al.*, 2002). Ongoing hippocampus neurogenesis is known to facilitate long-term potentiation and stimulate learning and memory (Van Praag*, et al.*, 1999, Wang*, et al.*, 2005, Imayoshi*, et al.*, 2008) with ablation of adult-born dentate granule cells impairing certain forms of hippocampaldependent learning (Dupret*, et al.*, 2008, Imayoshi*, et al.*, 2008, Clelland*, et al.*, 2009).

Adult neurogenesis is not static, but its rate may fluctuate in response to environmental change. Evidence from *in vitro* and *in vivo* studies have demonstrated that neurogenesis can be regulated by a range of growth and neurotrophic factors, neurotransmitters and hormones [for review see (Parent, 2003, Lie*, et al.*, 2004)]. Neurogenesis has also been shown to be altered by the presence of cell death induced by brain injury or disease [for review see (Peterson, 2002, Parent, 2003, Lie*, et al.*, 2004, Goldman, 2005)]. A critical issue of neurogenesis, both during development and in adulthood, is the appropriate integration of different cell types to form mature neural cells. This means that progenitor cells need to migrate from their places of birth to their final positions. Such a highly regulated process is mediated by a number of environmental cues like substrates, chemoattractive/ chemorepulsive factors, and detachment/stop signals. Although some of these factors have been identified, many remain to be discovered [for review see (Cayre*, et al.*, 2009)]. Progenitor cell migration is most extensive in the developing and immature brain. In the adult brain, neural cell migration still continues, although in a more limited capacity with the most extensive region of migration observed in the SVZ-OB pathway. It is not yet clear why new neurons are not born in the place they need to reside. While the maintenance of stem cell niches in the adult brain may provide a potential source of cells for brain repair and cell replacement, these regions may be costly for the organism and may also require specific features that restrict the structures where they can persist. As a result, in both normal and pathological conditions cells need to be able to migrate from these discrete niches to their final destination. During pathological processes, such as brain injury, the brain demonstrates spontaneous attempts at repair and regeneration. These processes result in a distinct profile of cell proliferation and migration not observed in the normal adult brain, which appear to be mediated by an independent set of environmental cues. This chapter will discuss what is known about the response of endogenous adult neural progenitor cells to brain injury including stroke, traumatic brain injury, epilepsy and excitotoxic injury, the mechanisms by which this response may occur, and how this knowledge may be translated to effective therapeutic strategies.

#### **2. The response of progenitor cells to the injured brain**

#### **2.1 Temporal lobe epilepsy**

64 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

2007). Studies have shown that olfactory granule and periglomerular cells are continuously added to the olfactory bulb to both increase total cell number over time in these layers as well as replace pre-existing cells (Lagace*, et al.*, 2007, Imayoshi*, et al.*, 2008). The function of persistent olfactory bulb neurogenesis is largely unknown, but increasing evidence supports a role for the new neurons in olfactory memory and odour discrimination (Gheusi*, et al.*,

In contrast to the extensive migration undertaken by neurons destined for the olfactory bulb, dentate gyrus granule neurons are born locally in the subgranular zone (SGZ), a germinal layer between the dentate gyrus and the hilus (Altman*, et al.*, 1965, Kaplan*, et al.*, 1977, Eriksson*, et al.*, 1998, Kornack*, et al.*, 1999, Gould*, et al.*, 2001). Within the SGZ, GFAP positive cells (Type B cells) divide to give rise to immature Type D cells, which then generate granule neurons (Palmer*, et al.*, 2000, Seri*, et al.*, 2001). Interestingly, Type D cells divide less frequently and are more differentiated than the transit amplifying Type C cells in the SVZ. SGZ-derived neural progenitor cells generate new neurons that make and receive functional synapses (Palmer*, et al.*, 2000, Song*, et al.*, 2002, Van Praag*, et al.*, 2002). Ongoing hippocampus neurogenesis is known to facilitate long-term potentiation and stimulate learning and memory (Van Praag*, et al.*, 1999, Wang*, et al.*, 2005, Imayoshi*, et al.*, 2008) with ablation of adult-born dentate granule cells impairing certain forms of hippocampal-

dependent learning (Dupret*, et al.*, 2008, Imayoshi*, et al.*, 2008, Clelland*, et al.*, 2009).

knowledge may be translated to effective therapeutic strategies.

Adult neurogenesis is not static, but its rate may fluctuate in response to environmental change. Evidence from *in vitro* and *in vivo* studies have demonstrated that neurogenesis can be regulated by a range of growth and neurotrophic factors, neurotransmitters and hormones [for review see (Parent, 2003, Lie*, et al.*, 2004)]. Neurogenesis has also been shown to be altered by the presence of cell death induced by brain injury or disease [for review see (Peterson, 2002, Parent, 2003, Lie*, et al.*, 2004, Goldman, 2005)]. A critical issue of neurogenesis, both during development and in adulthood, is the appropriate integration of different cell types to form mature neural cells. This means that progenitor cells need to migrate from their places of birth to their final positions. Such a highly regulated process is mediated by a number of environmental cues like substrates, chemoattractive/ chemorepulsive factors, and detachment/stop signals. Although some of these factors have been identified, many remain to be discovered [for review see (Cayre*, et al.*, 2009)]. Progenitor cell migration is most extensive in the developing and immature brain. In the adult brain, neural cell migration still continues, although in a more limited capacity with the most extensive region of migration observed in the SVZ-OB pathway. It is not yet clear why new neurons are not born in the place they need to reside. While the maintenance of stem cell niches in the adult brain may provide a potential source of cells for brain repair and cell replacement, these regions may be costly for the organism and may also require specific features that restrict the structures where they can persist. As a result, in both normal and pathological conditions cells need to be able to migrate from these discrete niches to their final destination. During pathological processes, such as brain injury, the brain demonstrates spontaneous attempts at repair and regeneration. These processes result in a distinct profile of cell proliferation and migration not observed in the normal adult brain, which appear to be mediated by an independent set of environmental cues. This chapter will discuss what is known about the response of endogenous adult neural progenitor cells to brain injury including stroke, traumatic brain injury, epilepsy and excitotoxic injury, the mechanisms by which this response may occur, and how this

2000, Petreanu*, et al.*, 2002, Rochefort*, et al.*, 2002).

Epilepsy, characterized by periodic and unpredictable occurrence of seizure activity, affects ~50 million people worldwide and temporal lobe epilepsy (TLE) is among the most frequent types of intractable epilepsy. Abnormal hippocampal neurogenesis has emerged as an important pathophysiology of TLE over the past decade [for review see (Kuruba*, et al.*, 2009)]. Initial studies on neurogenesis in animal models of TLE by Parent and colleagues (Parent*, et al.*, 1997, Parent*, et al.*, 1998) and Bengzon and colleagues (Bengzon*, et al.*, 1997) provided the first evidence for increased hippocampal neurogenesis following acute seizures. In these studies, an increase in the production of new cells was observed in the SGZ of the dentate gyrus following pilocarpine-induced status epilepticus (SE) (Parent*, et al.*, 1997, Gray*, et al.*, 1998) or kindling stimulations (Bengzon*, et al.*, 1997, Parent*, et al.*, 1998). However, by 3-4 weeks after seizure induction, neurogenesis returned to baseline levels. In normal animals, proliferating cells labeled with the mitotic marker bromodeoxyuridine (BrdU) are restricted to the SGZ of the hippocampus. In contrast, following seizure activity BrdU+ cells were found extensively in the dentate hilus and/or dentate molecular layer of the hippocampus, indicating aberrant migration of dividing cells in response to seizure-induced cell loss (Parent*, et al.*, 1997, Scharfman*, et al.*, 2000, Scharfman*, et al.*, 2002, Scharfman*, et al.*, 2003, Parent*, et al.*, 2006). Similarly, displaced granule cells have been observed in hippocampal tissues obtained from patients with TLE (Houser, 1990, Thom*, et al.*, 2002, Liu*, et al.*, 2008). This suggests that acute seizure-induced dentate gyrus neurogenesis promotes aberrant circuitry development, which likely contributes to the evolution of initial seizure-induced hippocampal injury into chronic epilepsy (Kuruba*, et al.*, 2009).

In addition to the neurogenic response observed in the hippocampus, progenitor cells in the SVZ also respond to seizure activity in the adult rodent brain. Within 1-2 weeks following pilocarpine-induced seizure activity, Parent and colleagues (Parent*, et al.*, 2002) observed an increase in BrdU labeling and Nissl staining in the RMS. These changes were associated with an increase in expression of the Type A neuroblast marker Dcx 2 – 3 weeks following prolonged seizures. At these same time points the RMS expanded and contained more proliferating cells and immature neurons. BrdU labeling and retroviral tracing showed that prolonged seizures also increased neuroblast migration to the olfactory bulb. Importantly, a large number of labeled cells were found adjacent to the RMS instead of within its realms (most prominent at 14 days following seizure induction), indicating that seizure activity induces aberrant migration of SVZ-derived progenitor cells into surrounding regions of the brain (Parent*, et al.*, 2002).

Increased neurogenesis observed following acute seizure activity returns to baseline by about 2 months after the initial seizure episode in rats. The extent of neurogenesis has then been shown to decline significantly in the chronic phase of epilepsy when significant numbers of spontaneous seizures manifest [for review see (Hattiangady*, et al.*, 2008)]. A 64- 81% decrease in neurogenesis was reported at 5 months post-SE with an inverse relationship evident between the frequency of spontaneous seizures and the extent of neurogenesis (Hattiangady*, et al.*, 2004). The severe reduction in hippocampal neurogenesis observed in chronic TLE is not however associated with either decreased production of new cells or reduced survival of newly born cells in the dentate gyrus. Rather, it is due to a decline in the neuronal fate-choice decision of newly generated cells with the majority of newly born

Compensatory Neurogenesis in the Injured Adult Brain 67

limited to no neuronal differentiation observed (Chirumamilla*, et al.*, 2002, Goings*, et al.*, 2004). Finally, an increase in proliferative markers and the number of proliferative neural progenitor cells was recently observed to be increased in the perilesion cortex of the human brain following TBI (Zheng*, et al.*, 2011), indicating that TBI may also induce compensatory neurogenesis in the human brain. Thus, it appears that TBI results in compensatory neurogenesis in response to both hippocampal and cortical damage, with progenitor cell migration focused on recruitment to areas of neural injury. Further studies however are required to determine the fate and survival of adult-born cells in areas of TBI-induced injury.

Ischemic stroke involves an interruption in blood supply to the brain and results in the death of neural cells and corresponding loss of brain function. Focal ischemia is generated through the blockage of blood vessels which supply specific regions of the brain, and is commonly modeled by the occurrence of transient middle cerebral artery occlusion (tMCAo) which results in damage to the cortex and striatum. Studies of experimental stroke in rodents over the past decade indicate that focal ischemia potently stimulates SVZ cell proliferation and neurogenesis (Jin*, et al.*, 2001, Zhang*, et al.*, 2001, Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002, Ohab*, et al.*, 2006). Although initial studies suggested that the increase in SVZ neurogenesis after stroke is transient (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002), more recent work indicates that it persists for at least 4 months after ischemia (Thored*, et al.*, 2006). SVZ progenitor cells have also been observed to migrate in chains into the ischemic striatum and cortex (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002, Jin*, et al.*, 2003, Ohab*, et al.*, 2006, Yamashita*, et al.*, 2006, Zhang*, et al.*, 2009). As with TBI, this appears to be at the expense of olfactory bulb migration. Recent evidence suggests that a similar long-distance migration of neuroblasts may occur in peri-infarct tissue in human stroke (Jin*, et al.*, 2006). Although a large number of neuroblasts reach regions of striatal damage after stroke, few of them differentiate into mature neurons. Most adult-born neurons appear to die (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002), perhaps from a failure to integrate or due to inflammatory milieu. However, the persistence of SVZ neuroblast migration to the injured striatum for up to a year after ischemia (Thored*, et al.*, 2006) suggests that the SVZ may serve as a constant reservoir of new neurons that offers an extended window for therapeutic manipulation. In most stroke models, many of the surviving cells differentiate into neurons, but the precise nature of the neurons that persist long term in the striatum is controversial. The generation of neurons expressing markers of the striatal medium spiny neurons including DARPP-32 and calbindin after tMCAo in adult rats has been reported by two groups (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002). More recently however, Liu and colleagues (Liu*, et al.*, 2009) used retroviral reporters to label SVZ progenitor cells prior to inducing stroke in adult rats and found that adult-born neurons exclusively differentiated into calretinin-expressing interneurons. This may be due to differences in the location and extent of focal ischemic injury, selectivity of ischemic-induced neural cell loss, or alternatively the response of the specific population of neural progenitor cells investigated (Lledo*, et al.*, 2008). Further research is also required to determine the potential for adult-born neurons to integrate into

the surrounding parenchyma following focal ischemic injury.

Striatal injection of the neurotoxin quinolinic acid (QA) generates the selective loss of the GABAergic medium spiny neurons in the striatum. This model has been used to investigate

**2.4 Excitotoxic brain injury** 

**2.3 Focal ischemia** 

cells differentiating to a glial rather than a neuronal lineage in response to chronic TLE (Hattiangady*, et al.*, 2010). Thus, diminished hippocampal neurogenesis might contribute to the persistence of spontaneous seizures, learning and memory deficits, and depression prevalent in chronic TLE.

#### **2.2 Traumatic brain injury**

Traumatic brain injury (TBI) is characterized by both neuronal and white matter loss, with resultant brain atrophy and functional neurological impairment. Injury may be in the form of focal damage, or it may be diffuse with widespread delayed neuronal loss. In addition to local neuronal loss resulting from the mechanical primary insult, TBI also induces a cascade of delayed secondary events that contribute to neuronal death, including ischemia, Wallerian degeneration secondary to diffuse axonal injury, excitotoxicity, dysregulation of calcium homeostasis, mitochondrial dysfunction and free radical-mediated damage. Among the diffuse injury sites, the hippocampus is known to be especially vulnerable in humans and shows the earliest evidence of TBI-induced degeneration in experimental models. The most frequently used experimental models of TBI include the controlled cortical impact (CCI) and lateral fluid percussion (FPI) models (Wang*, et al.*, 2010). The lateral FPI model can reproduce multiple types of human TBI, including focal contusion, intraparenchymal and subarachnoid hemorrhage, tissue tears and axonal damage, and has been widely adopted as a combined model of focal and diffuse brain injury. The CCI model generally has been found to produce a more focused injury compared to lateral FPI; the severity of injury is also significantly greater in the gray matter relative to the underlying white matter. In both injury models there is an acute neurogenic response with an increase in hippocampal progenitor cell proliferation observed from 24hr to 1-2 weeks following TBI (Dash*, et al.*, 2001, Chirumamilla*, et al.*, 2002, Emery*, et al.*, 2005). Newly generated neurons in the dentate gyrus integrate into the existing hippocampal circuitry following TBI, potentially resulting in cognitive recovery (Sun*, et al.*, 2005). Transgenic approaches have demonstrated that following TBI, the nestin-expressing progenitor cells are first activated by injury, whereas the later Dcx-expressing committed neuroblasts appear to be eliminated (Miles*, et al.*, 2008, Yu*, et al.*, 2008). Later, the Dcx-expressing cells within the dentate gyrus reemerge and are likely contributors to stable neurogenesis (Yu*, et al.*, 2008).

Adult SVZ neurogenesis has also been investigated in the CCI model of TBI (Goings*, et al.*, 2002, Ramaswamy*, et al.*, 2005). In these studies, SVZ progenitor cell proliferation was observed either to be reduced (Goings*, et al.*, 2002), or to exhibit a delayed increase in proliferation (Ramaswamy*, et al.*, 2005) following TBI. In the lateral FPI model, an increase in SVZ progenitor cell incorporation of BrdU was observed between 2 – 8 days post injury (Chirumamilla*, et al.*, 2002). Interestingly, in the CCI model progenitor cell migration within the SVZ - OB pathway, as demonstrated by PSA-NCAM expression, was not enhanced until 25-35 days post TBI (Goings*, et al.*, 2002). Retroviral labeling of SVZ progenitor cells and examination of the location of labeled cells at 4 days and 3 weeks post injury in adult mice determined that very few cells migrated into the cerebral cortex in the normal brain, whereas a large number of labeled cells migrated into the lesioned area following cortical impact (Goings*, et al.*, 2004). Migration of progenitor cells into the lesioned cortex appeared to be at the expense of migration to the olfactory bulb; in control animals approximately half of the labeled SVZ cells were found in the olfactory bulb, whereas only a quarter of labeled cells migrated there following cortical injury (Goings*, et al.*, 2004). However, the majority of adult-born cells located in the lesioned area appear to be newly generated glial cells, with limited to no neuronal differentiation observed (Chirumamilla*, et al.*, 2002, Goings*, et al.*, 2004). Finally, an increase in proliferative markers and the number of proliferative neural progenitor cells was recently observed to be increased in the perilesion cortex of the human brain following TBI (Zheng*, et al.*, 2011), indicating that TBI may also induce compensatory neurogenesis in the human brain. Thus, it appears that TBI results in compensatory neurogenesis in response to both hippocampal and cortical damage, with progenitor cell migration focused on recruitment to areas of neural injury. Further studies however are required to determine the fate and survival of adult-born cells in areas of TBI-induced injury.

#### **2.3 Focal ischemia**

66 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

cells differentiating to a glial rather than a neuronal lineage in response to chronic TLE (Hattiangady*, et al.*, 2010). Thus, diminished hippocampal neurogenesis might contribute to the persistence of spontaneous seizures, learning and memory deficits, and depression

Traumatic brain injury (TBI) is characterized by both neuronal and white matter loss, with resultant brain atrophy and functional neurological impairment. Injury may be in the form of focal damage, or it may be diffuse with widespread delayed neuronal loss. In addition to local neuronal loss resulting from the mechanical primary insult, TBI also induces a cascade of delayed secondary events that contribute to neuronal death, including ischemia, Wallerian degeneration secondary to diffuse axonal injury, excitotoxicity, dysregulation of calcium homeostasis, mitochondrial dysfunction and free radical-mediated damage. Among the diffuse injury sites, the hippocampus is known to be especially vulnerable in humans and shows the earliest evidence of TBI-induced degeneration in experimental models. The most frequently used experimental models of TBI include the controlled cortical impact (CCI) and lateral fluid percussion (FPI) models (Wang*, et al.*, 2010). The lateral FPI model can reproduce multiple types of human TBI, including focal contusion, intraparenchymal and subarachnoid hemorrhage, tissue tears and axonal damage, and has been widely adopted as a combined model of focal and diffuse brain injury. The CCI model generally has been found to produce a more focused injury compared to lateral FPI; the severity of injury is also significantly greater in the gray matter relative to the underlying white matter. In both injury models there is an acute neurogenic response with an increase in hippocampal progenitor cell proliferation observed from 24hr to 1-2 weeks following TBI (Dash*, et al.*, 2001, Chirumamilla*, et al.*, 2002, Emery*, et al.*, 2005). Newly generated neurons in the dentate gyrus integrate into the existing hippocampal circuitry following TBI, potentially resulting in cognitive recovery (Sun*, et al.*, 2005). Transgenic approaches have demonstrated that following TBI, the nestin-expressing progenitor cells are first activated by injury, whereas the later Dcx-expressing committed neuroblasts appear to be eliminated (Miles*, et al.*, 2008, Yu*, et al.*, 2008). Later, the Dcx-expressing cells within the dentate gyrus

reemerge and are likely contributors to stable neurogenesis (Yu*, et al.*, 2008).

Adult SVZ neurogenesis has also been investigated in the CCI model of TBI (Goings*, et al.*, 2002, Ramaswamy*, et al.*, 2005). In these studies, SVZ progenitor cell proliferation was observed either to be reduced (Goings*, et al.*, 2002), or to exhibit a delayed increase in proliferation (Ramaswamy*, et al.*, 2005) following TBI. In the lateral FPI model, an increase in SVZ progenitor cell incorporation of BrdU was observed between 2 – 8 days post injury (Chirumamilla*, et al.*, 2002). Interestingly, in the CCI model progenitor cell migration within the SVZ - OB pathway, as demonstrated by PSA-NCAM expression, was not enhanced until 25-35 days post TBI (Goings*, et al.*, 2002). Retroviral labeling of SVZ progenitor cells and examination of the location of labeled cells at 4 days and 3 weeks post injury in adult mice determined that very few cells migrated into the cerebral cortex in the normal brain, whereas a large number of labeled cells migrated into the lesioned area following cortical impact (Goings*, et al.*, 2004). Migration of progenitor cells into the lesioned cortex appeared to be at the expense of migration to the olfactory bulb; in control animals approximately half of the labeled SVZ cells were found in the olfactory bulb, whereas only a quarter of labeled cells migrated there following cortical injury (Goings*, et al.*, 2004). However, the majority of adult-born cells located in the lesioned area appear to be newly generated glial cells, with

prevalent in chronic TLE.

**2.2 Traumatic brain injury** 

Ischemic stroke involves an interruption in blood supply to the brain and results in the death of neural cells and corresponding loss of brain function. Focal ischemia is generated through the blockage of blood vessels which supply specific regions of the brain, and is commonly modeled by the occurrence of transient middle cerebral artery occlusion (tMCAo) which results in damage to the cortex and striatum. Studies of experimental stroke in rodents over the past decade indicate that focal ischemia potently stimulates SVZ cell proliferation and neurogenesis (Jin*, et al.*, 2001, Zhang*, et al.*, 2001, Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002, Ohab*, et al.*, 2006). Although initial studies suggested that the increase in SVZ neurogenesis after stroke is transient (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002), more recent work indicates that it persists for at least 4 months after ischemia (Thored*, et al.*, 2006). SVZ progenitor cells have also been observed to migrate in chains into the ischemic striatum and cortex (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002, Jin*, et al.*, 2003, Ohab*, et al.*, 2006, Yamashita*, et al.*, 2006, Zhang*, et al.*, 2009). As with TBI, this appears to be at the expense of olfactory bulb migration. Recent evidence suggests that a similar long-distance migration of neuroblasts may occur in peri-infarct tissue in human stroke (Jin*, et al.*, 2006). Although a large number of neuroblasts reach regions of striatal damage after stroke, few of them differentiate into mature neurons. Most adult-born neurons appear to die (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002), perhaps from a failure to integrate or due to inflammatory milieu. However, the persistence of SVZ neuroblast migration to the injured striatum for up to a year after ischemia (Thored*, et al.*, 2006) suggests that the SVZ may serve as a constant reservoir of new neurons that offers an extended window for therapeutic manipulation. In most stroke models, many of the surviving cells differentiate into neurons, but the precise nature of the neurons that persist long term in the striatum is controversial. The generation of neurons expressing markers of the striatal medium spiny neurons including DARPP-32 and calbindin after tMCAo in adult rats has been reported by two groups (Arvidsson*, et al.*, 2002, Parent*, et al.*, 2002). More recently however, Liu and colleagues (Liu*, et al.*, 2009) used retroviral reporters to label SVZ progenitor cells prior to inducing stroke in adult rats and found that adult-born neurons exclusively differentiated into calretinin-expressing interneurons. This may be due to differences in the location and extent of focal ischemic injury, selectivity of ischemic-induced neural cell loss, or alternatively the response of the specific population of neural progenitor cells investigated (Lledo*, et al.*, 2008). Further research is also required to determine the potential for adult-born neurons to integrate into the surrounding parenchyma following focal ischemic injury.

#### **2.4 Excitotoxic brain injury**

Striatal injection of the neurotoxin quinolinic acid (QA) generates the selective loss of the GABAergic medium spiny neurons in the striatum. This model has been used to investigate

Compensatory Neurogenesis in the Injured Adult Brain 69

and chemokines from reactive microglia and blood vessels are also involved in directing the migration of neural progenitor cells to areas of neuronal loss and injury, as well as controlling adult-born neuron survival (Gonzalez-Perez*, et al.*, 2010). Angiogenesis and the expression of pro-angiogenic factors appear to play an important role both in progenitor cell proliferation and survival as well as migration (Xiong*, et al.*, 2010, Yang*, et al.*, 2011). In addition, alteration in neurochemical signaling, such as GABAergic and glutamtergic transmission, and neuronal activity have been shown to modulate neurogenesis following brain injury (Deisseroth*, et al.*, 2004, Ge*, et al.*, 2007). Thus, it appears multiple mechanisms underlie the regulation of compensatory neurogenesis following brain injury; these will be

Multiple studies have demonstrated that several factors known to promote neural progenitor cell proliferation and neuron survival such as nerve growth factor (NGF), brainderived neurotrophic factor (BDNF), fibroblast growth factor-2 (FGF2), vascular endothelial growth factor (VEGF) and sonic hedgehog (Shh) are all up-regulated in the hippocampus after acute seizures (Lowenstein*, et al.*, 1993, Gall*, et al.*, 1994, Riva*, et al.*, 1994, Gómez-Pinilla*, et al.*, 1995, Shetty*, et al.*, 2003, Croll*, et al.*, 2004, Shetty*, et al.*, 2004, Banerjee*, et al.*, 2005). Increased levels of GABA in the dentate gyrus during the early post-seizure period may also positively regulate hippocampal neurogenesis, as studies show that GABA has crucial roles in regulating various steps of adult neurogenesis, including progenitor cell proliferation, migration and differentiation of neuroblasts, and synaptic integration of adult-born neurons (Ge*, et al.*, 2007). Further, increased levels of neuropeptide Y (NPY) found typically after acute seizures may enhance the proliferation of neural progenitor cells in the dentate gyrus, as studies have shown that neural progenitor cells increase neurogenesis in the presence of NPY (Howell*, et al.*, 2003, Howell*, et al.*, 2005, Howell*, et al.*,

**3.1 Potential mechanisms of increased hippocampal neurogenesis after** 

**3.2 Abnormal migration of adult-born cells after acute seizure activity** 

As discussed in Section 2.1, aberrant migration of progenitor cells is observed in response to seizure-induced cell loss. The precise reason for aberrant migration of adult-born granule cells is still being examined. However, it has been shown that acute seizures do not significantly influence the proliferation of nestin-expressing neural stem cells but rather stimulate the division of Dcx-expressing transient amplifying cells and immature neurons (Jessberger*, et al.*, 2005). Based on this, it has been proposed that delayed proliferation during the process of neurogenesis interferes with migration, leading to a significant dispersion of Dcx-positive cells away from the granule cell layer into the dentate hilus and the molecular layer. In addition, recent evidence suggests that a loss of the migration guidance cue Reelin due to seizure activity may lead to aberrant chain migration of newly born dentate granule cells (Gong*, et al.*, 2007). Interneuron subsets typically lost in human and experimental TLE express Reelin, and dentate granule progenitor cells express the downstream Reelin signaling molecule Disabled 1 (Dab1). Prolonged seizure activity has been shown to decrease Reelin expression in the adult rat dentate gyrus and increase Dab1 expression in hilar ectopic neuroblasts. Further, exogenous Reelin increased detachment of chain-migrating neuroblasts in dentate gyrus explants, and blockade of Reelin signaling

summarized in the following section.

**seizure activity** 

2007, Rodrigo*, et al.*, 2010).

the effect of excitotoxic striatal injury on SVZ-derived neurogenesis. QA lesioning results in a significant increase in progenitor cell proliferation at days 1 – 14 following injury (Tattersfield*, et al.*, 2004, Collin*, et al.*, 2005). In addition, both expansion of the RMS and aberrant migration of SVZ-derived Dcx-expressing progenitor cells into the lesioned striatum has been demonstrated following QA-induced striatum cell loss (Tattersfield*, et al.*, 2004, Collin*, et al.*, 2005, Gordon*, et al.*, 2007). In order to elucidate the temporal profile of progenitor cell migration in response to QA-induced striatal cell loss, Gordon and colleagues (Gordon*, et al.*, 2007) used retroviral tracing to label SVZ-derived progenitor cells and track their migratory profile. This study demonstrated that SVZ-derived progenitor cell migration was significantly enhanced in the RMS of QA lesioned animals immediately following, and up to 30 days following QA-induced striatal cell loss. This was in contrast to the migratory response observed in both TBI and ischemic stroke, and demonstrated that recruitment of SVZ-derived progenitor cells into the QA lesioned striatum was not at the expense of olfactory bulb migration. In addition, Gordon and colleagues (Gordon*, et al.*, 2007) identified that aberrant migration of SVZ-derived progenitor cells into the QA lesioned striatum is transient, with progenitor cell recruitment predominantly observed by cells labeled either 2 days prior or up to 3 days following QA lesioning. Interestingly, a change in the morphology of the recruited SVZ-derived progenitor cells was observed over time. SVZ-derived progenitor cells labeled either 2 days prior, or on the day of QA lesioning predominantly exhibited a bipolar morphology and expressed Dcx. In contrast, the majority of progenitor cells labeled from the day of QA lesioning up to 3 days following lesioning displayed a multipolar morphology and did not express Dcx (Gordon*, et al.*, 2007). This indicates that striatal cell loss induces an expansion of the SVZ progenitor cell population, in which a sub-population of SVZ-derived progenitor cells are responsive to recruitment into the lesioned area. In addition, the novel observation of a temporal change in the morphological profile of progenitor cells recruited into the QA lesioned striatum is of great interest, and warrants further investigation. This alteration in progenitor cell morphology may be in response to changes in environmental cues present in the lesioned striatum. Following recruitment into the QA-lesioned striatum, about 80% of adult-born neurons survive up to 6 weeks, when they express the mature neuronal marker NeuN and phenotypic markers of striatal medium spiny neurons (DARPP-32) and interneurons (parvalbumin or neuropeptide Y) (Tattersfield*, et al.*, 2004, Collin*, et al.*, 2005). However, similar to the observations made in models of ischemic stroke, relatively few adult-born neurons survive long term. The low level of adult-born cell survival in models of both focal ischemia and excitotoxic striatal cell loss indicates that further investigation is required in both injury models to determine the effect of the environment of cell fate, integration and long-term survival.

#### **3. Factors modulating compensatory neurogenesis**

The precise mechanisms underlying injury-induced compensatory neurogenesis in the adult brain are unclear. However, several potential mechanisms have been proposed. First it is believed that the release of mitogenic factors from dying neurons and reactive glia probably increases the proliferation of neural progenitor cells and the survival of newly generated neurons. Expression of mitogenic factors can also alter transcriptional signaling pathways in neural progenitor cells, redirecting neurogenic processes from a normal physiological role (Bath*, et al.*, 2010, Hodge*, et al.*, 2011, Jones*, et al.*, 2011). Increased expression of cytokines

the effect of excitotoxic striatal injury on SVZ-derived neurogenesis. QA lesioning results in a significant increase in progenitor cell proliferation at days 1 – 14 following injury (Tattersfield*, et al.*, 2004, Collin*, et al.*, 2005). In addition, both expansion of the RMS and aberrant migration of SVZ-derived Dcx-expressing progenitor cells into the lesioned striatum has been demonstrated following QA-induced striatum cell loss (Tattersfield*, et al.*, 2004, Collin*, et al.*, 2005, Gordon*, et al.*, 2007). In order to elucidate the temporal profile of progenitor cell migration in response to QA-induced striatal cell loss, Gordon and colleagues (Gordon*, et al.*, 2007) used retroviral tracing to label SVZ-derived progenitor cells and track their migratory profile. This study demonstrated that SVZ-derived progenitor cell migration was significantly enhanced in the RMS of QA lesioned animals immediately following, and up to 30 days following QA-induced striatal cell loss. This was in contrast to the migratory response observed in both TBI and ischemic stroke, and demonstrated that recruitment of SVZ-derived progenitor cells into the QA lesioned striatum was not at the expense of olfactory bulb migration. In addition, Gordon and colleagues (Gordon*, et al.*, 2007) identified that aberrant migration of SVZ-derived progenitor cells into the QA lesioned striatum is transient, with progenitor cell recruitment predominantly observed by cells labeled either 2 days prior or up to 3 days following QA lesioning. Interestingly, a change in the morphology of the recruited SVZ-derived progenitor cells was observed over time. SVZ-derived progenitor cells labeled either 2 days prior, or on the day of QA lesioning predominantly exhibited a bipolar morphology and expressed Dcx. In contrast, the majority of progenitor cells labeled from the day of QA lesioning up to 3 days following lesioning displayed a multipolar morphology and did not express Dcx (Gordon*, et al.*, 2007). This indicates that striatal cell loss induces an expansion of the SVZ progenitor cell population, in which a sub-population of SVZ-derived progenitor cells are responsive to recruitment into the lesioned area. In addition, the novel observation of a temporal change in the morphological profile of progenitor cells recruited into the QA lesioned striatum is of great interest, and warrants further investigation. This alteration in progenitor cell morphology may be in response to changes in environmental cues present in the lesioned striatum. Following recruitment into the QA-lesioned striatum, about 80% of adult-born neurons survive up to 6 weeks, when they express the mature neuronal marker NeuN and phenotypic markers of striatal medium spiny neurons (DARPP-32) and interneurons (parvalbumin or neuropeptide Y) (Tattersfield*, et al.*, 2004, Collin*, et al.*, 2005). However, similar to the observations made in models of ischemic stroke, relatively few adult-born neurons survive long term. The low level of adult-born cell survival in models of both focal ischemia and excitotoxic striatal cell loss indicates that further investigation is required in both injury models to determine the effect of the environment of cell fate, integration and

long-term survival.

**3. Factors modulating compensatory neurogenesis** 

The precise mechanisms underlying injury-induced compensatory neurogenesis in the adult brain are unclear. However, several potential mechanisms have been proposed. First it is believed that the release of mitogenic factors from dying neurons and reactive glia probably increases the proliferation of neural progenitor cells and the survival of newly generated neurons. Expression of mitogenic factors can also alter transcriptional signaling pathways in neural progenitor cells, redirecting neurogenic processes from a normal physiological role (Bath*, et al.*, 2010, Hodge*, et al.*, 2011, Jones*, et al.*, 2011). Increased expression of cytokines and chemokines from reactive microglia and blood vessels are also involved in directing the migration of neural progenitor cells to areas of neuronal loss and injury, as well as controlling adult-born neuron survival (Gonzalez-Perez*, et al.*, 2010). Angiogenesis and the expression of pro-angiogenic factors appear to play an important role both in progenitor cell proliferation and survival as well as migration (Xiong*, et al.*, 2010, Yang*, et al.*, 2011). In addition, alteration in neurochemical signaling, such as GABAergic and glutamtergic transmission, and neuronal activity have been shown to modulate neurogenesis following brain injury (Deisseroth*, et al.*, 2004, Ge*, et al.*, 2007). Thus, it appears multiple mechanisms underlie the regulation of compensatory neurogenesis following brain injury; these will be summarized in the following section.

#### **3.1 Potential mechanisms of increased hippocampal neurogenesis after seizure activity**

Multiple studies have demonstrated that several factors known to promote neural progenitor cell proliferation and neuron survival such as nerve growth factor (NGF), brainderived neurotrophic factor (BDNF), fibroblast growth factor-2 (FGF2), vascular endothelial growth factor (VEGF) and sonic hedgehog (Shh) are all up-regulated in the hippocampus after acute seizures (Lowenstein*, et al.*, 1993, Gall*, et al.*, 1994, Riva*, et al.*, 1994, Gómez-Pinilla*, et al.*, 1995, Shetty*, et al.*, 2003, Croll*, et al.*, 2004, Shetty*, et al.*, 2004, Banerjee*, et al.*, 2005). Increased levels of GABA in the dentate gyrus during the early post-seizure period may also positively regulate hippocampal neurogenesis, as studies show that GABA has crucial roles in regulating various steps of adult neurogenesis, including progenitor cell proliferation, migration and differentiation of neuroblasts, and synaptic integration of adult-born neurons (Ge*, et al.*, 2007). Further, increased levels of neuropeptide Y (NPY) found typically after acute seizures may enhance the proliferation of neural progenitor cells in the dentate gyrus, as studies have shown that neural progenitor cells increase neurogenesis in the presence of NPY (Howell*, et al.*, 2003, Howell*, et al.*, 2005, Howell*, et al.*, 2007, Rodrigo*, et al.*, 2010).

#### **3.2 Abnormal migration of adult-born cells after acute seizure activity**

As discussed in Section 2.1, aberrant migration of progenitor cells is observed in response to seizure-induced cell loss. The precise reason for aberrant migration of adult-born granule cells is still being examined. However, it has been shown that acute seizures do not significantly influence the proliferation of nestin-expressing neural stem cells but rather stimulate the division of Dcx-expressing transient amplifying cells and immature neurons (Jessberger*, et al.*, 2005). Based on this, it has been proposed that delayed proliferation during the process of neurogenesis interferes with migration, leading to a significant dispersion of Dcx-positive cells away from the granule cell layer into the dentate hilus and the molecular layer. In addition, recent evidence suggests that a loss of the migration guidance cue Reelin due to seizure activity may lead to aberrant chain migration of newly born dentate granule cells (Gong*, et al.*, 2007). Interneuron subsets typically lost in human and experimental TLE express Reelin, and dentate granule progenitor cells express the downstream Reelin signaling molecule Disabled 1 (Dab1). Prolonged seizure activity has been shown to decrease Reelin expression in the adult rat dentate gyrus and increase Dab1 expression in hilar ectopic neuroblasts. Further, exogenous Reelin increased detachment of chain-migrating neuroblasts in dentate gyrus explants, and blockade of Reelin signaling

Compensatory Neurogenesis in the Injured Adult Brain 71

increase in the number of neuroblasts was found, both in the ischemic striatum and SVZ. Co-administration of EGF and FGF2 into the lateral ventricle for 5 days in a rodent model of global cerebral ischemia has been shown to increase the proliferative rate and differentiation of newly generated hippocampal neurons (Nakatomi*, et al.*, 2002). The newborn neurons exhibited histological markers of young and maturing neurons, appropriate connectivity and synapse formation as well as electrophysiological characteristics of young neurons. Further, memory deficits were resolved in EGF and FGF2 treated rats within 90 days. Erythropoietin (EPO) also plays a role in regulating compensatory SVZ neurogenesis following ischemic injury. EPO stimulates the maturation, differentiation and survival of hematopoietic progenitor cells and promotes angiogenesis. While EPO and its receptor are only weakly expressed in normal adult brain, expression of EPO and its receptor is greatly increased in neurons, neural progenitor cells, glia and cerebrovascular endothelial cells in response to brain injury. Infusion of EPO into the adult lateral ventricles results in a decrease in the number of neural progenitor cells in the SVZ, an increase in neural precursor cells migrating to the olfactory bulb and an increase in the generation of new olfactory bulb neurons (Shingo*, et al.*, 2001). Further, delivery of EPO for 7 days following 7 days of EGF treatment has been shown to enhance SVZ neurogenesis and direct progenitor cell migration to the ischemic cortex, resulting in cortical regeneration and functional recovery (Kolb*, et al.*, 2006). It is thought that EPO might affect the number of daughter cells that stay in cell cycle and promote cell cycle exit and terminal differentiation with preference towards neuronal differentiation (Shingo*, et al.*, 2001). Systemic administration of BDNF has also been shown to induce neurogenesis and improve sensorimotor function in a rodent model of ischemic injury (Schabitz*, et al.*, 2007). In addition, a range of signaling pathways appear to be important in regulating compensatory neurogenesis following ischemic injury. These include notch, retinoid, bone morphogenic protein, tumor necrosis factor-alpha (TNF-α) and Shh pathways (Androutsellis-Theotokis*, et al.*, 2006, Chou*, et al.*, 2006, Iosif*, et al.*, 2008,

Plane*, et al.*, 2008, Zhang*, et al.*, 2008, Sims*, et al.*, 2009, Wang*, et al.*, 2009).

**following brain injury** 

**3.6 The role of chemoattractants in regulating neural progenitor cell migration** 

A fundamental issue concerning progenitor cell migration in the adult brain is to understand the extracellular cues and mechanisms that allow the persistence of normal migratory pathways, as well as the recruitment of progenitor cells into the areas of neural damage. Increasing evidence indicates the involvement of developmental signals that are maintained in restricted regions of the adult brain, including factors such as extracellular matrix molecules, Eph-Ephrin interactions, neuregulins, and a range of chemoattractant and chemorepulsive molecules [for review see (Cayre*, et al.*, 2009)]. In addition, several mechanisms and migratory tracks have been proposed for the guidance of migrating progenitor cells towards regions of neural damage. These include migration along: 1) myelinated fiber tracks; 2) radial processes; and 3) blood vessels [for review see (Cayre*, et al.*, 2009)]. Besides these mechanisms, inflammation-induced chemoattraction plays a major role in progenitor cell migration following neural cell loss. Upon insult or infection, the brain exhibits a profound innate response, characterised predominantly by robust activation of microglia (resident macrophages of the CNS). Activated microglia play a dual role, scavenging the damaged and dying neurons as well as initiating a prompt local inflammatory reaction. The inflammatory response involves production of proinflammatory cytokines and chemokines, as well as various reactive nitrogen and oxygen

increased chain migration (Gong*, et al.*, 2007). These observations suggest that Reelin modulates dentate gyrus progenitor cell migration and loss of Reelin expression in the epileptic adult hippocampus may contribute to ectopic chain migration and aberrant integration of newborn granule cells.

#### **3.3 Potential mechanisms underlying decreased neurogenesis in chronic TLE**

The precise mechanisms underlying decreased neurogenesis in chronic TLE are unknown, however several explanations have been proposed [for review see (Kuruba*, et al.*, 2009)]. While a role for chronic inflammation is an attractive hypothesis, this has been ruled out as only minimal density of activated microglia have been observed in the hippocampus during chronic epilepsy (Hattiangady*, et al.*, 2004). One potential mechanism may be a reduction in mitogenic factors such as FGF-2, BDNF and insulin-like growth factor 1 (IGF-1) in the epileptic hippocampus resulting in an unfavourable neurogenic environment (Hattiangady*, et al.*, 2004, Shetty*, et al.*, 2004). As neuronal differentiation rather than progenitor cell number and proliferation is predominantly affected in chronic TLE, the presence of an unfavourable hippocampal milieu due to reduction of mitogenic factors currently remains the most plausible mechanism (Altar*, et al.*, 2004, Chan*, et al.*, 2008).

#### **3.4 Potential mechanisms of increased neurogenesis after TBI**

Several studies have shown that neurotrophic factor expression is significantly altered after TBI. Some neurotrophic factors such as NGF and BDNF are up-regulated, while others such as neurotrophic factor-3 (NT-3) have been shown to be down-regulated (Yang*, et al.*, 1996, Hicks*, et al.*, 1997, Oyesiku*, et al.*, 1999, Truettner*, et al.*, 1999). Interestingly, BDNF levels after TBI have been reported to be increased to a greater extent in older rather than younger animals (Shah*, et al.*, 2006), despite the well known fact that older age is correlated with a worse outcome after TBI. Results from the CCI model also suggest that FGF-2 is upregulated, potentially stimulating post-traumatic neurogenesis (Yoshimura*, et al.*, 2003). In addition, up-regulation of VEGF has been observed following both CCI (Sköld*, et al.*, 2005, Lu*, et al.*, 2011) and lateral FPI (Lee*, et al.*, 2010), and may be involved in enhancing neurogenesis and promoting migration following TBI as observed in rodent models of focal ischemia.

#### **3.5 Potential mechanisms of increased neurogenesis after stroke**

Potential mediators of stroke-induced cell proliferation and neurogenesis are beginning to be identified (Yan*, et al.*, 2006, Zhang*, et al.*, 2008, Leker*, et al.*, 2009, Luo, 2011). Through infusion studies, a range of growth factors have been identified to play a role in regulating SVZ neurogenesis following focal ischemia. Factors such as GDNF, VEGF, EGF, transforming growth factor-α (TGF-α) and IGF-1 have all been shown to increase progenitor cell proliferation in the ipsilateral SVZ following ischemic damage (Jin*, et al.*, 2002, Sun*, et al.*, 2003, Schänzer*, et al.*, 2004, Kobayashi*, et al.*, 2006, Ninomiya*, et al.*, 2006, Yan*, et al.*, 2006, Leker*, et al.*, 2009, Guerra-Crespo*, et al.*, 2010). VEGF was shown not only to increase progenitor cell proliferation, but to also increase the survival of adult-born neurons and induce neurite outgrowth in newborn cells (Wang*, et al.*, 2009, Zheng*, et al.*, 2010). Another study (Ninomiya*, et al.*, 2006) demonstrated that EGF infusion into the ischemic brain caused the number of Type C transient amplifying cells to increase and the number of neuroblasts to decrease. However, 6 weeks after the discontinuation of EGF infusion, a significant

increased chain migration (Gong*, et al.*, 2007). These observations suggest that Reelin modulates dentate gyrus progenitor cell migration and loss of Reelin expression in the epileptic adult hippocampus may contribute to ectopic chain migration and aberrant

The precise mechanisms underlying decreased neurogenesis in chronic TLE are unknown, however several explanations have been proposed [for review see (Kuruba*, et al.*, 2009)]. While a role for chronic inflammation is an attractive hypothesis, this has been ruled out as only minimal density of activated microglia have been observed in the hippocampus during chronic epilepsy (Hattiangady*, et al.*, 2004). One potential mechanism may be a reduction in mitogenic factors such as FGF-2, BDNF and insulin-like growth factor 1 (IGF-1) in the epileptic hippocampus resulting in an unfavourable neurogenic environment (Hattiangady*, et al.*, 2004, Shetty*, et al.*, 2004). As neuronal differentiation rather than progenitor cell number and proliferation is predominantly affected in chronic TLE, the presence of an unfavourable hippocampal milieu due to reduction of mitogenic factors currently remains

Several studies have shown that neurotrophic factor expression is significantly altered after TBI. Some neurotrophic factors such as NGF and BDNF are up-regulated, while others such as neurotrophic factor-3 (NT-3) have been shown to be down-regulated (Yang*, et al.*, 1996, Hicks*, et al.*, 1997, Oyesiku*, et al.*, 1999, Truettner*, et al.*, 1999). Interestingly, BDNF levels after TBI have been reported to be increased to a greater extent in older rather than younger animals (Shah*, et al.*, 2006), despite the well known fact that older age is correlated with a worse outcome after TBI. Results from the CCI model also suggest that FGF-2 is upregulated, potentially stimulating post-traumatic neurogenesis (Yoshimura*, et al.*, 2003). In addition, up-regulation of VEGF has been observed following both CCI (Sköld*, et al.*, 2005, Lu*, et al.*, 2011) and lateral FPI (Lee*, et al.*, 2010), and may be involved in enhancing neurogenesis and promoting migration following TBI as observed in rodent models of focal

Potential mediators of stroke-induced cell proliferation and neurogenesis are beginning to be identified (Yan*, et al.*, 2006, Zhang*, et al.*, 2008, Leker*, et al.*, 2009, Luo, 2011). Through infusion studies, a range of growth factors have been identified to play a role in regulating SVZ neurogenesis following focal ischemia. Factors such as GDNF, VEGF, EGF, transforming growth factor-α (TGF-α) and IGF-1 have all been shown to increase progenitor cell proliferation in the ipsilateral SVZ following ischemic damage (Jin*, et al.*, 2002, Sun*, et al.*, 2003, Schänzer*, et al.*, 2004, Kobayashi*, et al.*, 2006, Ninomiya*, et al.*, 2006, Yan*, et al.*, 2006, Leker*, et al.*, 2009, Guerra-Crespo*, et al.*, 2010). VEGF was shown not only to increase progenitor cell proliferation, but to also increase the survival of adult-born neurons and induce neurite outgrowth in newborn cells (Wang*, et al.*, 2009, Zheng*, et al.*, 2010). Another study (Ninomiya*, et al.*, 2006) demonstrated that EGF infusion into the ischemic brain caused the number of Type C transient amplifying cells to increase and the number of neuroblasts to decrease. However, 6 weeks after the discontinuation of EGF infusion, a significant

**3.3 Potential mechanisms underlying decreased neurogenesis in chronic TLE** 

the most plausible mechanism (Altar*, et al.*, 2004, Chan*, et al.*, 2008).

**3.4 Potential mechanisms of increased neurogenesis after TBI** 

**3.5 Potential mechanisms of increased neurogenesis after stroke** 

integration of newborn granule cells.

ischemia.

increase in the number of neuroblasts was found, both in the ischemic striatum and SVZ. Co-administration of EGF and FGF2 into the lateral ventricle for 5 days in a rodent model of global cerebral ischemia has been shown to increase the proliferative rate and differentiation of newly generated hippocampal neurons (Nakatomi*, et al.*, 2002). The newborn neurons exhibited histological markers of young and maturing neurons, appropriate connectivity and synapse formation as well as electrophysiological characteristics of young neurons. Further, memory deficits were resolved in EGF and FGF2 treated rats within 90 days. Erythropoietin (EPO) also plays a role in regulating compensatory SVZ neurogenesis following ischemic injury. EPO stimulates the maturation, differentiation and survival of hematopoietic progenitor cells and promotes angiogenesis. While EPO and its receptor are only weakly expressed in normal adult brain, expression of EPO and its receptor is greatly increased in neurons, neural progenitor cells, glia and cerebrovascular endothelial cells in response to brain injury. Infusion of EPO into the adult lateral ventricles results in a decrease in the number of neural progenitor cells in the SVZ, an increase in neural precursor cells migrating to the olfactory bulb and an increase in the generation of new olfactory bulb neurons (Shingo*, et al.*, 2001). Further, delivery of EPO for 7 days following 7 days of EGF treatment has been shown to enhance SVZ neurogenesis and direct progenitor cell migration to the ischemic cortex, resulting in cortical regeneration and functional recovery (Kolb*, et al.*, 2006). It is thought that EPO might affect the number of daughter cells that stay in cell cycle and promote cell cycle exit and terminal differentiation with preference towards neuronal differentiation (Shingo*, et al.*, 2001). Systemic administration of BDNF has also been shown to induce neurogenesis and improve sensorimotor function in a rodent model of ischemic injury (Schabitz*, et al.*, 2007). In addition, a range of signaling pathways appear to be important in regulating compensatory neurogenesis following ischemic injury. These include notch, retinoid, bone morphogenic protein, tumor necrosis factor-alpha (TNF-α) and Shh pathways (Androutsellis-Theotokis*, et al.*, 2006, Chou*, et al.*, 2006, Iosif*, et al.*, 2008, Plane*, et al.*, 2008, Zhang*, et al.*, 2008, Sims*, et al.*, 2009, Wang*, et al.*, 2009).

#### **3.6 The role of chemoattractants in regulating neural progenitor cell migration following brain injury**

A fundamental issue concerning progenitor cell migration in the adult brain is to understand the extracellular cues and mechanisms that allow the persistence of normal migratory pathways, as well as the recruitment of progenitor cells into the areas of neural damage. Increasing evidence indicates the involvement of developmental signals that are maintained in restricted regions of the adult brain, including factors such as extracellular matrix molecules, Eph-Ephrin interactions, neuregulins, and a range of chemoattractant and chemorepulsive molecules [for review see (Cayre*, et al.*, 2009)]. In addition, several mechanisms and migratory tracks have been proposed for the guidance of migrating progenitor cells towards regions of neural damage. These include migration along: 1) myelinated fiber tracks; 2) radial processes; and 3) blood vessels [for review see (Cayre*, et al.*, 2009)]. Besides these mechanisms, inflammation-induced chemoattraction plays a major role in progenitor cell migration following neural cell loss. Upon insult or infection, the brain exhibits a profound innate response, characterised predominantly by robust activation of microglia (resident macrophages of the CNS). Activated microglia play a dual role, scavenging the damaged and dying neurons as well as initiating a prompt local inflammatory reaction. The inflammatory response involves production of proinflammatory cytokines and chemokines, as well as various reactive nitrogen and oxygen

Compensatory Neurogenesis in the Injured Adult Brain 73

mechanisms by which to increase hippocampal neurogenesis in chronic epilepsy; administration of neurotrophic factors, physical exercise, exposure to an enriched environment and antidepressant therapy [for review see (Kuruba*, et al.*, 2009)]. Administration of neurotrophic factors is relevant as many factors that promote neurogenesis (e.g: BDNF, FGF-2, IGF-1) are reduced in chronic epilepsy (Hattiangady*, et al.*, 2004, Shetty*, et al.*, 2004). Supporting this, a range of studies have demonstrated that administration of neurotrophic factors to both the normal and injured adult rodent brain can enhance hippocampal neurogenesis (Lichtenwalner*, et al.*, 2001, Yoshimura*, et al.*, 2001, Jin*, et al.*, 2003, Scharfman*, et al.*, 2005, Rai*, et al.*, 2007, Paradiso*, et al.*, 2009, Paradiso*, et al.*, 2011). Performing physical exercise and environmental enrichment have also been shown to enhance hippocampal neurogenesis, potentially through increased expression of a range of mitogenic factors such as BDNF, FGF2, NGF, IGF-1 and VEGF as well as phosphorylation of cAMP-response binding protein (CREB) (Nithianantharajah*, et al.*, 2006, Van Praag, 2008, Llorens-Martín*, et al.*, 2009, 2010, Lafenetre*, et al.*, 2011) and may provide an appealing noninvasive therapeutic approach for the treatment of chronic TLE (Dhanushkodi*, et al.*, 2008, Arida*, et al.*, 2009). Antidepressant therapy in chronic TLE is another interesting approach for increasing neurogenesis and reducing cognitive impairments, as antidepressant therapy enhances hippocampal neurogenesis probably via increases in levels of serotonin, noradrenaline, BDNF, CREB and a range of other mitogenic factors (Sahay*, et al.*, 2007, Thomas*, et al.*, 2008, Lanni*, et al.*, 2009). In particular, a recent study demonstrated that repeated administration of the antidepressant agent citalopram counteracted kainic acidinduced neuronal loss and dispersion of PSA-NCAM-positive cells within the granule cell layer of the hippocampus (Jaako*, et al.*, 2011). Citalopram also counteracted the downregulation of Reelin on both mRNA and protein levels. As decreased neurogenesis, cognitive impairment and depression coexist in chronic epilepsy, prolonged antidepressant

treatment may provide an effective strategy for easing these problems.

For TBI, it remains unclear whether compensatory neurogenesis contributes at all to functional recovery. However, several studies have examined the effect of administering neurogenic agents to rodent models of TBI to assess the effect on neuronal replacement and functional recovery. Administration of EGF or FGF-2 into the lateral ventricles following FPI has been shown to increase the rate of memory recovery in the Morris Water Maze, and produce a concomitant increase in the number of new hippocampal neurons co-labeled with BrdU and NeuN (Sun*, et al.*, 2009, Sun*, et al.*, 2010). Interestingly, intraventricular administration of the calcium-binding protein S100β following TBI has also been shown to increase the percentage of newly generated hippocampal neurons expressing NeuN and improve cognitive recovery in the Morris water Maze [for review see (Kleindienst*, et al.*, 2007)]. This is in conflict with clinical data in which an increase in CSF levels of S100β is correlated with poor prognosis in patients with TBI. Delivery of VEGF to the lateral FPI model has been shown to significantly increase the number of BrdU labeled adult-born neurons in the adult hippocampus, but does not change the number of BrdU labeled newborn cells per se (Lee&Agoston, 2010) suggesting that in the hippocampus VEGF predominantly mediates survival of adult-born neurons rather than progenitor cell proliferation. In contrast, Thau-Zuchman and colleagues (Thau-Zuchman*, et al.*, 2010) observed an increase in the number of proliferating cells in the SVZ and the perilesion cortex following infusion of VEGF into the lateral ventricles of mice after TBI. Further, while

**4.2 Traumatic brain injury** 

species. Cytokines released by microglia subsequently activate resident astrocytes, which again release cytokines. Peripheral macrophages are recruited into the brain by chemotaxis in response to a superfamily of cytokines called chemokines. Chemokines are small, secreted proteins that play crucial roles in leukocyte migration under normal conditions as well as during neuroinflammatory responses. Following injury to the adult brain, a range of cytokines and chemokines have been shown to be up-regulated in the region of neural cell death, including GRO-α, IL-8, IP-10, MCP-1, MCP-2, MIP-1α , RANTES , SDF-1α , and TNFα (Mcmanus*, et al.*, 1998, Das*, et al.*, 2008, Gordon*, et al.*, 2009, Whitney*, et al.*, 2009). In addition, chemokine receptors, including CXCR1, CXCR2, CXCR4, CXCR7, CCR1, CCR2, CCR3 and CCR5, are widely expressed on neural progenitor cells (Ji*, et al.*, 2004, Tran*, et al.*, 2004, Gordon*, et al.*, 2009). The expression of chemokine receptors on neural progenitor cells signifies the crucial roles played by chemokines in guiding progenitor cell migration and the influence these factors have in the recovery process in the injured CNS.

While a number of cytokines and chemokines involved in the inflammatory process have been demonstrated to play a role in directing progenitor cell migration, MCP-1 and SDF-1α and their receptors have been the most widely examined and clearly regulate the directed migration of endogenous neural progenitor cells from the SVZ to the injured brain following either ischemic or excitotoxic neural cell loss (Imitola*, et al.*, 2004, Belmadani*, et al.*, 2006, Robin*, et al.*, 2006, Yan*, et al.*, 2006, Gordon*, et al.*, 2009). The SDF-1α receptors CXCR4 and CXCR7 are highly expressed on neural progenitor cells. SDF-1α expression is highly upregulated in reactive astrocytes, microglia and endothelial cells in the ischemic striatum during several weeks after focal ischemic injury (Thored*, et al.*, 2006) and has been shown to induce the migration of progenitor cells *in vitro* (Peng*, et al.*, 2004) and *in vivo* to areas of hypoxic-ischemic-induced inflammation via CXCR4 signalling pathways (Imitola*, et al.*, 2004, Robin*, et al.*, 2006). The chemokine MCP-1 is also up-regulated in response to inflammation and induces the migration of neural progenitor cells. The MCP-1 receptor CCR2 is expressed by neural progenitor cells and MCP-1 recruits progenitor cells to the site of brain inflammation by binding to CCR2 and inducing their migration (Widera*, et al.*, 2004, Belmadani*, et al.*, 2006, Gordon*, et al.*, 2009). These studies clearly indicate that neuroinflammation and the resulting expression of cytokines and chemokines play a major role in directing the migration of progenitor cells in the injured brain. However, inflammatory cues involved in directing the migration of progenitor cells can also contribute to decreased survival of these migrating cells, creating juxtaposition between regeneration and ongoing cell loss and highlighting the complexity of the neuroinflammatory environment: on one hand it is useful for attracting progenitor cells to the appropriate region for neural replacement, but on the other hand it prevents efficient cell replacement by affecting the survival abilities of the migrating precursor cells (Whitney*, et al.*, 2009). The opposing properties of neuroinflammation therefore complicates the development of therapeutic strategies involving the use of cytokines or chemokines.

#### **4. Therapeutic strategies**

#### **4.1 Chronic TLE**

The major issue associated with chronic TLE is the observed reduction in hippocampal neurogenesis and potential contribution this plays to the persistence of spontaneous seizures, learning and memory deficits, and depression prevalent in chronic TLE. Based on studies in animal models of brain disease and injury, the following strategies may provide

species. Cytokines released by microglia subsequently activate resident astrocytes, which again release cytokines. Peripheral macrophages are recruited into the brain by chemotaxis in response to a superfamily of cytokines called chemokines. Chemokines are small, secreted proteins that play crucial roles in leukocyte migration under normal conditions as well as during neuroinflammatory responses. Following injury to the adult brain, a range of cytokines and chemokines have been shown to be up-regulated in the region of neural cell death, including GRO-α, IL-8, IP-10, MCP-1, MCP-2, MIP-1α , RANTES , SDF-1α , and TNFα (Mcmanus*, et al.*, 1998, Das*, et al.*, 2008, Gordon*, et al.*, 2009, Whitney*, et al.*, 2009). In addition, chemokine receptors, including CXCR1, CXCR2, CXCR4, CXCR7, CCR1, CCR2, CCR3 and CCR5, are widely expressed on neural progenitor cells (Ji*, et al.*, 2004, Tran*, et al.*, 2004, Gordon*, et al.*, 2009). The expression of chemokine receptors on neural progenitor cells signifies the crucial roles played by chemokines in guiding progenitor cell migration and the

While a number of cytokines and chemokines involved in the inflammatory process have been demonstrated to play a role in directing progenitor cell migration, MCP-1 and SDF-1α and their receptors have been the most widely examined and clearly regulate the directed migration of endogenous neural progenitor cells from the SVZ to the injured brain following either ischemic or excitotoxic neural cell loss (Imitola*, et al.*, 2004, Belmadani*, et al.*, 2006, Robin*, et al.*, 2006, Yan*, et al.*, 2006, Gordon*, et al.*, 2009). The SDF-1α receptors CXCR4 and CXCR7 are highly expressed on neural progenitor cells. SDF-1α expression is highly upregulated in reactive astrocytes, microglia and endothelial cells in the ischemic striatum during several weeks after focal ischemic injury (Thored*, et al.*, 2006) and has been shown to induce the migration of progenitor cells *in vitro* (Peng*, et al.*, 2004) and *in vivo* to areas of hypoxic-ischemic-induced inflammation via CXCR4 signalling pathways (Imitola*, et al.*, 2004, Robin*, et al.*, 2006). The chemokine MCP-1 is also up-regulated in response to inflammation and induces the migration of neural progenitor cells. The MCP-1 receptor CCR2 is expressed by neural progenitor cells and MCP-1 recruits progenitor cells to the site of brain inflammation by binding to CCR2 and inducing their migration (Widera*, et al.*, 2004, Belmadani*, et al.*, 2006, Gordon*, et al.*, 2009). These studies clearly indicate that neuroinflammation and the resulting expression of cytokines and chemokines play a major role in directing the migration of progenitor cells in the injured brain. However, inflammatory cues involved in directing the migration of progenitor cells can also contribute to decreased survival of these migrating cells, creating juxtaposition between regeneration and ongoing cell loss and highlighting the complexity of the neuroinflammatory environment: on one hand it is useful for attracting progenitor cells to the appropriate region for neural replacement, but on the other hand it prevents efficient cell replacement by affecting the survival abilities of the migrating precursor cells (Whitney*, et al.*, 2009). The opposing properties of neuroinflammation therefore complicates the development of

influence these factors have in the recovery process in the injured CNS.

therapeutic strategies involving the use of cytokines or chemokines.

The major issue associated with chronic TLE is the observed reduction in hippocampal neurogenesis and potential contribution this plays to the persistence of spontaneous seizures, learning and memory deficits, and depression prevalent in chronic TLE. Based on studies in animal models of brain disease and injury, the following strategies may provide

**4. Therapeutic strategies** 

**4.1 Chronic TLE** 

mechanisms by which to increase hippocampal neurogenesis in chronic epilepsy; administration of neurotrophic factors, physical exercise, exposure to an enriched environment and antidepressant therapy [for review see (Kuruba*, et al.*, 2009)]. Administration of neurotrophic factors is relevant as many factors that promote neurogenesis (e.g: BDNF, FGF-2, IGF-1) are reduced in chronic epilepsy (Hattiangady*, et al.*, 2004, Shetty*, et al.*, 2004). Supporting this, a range of studies have demonstrated that administration of neurotrophic factors to both the normal and injured adult rodent brain can enhance hippocampal neurogenesis (Lichtenwalner*, et al.*, 2001, Yoshimura*, et al.*, 2001, Jin*, et al.*, 2003, Scharfman*, et al.*, 2005, Rai*, et al.*, 2007, Paradiso*, et al.*, 2009, Paradiso*, et al.*, 2011). Performing physical exercise and environmental enrichment have also been shown to enhance hippocampal neurogenesis, potentially through increased expression of a range of mitogenic factors such as BDNF, FGF2, NGF, IGF-1 and VEGF as well as phosphorylation of cAMP-response binding protein (CREB) (Nithianantharajah*, et al.*, 2006, Van Praag, 2008, Llorens-Martín*, et al.*, 2009, 2010, Lafenetre*, et al.*, 2011) and may provide an appealing noninvasive therapeutic approach for the treatment of chronic TLE (Dhanushkodi*, et al.*, 2008, Arida*, et al.*, 2009). Antidepressant therapy in chronic TLE is another interesting approach for increasing neurogenesis and reducing cognitive impairments, as antidepressant therapy enhances hippocampal neurogenesis probably via increases in levels of serotonin, noradrenaline, BDNF, CREB and a range of other mitogenic factors (Sahay*, et al.*, 2007, Thomas*, et al.*, 2008, Lanni*, et al.*, 2009). In particular, a recent study demonstrated that repeated administration of the antidepressant agent citalopram counteracted kainic acidinduced neuronal loss and dispersion of PSA-NCAM-positive cells within the granule cell layer of the hippocampus (Jaako*, et al.*, 2011). Citalopram also counteracted the downregulation of Reelin on both mRNA and protein levels. As decreased neurogenesis, cognitive impairment and depression coexist in chronic epilepsy, prolonged antidepressant treatment may provide an effective strategy for easing these problems.

#### **4.2 Traumatic brain injury**

For TBI, it remains unclear whether compensatory neurogenesis contributes at all to functional recovery. However, several studies have examined the effect of administering neurogenic agents to rodent models of TBI to assess the effect on neuronal replacement and functional recovery. Administration of EGF or FGF-2 into the lateral ventricles following FPI has been shown to increase the rate of memory recovery in the Morris Water Maze, and produce a concomitant increase in the number of new hippocampal neurons co-labeled with BrdU and NeuN (Sun*, et al.*, 2009, Sun*, et al.*, 2010). Interestingly, intraventricular administration of the calcium-binding protein S100β following TBI has also been shown to increase the percentage of newly generated hippocampal neurons expressing NeuN and improve cognitive recovery in the Morris water Maze [for review see (Kleindienst*, et al.*, 2007)]. This is in conflict with clinical data in which an increase in CSF levels of S100β is correlated with poor prognosis in patients with TBI. Delivery of VEGF to the lateral FPI model has been shown to significantly increase the number of BrdU labeled adult-born neurons in the adult hippocampus, but does not change the number of BrdU labeled newborn cells per se (Lee&Agoston, 2010) suggesting that in the hippocampus VEGF predominantly mediates survival of adult-born neurons rather than progenitor cell proliferation. In contrast, Thau-Zuchman and colleagues (Thau-Zuchman*, et al.*, 2010) observed an increase in the number of proliferating cells in the SVZ and the perilesion cortex following infusion of VEGF into the lateral ventricles of mice after TBI. Further, while

Compensatory Neurogenesis in the Injured Adult Brain 75

angiogenesis and neurogenesis (Zhang*, et al.*, 2006). Treatment of ischemic stroke with EPO is also under investigation, with additional studies examining the use of nonhematopoietic EPO analogues such as CEPO. As discussed in Section 4.2, EPO has been shown to promote both neurogenesis and angiogenesis, resulting in functional recovery in rodent models of focal ischemic injury. Clinical trials investigating the therapeutic application of EPO or CEPO for the treatment of stroke are currently being undertaken [for review see (Xiong*, et* 

The presence of both neural and glial progenitor cells in the adult central nervous system (CNS), and the capacity of these cells to migrate through this mature structure to areas of pathological damage and injury raises hope for the development of new therapeutic strategies to treat brain injury. Although at present time the compensatory neurogenesis described after various types of brain injuries appears to be modest, the development of a strategy promoting the proliferation, directed mobilization and phenotypic induction of endogenous progenitor cells to areas of neural cell loss remains of high interest. However, the development of novel neuroregenerative strategies focusing on the promotion of compensatory adult neurogenesis will only be achieved once we fully understand the mechanisms promoting the response of endogenous progenitor cells to neural injury and cell loss. An important factor that needs to be addressed when investigating therapeutic strategies by which to enhance compensatory neurogenesis following brain injury is whether adult-born cells become functional and integrate appropriately into existing circuitry and contribute to the recovery process, or whether they just enhance or restore the functionality and survival of existing dysfunctional cells. While striving to identify potential factors or the redirected use of current pharmaceuticals to promote compensatory neurogenesis for the treatment of brain injury, caution must also be taken. Post-traumatic epilepsy is a fairly common morbidity associated with both stroke and TBI and one postulated mechanism for this is that aberrant neurogenesis serves as the epileptic focus (Parent*, et al.*, 2008). Therefore, any strategy aimed at enhancing neurogenesis may inadvertently result in this and other unwanted side effects. In addition, since many strategies aimed towards enhancing neurogenesis promote cell growth, it remains a possibility that increasing proliferation may result in potentially unwanted tumour growth. Thus, while enhancing compensatory neurogenesis for the treatment of brain injury remains an exciting and potentially revolutionary therapeutic strategy, many issues regarding specificity, mechanism and potential toxicity need to be thoroughly investigated before

Altar, CA, Laeng, P, Jurata, LW*, et al.*, (2004). Electroconvulsive seizures regulate gene

Altman, J & Das, GD. (1965). Autoradiographic and histological evidence of postnatal neurogenesis in rats. *Journal of Comparative Neurology*. 124, pp. (319-335), Androutsellis-Theotokis, A, Leker, RR, Soldner, F*, et al.*, (2006). Notch signalling regulates

stem cell numbers in vitro and in vivo. *Nature*. 442, pp. (823 -826).

expression of distinct neurotrophic signaling pathways. *The Journal of Neuroscience*.

*al.*, 2010)].

**5. Conclusions** 

meaningful clinical intervention can occur.

24, pp. (2667-2677)

**6. References** 

functional outcome was significantly improved in mice treated with VEGF compared to vehicle treated animals following TBI, fate analysis demonstrated that most newborn cells differentiated into astrocytes and oligodendroglia, and only a few cells differentiated into neurons (Thau-Zuchman*, et al.*, 2010).

The effect of mitogen support on hippocampal neurogenesis following TBI has also been examined using transgenic models. FGF-2(-/-) mice subjected to CCI injury exhibit a reduction in the number of both BrdU-positive cells and BrdU-positive neurons when compared to FGF-2(+/+) mice. In contrast, over-expression of FGF-2 by intracerebral injection of herpes simplex virus-1 amplicon vectors encoding for this factor increased both the number of dividing cells and BrdU-positive neurons (Yoshimura*, et al.*, 2003). This suggests that FGF-2 up-regulates neurogenesis and protects the survival of adult-born neurons in the adult hippocampus after TBI. BDNF has also been shown to play a role in regulating the survival of adult-born immature neurons in the hippocampus following TBI, with the level of adult-born immature neuron death in the dentate gyrus significantly increased in BDNF conditional knockout mice following TBI.

A number of studies have demonstrated that the injured brain can be stimulated to promote angiogenesis and neurogenesis, which are coupled restorative processes that contribute to functional recovery in both TBI and stroke [for review see (Xiong*, et al.*, 2010)]. Studies have demonstrated that intraperitoneal administration of EPO post-TBI significantly increases BDNF expression and enhances hippocampal neurogenesis with subsequent improvement in sensorimotor and spatial learning functions (Meng*, et al.*, Lu*, et al.*, 2005, Xiong*, et al.*, 2008, Xiong*, et al.*, 2010). Statins also show neurorestorative effects in animal models of TBI through the induction of angiogenesis and neurogenesis. Simvastatin treatment provides long-lasting (3 month) functional improvement after TBI in rats. This was coupled with increased expression of VEGF and BDNF and enhanced in the dentate gyrus of rats following TBI (Lu*, et al.*, 2007, Wu*, et al.*, 2008). Clinical trials investigating the use of either EPO or CEPO, or the use of statins for the treatment of TBI are currently being undertaken [for review see (Xiong*, et al.*, 2010)].

#### **4.3 Stroke**

A range of therapeutic strategies promoting regeneration in stroke are being investigated. However, some of the most interesting approaches are based around the use of statins and the phosphodiesterase type 5 (PDE5) inhibitors such as sildenafil (Xiong*, et al.*, 2010). Statins have been shown to induce angiogenesis, neurogenesis and synaptogenesis, and to enhance functional recovery after stroke in rats (Chen*, et al.*, 2003). It is thought that expression of BDNF, VEGF and VEGFR2, and regulation of Notch signaling activity contribute to these regenerative processes (Chen*, et al.*, 2005, Chen*, et al.*, 2008). Clinical trials for both lovastatin and simvastatin in stroke patients are currently being undertaken [for review see (Xiong*, et al.*, 2010)]. Given the wide use of statins, their favourable safety profile, rare serious adverse effects and the extensive preclinical data showing neuroprotection and neurorestoration in rodent models of stroke, further clinical studies investigating the potential use of statins to promote neuroregeneration following stroke are warranted. The PDE5 inhibitor sildenafil has also been shown to promote neurogenesis and reduce functional deficits when administered to rats either 2 or 24 hours after ischemic injury (Zhang*, et al.*, 2002), or for 7 consecutive days starting 7 days following focal ischemia (Zhang*, et al.*, 2006). Further, treatment of ischemic stroke with a long-acting PDE5 inhibitor tadalafil improves functional recovery, which is associated with increases in brain cGMP levels and enhanced angiogenesis and neurogenesis (Zhang*, et al.*, 2006). Treatment of ischemic stroke with EPO is also under investigation, with additional studies examining the use of nonhematopoietic EPO analogues such as CEPO. As discussed in Section 4.2, EPO has been shown to promote both neurogenesis and angiogenesis, resulting in functional recovery in rodent models of focal ischemic injury. Clinical trials investigating the therapeutic application of EPO or CEPO for the treatment of stroke are currently being undertaken [for review see (Xiong*, et al.*, 2010)].

#### **5. Conclusions**

74 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

functional outcome was significantly improved in mice treated with VEGF compared to vehicle treated animals following TBI, fate analysis demonstrated that most newborn cells differentiated into astrocytes and oligodendroglia, and only a few cells differentiated into

The effect of mitogen support on hippocampal neurogenesis following TBI has also been examined using transgenic models. FGF-2(-/-) mice subjected to CCI injury exhibit a reduction in the number of both BrdU-positive cells and BrdU-positive neurons when compared to FGF-2(+/+) mice. In contrast, over-expression of FGF-2 by intracerebral injection of herpes simplex virus-1 amplicon vectors encoding for this factor increased both the number of dividing cells and BrdU-positive neurons (Yoshimura*, et al.*, 2003). This suggests that FGF-2 up-regulates neurogenesis and protects the survival of adult-born neurons in the adult hippocampus after TBI. BDNF has also been shown to play a role in regulating the survival of adult-born immature neurons in the hippocampus following TBI, with the level of adult-born immature neuron death in the dentate gyrus significantly

A number of studies have demonstrated that the injured brain can be stimulated to promote angiogenesis and neurogenesis, which are coupled restorative processes that contribute to functional recovery in both TBI and stroke [for review see (Xiong*, et al.*, 2010)]. Studies have demonstrated that intraperitoneal administration of EPO post-TBI significantly increases BDNF expression and enhances hippocampal neurogenesis with subsequent improvement in sensorimotor and spatial learning functions (Meng*, et al.*, Lu*, et al.*, 2005, Xiong*, et al.*, 2008, Xiong*, et al.*, 2010). Statins also show neurorestorative effects in animal models of TBI through the induction of angiogenesis and neurogenesis. Simvastatin treatment provides long-lasting (3 month) functional improvement after TBI in rats. This was coupled with increased expression of VEGF and BDNF and enhanced in the dentate gyrus of rats following TBI (Lu*, et al.*, 2007, Wu*, et al.*, 2008). Clinical trials investigating the use of either EPO or CEPO, or the use of statins for the treatment of TBI are currently being undertaken

A range of therapeutic strategies promoting regeneration in stroke are being investigated. However, some of the most interesting approaches are based around the use of statins and the phosphodiesterase type 5 (PDE5) inhibitors such as sildenafil (Xiong*, et al.*, 2010). Statins have been shown to induce angiogenesis, neurogenesis and synaptogenesis, and to enhance functional recovery after stroke in rats (Chen*, et al.*, 2003). It is thought that expression of BDNF, VEGF and VEGFR2, and regulation of Notch signaling activity contribute to these regenerative processes (Chen*, et al.*, 2005, Chen*, et al.*, 2008). Clinical trials for both lovastatin and simvastatin in stroke patients are currently being undertaken [for review see (Xiong*, et al.*, 2010)]. Given the wide use of statins, their favourable safety profile, rare serious adverse effects and the extensive preclinical data showing neuroprotection and neurorestoration in rodent models of stroke, further clinical studies investigating the potential use of statins to promote neuroregeneration following stroke are warranted. The PDE5 inhibitor sildenafil has also been shown to promote neurogenesis and reduce functional deficits when administered to rats either 2 or 24 hours after ischemic injury (Zhang*, et al.*, 2002), or for 7 consecutive days starting 7 days following focal ischemia (Zhang*, et al.*, 2006). Further, treatment of ischemic stroke with a long-acting PDE5 inhibitor tadalafil improves functional recovery, which is associated with increases in brain cGMP levels and enhanced

neurons (Thau-Zuchman*, et al.*, 2010).

[for review see (Xiong*, et al.*, 2010)].

**4.3 Stroke** 

increased in BDNF conditional knockout mice following TBI.

The presence of both neural and glial progenitor cells in the adult central nervous system (CNS), and the capacity of these cells to migrate through this mature structure to areas of pathological damage and injury raises hope for the development of new therapeutic strategies to treat brain injury. Although at present time the compensatory neurogenesis described after various types of brain injuries appears to be modest, the development of a strategy promoting the proliferation, directed mobilization and phenotypic induction of endogenous progenitor cells to areas of neural cell loss remains of high interest. However, the development of novel neuroregenerative strategies focusing on the promotion of compensatory adult neurogenesis will only be achieved once we fully understand the mechanisms promoting the response of endogenous progenitor cells to neural injury and cell loss. An important factor that needs to be addressed when investigating therapeutic strategies by which to enhance compensatory neurogenesis following brain injury is whether adult-born cells become functional and integrate appropriately into existing circuitry and contribute to the recovery process, or whether they just enhance or restore the functionality and survival of existing dysfunctional cells. While striving to identify potential factors or the redirected use of current pharmaceuticals to promote compensatory neurogenesis for the treatment of brain injury, caution must also be taken. Post-traumatic epilepsy is a fairly common morbidity associated with both stroke and TBI and one postulated mechanism for this is that aberrant neurogenesis serves as the epileptic focus (Parent*, et al.*, 2008). Therefore, any strategy aimed at enhancing neurogenesis may inadvertently result in this and other unwanted side effects. In addition, since many strategies aimed towards enhancing neurogenesis promote cell growth, it remains a possibility that increasing proliferation may result in potentially unwanted tumour growth. Thus, while enhancing compensatory neurogenesis for the treatment of brain injury remains an exciting and potentially revolutionary therapeutic strategy, many issues regarding specificity, mechanism and potential toxicity need to be thoroughly investigated before meaningful clinical intervention can occur.

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**5** 

Aysegul Bayir

 *Turkey* 

*Selçuk University Konya* 

**The Effects of Melatonin on Brain** 

*Department of Emergency Medicine, Meram Faculty of Medicine* 

**Injury in Acute Organophosphate Toxicity** 

Organophosphates (OP) are potent toxic substances used in agriculture as insecticide and pesticides, and in warfare. Over 200,000 cases of accidental toxic exposure to OPs are

OPs inhibit acetylcholine esterase (ACE), an enzyme which breaks down acetylcholine in cholinergic synapses in the peripheral nervous system (PNS) and central nervous system (CNS). Thus OP intoxication is characterized by findings related to hyperstimulation of cholinergic synapses in the PNS and CNS. Hyper-stimulation of cholinergic synapses in CNS may result in rapid blackout attacks and inhibition of respiratory center in medulla oblongata (Marrs, 2007). In animal studies of OPs used as chemical warfare agents, status epilepticus occurs rapidly due to severe brain damage, which is demonstrated on both electrophysiologic and histopathologic studies (McDonough et al, 1998). Pharmacological treatment of OP intoxication includes anticholinergic agents like atropine sulfate to block postsynaptic cholinergic receptors, oximes to reactivate inhibited enzymes, and antiepileptics to control

In previous studies, oxidative stress caused by OPs was demonstrated in humans and rats. Lipid peroxidation in rat brain and human erythrocytes caused by OPs was confirmed as well (Abdollahi et al, 2004). Melatonin removes the potent hydroxyl radical secreted from pineal gland. Blood can easily pass the brain barrier and provides oxidative protection in the brain. At the same time, it also removes other reactive molecules such as hydrogen peroxide, singlet oxygen, peroxynitrite, and nitric oxide. Melatonin decreases oxidative stress by increasing the production of antioxidant enzymes like melatonin superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px), the most important protective substance in the

The aim of this study was to investigate the effects of melatonin on lipid peroxidation in erythrocytes and brain tissue in the setting of acute OP intoxication in rats and compare its

The study was carried out in the Experimental Medicine and Research Center at Selçuk University after being approved by the Ethical Board of the Experimental Medicine and

effects with those of routine treatment (pralidoxime and atropine).

**1. Introduction** 

reported annually (Jyaratnam, 1999).

seizure activity (Marrs, 2007).

brain (Hsu et al, 2002).

**2. Materials and methods 2.1 Experimental methods** 


### **The Effects of Melatonin on Brain Injury in Acute Organophosphate Toxicity**

Aysegul Bayir

*Department of Emergency Medicine, Meram Faculty of Medicine Selçuk University Konya Turkey* 

#### **1. Introduction**

86 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Zhang, RL, Zhang, Z, Zhang, L*, et al.*, (2006). Delayed treatment with sildenafil enhances

Zhang, RL, Zhang, ZG & Chopp, M. (2008). Ischemic stroke and neurogenesis in the

Zhang, RL, Chopp, M, Gregg, SR*, et al.*, (2009). Patterns and dynamics of subventricular

Zheng, W, Zhuge, Q, Zhong, M*, et al.*, (2011). Neurogenesis in adult human brain after

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ischemia. *Journal of Neuroscience Research*. 83, pp. (1213-1219).

subventricular zone. *Neuropharmacology*. 55, pp. (345-352).

traumatic brain injury. *Journal of Neurotrauma*. In press,

neonatal rats. *Brain Research Bulletin*. 81, pp. (372-377).

*Blood Flow Metab*. 29, pp. (1240 - 1250).

neurogenesis and improves functional recovery in aged rats after focal cerebral

zone neuroblast migration in the ischemic striatum of the adult mouse. *J Cereb* 

VEGF improves neural functional recovery after hypoxia-ischemic brain damage in

Organophosphates (OP) are potent toxic substances used in agriculture as insecticide and pesticides, and in warfare. Over 200,000 cases of accidental toxic exposure to OPs are reported annually (Jyaratnam, 1999).

OPs inhibit acetylcholine esterase (ACE), an enzyme which breaks down acetylcholine in cholinergic synapses in the peripheral nervous system (PNS) and central nervous system (CNS). Thus OP intoxication is characterized by findings related to hyperstimulation of cholinergic synapses in the PNS and CNS. Hyper-stimulation of cholinergic synapses in CNS may result in rapid blackout attacks and inhibition of respiratory center in medulla oblongata (Marrs, 2007). In animal studies of OPs used as chemical warfare agents, status epilepticus occurs rapidly due to severe brain damage, which is demonstrated on both electrophysiologic and histopathologic studies (McDonough et al, 1998). Pharmacological treatment of OP intoxication includes anticholinergic agents like atropine sulfate to block postsynaptic cholinergic receptors, oximes to reactivate inhibited enzymes, and antiepileptics to control seizure activity (Marrs, 2007).

In previous studies, oxidative stress caused by OPs was demonstrated in humans and rats. Lipid peroxidation in rat brain and human erythrocytes caused by OPs was confirmed as well (Abdollahi et al, 2004). Melatonin removes the potent hydroxyl radical secreted from pineal gland. Blood can easily pass the brain barrier and provides oxidative protection in the brain. At the same time, it also removes other reactive molecules such as hydrogen peroxide, singlet oxygen, peroxynitrite, and nitric oxide. Melatonin decreases oxidative stress by increasing the production of antioxidant enzymes like melatonin superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px), the most important protective substance in the brain (Hsu et al, 2002).

The aim of this study was to investigate the effects of melatonin on lipid peroxidation in erythrocytes and brain tissue in the setting of acute OP intoxication in rats and compare its effects with those of routine treatment (pralidoxime and atropine).

#### **2. Materials and methods**

#### **2.1 Experimental methods**

The study was carried out in the Experimental Medicine and Research Center at Selçuk University after being approved by the Ethical Board of the Experimental Medicine and

The Effects of Melatonin on Brain Injury in Acute Organophosphate Toxicity 89

A brain tissue sample (0.5 g) was taken and preserved at -80° C. Using a cold 150 mM KCL solution, the tissue sample was homogenized to make a 10% homogenate, and was then centrifuged at 10,000 rpm for 10 minutes. The following substances were mixed: 0.1 ml of the homogenate, 0.2 mL of 8.1% sodium dodecyl sulfate (SDS) solution, 1.5 mL of 20% acetic acid solution (sodium hydroxide was added to this mixture for adjust pH>3), and 1.5 ml of 0.8% thiobarbituric acid liquid; this mixture was then stirred with a vortex. The mixture was then boiled in distilled water at 95° C for 60 minutes. Then it was cooled, and the following were added to the mixture: 1 mL of distilled water, 5 mL of n-butanol and pyridine (15:l, v/v) were added, and the mixture was rinsed. The resulting mixture was spun at 4,000 rpm for 10 minutes. A sample was from the upper layer of the mixture was taken, and absorbance at 532 nm was measured spectrophotometrically. MDA concentrations were

C = Measured absorbance x 320.5 x dilution factor / microprotein of homogenate=

Blood was centrifuged and the plasma was separated. After being washed with normal saline solution once, 1.5 mL was taken from the erythrocyte plug and 1.5 mL of buffered sodium azide was added. 50 mL was taken from this hemolizate and 12.5 mL of Drabkin solution was added and the Hb was measured. 5 mL was taken from this mixture and 5 mL of 35% H2O2 was added and this mixture was incubated for 2 hours at 37° C with tubes open. After this was cooled, 3 mL was taken and 2 mL of trichloroacetic acid-arsenide solution was added and the mixture was then centrifuged at 2,500 rpm. 3 mL was taken from this supernatant and 1 mL of thiobarbituric acid was added and then the mixture was boiled for 15 min. After it cooled, absorbance at 532 nm was measured

spectrophotometrically and the results were calculated for each gram of hemoglobin.

Statistical analyses were performed using SPSS for Windows 13.0 (SPSS, Inc., Chicago, USA). Between group comparisons were made by repeated measurements with variance analysis (ANOVA). For significant values, Bonferroni one-way variance analysis as a post hoc test, and then the Tukey HSD test was applied. Comparisons with a P value of less than 0.05 were regarded as statistically significant. When comparing intra-group repeated measurements, the student t test was used. Means of each group's values were calculated and reported as a table. To compare tissue ACE and tissue MDA values, one-way ANOVA

All sham group animals died before 24 hours after intoxication, therefore no blood sample

No significant differences between groups in erythrocyte ACE levels were found. At 12 hours after treatment, the mean erythrocyte ACE level of the melatonin+PAM+atropine group was not significantly different from that of the PAM+atropine group, but it was significantly higher than that of the sham group (p=0.023). The mean erythrocyte ACE level

**2.2.4 Measurement of MDA in brain tissue** 

derived with the following formula:

**2.2.4 Measurement of MDA in erythrocytes** 

and then Tukey HSD tests were performed.

was collected from those subjects at 24 hours.

nmol/mg tissue

**2.3 Statistical methods** 

**3. Results** 

Research Center. Twenty (12 male, 8 female, weight range 2500-4000 g) New Zealand rabbits were used. The subjects were divided into three groups: a sham group (n=8), a pralidoxime (PAM) plus atropine group (n=6), and a melatonin plus PAM plus atropine group (n=6). Subjects were anaesthetized with 50 mg/kg IM ketamine and 15 mg/kg IM xylazine HCL. The central ear artery and marginal ear vein were catheterized. Blood was drawn in EDTA tubes to measure baseline plasma ACE, nitric oxide (NO), and plasma and erythrocyte malondialdehyde (MDA).

Orogastric feeding tubes were inserted and 50 mg/kg (LD50=50 mg/kg) dichlorvos was administered. One hour later, when signs of toxicity (hypersalivation, bronchospasm, fasciculations, convulsions) appeared, venous blood samples were taken again in order to measure plasma ACE, nitric oxide (NO), and plasma and erythrocyte MDA.

In the sham group, no treatment was given. Venous blood samples were taken at 12 hours after OP administration hour to measure plasma ACE, nitric oxide (NO), and plasma and erythrocyte MDA. In the PAM+atropine group, 0.05 mg/kg IV atropine was given and this dose was administered again as needed. In addition, a 30 mg/kg IV bolus of PAM was given, then 15 mg/kg IV PAM was given every 4 hours. In the melatonin plus PAMatropine group, 10 mg/kg IV melatonin was administered, as well as PAM and atropine as in the PAM-atropine group. Blood samples were taken from the subjects in PAM-atropine and melatonin-PAM-atropine groups at 12 and 24 hours after intoxication in order to measure plasma ACE, nitric oxide (NO), and plasma and erythrocyte MDA.

At 24 hours post-intoxication, craniotomy was performed and liver samples were taken after laparotomy to evaluate ACE, NO and MDA levels. At the end of the study, subjects were sacrificed by administering a high dose of ketamine.

#### **2.2 Biochemical methods**

#### **2.2.1 Measurement of plasma ACE activity**

Plasma was separated from erythrocytes by centrifuging for 15 minutes at 3000 rpm. The following were placed into a 10 mL test tube: 3 mL of distilled water, 0.2 mL of plasma, and 3 mL of barbital phosphate (pH 8.1). The pH (pH1) of the mixture was measured with a glass electrode pH meter. Then, 0.1 ml of 7.5% acetylcholine iodide solution was added to the reaction mixture and incubated for 20 min at 37° C. At the end of incubation period, the pH of the reaction mixture was measured (pH2). ACE activity was calculated using the following formula:

ACE activity (ΔpH/20 minutes) = pH1 – pH2 – (Δ pH of the blank)

#### **2.2.2 Measurement of ACE activity in brain tissue**

To measure brain ACE activity, a brain tissue sample was homogenized (at 25% of the maximum speed) in barbital phosphate (pH 8.1) to weigh 3 ml/100 mg when wet. Homogenization was performed in an ice bath and brain homogenate was preserved in ice before cholinesterase determination. For determining brain ACE activity, 0.2 mL of tissue homogenate was used. ACE activity was calculated using the same formula as shown above.

#### **2.2.3 Measurement of NO in plasma and brain tissue**

To measure NO in plasma and brain tissue homogenate, the Nitric Oxide Synthase Assay Kit (Colorimetric) (Merck Chemicals, Darmstadt, Germany) was used.

#### **2.2.4 Measurement of MDA in brain tissue**

88 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Research Center. Twenty (12 male, 8 female, weight range 2500-4000 g) New Zealand rabbits were used. The subjects were divided into three groups: a sham group (n=8), a pralidoxime (PAM) plus atropine group (n=6), and a melatonin plus PAM plus atropine group (n=6). Subjects were anaesthetized with 50 mg/kg IM ketamine and 15 mg/kg IM xylazine HCL. The central ear artery and marginal ear vein were catheterized. Blood was drawn in EDTA tubes to measure baseline plasma ACE, nitric oxide (NO), and plasma and erythrocyte

Orogastric feeding tubes were inserted and 50 mg/kg (LD50=50 mg/kg) dichlorvos was administered. One hour later, when signs of toxicity (hypersalivation, bronchospasm, fasciculations, convulsions) appeared, venous blood samples were taken again in order to

In the sham group, no treatment was given. Venous blood samples were taken at 12 hours after OP administration hour to measure plasma ACE, nitric oxide (NO), and plasma and erythrocyte MDA. In the PAM+atropine group, 0.05 mg/kg IV atropine was given and this dose was administered again as needed. In addition, a 30 mg/kg IV bolus of PAM was given, then 15 mg/kg IV PAM was given every 4 hours. In the melatonin plus PAMatropine group, 10 mg/kg IV melatonin was administered, as well as PAM and atropine as in the PAM-atropine group. Blood samples were taken from the subjects in PAM-atropine and melatonin-PAM-atropine groups at 12 and 24 hours after intoxication in order to

At 24 hours post-intoxication, craniotomy was performed and liver samples were taken after laparotomy to evaluate ACE, NO and MDA levels. At the end of the study, subjects were

Plasma was separated from erythrocytes by centrifuging for 15 minutes at 3000 rpm. The following were placed into a 10 mL test tube: 3 mL of distilled water, 0.2 mL of plasma, and 3 mL of barbital phosphate (pH 8.1). The pH (pH1) of the mixture was measured with a glass electrode pH meter. Then, 0.1 ml of 7.5% acetylcholine iodide solution was added to the reaction mixture and incubated for 20 min at 37° C. At the end of incubation period, the pH of the reaction mixture was measured (pH2). ACE activity was calculated using the

To measure brain ACE activity, a brain tissue sample was homogenized (at 25% of the maximum speed) in barbital phosphate (pH 8.1) to weigh 3 ml/100 mg when wet. Homogenization was performed in an ice bath and brain homogenate was preserved in ice before cholinesterase determination. For determining brain ACE activity, 0.2 mL of tissue homogenate was used. ACE activity was calculated using the same formula as shown

To measure NO in plasma and brain tissue homogenate, the Nitric Oxide Synthase Assay

measure plasma ACE, nitric oxide (NO), and plasma and erythrocyte MDA.

measure plasma ACE, nitric oxide (NO), and plasma and erythrocyte MDA.

ACE activity (ΔpH/20 minutes) = pH1 – pH2 – (Δ pH of the blank)

**2.2.2 Measurement of ACE activity in brain tissue** 

**2.2.3 Measurement of NO in plasma and brain tissue** 

Kit (Colorimetric) (Merck Chemicals, Darmstadt, Germany) was used.

sacrificed by administering a high dose of ketamine.

**2.2.1 Measurement of plasma ACE activity** 

malondialdehyde (MDA).

**2.2 Biochemical methods** 

following formula:

above.

A brain tissue sample (0.5 g) was taken and preserved at -80° C. Using a cold 150 mM KCL solution, the tissue sample was homogenized to make a 10% homogenate, and was then centrifuged at 10,000 rpm for 10 minutes. The following substances were mixed: 0.1 ml of the homogenate, 0.2 mL of 8.1% sodium dodecyl sulfate (SDS) solution, 1.5 mL of 20% acetic acid solution (sodium hydroxide was added to this mixture for adjust pH>3), and 1.5 ml of 0.8% thiobarbituric acid liquid; this mixture was then stirred with a vortex. The mixture was then boiled in distilled water at 95° C for 60 minutes. Then it was cooled, and the following were added to the mixture: 1 mL of distilled water, 5 mL of n-butanol and pyridine (15:l, v/v) were added, and the mixture was rinsed. The resulting mixture was spun at 4,000 rpm for 10 minutes. A sample was from the upper layer of the mixture was taken, and absorbance at 532 nm was measured spectrophotometrically. MDA concentrations were derived with the following formula:

C = Measured absorbance x 320.5 x dilution factor / microprotein of homogenate= nmol/mg tissue

#### **2.2.4 Measurement of MDA in erythrocytes**

Blood was centrifuged and the plasma was separated. After being washed with normal saline solution once, 1.5 mL was taken from the erythrocyte plug and 1.5 mL of buffered sodium azide was added. 50 mL was taken from this hemolizate and 12.5 mL of Drabkin solution was added and the Hb was measured. 5 mL was taken from this mixture and 5 mL of 35% H2O2 was added and this mixture was incubated for 2 hours at 37° C with tubes open. After this was cooled, 3 mL was taken and 2 mL of trichloroacetic acid-arsenide solution was added and the mixture was then centrifuged at 2,500 rpm. 3 mL was taken from this supernatant and 1 mL of thiobarbituric acid was added and then the mixture was boiled for 15 min. After it cooled, absorbance at 532 nm was measured spectrophotometrically and the results were calculated for each gram of hemoglobin.

#### **2.3 Statistical methods**

Statistical analyses were performed using SPSS for Windows 13.0 (SPSS, Inc., Chicago, USA). Between group comparisons were made by repeated measurements with variance analysis (ANOVA). For significant values, Bonferroni one-way variance analysis as a post hoc test, and then the Tukey HSD test was applied. Comparisons with a P value of less than 0.05 were regarded as statistically significant. When comparing intra-group repeated measurements, the student t test was used. Means of each group's values were calculated and reported as a table. To compare tissue ACE and tissue MDA values, one-way ANOVA and then Tukey HSD tests were performed.

#### **3. Results**

All sham group animals died before 24 hours after intoxication, therefore no blood sample was collected from those subjects at 24 hours.

No significant differences between groups in erythrocyte ACE levels were found. At 12 hours after treatment, the mean erythrocyte ACE level of the melatonin+PAM+atropine group was not significantly different from that of the PAM+atropine group, but it was significantly higher than that of the sham group (p=0.023). The mean erythrocyte ACE level

The Effects of Melatonin on Brain Injury in Acute Organophosphate Toxicity 91

Treatment group 1 hour 12 hours 24 hours

Pralidoxime + atropine 5.37±0.67 8.80±0.30 9.48±0.76

+ atropine 5.12±0.53 5.93±0.37 6.14±0.42

p value p>0.05 p<0.05 p<0.05

Table 3. Mean erythrocyte malondialdehyde levels (nmol/mL) at various times after intoxication with dichlorvos in the three groups. Levels were compared using the Mann

Sham 5.40±0.45 9.05±0.66

Melatonin+pralidoxime

Whitney U test.

Fig. 1.

Fig. 2.

in the melatonin+PAM+atropine group was significantly higher (p=0.031) than that of the PAM+atropine group (Table 1).


Table 1. Mean erythrocyte acetylcholine esterase levels (U/L) at various times after intoxication with dichlorvos in the three groups. Levels were compared using the Mann Whitney U test.

NO levels in the three groups were not significantly different from each other at 1 hour and 12 hours post-intoxication (p>0.05). The NO levels at 24 hours post-intoxication in the melatonin+PAM+atropine group were not significantly different from that of the PAM+atropine group (p>0.05, Table 2).


Table 2. Mean erythrocyte nitric oxide levels (mmol/gr Hb) at various times after intoxication with dichlorvos in the three groups. Levels were compared using the Mann Whitney U test.

At one hour post-intoxication, mean erythrocyte MDA levels were similar in all groups. At 12 hours, the mean erythrocyte MDA levels in the melatonin+PAM+atropine group were lower than those of both the sham group and the PAM+atropine group (p=0.001, p=0.012). At 24 hours, the mean erythrocyte MDA levels in the melatonin+PAM+atropine group were significantly lower than those of the PAM+atropine group (p=0.002, Table 3).

Mean brain tissue ACE levels in the melatonin+PAM+atropine group were significantly higher than those of the sham group and PAM+atropine group (p=0.001, p=0.041, Figure 1).

Mean brain tissue NO levels in the melatonin+PAM+atropine group were not significantly different from those of the sham group and PAM+atropine group (p=0.28, p=0.65, Figure 2).

The mean brain tissue MDA levels in the melatonin+PAM+atropine group were significantly lower than those of both the sham group and PAM+atropine group (p=0.001, p=0.002, Figure 3).


Table 3. Mean erythrocyte malondialdehyde levels (nmol/mL) at various times after intoxication with dichlorvos in the three groups. Levels were compared using the Mann Whitney U test.

Fig. 1.

90 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

in the melatonin+PAM+atropine group was significantly higher (p=0.031) than that of the

Treatment group 1 hour 12 hours 24 hours

Pralidoxime + atropine 1.89±0.8 1.79±1.7 1.85±2.0

atropine 2.10±1.2 2.31±1.3 2.95±1.8 p value p>0.05 p<0.01 p<0.05

NO levels in the three groups were not significantly different from each other at 1 hour and 12 hours post-intoxication (p>0.05). The NO levels at 24 hours post-intoxication in the melatonin+PAM+atropine group were not significantly different from that of the

Treatment group 1 hour 12 hours 24 hours

Pralidoxime + atropine 5.10±1.81 6.21±1.68 7.73±2.67 Melatonin+pralidoxime+atropine 5.41±2.10 5.81±1.89 7.05±2.71 p value p>0.05 p>0.05 p>0.05

At one hour post-intoxication, mean erythrocyte MDA levels were similar in all groups. At 12 hours, the mean erythrocyte MDA levels in the melatonin+PAM+atropine group were lower than those of both the sham group and the PAM+atropine group (p=0.001, p=0.012). At 24 hours, the mean erythrocyte MDA levels in the melatonin+PAM+atropine group were significantly lower than those of the PAM+atropine group (p=0.002,

Mean brain tissue ACE levels in the melatonin+PAM+atropine group were significantly higher than those of the sham group and PAM+atropine group (p=0.001, p=0.041,

Mean brain tissue NO levels in the melatonin+PAM+atropine group were not significantly different from those of the sham group and PAM+atropine group (p=0.28, p=0.65, Figure 2). The mean brain tissue MDA levels in the melatonin+PAM+atropine group were significantly lower than those of both the sham group and PAM+atropine group (p=0.001,

Table 2. Mean erythrocyte nitric oxide levels (mmol/gr Hb) at various times after intoxication with dichlorvos in the three groups. Levels were compared using the Mann

Sham 5.36±1.89 5.92±3.65

Table 1. Mean erythrocyte acetylcholine esterase levels (U/L) at various times after intoxication with dichlorvos in the three groups. Levels were compared using the Mann

Sham 1.75±1.0 1.45±1.1

PAM+atropine group (Table 1).

Melatonin+pralidoxime+

PAM+atropine group (p>0.05, Table 2).

Whitney U test.

Whitney U test.

Table 3).

Figure 1).

p=0.002, Figure 3).

The Effects of Melatonin on Brain Injury in Acute Organophosphate Toxicity 93

poisoning in rats, the group given oxime and atropine preserved cognitive functions compared to the atropine only group. The helpful effects of PAM on brain damage in OP intoxication may be partially explained by its peripheral effects which resolve any respiratory problems. Hypoxic brain damage is slight due to the peripheral effects of PAM

We found that in rabbit model of OP poisoning, melatonin added to PAM and atropine had more positive effects on erythrocytes and brain tissue than PAM and atropine alone. For example, erythrocyte ACE activity of the melatonin+PAM+atropine group was higher than the PAM+atropine group, a finding which can be attributed to lower lipid peroxidation in the group receiving melatonin. The activity of ACE localized in erythrocyte membranes is a significant indicator of OP poisoning severity (13). In previous studies (chronic and subchronic exposure) in rats and humans, acute OP poisoning erythrocyte ACE activity was not significantly different than levels in healthy controls (Tinoco & Halperine, 1998; Öğüt et al, 2011). On the contrary, in a rat study of subchronic OP exposure, erythrocyte ACE activity and TBARS levels were found to be significantly lower in the toxicity group compared to healthy controls (Lukaszewicz-Hussain & Moniuszko-Jakoniuk, 2005). In our acute toxicity study, we found that melatonin added to PAM-atropine was beneficial to erythrocyte and

In an in vitro study by Durak D et al, the effect of C and E vitamins in human erythrocytes exposed to OPs on some anti-oxidant enzymes and MDA levels was measured (Durak et al, 2009). In their study, antioxidant enzyme levels in erythrocytes pre-treated with vitamin C

In our study, the addition of melatonin to 'routine' treatments for OP poisoning did not make a significant effect on erythrocyte NO levels compared to PAM+atropine. Casares et al. stated that OPs may spoil cell calcium homeostasis and change NO and NOS production, and thus decrease the effect of additional environmental negative factors. In our study, we did not find any result that supported Casares's hypothesis (Casares & Mantione, 2007). In an in vitro OP toxicity study, levels of antioxidant enzymes like erythrocyte superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GSH-Px) decreased and erythrocyte MDA level increased (Karademir Çatalgöl et al, 2007). Öğüt et al. (Öğüt et al, 2011) reported that MDA levels in erythrocyte samples taken from agriculture workers who were chronically exposed to OP insecticides were significantly higher compared to levels in healthy controls. On the contrary, erythrocyte SOD, CAT and GSH-Px levels were significantly lower than healthy controls. In another in vitro study, in the group in which C and E vitamins were added before OP toxicity occurred, erythrocyte MDA levels were significantly lower compared to the group which was not treated with vitamins C and E. In our study, erythrocyte MDA levels of the sham group were higher than those of other groups. Erythrocyte MDA levels of the melatonin+PAM+atropine group were lower than those of PAM+atropine group. This result is compatible with the results of the previous studies (Puntel et al, 2009). The intense oxidative tissue damage caused by OPs can be decreased with PAM+atropine. Puntel et al., who studied the antioxidant effects of oximes, reported that lipid peroxidation caused by various oxidizing substances was decreased with oximes. In our study, melatonin added to routine treatment decreased lipid peroxidation compared to routine PAM+atropine treatment. Thus, erythrocytes are better protected from

In OP poisonings, the brain is one of the most damaged organs. Sub-acute poisonings are characterized by significant brain edema and corresponding clinic symptoms. Even with a

brain tissue, findings similar to those of Lukaszewicz-Hussein.

and E were higher, and lipid peroxidation was slighter lower.

oxidative stress when melatonin is added to the treatment regimen.

(Shrot et al, 2009).

#### **4. Discussion**

Reactive oxygen species play a key role in initiating secondary brain damage (Özdemir et al, 2005; Tyurin et al, 2000). The brain is prone to oxidative damage which results from high oxygen administration. High concentrations of metals like iron can catalyze reactive radicals, which leads to intense reactive radical production. Neural membranes are also rich in polyunsaturated fatty acids which also contribute to lipid peroxidation reactions (Reiter et al, 2000). Lipid peroxidation changes cell membrane permeability, increases the rate of protein degradation, and ultimately results in the destruction of cell membranes (Tyurin et al, 2000). Non-radical substances containing alkaline and carbonyl moieties produced during the last phases of lipid peroxidation can be measured by their reaction with thiobarbituric acid. Thiobarbituric acid reactive substances (TBARS), of which MDA is the most significant, reflect lipid peroxide production. Increased erythrocyte TBARS concentrations are correlated with severity of cerebral damage (Kasprzak et al, 2001).

Toxicity after an acute intentional or accidental exposure to OP insecticides is largely a reflection of inhibition of ACE in the peripheral and central nervous systems. However, the toxic effects of OPs are not limited to ACE inhibition. In both acute and chronic OP toxictity, changes in antioxidant enzymes occur, and lipid peroxidation increases in many organs, especially the brain. In acute OP poisonings, a decrease in antioxidants occur, which upsets the critical balance between oxidants and antioxidants – thus accumulation of reactive oxygen species and cell destruction begins. In OP toxicity, oxidative stress is an important patho-physiological mechanism, especially for neurotoxicity and cerebral damage (Lukaszewicz-Hussain, 2008).

Atropine and oximes are the fundamental medicines used in the treatment of OP intoxications. Atropine blocks muscarinic receptors in the peripheral and central nervous systems, crosses the blood-brain barrier, and is widely used in OP poisonings. Pralidoxime is the most commonly used oxime in the management of OP poisonings. It reactivates ACE which has been inhibited by OPs (Eddleston et al, 2008). In OP acute poisoning, PAM's penetration into brain tissue may be enhanced by local inflammation. In sublethal OP

Reactive oxygen species play a key role in initiating secondary brain damage (Özdemir et al, 2005; Tyurin et al, 2000). The brain is prone to oxidative damage which results from high oxygen administration. High concentrations of metals like iron can catalyze reactive radicals, which leads to intense reactive radical production. Neural membranes are also rich in polyunsaturated fatty acids which also contribute to lipid peroxidation reactions (Reiter et al, 2000). Lipid peroxidation changes cell membrane permeability, increases the rate of protein degradation, and ultimately results in the destruction of cell membranes (Tyurin et al, 2000). Non-radical substances containing alkaline and carbonyl moieties produced during the last phases of lipid peroxidation can be measured by their reaction with thiobarbituric acid. Thiobarbituric acid reactive substances (TBARS), of which MDA is the most significant, reflect lipid peroxide production. Increased erythrocyte TBARS

concentrations are correlated with severity of cerebral damage (Kasprzak et al, 2001).

Toxicity after an acute intentional or accidental exposure to OP insecticides is largely a reflection of inhibition of ACE in the peripheral and central nervous systems. However, the toxic effects of OPs are not limited to ACE inhibition. In both acute and chronic OP toxictity, changes in antioxidant enzymes occur, and lipid peroxidation increases in many organs, especially the brain. In acute OP poisonings, a decrease in antioxidants occur, which upsets the critical balance between oxidants and antioxidants – thus accumulation of reactive oxygen species and cell destruction begins. In OP toxicity, oxidative stress is an important patho-physiological mechanism, especially for neurotoxicity and cerebral damage

Atropine and oximes are the fundamental medicines used in the treatment of OP intoxications. Atropine blocks muscarinic receptors in the peripheral and central nervous systems, crosses the blood-brain barrier, and is widely used in OP poisonings. Pralidoxime is the most commonly used oxime in the management of OP poisonings. It reactivates ACE which has been inhibited by OPs (Eddleston et al, 2008). In OP acute poisoning, PAM's penetration into brain tissue may be enhanced by local inflammation. In sublethal OP

Fig. 3.

**4. Discussion** 

(Lukaszewicz-Hussain, 2008).

poisoning in rats, the group given oxime and atropine preserved cognitive functions compared to the atropine only group. The helpful effects of PAM on brain damage in OP intoxication may be partially explained by its peripheral effects which resolve any respiratory problems. Hypoxic brain damage is slight due to the peripheral effects of PAM (Shrot et al, 2009).

We found that in rabbit model of OP poisoning, melatonin added to PAM and atropine had more positive effects on erythrocytes and brain tissue than PAM and atropine alone. For example, erythrocyte ACE activity of the melatonin+PAM+atropine group was higher than the PAM+atropine group, a finding which can be attributed to lower lipid peroxidation in the group receiving melatonin. The activity of ACE localized in erythrocyte membranes is a significant indicator of OP poisoning severity (13). In previous studies (chronic and subchronic exposure) in rats and humans, acute OP poisoning erythrocyte ACE activity was not significantly different than levels in healthy controls (Tinoco & Halperine, 1998; Öğüt et al, 2011). On the contrary, in a rat study of subchronic OP exposure, erythrocyte ACE activity and TBARS levels were found to be significantly lower in the toxicity group compared to healthy controls (Lukaszewicz-Hussain & Moniuszko-Jakoniuk, 2005). In our acute toxicity study, we found that melatonin added to PAM-atropine was beneficial to erythrocyte and brain tissue, findings similar to those of Lukaszewicz-Hussein.

In an in vitro study by Durak D et al, the effect of C and E vitamins in human erythrocytes exposed to OPs on some anti-oxidant enzymes and MDA levels was measured (Durak et al, 2009). In their study, antioxidant enzyme levels in erythrocytes pre-treated with vitamin C and E were higher, and lipid peroxidation was slighter lower.

In our study, the addition of melatonin to 'routine' treatments for OP poisoning did not make a significant effect on erythrocyte NO levels compared to PAM+atropine. Casares et al. stated that OPs may spoil cell calcium homeostasis and change NO and NOS production, and thus decrease the effect of additional environmental negative factors. In our study, we did not find any result that supported Casares's hypothesis (Casares & Mantione, 2007).

In an in vitro OP toxicity study, levels of antioxidant enzymes like erythrocyte superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GSH-Px) decreased and erythrocyte MDA level increased (Karademir Çatalgöl et al, 2007). Öğüt et al. (Öğüt et al, 2011) reported that MDA levels in erythrocyte samples taken from agriculture workers who were chronically exposed to OP insecticides were significantly higher compared to levels in healthy controls. On the contrary, erythrocyte SOD, CAT and GSH-Px levels were significantly lower than healthy controls. In another in vitro study, in the group in which C and E vitamins were added before OP toxicity occurred, erythrocyte MDA levels were significantly lower compared to the group which was not treated with vitamins C and E.

In our study, erythrocyte MDA levels of the sham group were higher than those of other groups. Erythrocyte MDA levels of the melatonin+PAM+atropine group were lower than those of PAM+atropine group. This result is compatible with the results of the previous studies (Puntel et al, 2009). The intense oxidative tissue damage caused by OPs can be decreased with PAM+atropine. Puntel et al., who studied the antioxidant effects of oximes, reported that lipid peroxidation caused by various oxidizing substances was decreased with oximes. In our study, melatonin added to routine treatment decreased lipid peroxidation compared to routine PAM+atropine treatment. Thus, erythrocytes are better protected from oxidative stress when melatonin is added to the treatment regimen.

In OP poisonings, the brain is one of the most damaged organs. Sub-acute poisonings are characterized by significant brain edema and corresponding clinic symptoms. Even with a

The Effects of Melatonin on Brain Injury in Acute Organophosphate Toxicity 95

Melatonin added to PAM and atropine in the treatment of acute OP poisoning increases ACE activity in brain tissue, and shows a beneficial effect on brain injury by decreasing lipid

Abdollahi, M., Ranjbar, A., Shadnia, S., Nikfar, S., & Rezaie, A. (2004). Pesticides and

Casares, F., & Mantione, KJ. (2006). Pesticides may be altering constitutive nitric oxide release, thereby compromising health. *Med Sci Monit*; 12:RA235-240, 1234-1010. Chen, Q., Niu, Y., Zhang, R., Guo, H., Gao, Y., Li, Y., & Liu, R. (2010). The toxic influence of

Durak, D., Uzun, FG., Kalender, S., Öğütçü, A., Uzunhisarckl, M., & Kalender, Y. (2009).

Eddleston, M., Buckley, NA., Eyer, P., & Dawson, AH. (2008). Management of acute organophosphorus pesticide poisoning. *Lancet*;371:597-607, 0140-6736. Hsu, C-H., Chi, B-C., & Casida, JE. (2002). Melatonin reduces phosphine-induced lipid and DNA oxidation in vitro and in vivo in rat brain. *J Pineal Res*;32:53-58, 0742-3098. Jyaratnam, J. Acute pesticide poisoning. A major global health problem. (1990). *World Health* 

Karademir Çatalgöl, B., Özden, S., & Alpertunga, B. (2007). Effects of triclorfon on

Kasprzak, HA., Wozniak, A., Drewa, G., & Wozniak, B. (2001). Enhanced lipid peroxidation procesess in patients after brain contusion. *J Neurotrauma*;18:793-797. 0897-7151. Lukaszewicz-Hussain, A., & Moniuszko-Jakoniuk, J. (2005.) A low dose of chlorfenvinphos

Lukaszewicz-Hussain, A. (2008). Subchronic intoxication with chlorfenvinphos, an

Marrs, TC., Maynard, RL., & Sidell Frederic, R. (2007) *Chemical warefare agents toxicology and treatment*. Second Edt. John Wiley & Sons, Chichester, 978047001359. McDonough, JH Jr., Clark, TR., Slone, TW Jr., Zoeffel, D., Brown, K., Kim, S., & Smith, CD,.

Mitra, NK., Siong, HH., & Nadarajah, VD.. (2008). Evaluation of neurotoxicity of repeated

Öğüt, S., Gültekin, F., Kişioğlu, AN., & Küçüköner, E. (2011). Oxidative stress in the blood

liver of the rat. *Pol J Environ Stud*;14:199-202, 1230-1485.

glutathione level. *Food and Chem Tox*;46:82-86, 0278-6915.

malondialdehyde and antioxidant system in human erythrocytes. *Toxicol In* 

affects hepatic enzymes in serum and antioxidant enzymes in erythrocytes and

organophosphate insecticide, affects rat brain antioxidative enzymes and

(1998). Neural lesions in the rat and their relationship to EEG delta activity following seizures induced by the nevre agent soman*. Neurotoxicology*;19:381-391,

dermal application of chlorpyrifos on hippocampus of adult mice. *Ann Agric*

farm workers following intensive pesticide exposure. *Toxicol Ind Health*;

paraquat on hippocampus of mice: involvement of oxidative stres. *Neurotoxicology*;

Malathion-Induced oxidative stress in human erythrocytes and the protective effect

oxidative stress: a review. *Med Sci Monit*;10:RA141-147, 1234-1010.

of vitamins C and E in vitro. *Environ Toxicol*;24:235-242, 1520-4081.

**5. Conclusion** 

**6. References** 

peroxidation and oxidative stress in brain tissue.

31:310-316, 0161-813X.

*Stat Q*; 43:139-144, 0043-8510.

*Vitro;*21:1538-1544, 0887-2333.

*Environ Med*;15:211-216, 1232-1966.

doi:10.1177/0748233711399308, 0748-2337.

0161-813X.

single high dose, heavy axonal degeneration can be seen (Read et al, 2010). Major side effects of OP poisoning are rapid loss of conscious resulting from hyperstimulation in central cholinergic synapses, and inhibition of the respiratory center in the medulla oblongata. In animal models, status epilepticus with profound brain damage occurs after significant OP intoxications. Oximes pass through the blood-brain barrier insubstantially and reactivate ACE enzymes which were previously inactivated by OPs. Although the concentrations of oximes in the brain are low, they are adequate to reactivate ACE enzymes and produce positive clinical responses. However, oximes' positive effects on brain tissue are not only dependent on reactivation of ACE enzymes, because studies to date have not found a significant correlation between ACE enzyme levels reactivated in the brain (Eddleston et al, 2008). On the other hand, studies have found that even a small amount of ACE reactivation can increase the rate of survival (Shrot et al, 2009).

In our study, brain tissue ACE activity of the melatonin+PAM+atropine group was higher than that of PAM+atropine group, which were only slightly higher than that of the sham group. This result suggests that the beneficial effects of melatonin are not only related to PAM's reactivation of inactivated ACE enzyme. Hsu et al. studied the effects of melatonin on antioxidant enzymes and MDA levels in the brain tissue of rats that they exposed to OPs in vivo and in vitro (Hsu et al, 2002). OPs lead to lipid peroxidation and DNA oxidation both in vivo and in vitro mediums. However, in the melatonin-treated groups, GSH-Px activity in the brain was significantly higher than non-treated groups; MDA levels were much lover afer melatonin treatment. Our study results are compatible with theirs. Brain tissue MDA levels of the PAM+atropine group were close to those of the sham group. The MDA levels in the animals receiving melatonin were lower than the other two groups. This result indicates that a significant amount of peroxidation lipid develops in the brain after exposure to OPs. This lipid peroxidation and ensuing damage in brain tissue can be significantly decreased with melatonin.

Rats with untreated subchronic OP toxicity develop very high MDA levels in the hippocampus and low SOD levels (Chen et al, 2010). In another study, ACE activity in the hippocampus decreased after subchronic dermal exposure (Mitra et al, 2008). In chronic and subchronic exposures to OPs, the memory and learning functions of the brain are seriously affected due to damage in this area. Giving melatonin before and after acute OP poisoning in rats prevented an increase in brain tissue MDA levels. Brain tissue NO levels in groups treated with melatonin before and after toxicity were significantly higher than those of controls not given OP. In our study, lipid peroxidation in a particular region of the brain, localized ACE activity, NO levels, and oxidative damage were not researched. However, in our acute OP poisoning model, lipid peroxidation in brain tissue and oxidative damage decreased in general, and ACE activity decreased. In our study, melatonin did not show any beneficial effect on brain tissue NO levels. However, lipid peroxidation in brain tissue of the group in which melatonin was added to treatment and ACE levels were positively influenced. Our results suggest that brain damage may be decreased and memory and learning functions can be preserved with the addition of melatonin to routine OP poisoning treatment. Further studies should be performed to determine melatonin's effect in a variety of clinical processes.

Limitations of this study include its low number of subjects; but the ethics board did not allow us to use more subjects. In addition, histopathological examination of brain tissue samples was not performed.

#### **5. Conclusion**

94 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

single high dose, heavy axonal degeneration can be seen (Read et al, 2010). Major side effects of OP poisoning are rapid loss of conscious resulting from hyperstimulation in central cholinergic synapses, and inhibition of the respiratory center in the medulla oblongata. In animal models, status epilepticus with profound brain damage occurs after significant OP intoxications. Oximes pass through the blood-brain barrier insubstantially and reactivate ACE enzymes which were previously inactivated by OPs. Although the concentrations of oximes in the brain are low, they are adequate to reactivate ACE enzymes and produce positive clinical responses. However, oximes' positive effects on brain tissue are not only dependent on reactivation of ACE enzymes, because studies to date have not found a significant correlation between ACE enzyme levels reactivated in the brain (Eddleston et al, 2008). On the other hand, studies have found that even a small amount of ACE reactivation

In our study, brain tissue ACE activity of the melatonin+PAM+atropine group was higher than that of PAM+atropine group, which were only slightly higher than that of the sham group. This result suggests that the beneficial effects of melatonin are not only related to PAM's reactivation of inactivated ACE enzyme. Hsu et al. studied the effects of melatonin on antioxidant enzymes and MDA levels in the brain tissue of rats that they exposed to OPs in vivo and in vitro (Hsu et al, 2002). OPs lead to lipid peroxidation and DNA oxidation both in vivo and in vitro mediums. However, in the melatonin-treated groups, GSH-Px activity in the brain was significantly higher than non-treated groups; MDA levels were much lover afer melatonin treatment. Our study results are compatible with theirs. Brain tissue MDA levels of the PAM+atropine group were close to those of the sham group. The MDA levels in the animals receiving melatonin were lower than the other two groups. This result indicates that a significant amount of peroxidation lipid develops in the brain after exposure to OPs. This lipid peroxidation and ensuing damage in brain tissue can be

Rats with untreated subchronic OP toxicity develop very high MDA levels in the hippocampus and low SOD levels (Chen et al, 2010). In another study, ACE activity in the hippocampus decreased after subchronic dermal exposure (Mitra et al, 2008). In chronic and subchronic exposures to OPs, the memory and learning functions of the brain are seriously affected due to damage in this area. Giving melatonin before and after acute OP poisoning in rats prevented an increase in brain tissue MDA levels. Brain tissue NO levels in groups treated with melatonin before and after toxicity were significantly higher than those of controls not given OP. In our study, lipid peroxidation in a particular region of the brain, localized ACE activity, NO levels, and oxidative damage were not researched. However, in our acute OP poisoning model, lipid peroxidation in brain tissue and oxidative damage decreased in general, and ACE activity decreased. In our study, melatonin did not show any beneficial effect on brain tissue NO levels. However, lipid peroxidation in brain tissue of the group in which melatonin was added to treatment and ACE levels were positively influenced. Our results suggest that brain damage may be decreased and memory and learning functions can be preserved with the addition of melatonin to routine OP poisoning treatment. Further studies should be performed to determine melatonin's effect in a variety

Limitations of this study include its low number of subjects; but the ethics board did not allow us to use more subjects. In addition, histopathological examination of brain tissue

can increase the rate of survival (Shrot et al, 2009).

significantly decreased with melatonin.

of clinical processes.

samples was not performed.

Melatonin added to PAM and atropine in the treatment of acute OP poisoning increases ACE activity in brain tissue, and shows a beneficial effect on brain injury by decreasing lipid peroxidation and oxidative stress in brain tissue.

#### **6. References**


**6** 

*Poland* 

**Alzheimer's Factors in Ischemic Brain Injury**

Aging nations are growing worldwide and now one in four of us may expect to experience an ischemic brain injury by the age 85. Stroke is the third most common cause of death and the second most common cause of dementia in industrialized societies with a mortality rate of circa 30% and an incidence of about 250–400 in 100,000. Stroke affects circa 700,000 people each year in the US alone, and about 50% of these individuals will experience lasting functional dysfunctions including sensory problems and cognitive deficits (Hillis 2006). It is estimated that ischemic stroke is responsible for approximately half of all patients hospitalized for acute neurological disorders. As outlined earlier, it can cause neurological dysfunctions in a number of neurological functions most commonly in the motor activity, cognitive decline, and dementia. Postischemic dementia is characterized by progressive cognitive deterioration including language, reasoning and memory. Of those individuals suffering from ischemic brain injury less than 50% will return to independent living during the following year. Even among those who regain functional independence, many stroke patients continue to manifest significant deficits, limitations and changes in their cognitive functioning and behavior. As such, stroke is one of the leading causes of disability and experiencing a stroke results in two-fold increase in risk for dementia. Other data showed that 1-in-10 developing dementia soon after first stroke, and over 1-in-3 being demented after recurrent stroke. The brain has limited responses to different kind of neuropathogens. Similar neuropathological features are observed in different cerebrovascular diseases and Alzheimer's disease (Kalaria 2000; Pluta 2004a; Pluta 2004b; De la Torre 2005; Pluta 2006a; Benarroch 2007; Niedermeyer 2007; Pluta 2007c; Bell, Zlokovic 2009). Brain stroke is the leading cause of cognitive impairment worldwide. These data are supported by observations in clinical as well as in experimental studies, which suggest that ischemic brain injury is a major risk factor of dementia ranking only second to age (Gorelick 1997; Pluta 2006a; Pluta 2007c). Dementia, which is observed following different brain ischemic injuries, is associated with intellectual impairment and finally brain atrophy (Hossmann et al., 1987; Loeb et al., 1988; Tatemichi et al., 1990; Pluta 2002b; Kiryk et al., 2011). Amyloid plaques, which are the main pathological hallmarks of Alzheimer's disease, account for about 90% of dementias including ischemic-type dementia (Jendroska et al., 1995; Wisniewski, Maslinska 1996; Shi et al., 1998; Pluta, 2007a; Qi et al., 2007). The relationship between brain ischemic injury dementia and Alzheimer's disease type dementia is recently much debated. The mechanisms of the progressive cognitive decline after ischemic brain injury are not yet clear

**1. Introduction** 

*1Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw* 

Ryszard Pluta1 and Mirosław Jabłoński2

*2Lublin Medical University, Lublin* 


### **Alzheimer's Factors in Ischemic Brain Injury**

Ryszard Pluta1 and Mirosław Jabłoński2

*1Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw 2Lublin Medical University, Lublin Poland* 

#### **1. Introduction**

96 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

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distal axonal damage, but not brain oedema, by inactivating neuropathy target

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antidotal therapy in organophosphate-induced brain damage. *Neurotoxicology*;

cholinesterase via occupational exposure to organophosphate insecticides in

Kochanek, M., Graham, SH., & Kagan, VE. (2000). Oxidative stres following traumatic brain injury in rat: quantitation of biomarkers and detection of free Aging nations are growing worldwide and now one in four of us may expect to experience an ischemic brain injury by the age 85. Stroke is the third most common cause of death and the second most common cause of dementia in industrialized societies with a mortality rate of circa 30% and an incidence of about 250–400 in 100,000. Stroke affects circa 700,000 people each year in the US alone, and about 50% of these individuals will experience lasting functional dysfunctions including sensory problems and cognitive deficits (Hillis 2006). It is estimated that ischemic stroke is responsible for approximately half of all patients hospitalized for acute neurological disorders. As outlined earlier, it can cause neurological dysfunctions in a number of neurological functions most commonly in the motor activity, cognitive decline, and dementia. Postischemic dementia is characterized by progressive cognitive deterioration including language, reasoning and memory. Of those individuals suffering from ischemic brain injury less than 50% will return to independent living during the following year. Even among those who regain functional independence, many stroke patients continue to manifest significant deficits, limitations and changes in their cognitive functioning and behavior. As such, stroke is one of the leading causes of disability and experiencing a stroke results in two-fold increase in risk for dementia. Other data showed that 1-in-10 developing dementia soon after first stroke, and over 1-in-3 being demented after recurrent stroke. The brain has limited responses to different kind of neuropathogens. Similar neuropathological features are observed in different cerebrovascular diseases and Alzheimer's disease (Kalaria 2000; Pluta 2004a; Pluta 2004b; De la Torre 2005; Pluta 2006a; Benarroch 2007; Niedermeyer 2007; Pluta 2007c; Bell, Zlokovic 2009). Brain stroke is the leading cause of cognitive impairment worldwide. These data are supported by observations in clinical as well as in experimental studies, which suggest that ischemic brain injury is a major risk factor of dementia ranking only second to age (Gorelick 1997; Pluta 2006a; Pluta 2007c). Dementia, which is observed following different brain ischemic injuries, is associated with intellectual impairment and finally brain atrophy (Hossmann et al., 1987; Loeb et al., 1988; Tatemichi et al., 1990; Pluta 2002b; Kiryk et al., 2011). Amyloid plaques, which are the main pathological hallmarks of Alzheimer's disease, account for about 90% of dementias including ischemic-type dementia (Jendroska et al., 1995; Wisniewski, Maslinska 1996; Shi et al., 1998; Pluta, 2007a; Qi et al., 2007). The relationship between brain ischemic injury dementia and Alzheimer's disease type dementia is recently much debated. The mechanisms of the progressive cognitive decline after ischemic brain injury are not yet clear

Alzheimer's Factors in Ischemic Brain Injury 99

Pohjasvaara et al., 1998; Tatemichi et al., 1992) and 4-12 times higher than in controls 4 years after a lacunar infarct (Loeb et al., 1992). Different patterns of cognitive decline as effect of ischemia brain injury have been shown by longitudinal epidemiological, studies which have suggested a progressive course of dementia following ischemic stroke. Tatemichi et al., (1990) presented that the incidence of dementia was 6.7% among patients directly after 1 year of survival in a group of 610 subjects who were initially free of dementia following stroke. Bornstein et al., (1996) reported that 32% individuals who were initially free of dementia directly after stroke developed incidental dementia during 5 years of survival following first ischemic episode. Henon et al., (2001) observed a sample of 169 patients who had been free of dementia before stroke and reported that the cumulative proportion of individuals with incidental dementia was 21.3% after 3 years of survival. Altieri et al., (2004) examined 191 free of dementia stroke patients for a 4 years, and noted that the incidence of dementia increasing gradually with 21.5% subjects had developed dementia by the end of the follow-up time. In population-based investigations of stroke and dementia subjects, Kokmen et al., (1996) checked the medical records of 971 patients who were nondemented before first stroke. The incidence of dementia was 7% at 1 y, 10% at 3 y, 15% at 5 y and 23% at 10 y. Desmond et al., (2002) performed functional assessments annually on 334 ischemic brain injury patients and 241 ischemia free control individuals, all of whom were free of dementia in baseline examinations, and noted a progressive course of dementia with the incidence rate of 8.94/100 person/year in the ischemic group and 1.37/100 person/year in the control group. In two studies based on subjects presenting with a lacunar infarction as their first ischemic stroke, Samuelsson et al., (1996) found that 4.9% and 9.9% of 81 patients had dementia after 1 and 3 years of observation, respectively, and Loeb et al., (1992) reported that 23.2% individuals had dementia during an average of 4 years of survival. Removal of the above deficits/abnormalities is a topic to which a neurologist and scientists devotes little time. In different patients, some spontaneous functional restoration is noted during weeks/months after ischemic brain injury. However, in general, this spontaneous recovery is incomplete. Moreover, ischemic brain injury often leaves its victims functionally devastated and as such is the leading cause of permanent disability requiring long-term institutional care in our nations. The loss of life quality years and health care resources are staggering. The situation is even aggravated by the fact that unlike many other neurological diseases, no safe, effective therapy is available for the majority of patients with acute ischemic brain injury. The burden after ischemic brain injury on our societies is dramatically increasing. Thus, an understanding of the underlying progressing pathological processes/cascades is urgently needed. This chapter tends to summarize the neuropathological changes of chronic

postischemic brain injury and reveal the convinced mechanisms.

**2. Amyloid precursor protein and β-amyloid peptide after ischemia** 

After brain ischemia, amyloid precursor protein mRNA had enhanced till 200% in the brain during the seventh day of reperfusion. The above data suggest that local ischemic brain injury increases amyloid precursor protein mRNA level, which may contribute to the progression of cognitive impairment in ischemic brain injury (Abe et al., 1991; Koistinaho et al., 1996; Shi et al., 1998; Shi et al., 2000). Above studies also show that focal ischemic brain injury alters Kunitz protease inhibitor amyloid precursor protein/amyloid precursor protein 695 ratios in brain and this shift in precursor isoforms could be related to degeneration and activation of astrocyte following the ischemic injury (Kim et al., 1998). In permanent local

but animal investigations have demonstrated an increase in expression and processing of amyloid precursor protein to β-amyloid peptide (Pluta et al., 1994b; Pluta et al., 1997b; Pluta et al., 1997c; Pluta et al., 1998b; Lin et al., 1999; Shi et al., 2000; Lin et al., 2001; Badan et al., 2004; Pluta et al., 2009) and an increase in the phosphorylation of tau protein (Dewar, Dawson 1995; Wen et al., 2004b; Wen et al., 2004c, Wen et al., 2007). Moreover, the common mechanism that links progressive cognitive decline after ischemic brain injury and during Alzheimer's disease is neuroinflammation (Koistinaho et al., 2002), which can cause gradual neurodegeneration during prolonged face of injury. However, the link between ischemic brain injury and delayed progressive cognitive decline opens a new area for potential treatment in that the onset of the progressive cognitive decline after ischemia is delayed. The above data raise the question whether Alzheimer's related proteins affect ischemic brain tissue. The details of Alzheimer's protein-related mechanisms, which probably mediate ischemic brain cell damage and neurotoxicity (Mattson et al., 2000; Malm, Koistinaho 2007) and involvement of these proteins in brain accumulation will be reviewed. This chapter summarizes some of the findings, which suggest that ischemic overexpression of amyloid precursor protein renders the brain more vulnerable to ischemic episodes (Koistinaho et al., 2002) and describes the factors that are involved in increased neuronal susceptibility to ischemic injury (Mattson et al., 2000; Malm, Koistinaho 2007).

#### **1.1 Consequences of ischemic brain injury**

Brain ischemic injury is the most common chronic cause of disability around world and has generally a negative influence on the individuals it affects, caregivers and society as a whole (Flynn et al., 2008). Ischemic stroke survivors suffer from chronic progressing neurological disabilities that significantly influence their ability to return to society. A more insidious consequence of brain ischemia is a post-stroke dementia (Jellinger 2007) that is also associated with severe disability. Worldwide brain vascular disorders like ischemia are responsible for 5.4 million deaths every year (Flynn et al., 2008). Circa 3% of total healthcare finances are attributable to brain ischemia. Cost of ischemic stroke to the EU economy is estimated at 21 billion euro and to USA economy at 2.2 trillion dollars (Fillit, Hill 2002, Flynn et al., 2008). The global scale of the problem and the enormous associated costs it is clear that there is an urgent need for advances in the prevention of ischemic brain injury and its consequences like postischemic dementia. Dementia is the worst consequence for survivors following brain ischemia and being responsible for approximately 20% of all confirmed dementias (Fillit, Hill 2002). Globally cerebrovascular diseases dementia varies from 10 to 50% depending on the diagnostic criteria, geographic location and population demographic (Leys et al., 2002). Recently it is becoming clear, that cerebrovascular diseases dementia in fact shares many risk factors in common with Alzheimer's disease. Indeed ischemic brain injuries may precede the onset of this form of dementia strongly suggesting that brain ischemic episodes may trigger neurodegenerative dementias. Postischemic dementia connected with chronic delayed secondary injury occurs in individuals suffering from focal or global brain ischemia in a progressive manner (Jellinger 2007). The chronic postischemic injury including dementia has received far less attention in clinical and experimental stroke investigations. Vascular dementia incorporates cognitive dysfunction with cerebrovascular diseases.

#### **1.2 Epidemiology of postischemic dementia**

Epidemiological studies have shown that the prevalence of dementia in ischemic brain injury patients is nine-fold higher than controls at 3 months (Madureira et al., 2001;

but animal investigations have demonstrated an increase in expression and processing of amyloid precursor protein to β-amyloid peptide (Pluta et al., 1994b; Pluta et al., 1997b; Pluta et al., 1997c; Pluta et al., 1998b; Lin et al., 1999; Shi et al., 2000; Lin et al., 2001; Badan et al., 2004; Pluta et al., 2009) and an increase in the phosphorylation of tau protein (Dewar, Dawson 1995; Wen et al., 2004b; Wen et al., 2004c, Wen et al., 2007). Moreover, the common mechanism that links progressive cognitive decline after ischemic brain injury and during Alzheimer's disease is neuroinflammation (Koistinaho et al., 2002), which can cause gradual neurodegeneration during prolonged face of injury. However, the link between ischemic brain injury and delayed progressive cognitive decline opens a new area for potential treatment in that the onset of the progressive cognitive decline after ischemia is delayed. The above data raise the question whether Alzheimer's related proteins affect ischemic brain tissue. The details of Alzheimer's protein-related mechanisms, which probably mediate ischemic brain cell damage and neurotoxicity (Mattson et al., 2000; Malm, Koistinaho 2007) and involvement of these proteins in brain accumulation will be reviewed. This chapter summarizes some of the findings, which suggest that ischemic overexpression of amyloid precursor protein renders the brain more vulnerable to ischemic episodes (Koistinaho et al., 2002) and describes the factors that are involved in increased neuronal susceptibility to

Brain ischemic injury is the most common chronic cause of disability around world and has generally a negative influence on the individuals it affects, caregivers and society as a whole (Flynn et al., 2008). Ischemic stroke survivors suffer from chronic progressing neurological disabilities that significantly influence their ability to return to society. A more insidious consequence of brain ischemia is a post-stroke dementia (Jellinger 2007) that is also associated with severe disability. Worldwide brain vascular disorders like ischemia are responsible for 5.4 million deaths every year (Flynn et al., 2008). Circa 3% of total healthcare finances are attributable to brain ischemia. Cost of ischemic stroke to the EU economy is estimated at 21 billion euro and to USA economy at 2.2 trillion dollars (Fillit, Hill 2002, Flynn et al., 2008). The global scale of the problem and the enormous associated costs it is clear that there is an urgent need for advances in the prevention of ischemic brain injury and its consequences like postischemic dementia. Dementia is the worst consequence for survivors following brain ischemia and being responsible for approximately 20% of all confirmed dementias (Fillit, Hill 2002). Globally cerebrovascular diseases dementia varies from 10 to 50% depending on the diagnostic criteria, geographic location and population demographic (Leys et al., 2002). Recently it is becoming clear, that cerebrovascular diseases dementia in fact shares many risk factors in common with Alzheimer's disease. Indeed ischemic brain injuries may precede the onset of this form of dementia strongly suggesting that brain ischemic episodes may trigger neurodegenerative dementias. Postischemic dementia connected with chronic delayed secondary injury occurs in individuals suffering from focal or global brain ischemia in a progressive manner (Jellinger 2007). The chronic postischemic injury including dementia has received far less attention in clinical and experimental stroke investigations. Vascular

dementia incorporates cognitive dysfunction with cerebrovascular diseases.

Epidemiological studies have shown that the prevalence of dementia in ischemic brain injury patients is nine-fold higher than controls at 3 months (Madureira et al., 2001;

ischemic injury (Mattson et al., 2000; Malm, Koistinaho 2007).

**1.1 Consequences of ischemic brain injury** 

**1.2 Epidemiology of postischemic dementia** 

Pohjasvaara et al., 1998; Tatemichi et al., 1992) and 4-12 times higher than in controls 4 years after a lacunar infarct (Loeb et al., 1992). Different patterns of cognitive decline as effect of ischemia brain injury have been shown by longitudinal epidemiological, studies which have suggested a progressive course of dementia following ischemic stroke. Tatemichi et al., (1990) presented that the incidence of dementia was 6.7% among patients directly after 1 year of survival in a group of 610 subjects who were initially free of dementia following stroke. Bornstein et al., (1996) reported that 32% individuals who were initially free of dementia directly after stroke developed incidental dementia during 5 years of survival following first ischemic episode. Henon et al., (2001) observed a sample of 169 patients who had been free of dementia before stroke and reported that the cumulative proportion of individuals with incidental dementia was 21.3% after 3 years of survival. Altieri et al., (2004) examined 191 free of dementia stroke patients for a 4 years, and noted that the incidence of dementia increasing gradually with 21.5% subjects had developed dementia by the end of the follow-up time. In population-based investigations of stroke and dementia subjects, Kokmen et al., (1996) checked the medical records of 971 patients who were nondemented before first stroke. The incidence of dementia was 7% at 1 y, 10% at 3 y, 15% at 5 y and 23% at 10 y. Desmond et al., (2002) performed functional assessments annually on 334 ischemic brain injury patients and 241 ischemia free control individuals, all of whom were free of dementia in baseline examinations, and noted a progressive course of dementia with the incidence rate of 8.94/100 person/year in the ischemic group and 1.37/100 person/year in the control group. In two studies based on subjects presenting with a lacunar infarction as their first ischemic stroke, Samuelsson et al., (1996) found that 4.9% and 9.9% of 81 patients had dementia after 1 and 3 years of observation, respectively, and Loeb et al., (1992) reported that 23.2% individuals had dementia during an average of 4 years of survival. Removal of the above deficits/abnormalities is a topic to which a neurologist and scientists devotes little time. In different patients, some spontaneous functional restoration is noted during weeks/months after ischemic brain injury. However, in general, this spontaneous recovery is incomplete. Moreover, ischemic brain injury often leaves its victims functionally devastated and as such is the leading cause of permanent disability requiring long-term

institutional care in our nations. The loss of life quality years and health care resources are staggering. The situation is even aggravated by the fact that unlike many other neurological diseases, no safe, effective therapy is available for the majority of patients with acute ischemic brain injury. The burden after ischemic brain injury on our societies is dramatically increasing. Thus, an understanding of the underlying progressing pathological processes/cascades is urgently needed. This chapter tends to summarize the neuropathological changes of chronic postischemic brain injury and reveal the convinced mechanisms.

#### **2. Amyloid precursor protein and β-amyloid peptide after ischemia**

After brain ischemia, amyloid precursor protein mRNA had enhanced till 200% in the brain during the seventh day of reperfusion. The above data suggest that local ischemic brain injury increases amyloid precursor protein mRNA level, which may contribute to the progression of cognitive impairment in ischemic brain injury (Abe et al., 1991; Koistinaho et al., 1996; Shi et al., 1998; Shi et al., 2000). Above studies also show that focal ischemic brain injury alters Kunitz protease inhibitor amyloid precursor protein/amyloid precursor protein 695 ratios in brain and this shift in precursor isoforms could be related to degeneration and activation of astrocyte following the ischemic injury (Kim et al., 1998). In permanent local

Alzheimer's Factors in Ischemic Brain Injury 101

aforementioned observations indicate that the late neurotoxic β-amyloid peptide and C-terminal of amyloid precursor protein deposition after ischemic brain injury may represent a secondary injury process that could deteriorate the ischemic brain outcome by unexpected additional neurons death (Pluta et al., 1997c, Pluta et al., 1998b). Following ischemia β-amyloid peptide is produced as a result of neurons injury (Ishimaru et al., 1996a) and probably appears its effects, influencing ischemic neurons and glia as dementia. It is generally received that β-amyloid peptide takes part in neurons death (Cotter et al., 1999). The β-amyloid peptide is a toxic protein and entangles within an ischemic process in astrocytes, oligodendrocytes, and microglia that lead neurons and glia finally to death

The amyloid precursor protein is cleaved by α-secretase and it is not pathological pathway in brain. Ischemic brain injury results in the downregulation of α-secretase mRNA and decreases its net activity (Nalivaeva et al., 2004; Yan et al., 2007). In the pathological pathway called amyloidogenic precursor is cleaved by β-secretase and γ-secretase to form β-amyloid peptide. The formation of β-amyloid peptide in the brain after ischemic injury increases and impairs the memory (Yan et al., 2007). Current investigations have shown that brain ischemia stimulates the formation and activity of β-secretase in brain tissue (Wen et al., 2004a; Chuang et al., 2008). Presenilin, which is overexpressed after ischemic brain injury (Tanimukai et al., 1998; Pennypacker et al., 1999), is involved in ischemic β-amyloid peptide

Important brain trigger, which initiates amyloid precursor protein cleavage, is ischemic episode. The main proteolysis is performed by α- or β-secretase that produce large soluble N-terminal parts called respectively soluble N-terminal domain of amyloid precursor protein α (sAPPα) or soluble N-terminal domain of amyloid precursor protein β (sAPPβ). These fragments are release into the extracellular space. Remaining C-terminal domains are bind with membrane and called respectively C-terminal fragment 83 or 99 (CTF83/CTFα or CTF99/CTFβ). The second cleavage occurs in the intramembrane area by γ-secretase, which depending on where the first proteolysis was made and finally releases either the β-amyloid peptide or p3 fragment. This phenomenon seems to be largely nonselective occurring in at least 3 different sites of the amyloid precursor protein like V636, A638 and L645 (ε-cleavage site) (Sastre et al., 2001; Yu et al., 2001). The final products are β-amyloid peptide 40/42 and an intracellular 50 aa C-terminal of amyloid precursor protein domain (5kDa) (Pinnix et al., 2001). Amyloid intracellular domain is very labile and can be further disintegrated by the insulin degrading enzyme or proteasome. Amyloid intracellular domain with specific binding proteins initiating a signal cascade, which subsequently migrates to the cell nucleus to become a component of a transcriptional process but the adaptor protein FE65 rescues the

Tau protein overexpression in neurons was observed in the hippocampus (Geddes et al., 1994) and the brain cortex (Dewar et al., 1993; Dewar et al., 1994) after ischemic brain injury

**3. Amyloid precursor protein secretases after ischemia** 

**4. Amyloid precursor protein intracellular domain after ischemia** 

synthesis by γ-secretase (Polavarapu et al., 2008).

amyloid intracellular domain from rapid proteolysis.

**5. Tau protein after ischemia** 

(Giulian et al., 1995).

brain ischemia injury, amyloid precursor protein mRNA species, which contain a Kunitztype protease inhibitor domain, were expressed in the cortex by day 21 of survival but the net amount of precursor mRNA did not change. This investigation suggests a selective role of amyloid precursor protein species that contain the Kunitz protease inhibitor domain in cascade of focal brain ischemia (Abe et al., 1991). After local ischemia amyloid precursor protein 770 and amyloid precursor protein 751 mRNAs were increased during 7 days in the brain (Koistinaho et al., 1996).

Animals after focal and global ischemic brain injury with a survival time up to 1 year presented increased brain immunoreactivity to the β-amyloid peptide and as well as to the N- and C-terminal of amyloid precursor protein. The staining was observed extracellularly and intracellularly (Pluta et al., 1994b; Hall et al., 1995; Tomimoto et al., 1995; Horsburgh, Nicoll, 1996a; Ishimaru et al., 1996a; Yokota et al., 1996; Pluta et al., 1997b; Pluta et al., 1998b; Lin et al., 1999; Pluta 2000; Lin et al., 2001; Sinigaglia-Coimbra et al., 2002; Fujioka et al., 2003; Yang, Simpkins 2007). Different fragments of amyloid precursor protein were noted in astrocytes, neurons, oligodendrocytes, and microglia (Banati et al., 1995; Palacios et al., 1995; Pluta et al., 1997b; Nihashi et al., 2001; Pluta, 2002a; Pluta2002b; Badan et al., 2003; Badan et al., 2004). Animals with long survival after ischemic brain injury from 0.5 to 1 year showed pathological brain staining only to the β-amyloid peptide and to the C-terminal of amyloid precursor protein (Pluta et al., 1998b; Pluta 2000). The reactive astrocytes with deposition of different fragments of amyloid precursor protein might be involved in the development of glial scar (Nihashi et al., 2001; Pluta 2002a; Pluta 2002b; Badan et al., 2003; Badan et al., 2004). Reactive astrocytic cells with pathological level of β-amyloid peptide deposition might be involved in pathological repair of host tissue after ischemic brain injury including astrocytes death (Pluta et al., 1994b; Pluta 2002b; Wyss-Coray et al., 2003; Takuma et al., 2004).

Pathological amyloid precursor protein staining especially for β-amyloid peptide and C-terminal has been observed in periventricular and subcortical white matter after ischemic brain injury (Pluta et al., 2006, Pluta et al., 2008). The more intense postischemic brain injury of white matter is, the more extensive is the staining of different parts of amyloid precursor protein in this region (Yam et al., 1997). In contrast, in our unpublished studies, the data are opposite. We noted ischemic time-independent intensity of immunostaining, shorter ischemic brain injury stronger reactivity. Probably, this kind of abnormalities is responsible for leukoaraiosis formation after ischemic brain injury (Pluta et al., 2008). Extracellular accumulation of different fragments of amyloid precursor protein ranged from multifocal widespread very small dots to regular amyloid plaques (Pluta et al., 1994b; Pluta et al., 1998b; Pluta 2000; Pluta 2002b; Pluta 2003). Multifocal and widespread different kinds of amyloid plaques were observed mainly in the ischemic hippocampus, brain and entorhinal cortex, and corpus callosum, and subventriculary (Pluta et al., 1994b; Pluta et al., 1997b; Pluta et al., 1998b; Pluta 2000; Pluta 2003; Pluta 2005; Pluta et al., 2006; Pluta et al., 2008; Pluta et al., 2009; Pluta et al., 2010).

The accumulation of the β-amyloid peptide in astrocytes and the C-terminal of amyloid precursor protein in ischemic neurons underline the likely importance of these two proteins in ischemic brain injury cascade of degeneration (Pluta et al., 1994b; Yokota et al., 1996; Pluta 2002b; Badan et al., 2003; Badan et al., 2004). Moreover, the above parts of precursor deposits suggest that these fragments of precursor may initiate synaptic pathology and finally promote retrograde neuronal death after ischemic injury (Oster-Granite et al., 1996). The

brain ischemia injury, amyloid precursor protein mRNA species, which contain a Kunitztype protease inhibitor domain, were expressed in the cortex by day 21 of survival but the net amount of precursor mRNA did not change. This investigation suggests a selective role of amyloid precursor protein species that contain the Kunitz protease inhibitor domain in cascade of focal brain ischemia (Abe et al., 1991). After local ischemia amyloid precursor protein 770 and amyloid precursor protein 751 mRNAs were increased during 7 days in the

Animals after focal and global ischemic brain injury with a survival time up to 1 year presented increased brain immunoreactivity to the β-amyloid peptide and as well as to the N- and C-terminal of amyloid precursor protein. The staining was observed extracellularly and intracellularly (Pluta et al., 1994b; Hall et al., 1995; Tomimoto et al., 1995; Horsburgh, Nicoll, 1996a; Ishimaru et al., 1996a; Yokota et al., 1996; Pluta et al., 1997b; Pluta et al., 1998b; Lin et al., 1999; Pluta 2000; Lin et al., 2001; Sinigaglia-Coimbra et al., 2002; Fujioka et al., 2003; Yang, Simpkins 2007). Different fragments of amyloid precursor protein were noted in astrocytes, neurons, oligodendrocytes, and microglia (Banati et al., 1995; Palacios et al., 1995; Pluta et al., 1997b; Nihashi et al., 2001; Pluta, 2002a; Pluta2002b; Badan et al., 2003; Badan et al., 2004). Animals with long survival after ischemic brain injury from 0.5 to 1 year showed pathological brain staining only to the β-amyloid peptide and to the C-terminal of amyloid precursor protein (Pluta et al., 1998b; Pluta 2000). The reactive astrocytes with deposition of different fragments of amyloid precursor protein might be involved in the development of glial scar (Nihashi et al., 2001; Pluta 2002a; Pluta 2002b; Badan et al., 2003; Badan et al., 2004). Reactive astrocytic cells with pathological level of β-amyloid peptide deposition might be involved in pathological repair of host tissue after ischemic brain injury including astrocytes death (Pluta et al., 1994b; Pluta 2002b; Wyss-

Pathological amyloid precursor protein staining especially for β-amyloid peptide and C-terminal has been observed in periventricular and subcortical white matter after ischemic brain injury (Pluta et al., 2006, Pluta et al., 2008). The more intense postischemic brain injury of white matter is, the more extensive is the staining of different parts of amyloid precursor protein in this region (Yam et al., 1997). In contrast, in our unpublished studies, the data are opposite. We noted ischemic time-independent intensity of immunostaining, shorter ischemic brain injury stronger reactivity. Probably, this kind of abnormalities is responsible for leukoaraiosis formation after ischemic brain injury (Pluta et al., 2008). Extracellular accumulation of different fragments of amyloid precursor protein ranged from multifocal widespread very small dots to regular amyloid plaques (Pluta et al., 1994b; Pluta et al., 1998b; Pluta 2000; Pluta 2002b; Pluta 2003). Multifocal and widespread different kinds of amyloid plaques were observed mainly in the ischemic hippocampus, brain and entorhinal cortex, and corpus callosum, and subventriculary (Pluta et al., 1994b; Pluta et al., 1997b; Pluta et al., 1998b; Pluta 2000; Pluta 2003; Pluta 2005; Pluta et al., 2006; Pluta et al., 2008;

The accumulation of the β-amyloid peptide in astrocytes and the C-terminal of amyloid precursor protein in ischemic neurons underline the likely importance of these two proteins in ischemic brain injury cascade of degeneration (Pluta et al., 1994b; Yokota et al., 1996; Pluta 2002b; Badan et al., 2003; Badan et al., 2004). Moreover, the above parts of precursor deposits suggest that these fragments of precursor may initiate synaptic pathology and finally promote retrograde neuronal death after ischemic injury (Oster-Granite et al., 1996). The

brain (Koistinaho et al., 1996).

Coray et al., 2003; Takuma et al., 2004).

Pluta et al., 2009; Pluta et al., 2010).

aforementioned observations indicate that the late neurotoxic β-amyloid peptide and C-terminal of amyloid precursor protein deposition after ischemic brain injury may represent a secondary injury process that could deteriorate the ischemic brain outcome by unexpected additional neurons death (Pluta et al., 1997c, Pluta et al., 1998b). Following ischemia β-amyloid peptide is produced as a result of neurons injury (Ishimaru et al., 1996a) and probably appears its effects, influencing ischemic neurons and glia as dementia. It is generally received that β-amyloid peptide takes part in neurons death (Cotter et al., 1999). The β-amyloid peptide is a toxic protein and entangles within an ischemic process in astrocytes, oligodendrocytes, and microglia that lead neurons and glia finally to death (Giulian et al., 1995).

#### **3. Amyloid precursor protein secretases after ischemia**

The amyloid precursor protein is cleaved by α-secretase and it is not pathological pathway in brain. Ischemic brain injury results in the downregulation of α-secretase mRNA and decreases its net activity (Nalivaeva et al., 2004; Yan et al., 2007). In the pathological pathway called amyloidogenic precursor is cleaved by β-secretase and γ-secretase to form β-amyloid peptide. The formation of β-amyloid peptide in the brain after ischemic injury increases and impairs the memory (Yan et al., 2007). Current investigations have shown that brain ischemia stimulates the formation and activity of β-secretase in brain tissue (Wen et al., 2004a; Chuang et al., 2008). Presenilin, which is overexpressed after ischemic brain injury (Tanimukai et al., 1998; Pennypacker et al., 1999), is involved in ischemic β-amyloid peptide synthesis by γ-secretase (Polavarapu et al., 2008).

#### **4. Amyloid precursor protein intracellular domain after ischemia**

Important brain trigger, which initiates amyloid precursor protein cleavage, is ischemic episode. The main proteolysis is performed by α- or β-secretase that produce large soluble N-terminal parts called respectively soluble N-terminal domain of amyloid precursor protein α (sAPPα) or soluble N-terminal domain of amyloid precursor protein β (sAPPβ). These fragments are release into the extracellular space. Remaining C-terminal domains are bind with membrane and called respectively C-terminal fragment 83 or 99 (CTF83/CTFα or CTF99/CTFβ). The second cleavage occurs in the intramembrane area by γ-secretase, which depending on where the first proteolysis was made and finally releases either the β-amyloid peptide or p3 fragment. This phenomenon seems to be largely nonselective occurring in at least 3 different sites of the amyloid precursor protein like V636, A638 and L645 (ε-cleavage site) (Sastre et al., 2001; Yu et al., 2001). The final products are β-amyloid peptide 40/42 and an intracellular 50 aa C-terminal of amyloid precursor protein domain (5kDa) (Pinnix et al., 2001). Amyloid intracellular domain is very labile and can be further disintegrated by the insulin degrading enzyme or proteasome. Amyloid intracellular domain with specific binding proteins initiating a signal cascade, which subsequently migrates to the cell nucleus to become a component of a transcriptional process but the adaptor protein FE65 rescues the amyloid intracellular domain from rapid proteolysis.

#### **5. Tau protein after ischemia**

Tau protein overexpression in neurons was observed in the hippocampus (Geddes et al., 1994) and the brain cortex (Dewar et al., 1993; Dewar et al., 1994) after ischemic brain injury

Alzheimer's Factors in Ischemic Brain Injury 103

contribute to amyloidogenesis following brain ischemia (Ali et al., 1996). Apolipoprotein E mRNA overexpression in glia but not in neurons was noted in ischemic penumbra with a peak on 21st day. In ischemic core apolipoprotein E mRNA overexpression was observed in macrophages (Kamada et al., 2003). Overexpression of clusterin mRNA was shown in the penumbra in permanent focal brain ischemia. In these studies, reactive astrocytes in the cortex were stained abnormally for apolipoprotein J. It was suggested that local expression of clusterin mRNA might contribute to the neuroinflammation, which representing a main factor in secondary injury processes after focal ischemic brain episodes (Van Beek et al., 2000). After moderate ischemic brain injury a time-dependent deposition of clusterin was noted in pyramidal neurons of the CA1 and the CA2 sector in the hippocampus undergoing delayed neuronal death. Overexpression of apolipoprotein J mRNA in contrast to neuronal protein staining appeared to be glial in origin with increases in mRNA the hippocampus fissure and only a very weak signal over the CA1 and the CA2 pyramidal neuron layer. The above results support the idea that clusterin is synthesized in the astrocytes, secreted outside and next taken up by dying neurons (Nishio et al., 2003). Clusterin deposition was observed in neurons destined to die by apoptosis. Moreover, pathological overexpression of clusterin suggests that the synthesis of this protein was a result of selective delayed neuronal death rather than

involvement in the pathological cascade of events that cause it (Walton et al., 1996).

ischemic neurons indirectly influences development of ischemic-type dementia.

Brain ischemia provoked changes in a presynaptic protein α-synuclein in the ischemic hippocampus (Ishimaru et al., 1998; Kitamura et al., 2001). Intense α-synuclein

**8. -synuclein after ischemia** 

The pathological immunostaining for apolipoproteins A1, E, and J was shown extracellularly and intracellularly (Hall et al., 1995; Kida et al., 1995; Pluta et al., 1995a; Horsburgh, Nicoll 1996a, Horsburgh, Nicoll 1996b; Ishimaru et al., 1996b; Pluta 2000; Kamada et al., 2003). Intracellular staining was noted in damaged neurons exhibiting features of ischemic injury (Pluta 2000). Less often immunostaining for above proteins was observed in glia (Kamada et al., 2003). Extracellular accumulations of apolipoproteins were irregular and well delineated and mainly diffuse. Strong staining was noted also in acellular, necrotic, irregular and spiderlike foci (Kida et al., 1995; Pluta et al., 1995a; Ishimaru et al., 1996a). It is important to notice that accumulations of apolipoproteins colocalize with aggregates of different parts of amyloid precursor protein (Kida et al., 1995; Pluta et al., 1995b). Apolipoprotein E promotes the deposition of β-amyloid peptide into the oligomeric and the fibrillar form. Clusterin is engaged in transport of β-amyloid peptide through the blood-brain barrier. The main activity of apolipoproteins A1, E and J is controlling the level of soluble β-amyloid peptide in the intracellular and the extracellular space of brain tissue as well as their influence on fibrillar β-amyloid peptide conversion. Apolipoprotein E induces β-amyloid peptide increased lysosomal leakage and finally apoptosis in neuronal cells (Ji et al., 2002). Apolipoproteins A1, E, and J influence the deposition, structure and neurotoxicity of the β-amyloid peptide in brain ischemia. Additionally, in β-amyloid peptide production apolipoproteins E and J are involved prior to its accumulation. The above studies show principal roles of apolipoproteins E and J in β-amyloid peptide accumulation and that they play an important role in it extracellular β-amyloid peptide metabolism independent of β-amyloid peptide synthesis. These observations indicate that apolipoproteins A1, E and J deposition following ischemic brain injury may be a secondary damaging phenomenon, which could deteriorate healing of

(Sinigaglia-Coimbra et al., 2002). Moreover, an increase of tau immunostaining was noted in glia and oligodendrocytes following local brain ischemia (Dewar, Dawson 1995; Irving et al., 1997). Additionally pathological tau protein was found in microglia around the ischemic core (Uchihara et al., 2004). The above data indicate that only some neurons display pathologically changed tau protein following ischemic brain injury (Dewar, Dawson 1995), which may reflect an early alterations state of the degenerative processes in these cells (Irving et al., 1997). Another study noted a complete dephosphorylation of tau protein after ischemic brain injury (Mailliot et al., 2000). The dephosphorylation of tau protein may influence its transportation between axon and cell body and affects its susceptibility to proteolysis (Shackelford, Yeh 1998). Some other study noted that tau protein itself blocks transport of amyloid precursor protein from the neuron body into axon and dendrites causing amyloid precursor accumulation in the neuron body (Stamer et al., 2002). The recent studies show that after ischemic brain injury, hyperphosphorylated tau protein accumulates in cortical neurons and colocalizes with signs of apoptosis. This process may be important element in the etiology in ischemic brain degeneration. The above observations indicate that neuron ischemic apoptosis is connected with tau protein hyperphosphorylation (Wen et al., 2004b; Wen et al., 2007). Wen et al. (2004c, 2007) noted that reversible brain ischemia is associated with neurofibrillary tangle-like tauopathy formation in the brain. These data provide groundwork for the cause of dementia after ischemic brain injury (Wen et al., 2004c).

#### **6. Presenilins after ischemia**

Ischemic brain injury overexpression of presenilin 1 gene in neurons of the CA3 sector and dentate gyrus was noted (Tanimukai et al., 1998). In above study, increased expression of presenilin 1 mRNA was the highest at day 3 of reperfusion in affected regions. The above data suggest that the overexpression of presenilin 1 mRNA may be associated with some responses of neurons injured by ischemic pathology. In another study, the increased expression of presenilin mRNA was found in the hippocampus, striatum, cortex, and cerebellum following local ischemic brain injury (Pennypacker et al., 1999). Generally presenilin mRNA exhibited the highest expression in the hippocampus and brain cortex. The expressions were higher on the contralateral side to the local ischemic brain injury. This difference may reflect a loss in brain cells e.g. neurons expressing presenilin genes on the ipsilateral side. Staining of presenilin was more expressed in glia than in neurons and in a trace of the pyramidal neurons of hippocampus after ischemic brain injury (Pluta 2001). Presenilin 1 increases neuron vulnerability to ischemia by increasing intracellular calcium (Mattson et al., 2000; Pluta et al., 2009). A current investigation presented that presenilin 1 and intracellular calcium regulates neuron glutamate uptake (Yang et al., 2004). Taken together, above data indicate that presenilins and intracellular calcium may play an important role in regulating glutamate uptake, and therefore they may influence glutamate toxicity in the ischemic brain injury.

#### **7. Apolipoproteins after ischemia**

Astrocytic apolipoprotein E mRNA overexpression with the highest level at day 7 after ischemic brain injury was found, which suggests that ischemic neuron injury results in the induction of certain genes in the brain within reactive astrocytes and this induction may

(Sinigaglia-Coimbra et al., 2002). Moreover, an increase of tau immunostaining was noted in glia and oligodendrocytes following local brain ischemia (Dewar, Dawson 1995; Irving et al., 1997). Additionally pathological tau protein was found in microglia around the ischemic core (Uchihara et al., 2004). The above data indicate that only some neurons display pathologically changed tau protein following ischemic brain injury (Dewar, Dawson 1995), which may reflect an early alterations state of the degenerative processes in these cells (Irving et al., 1997). Another study noted a complete dephosphorylation of tau protein after ischemic brain injury (Mailliot et al., 2000). The dephosphorylation of tau protein may influence its transportation between axon and cell body and affects its susceptibility to proteolysis (Shackelford, Yeh 1998). Some other study noted that tau protein itself blocks transport of amyloid precursor protein from the neuron body into axon and dendrites causing amyloid precursor accumulation in the neuron body (Stamer et al., 2002). The recent studies show that after ischemic brain injury, hyperphosphorylated tau protein accumulates in cortical neurons and colocalizes with signs of apoptosis. This process may be important element in the etiology in ischemic brain degeneration. The above observations indicate that neuron ischemic apoptosis is connected with tau protein hyperphosphorylation (Wen et al., 2004b; Wen et al., 2007). Wen et al. (2004c, 2007) noted that reversible brain ischemia is associated with neurofibrillary tangle-like tauopathy formation in the brain. These data provide groundwork for the cause of dementia after ischemic brain injury (Wen et al.,

Ischemic brain injury overexpression of presenilin 1 gene in neurons of the CA3 sector and dentate gyrus was noted (Tanimukai et al., 1998). In above study, increased expression of presenilin 1 mRNA was the highest at day 3 of reperfusion in affected regions. The above data suggest that the overexpression of presenilin 1 mRNA may be associated with some responses of neurons injured by ischemic pathology. In another study, the increased expression of presenilin mRNA was found in the hippocampus, striatum, cortex, and cerebellum following local ischemic brain injury (Pennypacker et al., 1999). Generally presenilin mRNA exhibited the highest expression in the hippocampus and brain cortex. The expressions were higher on the contralateral side to the local ischemic brain injury. This difference may reflect a loss in brain cells e.g. neurons expressing presenilin genes on the ipsilateral side. Staining of presenilin was more expressed in glia than in neurons and in a trace of the pyramidal neurons of hippocampus after ischemic brain injury (Pluta 2001). Presenilin 1 increases neuron vulnerability to ischemia by increasing intracellular calcium (Mattson et al., 2000; Pluta et al., 2009). A current investigation presented that presenilin 1 and intracellular calcium regulates neuron glutamate uptake (Yang et al., 2004). Taken together, above data indicate that presenilins and intracellular calcium may play an important role in regulating glutamate uptake, and therefore they may influence glutamate

Astrocytic apolipoprotein E mRNA overexpression with the highest level at day 7 after ischemic brain injury was found, which suggests that ischemic neuron injury results in the induction of certain genes in the brain within reactive astrocytes and this induction may

2004c).

**6. Presenilins after ischemia** 

toxicity in the ischemic brain injury.

**7. Apolipoproteins after ischemia** 

contribute to amyloidogenesis following brain ischemia (Ali et al., 1996). Apolipoprotein E mRNA overexpression in glia but not in neurons was noted in ischemic penumbra with a peak on 21st day. In ischemic core apolipoprotein E mRNA overexpression was observed in macrophages (Kamada et al., 2003). Overexpression of clusterin mRNA was shown in the penumbra in permanent focal brain ischemia. In these studies, reactive astrocytes in the cortex were stained abnormally for apolipoprotein J. It was suggested that local expression of clusterin mRNA might contribute to the neuroinflammation, which representing a main factor in secondary injury processes after focal ischemic brain episodes (Van Beek et al., 2000). After moderate ischemic brain injury a time-dependent deposition of clusterin was noted in pyramidal neurons of the CA1 and the CA2 sector in the hippocampus undergoing delayed neuronal death. Overexpression of apolipoprotein J mRNA in contrast to neuronal protein staining appeared to be glial in origin with increases in mRNA the hippocampus fissure and only a very weak signal over the CA1 and the CA2 pyramidal neuron layer. The above results support the idea that clusterin is synthesized in the astrocytes, secreted outside and next taken up by dying neurons (Nishio et al., 2003). Clusterin deposition was observed in neurons destined to die by apoptosis. Moreover, pathological overexpression of clusterin suggests that the synthesis of this protein was a result of selective delayed neuronal death rather than involvement in the pathological cascade of events that cause it (Walton et al., 1996).

The pathological immunostaining for apolipoproteins A1, E, and J was shown extracellularly and intracellularly (Hall et al., 1995; Kida et al., 1995; Pluta et al., 1995a; Horsburgh, Nicoll 1996a, Horsburgh, Nicoll 1996b; Ishimaru et al., 1996b; Pluta 2000; Kamada et al., 2003). Intracellular staining was noted in damaged neurons exhibiting features of ischemic injury (Pluta 2000). Less often immunostaining for above proteins was observed in glia (Kamada et al., 2003). Extracellular accumulations of apolipoproteins were irregular and well delineated and mainly diffuse. Strong staining was noted also in acellular, necrotic, irregular and spiderlike foci (Kida et al., 1995; Pluta et al., 1995a; Ishimaru et al., 1996a). It is important to notice that accumulations of apolipoproteins colocalize with aggregates of different parts of amyloid precursor protein (Kida et al., 1995; Pluta et al., 1995b). Apolipoprotein E promotes the deposition of β-amyloid peptide into the oligomeric and the fibrillar form. Clusterin is engaged in transport of β-amyloid peptide through the blood-brain barrier. The main activity of apolipoproteins A1, E and J is controlling the level of soluble β-amyloid peptide in the intracellular and the extracellular space of brain tissue as well as their influence on fibrillar β-amyloid peptide conversion. Apolipoprotein E induces β-amyloid peptide increased lysosomal leakage and finally apoptosis in neuronal cells (Ji et al., 2002). Apolipoproteins A1, E, and J influence the deposition, structure and neurotoxicity of the β-amyloid peptide in brain ischemia. Additionally, in β-amyloid peptide production apolipoproteins E and J are involved prior to its accumulation. The above studies show principal roles of apolipoproteins E and J in β-amyloid peptide accumulation and that they play an important role in it extracellular β-amyloid peptide metabolism independent of β-amyloid peptide synthesis. These observations indicate that apolipoproteins A1, E and J deposition following ischemic brain injury may be a secondary damaging phenomenon, which could deteriorate healing of ischemic neurons indirectly influences development of ischemic-type dementia.

#### **8. -synuclein after ischemia**

Brain ischemia provoked changes in a presynaptic protein α-synuclein in the ischemic hippocampus (Ishimaru et al., 1998; Kitamura et al., 2001). Intense α-synuclein

Alzheimer's Factors in Ischemic Brain Injury 105

ischemic injury is the hippocampus. First, the hippocampus is the part of brain, which displays the same pathology as human ischemic brain. Second, the hippocampus is implicated in spatial learning and memory. Third, the hippocampus, especially its area CA1 is one of the brain sectors very sensitive to ischemic injury like in humans. Finally, the distinct laminar organization of the hippocampus and its final mapped synaptic connections allow exact layer-type or cell-type investigations. With respect to the above observations and metabolism, cerebral blood flow and pathology few models of brain ischemia, which mimicked human condition have been presented (Kirino 1982; Pulsinelli et al., 1982; Smith et al., 1984; Pluta et al., 1991). In these models selective ischemic pyramidal neurons death was noted in the CA1 sector of the hippocampus (Kirino 1982; Pulsinelli et al., 1982; Pluta 2000; Pluta 2002b). Loss of neurons develops during 7 days after ischemia and is called delayed neuronal death (Kirino 1982). Three min of ischemic brain injury in gerbils and 10 min in rats are sufficient to start this characteristic hippocampal pathology (Kirino 1982; Pulsinelli et al., 1982; Pluta 2000; Pluta 2002b). Prolongation of ischemic brain injury in rats to 10-20 min results in complete neurons death in the CA1 sector of the hippocampus and neuronal injury in the brain cortex and striatum (Pulsinelli et al., 1982; Kiryk et al., 2011). Prolongation of recirculation time ends in neuronal alterations in hippocampal regions of nonselective vulnerability (Pluta et al., 2009). Striatal pathology is mainly noted in the dorsolateral area and influence medium-sized neurons (Pluta 2002b). In the brain cortex, the layers 3, 5 and 6 presented neuronal changes (Pulsinelli et al., 1982; Pluta 2000; Pluta 2002b). Within these regions of selective neurons pathology strong activation of astrocytes and microglia were showed (Petito et al., 1990; Schmidt-Kastner et al., 1990; Gehrmann et al., 1992; Morioka et al., 1992; Orzyłowska et al., 1999; Pluta 2000; Pluta 2002b). In brain areas with neuronal disappearance and neuronal cobweb interruption brain ischemic atrophy finally develops (Hossmann et al., 1987; Pluta 2002b; Pluta 2004b; Pluta, Ulamek 2006) with

Ischemic brain injury is associated with both acute and chronic neuroinflammatory reactions, involving activation, hypertrophy and proliferation of astrocytes and microglia. Ischemically activated astrocytes in the CA1 area of the hippocampus overexpress cytokines (Orzylowska et al., 1999). These data show that upregulation of neuroinflammatory mediators by astrocytes are directly connected with selective vulnerability of neuronal cells in ischemic brain injury (Orzylowska et al., 1999; Touzani et al., 2002). The above data suggest that neurons in vulnerable sectors in ischemic brain are targets of astrocytes interleukin-1β. This idea is supported by overexpression of neuronal interleukin-1 receptor (Touzani et al., 2002). In addition, it was confirmed that interleukin-1β is the important factor in brain ischemia cells damage and edema formation (Yamasaki et al., 1995). Chronic synthesis by ischemic brain neuroinflammatory factors may start a self-sufficient cycle that shifts ischemic pathology into hallmarks typical for Alzheimer's disease. In ischemic brain interleukin-1 is a key factor, which motivates neurons to pathological cleavage of amyloid precursor (Griffin et al., 1998) and emits inflammatory mediators. All these events result in neuronal abnormal function and finally their death. Neuronal loss arises from neuroinflammatory factors, which induce neuronal damages that trigger microglia activity with further self-propagation of the neuroinflammatory events. Additionally, evidence has been showed that β-amyloid promotes the release of neuroinflammatory pathogens by microglia (Giulian et al., 1995). In the

all neurodegenerative consequences.

**11. Neuroinflammation after ischemia** 

immunostaining was found in the perivascular neighborhood of the CA1 sector in experiments with long-term survival following ischemic brain injury (Kitamura et al., 2001). In degenerating regions after brain ischemia glia presented intense reactivity for α-synuclein (Ishimaru et al., 1998). The above results suggest that α-synuclein may be essential protein in the neuropathological ischemic cascade (Goedert 2001). Abnormal α-synuclein accumulation might disrupt synaptic function, resulting in cognitive deficits (Hashimoto, Masliah 1999). The pathology of α-synuclein disturbs the synaptic activity that finally causes retrograde neurons loss in the ischemic brain injury (Goedert 2001).

#### **9. Platelets after ischemia**

Pluta et al., (1994c) for the first time directly presented the involvement of platelets in pathological processes after ischemic brain injury. They documented a key role of platelets during repeated vessels occlusion following ischemic brain injury (Pluta et al., 2009). These authors observed augmented thrombocytes aggregations and adhesiveness to vessel endothelium, which very well correlated with ischemic brain disease progression. Other study presented increased platelet microparticles and membrane remnants during reperfusion after ischemic brain damage (Mossakowski et al., 1993; Horstman et al., 2009). Next some study reported circulating platelets complexes and platelets-leukocytes aggregates in systemic circulation following brain ischemia injury (Ritter et al., 2005). Thus chronic abnormal platelets activity following brain ischemia injury now is established as an important pathological phenomenon. It may be suggested that platelets activity after ischemic insult is directly connected with development of general inflammation reply. However, the founding of platelets outside brain vessels after ischemic brain injury (Pluta et al., 1994c; Pluta 2003; Pluta 2006b; Pluta 2007a; Pluta 2007b) comes to evidence of platelets involvement in complex processes of neuroinflammtion and neurodegeneration. Different elements of coagulation system have been noted in brain ischemia episodes including collagen in perivascular space (Pluta et al., 1994c). Above findings, together with other direct evidences suggest that platelets interaction with white blood cells and next with the blood-brain barrier vessels is responsible for leukocyte passage through ischemic bloodbrain barrier. Platelets are capable of directly activating lymphocytes and are responsible for synthesis of immunoglobulins (Cognasse et al., 2007). In addition it is suggested involvement of platelet-activating factor in disruption endothelial tight junctions what means opening of the blood-brain barrier (Callea et al., 1999; Brkovic, Sirois 2007; Adamson et al., 2008; Knezevic et al., 2009). We feel that above observations are important in understanding the etiology of ischemic brain neurodegeneration with dementia and Alzheimer's disease etiology.

#### **10. Neuropathology after ischemia**

Most of the experiments with reference to ischemic brain injury were conducted on small rodents. The reproduction of overlapping pathological mechanisms in small rodent models is a suitable approach to unravel of causal relationships. Studies were conducted to support the hypothesis that the anatomy of the brain vasculature in small rodents is not different from that of humans. The preference to perform brain ischemia studies on rodents are also supported by pragmatic reasons including a high homogeneity due to inbreeding, accessibility and lower costs. For several reasons, the favored brain region for the study of

immunostaining was found in the perivascular neighborhood of the CA1 sector in experiments with long-term survival following ischemic brain injury (Kitamura et al., 2001). In degenerating regions after brain ischemia glia presented intense reactivity for α-synuclein (Ishimaru et al., 1998). The above results suggest that α-synuclein may be essential protein in the neuropathological ischemic cascade (Goedert 2001). Abnormal α-synuclein accumulation might disrupt synaptic function, resulting in cognitive deficits (Hashimoto, Masliah 1999). The pathology of α-synuclein disturbs the synaptic activity that finally causes

Pluta et al., (1994c) for the first time directly presented the involvement of platelets in pathological processes after ischemic brain injury. They documented a key role of platelets during repeated vessels occlusion following ischemic brain injury (Pluta et al., 2009). These authors observed augmented thrombocytes aggregations and adhesiveness to vessel endothelium, which very well correlated with ischemic brain disease progression. Other study presented increased platelet microparticles and membrane remnants during reperfusion after ischemic brain damage (Mossakowski et al., 1993; Horstman et al., 2009). Next some study reported circulating platelets complexes and platelets-leukocytes aggregates in systemic circulation following brain ischemia injury (Ritter et al., 2005). Thus chronic abnormal platelets activity following brain ischemia injury now is established as an important pathological phenomenon. It may be suggested that platelets activity after ischemic insult is directly connected with development of general inflammation reply. However, the founding of platelets outside brain vessels after ischemic brain injury (Pluta et al., 1994c; Pluta 2003; Pluta 2006b; Pluta 2007a; Pluta 2007b) comes to evidence of platelets involvement in complex processes of neuroinflammtion and neurodegeneration. Different elements of coagulation system have been noted in brain ischemia episodes including collagen in perivascular space (Pluta et al., 1994c). Above findings, together with other direct evidences suggest that platelets interaction with white blood cells and next with the blood-brain barrier vessels is responsible for leukocyte passage through ischemic bloodbrain barrier. Platelets are capable of directly activating lymphocytes and are responsible for synthesis of immunoglobulins (Cognasse et al., 2007). In addition it is suggested involvement of platelet-activating factor in disruption endothelial tight junctions what means opening of the blood-brain barrier (Callea et al., 1999; Brkovic, Sirois 2007; Adamson et al., 2008; Knezevic et al., 2009). We feel that above observations are important in understanding the etiology of ischemic brain neurodegeneration with dementia and

Most of the experiments with reference to ischemic brain injury were conducted on small rodents. The reproduction of overlapping pathological mechanisms in small rodent models is a suitable approach to unravel of causal relationships. Studies were conducted to support the hypothesis that the anatomy of the brain vasculature in small rodents is not different from that of humans. The preference to perform brain ischemia studies on rodents are also supported by pragmatic reasons including a high homogeneity due to inbreeding, accessibility and lower costs. For several reasons, the favored brain region for the study of

retrograde neurons loss in the ischemic brain injury (Goedert 2001).

**9. Platelets after ischemia** 

Alzheimer's disease etiology.

**10. Neuropathology after ischemia** 

ischemic injury is the hippocampus. First, the hippocampus is the part of brain, which displays the same pathology as human ischemic brain. Second, the hippocampus is implicated in spatial learning and memory. Third, the hippocampus, especially its area CA1 is one of the brain sectors very sensitive to ischemic injury like in humans. Finally, the distinct laminar organization of the hippocampus and its final mapped synaptic connections allow exact layer-type or cell-type investigations. With respect to the above observations and metabolism, cerebral blood flow and pathology few models of brain ischemia, which mimicked human condition have been presented (Kirino 1982; Pulsinelli et al., 1982; Smith et al., 1984; Pluta et al., 1991). In these models selective ischemic pyramidal neurons death was noted in the CA1 sector of the hippocampus (Kirino 1982; Pulsinelli et al., 1982; Pluta 2000; Pluta 2002b). Loss of neurons develops during 7 days after ischemia and is called delayed neuronal death (Kirino 1982). Three min of ischemic brain injury in gerbils and 10 min in rats are sufficient to start this characteristic hippocampal pathology (Kirino 1982; Pulsinelli et al., 1982; Pluta 2000; Pluta 2002b). Prolongation of ischemic brain injury in rats to 10-20 min results in complete neurons death in the CA1 sector of the hippocampus and neuronal injury in the brain cortex and striatum (Pulsinelli et al., 1982; Kiryk et al., 2011). Prolongation of recirculation time ends in neuronal alterations in hippocampal regions of nonselective vulnerability (Pluta et al., 2009). Striatal pathology is mainly noted in the dorsolateral area and influence medium-sized neurons (Pluta 2002b). In the brain cortex, the layers 3, 5 and 6 presented neuronal changes (Pulsinelli et al., 1982; Pluta 2000; Pluta 2002b). Within these regions of selective neurons pathology strong activation of astrocytes and microglia were showed (Petito et al., 1990; Schmidt-Kastner et al., 1990; Gehrmann et al., 1992; Morioka et al., 1992; Orzyłowska et al., 1999; Pluta 2000; Pluta 2002b). In brain areas with neuronal disappearance and neuronal cobweb interruption brain ischemic atrophy finally develops (Hossmann et al., 1987; Pluta 2002b; Pluta 2004b; Pluta, Ulamek 2006) with all neurodegenerative consequences.

#### **11. Neuroinflammation after ischemia**

Ischemic brain injury is associated with both acute and chronic neuroinflammatory reactions, involving activation, hypertrophy and proliferation of astrocytes and microglia. Ischemically activated astrocytes in the CA1 area of the hippocampus overexpress cytokines (Orzylowska et al., 1999). These data show that upregulation of neuroinflammatory mediators by astrocytes are directly connected with selective vulnerability of neuronal cells in ischemic brain injury (Orzylowska et al., 1999; Touzani et al., 2002). The above data suggest that neurons in vulnerable sectors in ischemic brain are targets of astrocytes interleukin-1β. This idea is supported by overexpression of neuronal interleukin-1 receptor (Touzani et al., 2002). In addition, it was confirmed that interleukin-1β is the important factor in brain ischemia cells damage and edema formation (Yamasaki et al., 1995). Chronic synthesis by ischemic brain neuroinflammatory factors may start a self-sufficient cycle that shifts ischemic pathology into hallmarks typical for Alzheimer's disease. In ischemic brain interleukin-1 is a key factor, which motivates neurons to pathological cleavage of amyloid precursor (Griffin et al., 1998) and emits inflammatory mediators. All these events result in neuronal abnormal function and finally their death. Neuronal loss arises from neuroinflammatory factors, which induce neuronal damages that trigger microglia activity with further self-propagation of the neuroinflammatory events. Additionally, evidence has been showed that β-amyloid promotes the release of neuroinflammatory pathogens by microglia (Giulian et al., 1995). In the

Alzheimer's Factors in Ischemic Brain Injury 107

generally, complete loss of vulnerable neurons in the CA1 sector was noted during 7 days following brain ischemia (Butler et al., 2002). Moreover, one third of subjects with ischemic brain injury did not present full loss of neurons in CA1 sector following ischemia with longterm survival (Sadowski et al., 1999; Pluta 2000). In some cases, complete disappearance of all neurons of CA1 area was observed in very late stages after ischemia (Pluta 2000; Pluta 2002a; Pluta 2002b; Pluta et al., 2009). Some investigations presented marked neuropathological alterations in pyramidal neurons considered to be completely resistant to ischemic injury such as: in areas CA2, CA3, and CA4 of hippocampus and dentate gyrus (Pluta 2000; Pluta et al., 2009). These regions presented unexpectedly acute ischemic changes in neuronal cells from 1 to 24 months after ischemic brain injury (Pluta 2000; Pluta et al., 2009). Currently was noted that neuropathological processes in ischemic neurons continue well beyond the acute stage of insult (Pluta 2000; Pluta 2002a; Pluta et al., 2009; Kiryk et al., 2011). In these situations, enduring ischemic blood–brain barrier opening (Pluta 2003; Pluta 2005; Pluta 2006b; Pluta 2007b, Pluta et al., 2010) probably leads to enhanced ischemic

Some investigations reported that astrocytic apoptosis may contribute to the neuropathogenesis of different diseases such as ischemic brain injury (Koistinaho et al., 2004; Takuma et al., 2004; Pluta 2006a). Astrocytic abnormal activities observed in the ischemic brain injuries: swelling, astrogliosis, and astrocytosis (Bernaudin et al., 1998; Stoltzner et al., 2000). In ischemic brain some animal studies showed the early import of different parts of amyloid precursor protein from brain tissue and systemic circulatory to the astrocytes and in the late stages the export of the toxic β-amyloid peptide and C-terminal of amyloid precursor protein from dead astrocytes to the brain parenchyma (Pluta et al

At early stages of ischemia-reperfusion brain injury, the N-terminal of amyloid precursor protein (Pluta et al., 1994b) may be produced by vascular endothelium that became damaged following injury (Badan et al., 2004). This hypothesis is supported by the overexpression and synthesis of β-secretase after brain ischemia (Wen et al., 2004a; Sun et al., 2006; Zhang et al., 2007). Furthermore presenilin overexpressed in postischemic brain (Tanimukai et al., 1998; Pennypacker et al., 1999; Pluta 2001) is involved in the cleavage of amyloid precursor protein to synthesize β-amyloid peptide through the γ-secretase complex (Wolfe et al., 1999). This secretase is involved in amyloidogenic cleavage of amyloid precursor protein. At the first step, amyloid precursor protein is cut at the N-terminal of the β-amyloid peptide fragment by protease called β-secretase. In the second step, the metabolite of β-secretase is cut by γ-secretase to form soluble β-amyloid peptide. Endothelial cells change structural features like: shape and size during time to become incorporated into the amyloid plaques in a close spatial relationship with damaged and dead astrocytes. The same investigations show that C-terminal of amyloid precursor protein aggregates in neurons following local brain ischemia and as the infarct increases, the Cterminal of amyloid precursor protein staining become increasingly larger in the core even though the neurons are dying and the core becomes largely acellular (Badan et al., 2004). The same and other studies reported that β-amyloid peptide and C-terminal of amyloid precursor protein noted in microglia could be due to the phagocytosis of dead neurons remnants containing β-amyloid peptide and C-terminal of amyloid precursor protein by microglia (Badan et al., 2004; D'Andrea et al., 2004). Moreover, there are data demonstrating that astrocytes but not microglia can swallow up β-amyloid peptide (Matsunaga et al., 2003; Wyss-Coray et al., 2003; Pluta 2006a). Other studies show that C-terminal of amyloid

neurons vulnerability to β-amyloid peptide (Koistinaho et al., 2002).

1994b; Pluta 2002b; Koistinaho et al., 2004; Pluta 2004a; Pluta 2004b).

hippocampus glia activity precedes neurons alternations and persists for long time after ischemic brain injury. Initially, this activity was combined with repair responses at the site of the brain injury, but currently it has been shown that neuroinflammatory reaction is a key play in the evolution processes of ischemic brain pathology (Stoll et al., 1998).

 Considerable evidence indicates that neuroinflammatory cascade modulates both the synthesis factors and proliferation reactions of activated astrocytes (Smith, Hale 1997), which exert both beneficial and harmful effects during repair mechanisms in the injured brain (Stoll et al., 1998). The reactive glia produce cytokines, which next stimulate glia, cytokine production and gliosis in a self-propagating, cycle (Barone, Feuerstein 1999). Neuroinflammatory genes overexpression peaks 24 h in the damage area, then decrease (Schroeter et al., 2003). Additionally, ischemic brain injury not only causes tissue cell injury, but also engages neuroinflammatory reactions that include the movement and depositions of leukocytes, macrophages, monocytes and different serum proteins due to open of the blood brain barrier (Danton, Dietrich 2003). In addition to the core ischemic injury neuroinflammatory reactions in the remote region to the primary ischemic injury have also been observed. Using the focal model of brain ischemia degeneration was noted in thalamus and substantia nigra in areas which are supplied by opened cerebral arteries and these areas showed no sign of ischemia (Danton, Dietrich 2003). Neurodegeneration in thalamus and substantia nigra were preceded by TNF overexpression, supporting the role of neuroinflammation in the remote region to the ischemic brain lesion (Danton, Dietrich 2003). Other authors additionally reported a transient overexpression of IL-6 in the substantia nigra following focal brain ischemia (Dihne, Block 2001). Increased number of neuronal progenitor cells has been noted in the hippocampus following focal (Takasawa et al., 2002) and global (Jin et al., 2001) brain ischemia and in subventricular zone after *cardiac arrest* in rats (Andjus et al., 2010), with a considerable number of cells differentiating into astrocytes that support the neuroinflammatory reaction in the remote area distal to the primary deadly injury. Finally focal or global brain ischemic can induce a general inflammatory reaction both in the brain and peripheral body system. Inflammatory markers such as interleukin-6 and matrix metalloproteinases-9 are significantly elevated in blood plasma following brain ischemia (Castillo, Rodriguez 2004).

Neuroinflammation has also been implicated in the neuropathogenesis of dementia. In dementia patients neuroinflammation is often combined with -amyloid peptide accumulation and neurofibrillary tangles development (Moore, O'Banion 2002). Neuronal cells in the hippocampus are peculiarly vulnerable to the influence of chronic inflammation (Hauss-Wengrzyniak et al., 2000; Wenk, Barnes 2000). In addition, hippocampus, the center involved in learning and memory, which demonstrates the greatest early activation of microglia in the different diseases, finally shows the highest degree of neuropathology and atrophy (Hossmann et al., 1987; Cagnin et al., 2001; Pluta 2002b; Pluta 2004b; Pluta, Ulamek 2006). A large number of different experimental and clinical treatment studies presented that reactive microglia and proinflammatory factors are present at areas of -amyloid plaques accumulation and anti-inflammatory therapy decreases the progression of the diseases connected with amyloid pathology in own etiology (McGeer et al., 1996; Kalaria 1999; Akiyama et al., 2000).

#### **12. Ischemic brain cells and β-amyloid peptide**

In the ischemic brain, the main pathological focus is concentrated on pyramidal neurons in hippocampus because this region of the brain is selectively vulnerable to ischemia. In

hippocampus glia activity precedes neurons alternations and persists for long time after ischemic brain injury. Initially, this activity was combined with repair responses at the site of the brain injury, but currently it has been shown that neuroinflammatory reaction is a key play

 Considerable evidence indicates that neuroinflammatory cascade modulates both the synthesis factors and proliferation reactions of activated astrocytes (Smith, Hale 1997), which exert both beneficial and harmful effects during repair mechanisms in the injured brain (Stoll et al., 1998). The reactive glia produce cytokines, which next stimulate glia, cytokine production and gliosis in a self-propagating, cycle (Barone, Feuerstein 1999). Neuroinflammatory genes overexpression peaks 24 h in the damage area, then decrease (Schroeter et al., 2003). Additionally, ischemic brain injury not only causes tissue cell injury, but also engages neuroinflammatory reactions that include the movement and depositions of leukocytes, macrophages, monocytes and different serum proteins due to open of the blood brain barrier (Danton, Dietrich 2003). In addition to the core ischemic injury neuroinflammatory reactions in the remote region to the primary ischemic injury have also been observed. Using the focal model of brain ischemia degeneration was noted in thalamus and substantia nigra in areas which are supplied by opened cerebral arteries and these areas showed no sign of ischemia (Danton, Dietrich 2003). Neurodegeneration in thalamus and substantia nigra were preceded by TNF overexpression, supporting the role of neuroinflammation in the remote region to the ischemic brain lesion (Danton, Dietrich 2003). Other authors additionally reported a transient overexpression of IL-6 in the substantia nigra following focal brain ischemia (Dihne, Block 2001). Increased number of neuronal progenitor cells has been noted in the hippocampus following focal (Takasawa et al., 2002) and global (Jin et al., 2001) brain ischemia and in subventricular zone after *cardiac arrest* in rats (Andjus et al., 2010), with a considerable number of cells differentiating into astrocytes that support the neuroinflammatory reaction in the remote area distal to the primary deadly injury. Finally focal or global brain ischemic can induce a general inflammatory reaction both in the brain and peripheral body system. Inflammatory markers such as interleukin-6 and matrix metalloproteinases-9 are significantly elevated in blood plasma following brain ischemia

Neuroinflammation has also been implicated in the neuropathogenesis of dementia. In dementia patients neuroinflammation is often combined with -amyloid peptide accumulation and neurofibrillary tangles development (Moore, O'Banion 2002). Neuronal cells in the hippocampus are peculiarly vulnerable to the influence of chronic inflammation (Hauss-Wengrzyniak et al., 2000; Wenk, Barnes 2000). In addition, hippocampus, the center involved in learning and memory, which demonstrates the greatest early activation of microglia in the different diseases, finally shows the highest degree of neuropathology and atrophy (Hossmann et al., 1987; Cagnin et al., 2001; Pluta 2002b; Pluta 2004b; Pluta, Ulamek 2006). A large number of different experimental and clinical treatment studies presented that reactive microglia and proinflammatory factors are present at areas of -amyloid plaques accumulation and anti-inflammatory therapy decreases the progression of the diseases connected with amyloid pathology in own etiology (McGeer et al., 1996; Kalaria 1999; Akiyama et al., 2000).

In the ischemic brain, the main pathological focus is concentrated on pyramidal neurons in hippocampus because this region of the brain is selectively vulnerable to ischemia. In

in the evolution processes of ischemic brain pathology (Stoll et al., 1998).

(Castillo, Rodriguez 2004).

**12. Ischemic brain cells and β-amyloid peptide** 

generally, complete loss of vulnerable neurons in the CA1 sector was noted during 7 days following brain ischemia (Butler et al., 2002). Moreover, one third of subjects with ischemic brain injury did not present full loss of neurons in CA1 sector following ischemia with longterm survival (Sadowski et al., 1999; Pluta 2000). In some cases, complete disappearance of all neurons of CA1 area was observed in very late stages after ischemia (Pluta 2000; Pluta 2002a; Pluta 2002b; Pluta et al., 2009). Some investigations presented marked neuropathological alterations in pyramidal neurons considered to be completely resistant to ischemic injury such as: in areas CA2, CA3, and CA4 of hippocampus and dentate gyrus (Pluta 2000; Pluta et al., 2009). These regions presented unexpectedly acute ischemic changes in neuronal cells from 1 to 24 months after ischemic brain injury (Pluta 2000; Pluta et al., 2009). Currently was noted that neuropathological processes in ischemic neurons continue well beyond the acute stage of insult (Pluta 2000; Pluta 2002a; Pluta et al., 2009; Kiryk et al., 2011). In these situations, enduring ischemic blood–brain barrier opening (Pluta 2003; Pluta 2005; Pluta 2006b; Pluta 2007b, Pluta et al., 2010) probably leads to enhanced ischemic neurons vulnerability to β-amyloid peptide (Koistinaho et al., 2002).

Some investigations reported that astrocytic apoptosis may contribute to the neuropathogenesis of different diseases such as ischemic brain injury (Koistinaho et al., 2004; Takuma et al., 2004; Pluta 2006a). Astrocytic abnormal activities observed in the ischemic brain injuries: swelling, astrogliosis, and astrocytosis (Bernaudin et al., 1998; Stoltzner et al., 2000). In ischemic brain some animal studies showed the early import of different parts of amyloid precursor protein from brain tissue and systemic circulatory to the astrocytes and in the late stages the export of the toxic β-amyloid peptide and C-terminal of amyloid precursor protein from dead astrocytes to the brain parenchyma (Pluta et al 1994b; Pluta 2002b; Koistinaho et al., 2004; Pluta 2004a; Pluta 2004b).

At early stages of ischemia-reperfusion brain injury, the N-terminal of amyloid precursor protein (Pluta et al., 1994b) may be produced by vascular endothelium that became damaged following injury (Badan et al., 2004). This hypothesis is supported by the overexpression and synthesis of β-secretase after brain ischemia (Wen et al., 2004a; Sun et al., 2006; Zhang et al., 2007). Furthermore presenilin overexpressed in postischemic brain (Tanimukai et al., 1998; Pennypacker et al., 1999; Pluta 2001) is involved in the cleavage of amyloid precursor protein to synthesize β-amyloid peptide through the γ-secretase complex (Wolfe et al., 1999). This secretase is involved in amyloidogenic cleavage of amyloid precursor protein. At the first step, amyloid precursor protein is cut at the N-terminal of the β-amyloid peptide fragment by protease called β-secretase. In the second step, the metabolite of β-secretase is cut by γ-secretase to form soluble β-amyloid peptide. Endothelial cells change structural features like: shape and size during time to become incorporated into the amyloid plaques in a close spatial relationship with damaged and dead astrocytes. The same investigations show that C-terminal of amyloid precursor protein aggregates in neurons following local brain ischemia and as the infarct increases, the Cterminal of amyloid precursor protein staining become increasingly larger in the core even though the neurons are dying and the core becomes largely acellular (Badan et al., 2004). The same and other studies reported that β-amyloid peptide and C-terminal of amyloid precursor protein noted in microglia could be due to the phagocytosis of dead neurons remnants containing β-amyloid peptide and C-terminal of amyloid precursor protein by microglia (Badan et al., 2004; D'Andrea et al., 2004). Moreover, there are data demonstrating that astrocytes but not microglia can swallow up β-amyloid peptide (Matsunaga et al., 2003; Wyss-Coray et al., 2003; Pluta 2006a). Other studies show that C-terminal of amyloid

Alzheimer's Factors in Ischemic Brain Injury 109

immunostained stronger by antibody to apolipoprotein E than apolipoprotein J (Kida et al., 1995; Pluta et al., 1995a). It is important to notice that deposits around vessels of apolipoproteins colocalize with deposits of different parts of amyloid precursor protein (Kida et al., 1995; Pluta et al., 1995a). Apolipoprotein E can promote the aggregation of βamyloid peptide into the fibrillar formation. Clusterin is involved in transport of β-amyloid peptide through the blood–brain barrier. The general role of apolipoproteins is controlling the content of β-amyloid peptide in the extracellular space of brain tissue as well as their control on amyloid plaques development. These data demonstrate significant additive effects of apolipoproteins on controlling β-amyloid peptide accumulation around bloodbrain barrier vessels and that they play a main role in influencing extracellular brain βamyloid peptide metabolism/clearance independent of β-amyloid peptide formation. Another activity, for apolipoprotein E in ischemic brain tissue is the proposed extracellular clearance of ischemic brain parenchyma by reverse movement of amyloid into blood (Pluta et al., 2000). Delayed clearance may exacerbate healing of the ischemic blood–brain barrier. Above data point out that around vessels apolipoproteins deposition following ischemic brain injury represents a secondary injury processes that could hamper healing and outcome

After brain ischemia injury thrombocytes are forming aggregates, which adhere to the endothelium lining of blood–brain barrier vessels (Pluta et al., 1994c; Pluta 2003; Pluta 2005). As an effect of this pathology the "no-reflow phenomenon" is developing (Mossakowski et al., 1993; Pluta et al., 1994c; Pluta 2003). Moreover, trombocytes were noted on the abluminal side of vessels following ischemic brain injury (Pluta et al., 1994c; Pluta 2003; Pluta 2005). This kind of pathology was observed in capillaries, venules, veins and arterioles independently of time after ischemic brain injury. Some study suggests that brain ischemia results in development platelet-leukocytes aggregates (Ishikawa et al., 2004) in the peripheral circulatory system (Ritter et al., 2005). Another study showed strong plateletleukocyte-endothelium reactions following focal ischemic brain injury (Ishikawa et al., 2004). An increasing body of evidence has supported the idea that white cells can play an additional pathological function in brain ischemia injury (Caceres et al., 1995; Gidday et al., 2005). White blood cells matrix metalloproteinase-9 recruited to the brain ischemic tissue next white blood cells to the same brain regions in a positive feedback manner and influence chronic opening of blood–brain barrier following a primary ischemic injury (Gidday et al., 2005). Investigation by electron microscopy of ischemic blood–brain barrier presented leukocytes adhering to the endothelial cells of capillaries and venules (Caceres et al., 1995). This observation is suggested probable movement of leukocytes across blood-brain barrier vessels. Endothelial cells alterations and white blood cells aggregation and finally their

In ischemic blood-brain barrier vessels damaged endothelium presented ruptures of endothelial membranes (Caceres et al., 1995). Other studies of ischemic endothelium presented an increased number of endothelium microvilli and deep crater-like pits, and enlarged junctional ridging with undulations of basement membrane (Pluta et al., 1991). As an effect of presented alterations, platelets developed microthrombi, which attached to the vessel wall and caused a permanent supply of neurotoxic constrictors such as β-amyloid peptide (Chen et al., 1995; Thomas et al., 1996). Final effect of above phenomenon is

adherence to vessel wall also reflect a "no-reflow phenomenon".

**14. Ischemic blood–brain barrier and β-amyloid peptide** 

of ischemic brain.

precursor protein triggers the loss of astrocytes whereas the death of neurons is a secondary and result of the neuronal dependency on astrocytes for antineurotoxic amyloid guard (Abramov et al., 2003; Pluta 2006a). The accumulation of some parts of amyloid precursor protein in astrocytes may be important in promotion of amyloidosis in ischemic brain tissue in which chronic astrocytosis is probably play a key role in the occurrence of different kinds of amyloid plaques.

#### **13. Blood–brain barrier after ischemia**

Ischemic brain injury provoked a number of vessel abnormalities, which are open tight junctions and blood–brain barrier, diffuse leakage through necrotic vessels and vasospasm (Petito et al., 1982; Mossakowski et al., 1993; Mossakowski et al., 1994; Pluta et al 1994a; Wisniewski et al., 1995; Gartshore et al., 1997; Shinnou et al., 1998; Lippoldt et al., 2000; Ueno et al., 2002; Pluta 2003; Pluta 2005; Pluta et al., 2006b). Till one year after ischemic brain injury brain white and gray regions contained many diffuse and focal sites of horseradish peroxidase and gadolinium extravasations (Mossakowski et al., 1994; Pluta et al., 1994a; Pluta 2003; Pluta 2005; Pluta et al., 2006; Andjus 2010). Horseradish peroxidase leakage involved capillaries, venules, veins and arterioles. The above leakage was observed in hippocampus, cortex, thalamus and basal ganglia, and cerebellum. In summary in ischemic brains were chronic blood–brain barrier abnormalities.

Short-term survival after ischemic brain injury, animals presented within gray and white matter around blood-brain barrier vessels staining for all parts of amyloid precursor protein (Pluta et al., 1994b). On the contrary, after long-term survival immunostaining only for the neurotoxic β-amyloid peptide and to the C-terminal of amyloid precursor protein was noted (Pluta et al., 1997b; Pluta 2000; Pluta 2003; Pluta 2005; Pluta et al., 2010). Multiple and abundant β-amyloid peptide and C-terminal of amyloid precursor protein staining embraced or adjoined the blood-brain barrier vessels. Diffuse deposits of β-amyloid peptide and C-terminal of amyloid precursor protein like "puff of smoke" were also noted. Immunostaining inside capillaries with a halo of β-amyloid peptide and C-terminal of amyloid precursor protein staining around vessels (Pluta 2005; Pluta et al., 2009) indicated diffusion of this part of amyloid precursor and β-amyloid peptide across the blood-brain barrier vessels. Above deposits were observed mainly in the hippocampus, entorhinal and brain cortex.

The above observations were supported by *i.v.* injection of human β-amyloid peptide 42 into animals with *cardiac arrest*, which accumulated amyloid in the ischemic brain white and gray matter in perivascular space (Pluta et al., 1996; Pluta et al., 1997a; Pluta et al., 1999). βamyloid peptide 42 can be moved by the blood–brain barrier receptor mediated system (Deane et al., 2003; Deane et al., 2004a; Deane et al., 2004b) and by blood–brain barrier leakage caused by ischemic brain injury (Pluta et al., 1996; Pluta et al., 1997a; Pluta et al., 1999; Pluta et al., 2000) or β-amyloid peptide toxicity on blood–brain barrier after ischemia (Thomas et al., 1996; Fiala et al., 1998; Farkas et al., 2003; Paris et al., 2004a; Paris et al., 2004b).

The pathological immunostaining for apolipoproteins A1, E and J was observed mainly around vessels (Kida et al., 1995; Pluta 2000). Perivascular deposits of above proteins were well delineated and irregular. Diffuse, broad, but faint areas were also seen. Extracellular apolipoproteins E and J staining were strongly labeled by antibody to apolipoprotein A1, stronger than by apolipoprotein E antibody (Kida et al., 1995; Pluta et al., 1995a). They were

precursor protein triggers the loss of astrocytes whereas the death of neurons is a secondary and result of the neuronal dependency on astrocytes for antineurotoxic amyloid guard (Abramov et al., 2003; Pluta 2006a). The accumulation of some parts of amyloid precursor protein in astrocytes may be important in promotion of amyloidosis in ischemic brain tissue in which chronic astrocytosis is probably play a key role in the occurrence of different kinds

Ischemic brain injury provoked a number of vessel abnormalities, which are open tight junctions and blood–brain barrier, diffuse leakage through necrotic vessels and vasospasm (Petito et al., 1982; Mossakowski et al., 1993; Mossakowski et al., 1994; Pluta et al 1994a; Wisniewski et al., 1995; Gartshore et al., 1997; Shinnou et al., 1998; Lippoldt et al., 2000; Ueno et al., 2002; Pluta 2003; Pluta 2005; Pluta et al., 2006b). Till one year after ischemic brain injury brain white and gray regions contained many diffuse and focal sites of horseradish peroxidase and gadolinium extravasations (Mossakowski et al., 1994; Pluta et al., 1994a; Pluta 2003; Pluta 2005; Pluta et al., 2006; Andjus 2010). Horseradish peroxidase leakage involved capillaries, venules, veins and arterioles. The above leakage was observed in hippocampus, cortex, thalamus and basal ganglia, and cerebellum. In summary in ischemic

Short-term survival after ischemic brain injury, animals presented within gray and white matter around blood-brain barrier vessels staining for all parts of amyloid precursor protein (Pluta et al., 1994b). On the contrary, after long-term survival immunostaining only for the neurotoxic β-amyloid peptide and to the C-terminal of amyloid precursor protein was noted (Pluta et al., 1997b; Pluta 2000; Pluta 2003; Pluta 2005; Pluta et al., 2010). Multiple and abundant β-amyloid peptide and C-terminal of amyloid precursor protein staining embraced or adjoined the blood-brain barrier vessels. Diffuse deposits of β-amyloid peptide and C-terminal of amyloid precursor protein like "puff of smoke" were also noted. Immunostaining inside capillaries with a halo of β-amyloid peptide and C-terminal of amyloid precursor protein staining around vessels (Pluta 2005; Pluta et al., 2009) indicated diffusion of this part of amyloid precursor and β-amyloid peptide across the blood-brain barrier vessels. Above deposits were observed mainly in the hippocampus, entorhinal and

The above observations were supported by *i.v.* injection of human β-amyloid peptide 42 into animals with *cardiac arrest*, which accumulated amyloid in the ischemic brain white and gray matter in perivascular space (Pluta et al., 1996; Pluta et al., 1997a; Pluta et al., 1999). βamyloid peptide 42 can be moved by the blood–brain barrier receptor mediated system (Deane et al., 2003; Deane et al., 2004a; Deane et al., 2004b) and by blood–brain barrier leakage caused by ischemic brain injury (Pluta et al., 1996; Pluta et al., 1997a; Pluta et al., 1999; Pluta et al., 2000) or β-amyloid peptide toxicity on blood–brain barrier after ischemia (Thomas et al., 1996; Fiala et al., 1998; Farkas et al., 2003; Paris et al., 2004a; Paris et al.,

The pathological immunostaining for apolipoproteins A1, E and J was observed mainly around vessels (Kida et al., 1995; Pluta 2000). Perivascular deposits of above proteins were well delineated and irregular. Diffuse, broad, but faint areas were also seen. Extracellular apolipoproteins E and J staining were strongly labeled by antibody to apolipoprotein A1, stronger than by apolipoprotein E antibody (Kida et al., 1995; Pluta et al., 1995a). They were

of amyloid plaques.

brain cortex.

2004b).

**13. Blood–brain barrier after ischemia** 

brains were chronic blood–brain barrier abnormalities.

immunostained stronger by antibody to apolipoprotein E than apolipoprotein J (Kida et al., 1995; Pluta et al., 1995a). It is important to notice that deposits around vessels of apolipoproteins colocalize with deposits of different parts of amyloid precursor protein (Kida et al., 1995; Pluta et al., 1995a). Apolipoprotein E can promote the aggregation of βamyloid peptide into the fibrillar formation. Clusterin is involved in transport of β-amyloid peptide through the blood–brain barrier. The general role of apolipoproteins is controlling the content of β-amyloid peptide in the extracellular space of brain tissue as well as their control on amyloid plaques development. These data demonstrate significant additive effects of apolipoproteins on controlling β-amyloid peptide accumulation around bloodbrain barrier vessels and that they play a main role in influencing extracellular brain βamyloid peptide metabolism/clearance independent of β-amyloid peptide formation. Another activity, for apolipoprotein E in ischemic brain tissue is the proposed extracellular clearance of ischemic brain parenchyma by reverse movement of amyloid into blood (Pluta et al., 2000). Delayed clearance may exacerbate healing of the ischemic blood–brain barrier. Above data point out that around vessels apolipoproteins deposition following ischemic brain injury represents a secondary injury processes that could hamper healing and outcome of ischemic brain.

After brain ischemia injury thrombocytes are forming aggregates, which adhere to the endothelium lining of blood–brain barrier vessels (Pluta et al., 1994c; Pluta 2003; Pluta 2005). As an effect of this pathology the "no-reflow phenomenon" is developing (Mossakowski et al., 1993; Pluta et al., 1994c; Pluta 2003). Moreover, trombocytes were noted on the abluminal side of vessels following ischemic brain injury (Pluta et al., 1994c; Pluta 2003; Pluta 2005). This kind of pathology was observed in capillaries, venules, veins and arterioles independently of time after ischemic brain injury. Some study suggests that brain ischemia results in development platelet-leukocytes aggregates (Ishikawa et al., 2004) in the peripheral circulatory system (Ritter et al., 2005). Another study showed strong plateletleukocyte-endothelium reactions following focal ischemic brain injury (Ishikawa et al., 2004). An increasing body of evidence has supported the idea that white cells can play an additional pathological function in brain ischemia injury (Caceres et al., 1995; Gidday et al., 2005). White blood cells matrix metalloproteinase-9 recruited to the brain ischemic tissue next white blood cells to the same brain regions in a positive feedback manner and influence chronic opening of blood–brain barrier following a primary ischemic injury (Gidday et al., 2005). Investigation by electron microscopy of ischemic blood–brain barrier presented leukocytes adhering to the endothelial cells of capillaries and venules (Caceres et al., 1995). This observation is suggested probable movement of leukocytes across blood-brain barrier vessels. Endothelial cells alterations and white blood cells aggregation and finally their adherence to vessel wall also reflect a "no-reflow phenomenon".

#### **14. Ischemic blood–brain barrier and β-amyloid peptide**

In ischemic blood-brain barrier vessels damaged endothelium presented ruptures of endothelial membranes (Caceres et al., 1995). Other studies of ischemic endothelium presented an increased number of endothelium microvilli and deep crater-like pits, and enlarged junctional ridging with undulations of basement membrane (Pluta et al., 1991). As an effect of presented alterations, platelets developed microthrombi, which attached to the vessel wall and caused a permanent supply of neurotoxic constrictors such as β-amyloid peptide (Chen et al., 1995; Thomas et al., 1996). Final effect of above phenomenon is

Alzheimer's Factors in Ischemic Brain Injury 111

cortex (Ishibashi et al., 2006). Alertness and sensorimotor capacities are affected for 2 days, whereas deficits in learning and memory seem to be rather long lasting (Kiryk et al., 2011). Taken together strong evidence from both basic research and epidemiological studies indicated that the deterioration of cognitive activities could not be explained only by direct primary ischemic brain injury, but rather by a progressive consequence of the additive effects of the ischemic episodes, aging and Alzheimer's factors (Pasquier, Leys 1997; Popa-

1998 is a turning point in the new history of novel strategies in ischemic brain injury and Alzheimer's disease treatment (Pluta et al., 1998a). At first the full success against human βamyloid peptide 42 *i.v.* immunization in rats with brain ischemic injury (Pluta et al., 1998a; Pluta et al., 1999) and second moderate effect by intraperitoneal immunization in transgenic mouse overexpressing amyloid precursor (Schenk et al., 1999) and third peripheral administration antibodies against β-amyloid peptide (Bard et al., 2000) led to the fast

Human β-amyloid peptide removal/treatment has remarkable effects in ischemic brain injury (Pluta et al., 1998a; Pluta et al., 1999; Pluta, Ulamek 2008) and less effect in mice with overexpressed amyloid pathology (Schenk et al., 1999). Experience in patient's vaccination was less convincing (Nicoll et al., 2003; Lemere et al., 2006; Hawkes, McLaurin 2007). Trials in cases with amyloid pathology were stopped when 6% of immunized patients developed meningoencephalitis (Nicoll et al., 2003; Orgogozo et al., 2003; Gilman et al., 2005). Moreover, only 20% of patients synthesized antibody against amyloid (Gilman et al., 2005). Patients treated with autovaccine in *post mortem* examination had less amyloid plaques in brain, as well as occurrence of T-cell lymphocytes. Recently, it has been proved that antibodies against β-amyloid are in normal human immunoglobulin that in particular recognize and inhibit the toxic hallmarks of β-amyloid peptide (Dodel et al., 2004). Within the past decade treatments have been concerned on inhibitors of γ- and β-secretases responsible for cleavage β-amyloid peptide from amyloid precursor protein (Dovey et al., 2001; Selkoe 2001; Roberts 2002). Reduction of β-amyloid peptide in the brain parenchyma of aged rats after oral administration of the γ-secretase inhibitors has been noted result in decrease levels of β-amyloid in both cerebrospinal fluid and brain tissue (Best et al., 2006; El Mouedden et al., 2006). Another recent study was used antibody anti-β-secretase in which decrease of amyloid was shown in transgenic model of amyloid pathology (Rakover et al., 2007). This decrease correlated very well with improvement of cognitive function. Two single-chain antibodies have been shown to possess α-secretase activity supplying a novel use of vaccine (Rangan et al., 2003; McCarty 2006). Another group of scientists have used small particle libraries to screen for substances that either interfere with assembly of βamyloid particles into fibrils (Lashuel et al., 2002; De Felice et al., 2004) or disaggregate them

Neprilysin is β-amyloid peptide degrading enzyme in the brain (Kanemitsu et al., 2003). Human neprilysin gene transfer into brain leads to a remarkable decrease of β-amyloid deposits in transgenic mice with amyloid pathology (Marr et al., 2003). These observations proved that the deficient metabolism of β-amyloid caused by decrease level of neprilysin might contribute to pathological amyloidogenic cascades including ischemic brain injury.

Wagner 2007).

**16.1 Anti-amyloid therapy** 

**16. New guarding of ischemic brain injury** 

development of new therapies against amyloid pathology.

(Soto 2001; Gong et al., 2003; Blanchard et al., 2004).

pathological vasoconstriction during reperfusion (Wisniewski et al., 1995; Ohtake et al., 2004). Recent data suggest that thrombocytes are the main ischemic factor in recirculation injury, not only through thrombus formation but also as cause of inflammation in cooperation with leukocytes (Nishijima et al., 2004). Due to the fact that β-amyloid peptide causes vasoconstriction (Thomas et al., 1996; Niwa et al., 2000) and endothelium damage (Thomas et al., 1996), a role for β-amyloid peptide in vasoconstriction and blood–brain barrier pathology has been proved. During reperfusion after brain ischemia, islets of necrotic endothelial cells in blood-brain barrier were noted (Petito et al., 1982; Mossakowski et al., 1994; Pluta et al., 1994a). Necrotic blood–brain barrier characterizes diffuse leakage of blood elements (Petito et al., 1982; Mossakowski et al., 1994; Pluta et al., 1994a; Pluta et al., 1994c) and different parts of amyloid precursor protein from blood serum (Pluta et al., 1994b; Pluta et al., 1996). This process is probably due to senescent endothelium and this phenomenon is increased during recirculation and is augmented by β-amyloid peptide toxicity (Mossakowski et al., 1994). Senescent endothelium is a common feature of vessel aging (Erusalimsky, Kurz 2005) and is also influenced by ischemic episodes (Mossakowski et al., 1994). Another problem during reperfusion with senescent endothelium is covering it with β-amyloid peptide where β-amyloid peptide acts as antiangiogenic factor (Paris et al., 2004a; Paris et al., 2004b). Ischemic brain insults together with β-amyloid peptide have harmful effects on astrocytes and pericytes (Lupo et al., 2001; Anfuso et al., 2004) and can influence blood–brain barrier vessel angiogenesis and finally can regulate the blood–brain barrier activity (Ramsauer et al., 2002).

#### **15. Disabilities after ischemia**

In addition to pathological and pathophysiological effects, cognitive abnormalities have been showed after ischemic brain injury (Block 1999; Kiryk et al., 2011). The cognitive abnormalities were found in regions of selective vulnerability to ischemic injury and they come before neuronal death. In addition, other brain areas, which are devoid of ischemic primary neurons lesions, display some functional changes. These abnormalities mainly seem to be due synaptic damage. Ischemic brain injury does not result in long-lasting neurological deficits in ischemic animals (Block 1999; Kiryk et al., 2011). Some spontaneous recovery of sensorimotor function has been demonstrated after brain ischemia (Yang, Simpkins 2007). Following ischemic brain injury a locomotor hyperactivity has been noted for 7 days (Kuroiwa et al., 1991; Karasawa et al., 1994). Hyperactivity was directly connected with neuronal alterations in the ischemic hippocampus (Kuroiwa et al., 1991; Kiryk et al., 2011). Longer ischemia and longer locomotor hyperactivity is significantly associated with increased hippocampal neurons changes (Block 1999). After ischemic brain injury, impairment in habituation up to 6 months as revealed by longer exploration time was noted (Mileson, Schwartz 1991; Colbourne, Corbett, 1995). Brain ischemia results in reference and working memory deficits (Davis et al., 1986; Kiyota et al., 1991; Kiryk et al., 2011). In addition, brain ischemia in animals leads to deterioration of spatial memory for up to 1.5 year (Block, Schwarz 1998; Karhunen et al., 2003; Kiryk et al., 2011). Deterioration of cognitive impairment has been observed consistently during reperfusion (Roof et al., 2001; Karhunen et al., 2003; Kiryk et al., 2011). Besides, data on repetitive ischemic brain injury have shown persistent locomotor hyperactivity, reduced anxiety, and severe cognitive deficits (Ishibashi et al., 2006). Above pathology was associated with brain atrophy, which connected with diffuse neurons loss in the CA1 sector of the hippocampus and in the brain

pathological vasoconstriction during reperfusion (Wisniewski et al., 1995; Ohtake et al., 2004). Recent data suggest that thrombocytes are the main ischemic factor in recirculation injury, not only through thrombus formation but also as cause of inflammation in cooperation with leukocytes (Nishijima et al., 2004). Due to the fact that β-amyloid peptide causes vasoconstriction (Thomas et al., 1996; Niwa et al., 2000) and endothelium damage (Thomas et al., 1996), a role for β-amyloid peptide in vasoconstriction and blood–brain barrier pathology has been proved. During reperfusion after brain ischemia, islets of necrotic endothelial cells in blood-brain barrier were noted (Petito et al., 1982; Mossakowski et al., 1994; Pluta et al., 1994a). Necrotic blood–brain barrier characterizes diffuse leakage of blood elements (Petito et al., 1982; Mossakowski et al., 1994; Pluta et al., 1994a; Pluta et al., 1994c) and different parts of amyloid precursor protein from blood serum (Pluta et al., 1994b; Pluta et al., 1996). This process is probably due to senescent endothelium and this phenomenon is increased during recirculation and is augmented by β-amyloid peptide toxicity (Mossakowski et al., 1994). Senescent endothelium is a common feature of vessel aging (Erusalimsky, Kurz 2005) and is also influenced by ischemic episodes (Mossakowski et al., 1994). Another problem during reperfusion with senescent endothelium is covering it with β-amyloid peptide where β-amyloid peptide acts as antiangiogenic factor (Paris et al., 2004a; Paris et al., 2004b). Ischemic brain insults together with β-amyloid peptide have harmful effects on astrocytes and pericytes (Lupo et al., 2001; Anfuso et al., 2004) and can influence blood–brain barrier vessel angiogenesis and finally can regulate the blood–brain

In addition to pathological and pathophysiological effects, cognitive abnormalities have been showed after ischemic brain injury (Block 1999; Kiryk et al., 2011). The cognitive abnormalities were found in regions of selective vulnerability to ischemic injury and they come before neuronal death. In addition, other brain areas, which are devoid of ischemic primary neurons lesions, display some functional changes. These abnormalities mainly seem to be due synaptic damage. Ischemic brain injury does not result in long-lasting neurological deficits in ischemic animals (Block 1999; Kiryk et al., 2011). Some spontaneous recovery of sensorimotor function has been demonstrated after brain ischemia (Yang, Simpkins 2007). Following ischemic brain injury a locomotor hyperactivity has been noted for 7 days (Kuroiwa et al., 1991; Karasawa et al., 1994). Hyperactivity was directly connected with neuronal alterations in the ischemic hippocampus (Kuroiwa et al., 1991; Kiryk et al., 2011). Longer ischemia and longer locomotor hyperactivity is significantly associated with increased hippocampal neurons changes (Block 1999). After ischemic brain injury, impairment in habituation up to 6 months as revealed by longer exploration time was noted (Mileson, Schwartz 1991; Colbourne, Corbett, 1995). Brain ischemia results in reference and working memory deficits (Davis et al., 1986; Kiyota et al., 1991; Kiryk et al., 2011). In addition, brain ischemia in animals leads to deterioration of spatial memory for up to 1.5 year (Block, Schwarz 1998; Karhunen et al., 2003; Kiryk et al., 2011). Deterioration of cognitive impairment has been observed consistently during reperfusion (Roof et al., 2001; Karhunen et al., 2003; Kiryk et al., 2011). Besides, data on repetitive ischemic brain injury have shown persistent locomotor hyperactivity, reduced anxiety, and severe cognitive deficits (Ishibashi et al., 2006). Above pathology was associated with brain atrophy, which connected with diffuse neurons loss in the CA1 sector of the hippocampus and in the brain

barrier activity (Ramsauer et al., 2002).

**15. Disabilities after ischemia** 

cortex (Ishibashi et al., 2006). Alertness and sensorimotor capacities are affected for 2 days, whereas deficits in learning and memory seem to be rather long lasting (Kiryk et al., 2011). Taken together strong evidence from both basic research and epidemiological studies indicated that the deterioration of cognitive activities could not be explained only by direct primary ischemic brain injury, but rather by a progressive consequence of the additive effects of the ischemic episodes, aging and Alzheimer's factors (Pasquier, Leys 1997; Popa-Wagner 2007).

#### **16. New guarding of ischemic brain injury**

#### **16.1 Anti-amyloid therapy**

1998 is a turning point in the new history of novel strategies in ischemic brain injury and Alzheimer's disease treatment (Pluta et al., 1998a). At first the full success against human βamyloid peptide 42 *i.v.* immunization in rats with brain ischemic injury (Pluta et al., 1998a; Pluta et al., 1999) and second moderate effect by intraperitoneal immunization in transgenic mouse overexpressing amyloid precursor (Schenk et al., 1999) and third peripheral administration antibodies against β-amyloid peptide (Bard et al., 2000) led to the fast development of new therapies against amyloid pathology.

Human β-amyloid peptide removal/treatment has remarkable effects in ischemic brain injury (Pluta et al., 1998a; Pluta et al., 1999; Pluta, Ulamek 2008) and less effect in mice with overexpressed amyloid pathology (Schenk et al., 1999). Experience in patient's vaccination was less convincing (Nicoll et al., 2003; Lemere et al., 2006; Hawkes, McLaurin 2007). Trials in cases with amyloid pathology were stopped when 6% of immunized patients developed meningoencephalitis (Nicoll et al., 2003; Orgogozo et al., 2003; Gilman et al., 2005). Moreover, only 20% of patients synthesized antibody against amyloid (Gilman et al., 2005). Patients treated with autovaccine in *post mortem* examination had less amyloid plaques in brain, as well as occurrence of T-cell lymphocytes. Recently, it has been proved that antibodies against β-amyloid are in normal human immunoglobulin that in particular recognize and inhibit the toxic hallmarks of β-amyloid peptide (Dodel et al., 2004). Within the past decade treatments have been concerned on inhibitors of γ- and β-secretases responsible for cleavage β-amyloid peptide from amyloid precursor protein (Dovey et al., 2001; Selkoe 2001; Roberts 2002). Reduction of β-amyloid peptide in the brain parenchyma of aged rats after oral administration of the γ-secretase inhibitors has been noted result in decrease levels of β-amyloid in both cerebrospinal fluid and brain tissue (Best et al., 2006; El Mouedden et al., 2006). Another recent study was used antibody anti-β-secretase in which decrease of amyloid was shown in transgenic model of amyloid pathology (Rakover et al., 2007). This decrease correlated very well with improvement of cognitive function. Two single-chain antibodies have been shown to possess α-secretase activity supplying a novel use of vaccine (Rangan et al., 2003; McCarty 2006). Another group of scientists have used small particle libraries to screen for substances that either interfere with assembly of βamyloid particles into fibrils (Lashuel et al., 2002; De Felice et al., 2004) or disaggregate them (Soto 2001; Gong et al., 2003; Blanchard et al., 2004).

Neprilysin is β-amyloid peptide degrading enzyme in the brain (Kanemitsu et al., 2003). Human neprilysin gene transfer into brain leads to a remarkable decrease of β-amyloid deposits in transgenic mice with amyloid pathology (Marr et al., 2003). These observations proved that the deficient metabolism of β-amyloid caused by decrease level of neprilysin might contribute to pathological amyloidogenic cascades including ischemic brain injury.

Alzheimer's Factors in Ischemic Brain Injury 113

through neurons loss. Epidemiological studies suggest that long use of anti-inflammatory treatment in amyloid and neuroinflammatory disease like Alzheimer's disease can prevent its development (Moore, O'Banion 2002; Szekely et al., 2004). From these observations considerable studies were undertaken to investigate the influence of anti-inflammation treatment in ischemic and amyloid brain diseases. These studies include nonsteroidal antiinflammatory therapy (Morihara et al., 2005), cannabinoids (Ramirez et al., 2005) and peroxisome proliferator-activated receptor-γ agonists (Sastre et al., 2003; Echeverria et al., 2005; Heneka et al., 2005; Sastre et al., 2006). Current results from transgenic model of amyloid pathology was presented data that therapy against β-secretase decreases reaction of

Delivery umbilical cord blood cells 48 h after ischemic brain injury are developing neuroprotection by blocking the neuroinflammatory reactions (Willing et al., 2007). Above cells show protective activities *via*: modulating the neuroinflammatory response, stopping the apoptotic events and enhancing neurogenesis and angiogenesis. Activation of sigma-1 and -2 receptors *via* 1,3-di-*0*-tolylguanidin injection 24 h after ischemic brain injury is impressive in reducing ischemic damage (Willing et al., 2007). Above substance is protective by reducing inflammatory reaction and decreasing intracellular calcium in neurons and by stopping the synthesis of cytokines. In ischemic brain informations from the damaging neuronal cells trigger immune cells for an inflammatory activity, with overproduction of cytokines. Whether the cause is known or not, neurological disorders present similar cellular neuronal abnormalities and inflammation. These treatments approaches may not only be beneficial for therapy of ischemic brain injury (Willing et al., 2007) but also other neurological disorders. Above presented treatments act in a similar manner by increasing neurons survival and inhibiting the activity of general immune system (Willing et al., 2007).

The natural activity of the brain is associated with the coupling between cerebral blood flow and transport *via* the blood-brain barrier and neurons activity. Cerebral blood flow controls the neuronal physiological environment not only by regulation of local blood flow but also by regulating focal transport through blood-brain barrier. The blood-brain barrier is an energetic system with two sites of transport by its blood- and brain-facing sites. Structure and function of the blood facing side allows entry of nutrients products but opposite brain facing eliminate metabolites such as β-amyloid peptide from brain (Pluta et al., 2000; Deane et al., 2004a; Deane et al., 2004b; Zlokovic 2005). A main role of the blood-brain barrier is control of the brain pool of pathological β-amyloid peptide. The aim of this part of chapter is to analyze knowledge of the association of the ischemic blood-brain barrier with final ischemic brain injury, especially with regards to the formation different amyloid plaques (Pluta 2006a; Pluta 2006b; Pluta 2007a; Pluta 2007b) and to develop a consensus on whether blood-brain barrier changes are a valid target for brain ischemia treatment (Pluta 2006a;

According to the new ischemic blood-brain barrier maturation idea of ischemic brain injury (Pluta 2006a) all parts of blood-brain barrier such as endothelium, basal lamina, pericyte and astrocyte cells are main targets for treatment of above disorder (Sohrabji 2007). The current idea states that pathological blood-brain barrier activity caused by ischemic injury at its abluminal and luminal sides for -amyloid with damaged neurons by ischemic insult are responsible for full-blown late onset ischemic-type dementia (Pluta 2004b; Pluta 2006a; Pluta 2006b; Pluta 2007a; Pluta 2007b). In this way a novel and more effective therapy approaches

neuroinflammation in brain (Rakover et al., 2007).

**16.4 Protecting blood-brain barrier** 

Pluta 2006b; Pluta 2007a; Pluta 2007b; Pluta, Ulamek 2008).

Ischemic brain injury results in the downregulation of α-secretase mRNA and decreases its net activity (Nalivaeva et al., 2004; Yan et al., 2007). Insulin degrading enzyme is another enzyme for β-amyloid clearance in the brain (McCarty 2006). Overexpression of above enzyme reduces β-amyloid levels and retards or completely prevents amyloid plaques development in the brain (Leissring et al., 2003). Some other enzymes like endothelin converting enzyme and angiotensin converting enzyme degraded/metabolized β-amyloid peptide, too (Eckman et al., 2003, Hemming, Selkoe 2005).

Treatment by gelsolin a molecule that has high affinity for β-amyloid reduced the level of β-amyloid in the brain intra- and extracellular space by peripheral action (Matsuoka et al., 2003). Other β-amyloid drug curcumin can moved across blood-brain barrier and reduce amyloid level and amyloid plaque burden in transgenic mice with amyloid pathology (Yang et al., 2005). The enoxaparin β-amyloid drug significantly reduced β-amyloid aggregates in cortex and the total amyloid cortical concentration by combining the blood serum β-amyloid peptide in systemic circulatory (Bergamaschini et al., 2004). In compliance with the sink hypothesis molecules, which are combining β-amyloid peptide in inactive complexes in the blood serum decreases the level of blood β-amyloid peptide, which then increase a net efflux of β-amyloid peptide from the brain into blood plasma (DeMattos et al., 2001; DeMattos et al., 2002).

Recently endogenous receptor for advanced glycation-end-products peptides and β-amyloid peptide antibodies has been found in sick and healthy subjects (Mruthinti et al., 2004). These observations suggest that naturally occurring antibodies for β-amyloid peptide and receptor for advanced glycation-end-products control β-amyloid peptide level in brain and peripheral blood.

#### **16.2 Anti-tauopathy therapy**

A novel therapy has been directed against hyperphosphorylated tau protein either by inhibiting various protein kinases or promoting phosphatase activities (Lau et al., 2002; Iqbal, Grudke-Iqbal 2004; Klafki et al., 2006). Recent *in vitro* studies shown particles, which inhibited tau protein fibrillization making these molecules a promising candidate to test them in experimental conditions (Chirita et al., 2004). A new interesting data concerning therapy against amyloid have been presented lastly in animals in which triple transgenic mice were injected with β-amyloid peptide antibodies (Oddo et al., 2004). β-amyloid peptide antibodies inducted *i.v.* lead to clearance of early hyperphosphorylated tau protein deposits (Oddo et al., 2004).

Some study showed that memantine reversed hyperphosphorylation of tau protein in hippocampal slices (Li et al., 2004) and this effect of memantine occurred by disinhibition of the activity of protein phosphatase 2A (Chohan et al., 2006) that earlier was noted to be downregulated in brains with amyloid pathology (Gong et al., 1993). Based on above data it was shown in humans that treatment amyloid pathology by memantine during one year significantly decreases hyperphosphorylated tau in cerebrospinal fluid (Gunnarsson et al., 2006).

#### **16.3 Suppressing neuroinflammation**

In ischemic brains the microglia are presented as neuroinflammatory invaders, which adding additional events *via* synthesis of cytokines designed to answer to primary neuropathology. This activity may lead to significant progression of brain ischemia cases

Ischemic brain injury results in the downregulation of α-secretase mRNA and decreases its net activity (Nalivaeva et al., 2004; Yan et al., 2007). Insulin degrading enzyme is another enzyme for β-amyloid clearance in the brain (McCarty 2006). Overexpression of above enzyme reduces β-amyloid levels and retards or completely prevents amyloid plaques development in the brain (Leissring et al., 2003). Some other enzymes like endothelin converting enzyme and angiotensin converting enzyme degraded/metabolized β-amyloid

Treatment by gelsolin a molecule that has high affinity for β-amyloid reduced the level of β-amyloid in the brain intra- and extracellular space by peripheral action (Matsuoka et al., 2003). Other β-amyloid drug curcumin can moved across blood-brain barrier and reduce amyloid level and amyloid plaque burden in transgenic mice with amyloid pathology (Yang et al., 2005). The enoxaparin β-amyloid drug significantly reduced β-amyloid aggregates in cortex and the total amyloid cortical concentration by combining the blood serum β-amyloid peptide in systemic circulatory (Bergamaschini et al., 2004). In compliance with the sink hypothesis molecules, which are combining β-amyloid peptide in inactive complexes in the blood serum decreases the level of blood β-amyloid peptide, which then increase a net efflux of β-amyloid peptide from the brain into blood plasma (DeMattos et al., 2001; DeMattos et

Recently endogenous receptor for advanced glycation-end-products peptides and β-amyloid peptide antibodies has been found in sick and healthy subjects (Mruthinti et al., 2004). These observations suggest that naturally occurring antibodies for β-amyloid peptide and receptor for advanced glycation-end-products control β-amyloid peptide level in brain and

A novel therapy has been directed against hyperphosphorylated tau protein either by inhibiting various protein kinases or promoting phosphatase activities (Lau et al., 2002; Iqbal, Grudke-Iqbal 2004; Klafki et al., 2006). Recent *in vitro* studies shown particles, which inhibited tau protein fibrillization making these molecules a promising candidate to test them in experimental conditions (Chirita et al., 2004). A new interesting data concerning therapy against amyloid have been presented lastly in animals in which triple transgenic mice were injected with β-amyloid peptide antibodies (Oddo et al., 2004). β-amyloid peptide antibodies inducted *i.v.* lead to clearance of early hyperphosphorylated tau protein deposits

Some study showed that memantine reversed hyperphosphorylation of tau protein in hippocampal slices (Li et al., 2004) and this effect of memantine occurred by disinhibition of the activity of protein phosphatase 2A (Chohan et al., 2006) that earlier was noted to be downregulated in brains with amyloid pathology (Gong et al., 1993). Based on above data it was shown in humans that treatment amyloid pathology by memantine during one year significantly decreases hyperphosphorylated tau in cerebrospinal fluid (Gunnarsson et

In ischemic brains the microglia are presented as neuroinflammatory invaders, which adding additional events *via* synthesis of cytokines designed to answer to primary neuropathology. This activity may lead to significant progression of brain ischemia cases

peptide, too (Eckman et al., 2003, Hemming, Selkoe 2005).

al., 2002).

peripheral blood.

(Oddo et al., 2004).

al., 2006).

**16.2 Anti-tauopathy therapy** 

**16.3 Suppressing neuroinflammation** 

through neurons loss. Epidemiological studies suggest that long use of anti-inflammatory treatment in amyloid and neuroinflammatory disease like Alzheimer's disease can prevent its development (Moore, O'Banion 2002; Szekely et al., 2004). From these observations considerable studies were undertaken to investigate the influence of anti-inflammation treatment in ischemic and amyloid brain diseases. These studies include nonsteroidal antiinflammatory therapy (Morihara et al., 2005), cannabinoids (Ramirez et al., 2005) and peroxisome proliferator-activated receptor-γ agonists (Sastre et al., 2003; Echeverria et al., 2005; Heneka et al., 2005; Sastre et al., 2006). Current results from transgenic model of amyloid pathology was presented data that therapy against β-secretase decreases reaction of neuroinflammation in brain (Rakover et al., 2007).

Delivery umbilical cord blood cells 48 h after ischemic brain injury are developing neuroprotection by blocking the neuroinflammatory reactions (Willing et al., 2007). Above cells show protective activities *via*: modulating the neuroinflammatory response, stopping the apoptotic events and enhancing neurogenesis and angiogenesis. Activation of sigma-1 and -2 receptors *via* 1,3-di-*0*-tolylguanidin injection 24 h after ischemic brain injury is impressive in reducing ischemic damage (Willing et al., 2007). Above substance is protective by reducing inflammatory reaction and decreasing intracellular calcium in neurons and by stopping the synthesis of cytokines. In ischemic brain informations from the damaging neuronal cells trigger immune cells for an inflammatory activity, with overproduction of cytokines. Whether the cause is known or not, neurological disorders present similar cellular neuronal abnormalities and inflammation. These treatments approaches may not only be beneficial for therapy of ischemic brain injury (Willing et al., 2007) but also other neurological disorders. Above presented treatments act in a similar manner by increasing neurons survival and inhibiting the activity of general immune system (Willing et al., 2007).

#### **16.4 Protecting blood-brain barrier**

The natural activity of the brain is associated with the coupling between cerebral blood flow and transport *via* the blood-brain barrier and neurons activity. Cerebral blood flow controls the neuronal physiological environment not only by regulation of local blood flow but also by regulating focal transport through blood-brain barrier. The blood-brain barrier is an energetic system with two sites of transport by its blood- and brain-facing sites. Structure and function of the blood facing side allows entry of nutrients products but opposite brain facing eliminate metabolites such as β-amyloid peptide from brain (Pluta et al., 2000; Deane et al., 2004a; Deane et al., 2004b; Zlokovic 2005). A main role of the blood-brain barrier is control of the brain pool of pathological β-amyloid peptide. The aim of this part of chapter is to analyze knowledge of the association of the ischemic blood-brain barrier with final ischemic brain injury, especially with regards to the formation different amyloid plaques (Pluta 2006a; Pluta 2006b; Pluta 2007a; Pluta 2007b) and to develop a consensus on whether blood-brain barrier changes are a valid target for brain ischemia treatment (Pluta 2006a; Pluta 2006b; Pluta 2007a; Pluta 2007b; Pluta, Ulamek 2008).

According to the new ischemic blood-brain barrier maturation idea of ischemic brain injury (Pluta 2006a) all parts of blood-brain barrier such as endothelium, basal lamina, pericyte and astrocyte cells are main targets for treatment of above disorder (Sohrabji 2007). The current idea states that pathological blood-brain barrier activity caused by ischemic injury at its abluminal and luminal sides for -amyloid with damaged neurons by ischemic insult are responsible for full-blown late onset ischemic-type dementia (Pluta 2004b; Pluta 2006a; Pluta 2006b; Pluta 2007a; Pluta 2007b). In this way a novel and more effective therapy approaches

Alzheimer's Factors in Ischemic Brain Injury 115

The interaction between lipoprotein receptor-related protein and β-amyloid peptide mediates amyloid blood-brain barrier vessels binding, endocytosis and transcytosis through blood-brain barrier into circulatory system (Herz 2003). Moreover, p-glycoprotein has been proposed to be engaged in amyloid movement by blood-brain barrier (Lam et al., 2001). Currently some data noted that the neonatal Fc receptor at the blood-brain barrier has an important role in IgG-assisted β-amyloid peptide removal from the brain (Deane et al., 2005). Receptor for advanced glycation-end-products mediates influx of β-amyloid peptide from blood into brain tissue (Deane et al., 2003; Deane et al., 2004b). Decrease of receptor for advanced glycation-end-products can reduce influx of β-amyloid peptide into brain (Deane et al., 2003). Glycoprotein 330/megalin probably is involved in receptor-mediated transport of apolipoprotein J alone and in a complex with amyloid at the blood-brain barrier (Zlokovic et al., 1996). Lipoprotein receptor-related protein and receptor for advanced glycation-endproducts play opposing roles in amyloid transport through blood-brain barrier (Deane et al., 2004b). For now the most important way would be to look for new drugs, which influence the function or overexpression of β-amyloid peptide transport receptors by bloodbrain barrier. The reduced function of receptor for advanced glycation-end-products and increased activity of lipoprotein receptor-related protein in ischemic blood-brain barrier might readjust the movement equilibrium for β-amyloid peptide by increasing its net efflux from brain into blood plasma. Statins, which increased lipoprotein receptor-related protein in blood-brain barrier, might facilitate the movement of β-amyloid peptide from brain tissue (Deane et al., 2004a). It is worth noting that receptor for advanced glycation-end-products blockades using receptor for advanced glycation-end-products specific IgG (Mruthinti et al., 2004) can also increase the expression of lipoprotein receptor-related protein (Deane

The incidence of ischemic brain injury is gender related (Pluta 2006a) and the risk of ischemic brain injury in aged women is greater than in men. The cumulative risk for ischemic brain insults in women is higher because of a lack of estrogen after menopause (Pluta 2006a). Estrogen treatment has been noted as blood–brain barrier function control through intercellular junction proteins (Kang et al., 2006) and/or intracellular transport elements and through protective effects on the cell elements of barrier such as endothelium, pericyte and astrocyte cells (Yang et al., 2005), cells which are vulnerable to influence of ischemia and aging together in the context of natural blood–brain barrier action (Sohrabji 2007; Zipser et al., 2007). Pathological opening of the blood–brain barrier can expose ischemic brain tissue to different cellular and plasma elements from blood that indirectly or directly impair neurons and press other pathological cascades. Age-related events in different sectors of the brain can have far reaching consequences for cognitive deficits e.g. after ischemic brain injury (Kiryk et al., 2011). Most scientists have taken the approach of studying estrogen effects on pathology related to ageing disorders (Simpkins et al., 1997; Dubal et al., 1998; Shi et al., 1998; Chi et al., 2002; Chi et al., 2005). Estrogens exert protective activity in animals ischemic brain injury (Simpkins et al., 1997; Dubal et al., 1998; Shi et al., 1998; Chen et al., 2001; Chi et al., 2002; Yang et al., 2005), but the mechanisms of their protection are not understood. These hormones may guard neuronal integrity (Chen et al., 2001) by readjusting the physiological activity of the blood–brain barrier (Chi et al., 2002; Chi et al., 2005). Another probable mechanism is that estrogens decreases overexpression of amyloid precursor protein messenger RNA in ischemic brain injury (Shi et al., 1998). The

et al., 2004b).

**16.5 Therapy by estrogens** 

can be formulated and more data on different kind amyloidosis can be gathered. Aforementioned data suggest that reducing movement of -amyloid peptide from blood to brain tissue (Dickstein et al., 2006) and significantly improving reverse transport from brain into blood plasma (Pluta et al., 2000; Bell et al., 2009) and preventing ischemic events in neurons (Pluta 2007c see for references) are principal main future points in treatment of ischemic brain injury (Iwata et al., 2001; Moore, O'Banion 2002; Cheng et al., 2003; Deane et al., 2003; Borlongan et al., 2004; Deane et al., 2004a; Deane et al., 2004b; Guo et al., 2004; Kalback et al., 2004; Koistinaho et al., 2004; Tanzi et al., 2004; Pluta, Ulamek 2008]. Current data provide new information that injection with -amyloid peptide reduces blood-brain barrier leakage, amyloid burden and microgliosis in transgenic model of amyloid pathology (Dickstein et al., 2006). It was presented that the blood-brain barrier is damaged in amyloid diseases and after -amyloid peptide delivery the immune system clears amyloid from the brain as it would in peripheral organs lacking barriers. Once -amyloid is cleared the activity of the blood-brain barrier is restored (Dickstein et al., 2006). This study directly proves that the blood-brain barrier is disrupted in amyloid brain diseases (Bowman et al., 2007; Sohrabji 2007; Zipser et al., 2007; Pluta et al., 2009) and that vaccination with -amyloid peptide heals the sides of damage blood-brain barrier in transgenic mice with amyloid pathology (Dickstein et al., 2006) and ischemic brain injury (Pluta et al., 2000). Earlier my laboratory has proved that *i.v.* immunization with human -amyloid peptide 42 in brain ischemia heals blood-brain barrier leakage for -amyloid peptide 42 (Pluta et al., 2000) and prevent disease neuroprogression (Pluta et al., 1998a; Pluta et al., 1999). Possible explanation of the reparation of the blood-brain barrier is that the vaccination leads to the decrease in the level of circulating -amyloid peptide (Dickstein et al., 2006), which could directly and/or indirectly damage the blood-brain barrier (Farkas et al., 2003; Marco, Skaper 2006; Bell et al., 2009). For example inflammatory factors (Boutin et al., 2001) that stimulate angiogenesis (Grammas, Ovase 2001) and -amyloid peptide have been shown to influence an increase of some angiogenic factors like VEGF and TGF- (Tarkowski et al., 2002; Pogue, Lukiw 2004). It can be proposed that with the removal of information provided by -amyloid peptide the endothelial cells behave normally and tight junctions are closed, thereby restoring a natural blood-brain barrier function. Increased concentration in plasma -amyloid peptide has been observed in a transgenic mice with amyloid pathology after active amyloid vaccination and *i.v.* delivery of molecules with an affinity to -amyloid peptide (DeMattos et al., 2002; Matsuoka et al., 2003) and after active immunization (Pluta et al., 1998a; Pluta et al., 1999) of non-human primates (Lemere et al., 2004). It is proposed that molecules that sequester blood serum β-amyloid peptide may decrease or prevent brain amyloidosis (Matsuoka et al., 2003). In addition studies with antibodies anti-intercellular adhesion molecule-1 (Zhang et al., 1994) or platelet-endothelial cell adhesion molecule-1 (Rosenblum et al., 1994) have presented that blockage of adhesion molecules and leukocyte adhesion or platelets (>90% of β-amyloid peptide is stored in blood platelets) attachment respectively reduces ischemic brain damage after effects.

Several different ways have been suggested to remove β-amyloid peptide by blood-brain barrier including: receptor-mediated β-amyloid peptide transport by blood-brain barrier, enzyme mediated β-amyloid peptide metabolism and β-amyloid peptide bindable molecules that mediated β-amyloid peptide clearance. Receptor mediated transport of β-amyloid peptide by blood-brain barrier is responsible for both influx and efflux of β-amyloid peptide. Lipoprotein receptor-related protein mediates efflux of β-amyloid peptide from brain tissue into blood (Deane et al., 2004a; Deane et al. 2004b; Bell et al., 2009).

can be formulated and more data on different kind amyloidosis can be gathered. Aforementioned data suggest that reducing movement of -amyloid peptide from blood to brain tissue (Dickstein et al., 2006) and significantly improving reverse transport from brain into blood plasma (Pluta et al., 2000; Bell et al., 2009) and preventing ischemic events in neurons (Pluta 2007c see for references) are principal main future points in treatment of ischemic brain injury (Iwata et al., 2001; Moore, O'Banion 2002; Cheng et al., 2003; Deane et al., 2003; Borlongan et al., 2004; Deane et al., 2004a; Deane et al., 2004b; Guo et al., 2004; Kalback et al., 2004; Koistinaho et al., 2004; Tanzi et al., 2004; Pluta, Ulamek 2008]. Current data provide new information that injection with -amyloid peptide reduces blood-brain barrier leakage, amyloid burden and microgliosis in transgenic model of amyloid pathology (Dickstein et al., 2006). It was presented that the blood-brain barrier is damaged in amyloid diseases and after -amyloid peptide delivery the immune system clears amyloid from the brain as it would in peripheral organs lacking barriers. Once -amyloid is cleared the activity of the blood-brain barrier is restored (Dickstein et al., 2006). This study directly proves that the blood-brain barrier is disrupted in amyloid brain diseases (Bowman et al., 2007; Sohrabji 2007; Zipser et al., 2007; Pluta et al., 2009) and that vaccination with -amyloid peptide heals the sides of damage blood-brain barrier in transgenic mice with amyloid pathology (Dickstein et al., 2006) and ischemic brain injury (Pluta et al., 2000). Earlier my laboratory has proved that *i.v.* immunization with human -amyloid peptide 42 in brain ischemia heals blood-brain barrier leakage for -amyloid peptide 42 (Pluta et al., 2000) and prevent disease neuroprogression (Pluta et al., 1998a; Pluta et al., 1999). Possible explanation of the reparation of the blood-brain barrier is that the vaccination leads to the decrease in the level of circulating -amyloid peptide (Dickstein et al., 2006), which could directly and/or indirectly damage the blood-brain barrier (Farkas et al., 2003; Marco, Skaper 2006; Bell et al., 2009). For example inflammatory factors (Boutin et al., 2001) that stimulate angiogenesis (Grammas, Ovase 2001) and -amyloid peptide have been shown to influence an increase of some angiogenic factors like VEGF and TGF- (Tarkowski et al., 2002; Pogue, Lukiw 2004). It can be proposed that with the removal of information provided by -amyloid peptide the endothelial cells behave normally and tight junctions are closed, thereby restoring a natural blood-brain barrier function. Increased concentration in plasma -amyloid peptide has been observed in a transgenic mice with amyloid pathology after active amyloid vaccination and *i.v.* delivery of molecules with an affinity to -amyloid peptide (DeMattos et al., 2002; Matsuoka et al., 2003) and after active immunization (Pluta et al., 1998a; Pluta et al., 1999) of non-human primates (Lemere et al., 2004). It is proposed that molecules that sequester blood serum β-amyloid peptide may decrease or prevent brain amyloidosis (Matsuoka et al., 2003). In addition studies with antibodies anti-intercellular adhesion molecule-1 (Zhang et al., 1994) or platelet-endothelial cell adhesion molecule-1 (Rosenblum et al., 1994) have presented that blockage of adhesion molecules and leukocyte adhesion or platelets (>90% of β-amyloid peptide is stored in blood platelets) attachment respectively reduces ischemic

Several different ways have been suggested to remove β-amyloid peptide by blood-brain barrier including: receptor-mediated β-amyloid peptide transport by blood-brain barrier, enzyme mediated β-amyloid peptide metabolism and β-amyloid peptide bindable molecules that mediated β-amyloid peptide clearance. Receptor mediated transport of β-amyloid peptide by blood-brain barrier is responsible for both influx and efflux of β-amyloid peptide. Lipoprotein receptor-related protein mediates efflux of β-amyloid peptide from brain tissue into blood (Deane et al., 2004a; Deane et al. 2004b; Bell et al., 2009).

brain damage after effects.

The interaction between lipoprotein receptor-related protein and β-amyloid peptide mediates amyloid blood-brain barrier vessels binding, endocytosis and transcytosis through blood-brain barrier into circulatory system (Herz 2003). Moreover, p-glycoprotein has been proposed to be engaged in amyloid movement by blood-brain barrier (Lam et al., 2001). Currently some data noted that the neonatal Fc receptor at the blood-brain barrier has an important role in IgG-assisted β-amyloid peptide removal from the brain (Deane et al., 2005). Receptor for advanced glycation-end-products mediates influx of β-amyloid peptide from blood into brain tissue (Deane et al., 2003; Deane et al., 2004b). Decrease of receptor for advanced glycation-end-products can reduce influx of β-amyloid peptide into brain (Deane et al., 2003). Glycoprotein 330/megalin probably is involved in receptor-mediated transport of apolipoprotein J alone and in a complex with amyloid at the blood-brain barrier (Zlokovic et al., 1996). Lipoprotein receptor-related protein and receptor for advanced glycation-endproducts play opposing roles in amyloid transport through blood-brain barrier (Deane et al., 2004b). For now the most important way would be to look for new drugs, which influence the function or overexpression of β-amyloid peptide transport receptors by bloodbrain barrier. The reduced function of receptor for advanced glycation-end-products and increased activity of lipoprotein receptor-related protein in ischemic blood-brain barrier might readjust the movement equilibrium for β-amyloid peptide by increasing its net efflux from brain into blood plasma. Statins, which increased lipoprotein receptor-related protein in blood-brain barrier, might facilitate the movement of β-amyloid peptide from brain tissue (Deane et al., 2004a). It is worth noting that receptor for advanced glycation-end-products blockades using receptor for advanced glycation-end-products specific IgG (Mruthinti et al., 2004) can also increase the expression of lipoprotein receptor-related protein (Deane et al., 2004b).

#### **16.5 Therapy by estrogens**

The incidence of ischemic brain injury is gender related (Pluta 2006a) and the risk of ischemic brain injury in aged women is greater than in men. The cumulative risk for ischemic brain insults in women is higher because of a lack of estrogen after menopause (Pluta 2006a). Estrogen treatment has been noted as blood–brain barrier function control through intercellular junction proteins (Kang et al., 2006) and/or intracellular transport elements and through protective effects on the cell elements of barrier such as endothelium, pericyte and astrocyte cells (Yang et al., 2005), cells which are vulnerable to influence of ischemia and aging together in the context of natural blood–brain barrier action (Sohrabji 2007; Zipser et al., 2007). Pathological opening of the blood–brain barrier can expose ischemic brain tissue to different cellular and plasma elements from blood that indirectly or directly impair neurons and press other pathological cascades. Age-related events in different sectors of the brain can have far reaching consequences for cognitive deficits e.g. after ischemic brain injury (Kiryk et al., 2011). Most scientists have taken the approach of studying estrogen effects on pathology related to ageing disorders (Simpkins et al., 1997; Dubal et al., 1998; Shi et al., 1998; Chi et al., 2002; Chi et al., 2005). Estrogens exert protective activity in animals ischemic brain injury (Simpkins et al., 1997; Dubal et al., 1998; Shi et al., 1998; Chen et al., 2001; Chi et al., 2002; Yang et al., 2005), but the mechanisms of their protection are not understood. These hormones may guard neuronal integrity (Chen et al., 2001) by readjusting the physiological activity of the blood–brain barrier (Chi et al., 2002; Chi et al., 2005). Another probable mechanism is that estrogens decreases overexpression of amyloid precursor protein messenger RNA in ischemic brain injury (Shi et al., 1998). The

Alzheimer's Factors in Ischemic Brain Injury 117

brain injury. A study with a transgenic model of amyloid pathology supports the notion that cytokines influence brain deposition of serum amyloid (Guo et al., 2002). It has been suggested that neuroinflammatory factors either raise the susceptibility for β-amyloid peptide deposition or directly influence amyloid precursor protein cleavage. Additionally, cytokines are able to transcriptionally upregulate β-secretase mRNA and its enzymatic activity (Sastre et al., 2003). β-secretase and γ-secretase are key enzymes for β-amyloid peptide synthesis. The above data can be linked to the increased overexpression and activity of β-secretase and γ-secretase noted in animal ischemic brain (Wen et al., 2004a; Polavarapu et al., 2008). Finally, interleukin-1β has been shown to significantly increase amyloid precursor protein production in astrocytes (Rogers et al., 1999). Moreover, cytokines may be involved in neurofibrillary tangle formation. The idea that interleukin-1 is the common link between β-amyloid peptide production, microglia activation and tau phosphorylation has recently been supported by a study in a triple transgenic animal model of amyloid pathology (Oddo et al., 2006). In this study, tau phosphorylation precedes β-amyloid peptide accumulation. Because the β-amyloid peptide and C-terminals of amyloid precursor protein and cytokines, such as interleukin-1β and tumor necrosis factor-α, directly impair neuronal activity, focal neuroinflammatory events may contribute to neurons dysfunction before neurons death. Neuroinflammatory mediators may directly contribute to ischemic brain degeneration like in Alzheimer's disease. β-amyloid peptide is formed by β- and γsecretases from the amyloid precursor protein. Above reaction is called amyloidogenic cascade. In nonamyloidogenic process mediated by α- and γ-secretases amyloid precursor protein is cleaved within the β-amyloid peptide fragment. In both pathways is the synthesis of a 5 kDa fragment called the amyloid precursor protein intercellular domain that is proposed to contribute the progressing neuropathology in degenerative diseases including ischemic brain episodes (Muller et al., 2008). Scientists during the last 15 y have suggested the important role of amyloid precursor protein and its enzymatic processing in the neuropathology of ischemic brain injury. Above is also highlighted by the fact of noted overexpression of mRNA amyloid precursor protein (Shi et al., 1998; Shi et al., 2000), mRNA presenilins (Tanimukai et al., 1998; Pennypacker et al., 1999) and mRNA β-secretase following brain ischemia (Wen et al., 2004a; Chuang et al., 2007). The amyloid precursor protein intercellular domain is synthesized intracellular following enzymatic processing from the plasma membrane-derived amyloid precursor protein and probably might have a more direct influence on ischemic pathology than extracellular β-amyloid peptide. Over the past decade the participation of amyloid precursor protein intercellular domain in cell events have been presented including modulation in gene expression, apoptosis, cytoskeletal dynamics and suppression of neurogenesis (Muller at al., 2008). All these processes initiate and contribute to a *vicious cycle* of the disease process, resulting in progressive synaptic and neuronal dysfunction and loss in ischemia with dementia (Pluta et

Primary brain ischemia creates secondary repeated, transient and silent focal ischemic episodes, which are sufficient to sustain chronic/gradual oxidative stress and other events that could be the reason for the creepy and progressive neurons damage and death (Pluta et al., 2009; Pluta et al., 2010). Evidence derived from mice overexpressing the C-terminal of amyloid precursor protein, indicates that this part of the amyloid precursor protein may promote synaptic degeneration and retrograde neurons death (Oster-Granite et al., 1996), and finally dementia (Nalbantoglu et al., 1997). Moreover, ischemic brain injury is age-

al., 2009; Kiryk et al., 2011).

dependent (Oster-Granite et al., 1996; Popa-Wagner 2007).

protective effects of estrogens are observed in all of the neurovascular elements like: endothelial, pericyte, astrocyte and neuron cells and microglia (Chen et al., 2001; Yang et al., 2005). In addition after ischemic brain injury estrogens increase cerebral blood flow and decrease secondary ischemic episodes (McCullough et al., 2001). Prevention of ischemic brain injury and treatment of repeated ischemic episodes after primary ischemic insult may have important implications for delayed postischemic pathology like dementia. In view of the earlier data that cognitive deficits are progressing after ischemic brain injury (Kiryk et al., 2011), there is the distinct possibility that we can stop this decline by targeting the gradually progressing degenerative events, which follows ischemic brain injury by aiming at molecular processes now shown to change after brain ischemia.

#### **17. Conclusion**

The complex of overlapping events, which potentially lead to neurons death and finally dementia in ischemic brain injury, start with neuronal energy shortages due to the stopped delivery of nutrients products during ischemic episodes. The energy failure during ischemic brain injury is reflected by a fast and rapid depletion of ATP. Ischemic loss of ATP is followed by the dysfunction of ion pumps and depolarization of the neural cells, and the production of high level of reactive oxygen species, which are dangerous for neurons. Reactive oxygen species initiate lipid peroxidation and generation of lipid peroxides, which are metabolized to pathological products (Muralikrishna Adibhatla, Hatcher 2006). Parallel to these events, the activities of antioxidants decrease following ischemic brain injury (Nita et al., 2001). During recirculation a marked increase in the neurotoxic β-amyloid peptide, C-terminal of amyloid precursor protein and neuroinflammatory factors were noted. The β-amyloid peptide and C-terminal of amyloid precursor protein can act as glia stimulants. The presence of large numbers of astrocytes associated with the β-amyloid peptide and C-terminal of amyloid precursor protein deposits, in particular around vessels of the hippocampus, suggest that these amyloid deposits generate chemotactic mediators, which stimulate recruitment of next astrocytes. This suggests that astrocytes gradually accumulate β-amyloid peptide and the amount of accumulation correlates very well with the extent of pathology in the hippocampus and the survival time after ischemic brain injury. β-amyloid peptide within astrocytes appears to be of blood origin, possibly deposited by phagocytosis of locally opened blood-brain barrier (Pluta et al., 1996). In contrast, current results suggest that astrocytes could also act as a source for β-amyloid peptide, because they overexpress β-secretase in response to long-term pathology (Rossner et al., 2005). Although it remains unclear to which degree astrocytes contribute to β-amyloid peptide synthesis or its clearance, it seems apparent that astrocytes contribute to neuroinflammation cascades. In addition, microglia has been associated with amyloid plaques, which indicates that plaques development and the degree of microglia activation are interrelated. β-amyloid peptide stimulates a nuclear factor kappa B dependent pathway that is important for cytokine gene transcription, reactive astrocytes and activated microglia. Moreover, other Alzheimer proteins involved in the ischemic metabolism of amyloid precursor protein have also been implicated in neuroinflammatory reactions. Evidence suggests that neurons themselves are capable of synthesizing neuroinflammatory factors. Thus, neurons can serve as a source of cytokines including tumor necrosis factor-α and interleukin-1β (Orzyłowska et al., 1999; Heneka, O'Banion 2007). It is possible that the neurons proper may exacerbate local neuroinflammatory activities and thus contribute to own progressive distraction in ischemic

protective effects of estrogens are observed in all of the neurovascular elements like: endothelial, pericyte, astrocyte and neuron cells and microglia (Chen et al., 2001; Yang et al., 2005). In addition after ischemic brain injury estrogens increase cerebral blood flow and decrease secondary ischemic episodes (McCullough et al., 2001). Prevention of ischemic brain injury and treatment of repeated ischemic episodes after primary ischemic insult may have important implications for delayed postischemic pathology like dementia. In view of the earlier data that cognitive deficits are progressing after ischemic brain injury (Kiryk et al., 2011), there is the distinct possibility that we can stop this decline by targeting the gradually progressing degenerative events, which follows ischemic brain injury by aiming

The complex of overlapping events, which potentially lead to neurons death and finally dementia in ischemic brain injury, start with neuronal energy shortages due to the stopped delivery of nutrients products during ischemic episodes. The energy failure during ischemic brain injury is reflected by a fast and rapid depletion of ATP. Ischemic loss of ATP is followed by the dysfunction of ion pumps and depolarization of the neural cells, and the production of high level of reactive oxygen species, which are dangerous for neurons. Reactive oxygen species initiate lipid peroxidation and generation of lipid peroxides, which are metabolized to pathological products (Muralikrishna Adibhatla, Hatcher 2006). Parallel to these events, the activities of antioxidants decrease following ischemic brain injury (Nita et al., 2001). During recirculation a marked increase in the neurotoxic β-amyloid peptide, C-terminal of amyloid precursor protein and neuroinflammatory factors were noted. The β-amyloid peptide and C-terminal of amyloid precursor protein can act as glia stimulants. The presence of large numbers of astrocytes associated with the β-amyloid peptide and C-terminal of amyloid precursor protein deposits, in particular around vessels of the hippocampus, suggest that these amyloid deposits generate chemotactic mediators, which stimulate recruitment of next astrocytes. This suggests that astrocytes gradually accumulate β-amyloid peptide and the amount of accumulation correlates very well with the extent of pathology in the hippocampus and the survival time after ischemic brain injury. β-amyloid peptide within astrocytes appears to be of blood origin, possibly deposited by phagocytosis of locally opened blood-brain barrier (Pluta et al., 1996). In contrast, current results suggest that astrocytes could also act as a source for β-amyloid peptide, because they overexpress β-secretase in response to long-term pathology (Rossner et al., 2005). Although it remains unclear to which degree astrocytes contribute to β-amyloid peptide synthesis or its clearance, it seems apparent that astrocytes contribute to neuroinflammation cascades. In addition, microglia has been associated with amyloid plaques, which indicates that plaques development and the degree of microglia activation are interrelated. β-amyloid peptide stimulates a nuclear factor kappa B dependent pathway that is important for cytokine gene transcription, reactive astrocytes and activated microglia. Moreover, other Alzheimer proteins involved in the ischemic metabolism of amyloid precursor protein have also been implicated in neuroinflammatory reactions. Evidence suggests that neurons themselves are capable of synthesizing neuroinflammatory factors. Thus, neurons can serve as a source of cytokines including tumor necrosis factor-α and interleukin-1β (Orzyłowska et al., 1999; Heneka, O'Banion 2007). It is possible that the neurons proper may exacerbate local neuroinflammatory activities and thus contribute to own progressive distraction in ischemic

at molecular processes now shown to change after brain ischemia.

**17. Conclusion** 

brain injury. A study with a transgenic model of amyloid pathology supports the notion that cytokines influence brain deposition of serum amyloid (Guo et al., 2002). It has been suggested that neuroinflammatory factors either raise the susceptibility for β-amyloid peptide deposition or directly influence amyloid precursor protein cleavage. Additionally, cytokines are able to transcriptionally upregulate β-secretase mRNA and its enzymatic activity (Sastre et al., 2003). β-secretase and γ-secretase are key enzymes for β-amyloid peptide synthesis. The above data can be linked to the increased overexpression and activity of β-secretase and γ-secretase noted in animal ischemic brain (Wen et al., 2004a; Polavarapu et al., 2008). Finally, interleukin-1β has been shown to significantly increase amyloid precursor protein production in astrocytes (Rogers et al., 1999). Moreover, cytokines may be involved in neurofibrillary tangle formation. The idea that interleukin-1 is the common link between β-amyloid peptide production, microglia activation and tau phosphorylation has recently been supported by a study in a triple transgenic animal model of amyloid pathology (Oddo et al., 2006). In this study, tau phosphorylation precedes β-amyloid peptide accumulation. Because the β-amyloid peptide and C-terminals of amyloid precursor protein and cytokines, such as interleukin-1β and tumor necrosis factor-α, directly impair neuronal activity, focal neuroinflammatory events may contribute to neurons dysfunction before neurons death. Neuroinflammatory mediators may directly contribute to ischemic brain degeneration like in Alzheimer's disease. β-amyloid peptide is formed by β- and γsecretases from the amyloid precursor protein. Above reaction is called amyloidogenic cascade. In nonamyloidogenic process mediated by α- and γ-secretases amyloid precursor protein is cleaved within the β-amyloid peptide fragment. In both pathways is the synthesis of a 5 kDa fragment called the amyloid precursor protein intercellular domain that is proposed to contribute the progressing neuropathology in degenerative diseases including ischemic brain episodes (Muller et al., 2008). Scientists during the last 15 y have suggested the important role of amyloid precursor protein and its enzymatic processing in the neuropathology of ischemic brain injury. Above is also highlighted by the fact of noted overexpression of mRNA amyloid precursor protein (Shi et al., 1998; Shi et al., 2000), mRNA presenilins (Tanimukai et al., 1998; Pennypacker et al., 1999) and mRNA β-secretase following brain ischemia (Wen et al., 2004a; Chuang et al., 2007). The amyloid precursor protein intercellular domain is synthesized intracellular following enzymatic processing from the plasma membrane-derived amyloid precursor protein and probably might have a more direct influence on ischemic pathology than extracellular β-amyloid peptide. Over the past decade the participation of amyloid precursor protein intercellular domain in cell events have been presented including modulation in gene expression, apoptosis, cytoskeletal dynamics and suppression of neurogenesis (Muller at al., 2008). All these processes initiate and contribute to a *vicious cycle* of the disease process, resulting in progressive synaptic and neuronal dysfunction and loss in ischemia with dementia (Pluta et al., 2009; Kiryk et al., 2011).

Primary brain ischemia creates secondary repeated, transient and silent focal ischemic episodes, which are sufficient to sustain chronic/gradual oxidative stress and other events that could be the reason for the creepy and progressive neurons damage and death (Pluta et al., 2009; Pluta et al., 2010). Evidence derived from mice overexpressing the C-terminal of amyloid precursor protein, indicates that this part of the amyloid precursor protein may promote synaptic degeneration and retrograde neurons death (Oster-Granite et al., 1996), and finally dementia (Nalbantoglu et al., 1997). Moreover, ischemic brain injury is agedependent (Oster-Granite et al., 1996; Popa-Wagner 2007).

Alzheimer's Factors in Ischemic Brain Injury 119

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**7** 

*India* 

**The Leukocyte Count, Immature** 

**Outcome in Head Injury Patients** 

Mohita Nimiya and Venencia Albert

*Jai Prakash Narayan Apex Trauma Centre, AIIMS* 

**Granulocyte Count and Immediate** 

Arulselvi Subramanian, Deepak Agrawal, Ravindra Mohan Pandey,

Proliferation and differentiation of hematopoietic stem cells into mature white blood cells (WBC) in the bone marrow, followed by release into the circulation of mature WBC, is an extremely regulated process (Metcalf, 2008). Differentiation and maturation of the hematopoietic cells into granulocytes, monocytes, lymphocytes, megakaryocytes and erythroid cells is influenced by soluble factors including growth factors and cytokines with the bone marrow stroma, and are mediated to a certain extent through an interaction of adhesion molecules. The synchronized production of leukocytes in bone marrow is crucial for innate and adaptive immunity**.** Leukocytes encompass several subtypes including neutrophils, lymphocytes, monocytes, eosinophils, and basophils, and play a vital role in innate and adaptive immunity against invading microorganisms. They are also involved in the pathogenesis of various acute and chronic diseases. The circulating numbers of

Mature neutrophils are ephemeral and localize rapidly to inflammatory sites where they deliver microbicidal activity. It takes about 14 days until it reaches the blood, of which the last 6-7 days are spent in maturation and storage pool. In less than a day after it arrives in the blood vessel, the neutrophil emigrates from the circulation in a random manner and enters the tissue. If not utilized in an inflammatory response, the neutrophils leave the body within a few days via secretions in bronchi, saliva, gastrointestinal tract and urine, or are destroyed by the reticuloendothelial system. The kinetics of eosinophils are similar to the neutrophils, they are stored in the bone marrow for several days after going through the different maturational stages. The half-life in the blood is approximately 18 hours before entering the tissues. Basophils have a life span similar to eosinophil; the maturation time in the marrow is about 7 days. Basophils circulate in the blood and are not normally found in the tissue. Monocytes share the same committed progenitor cell as neutrophils; they undergo maturation for a period of about 50-60 hours before being released in to the blood. Once monocytes enter the blood they leave randomly with a half-time of 8.4 hours. After monocytes leave the blood, they spend several months, or longer as tissue macrophages.

leukocytes can be influenced by stress, infection, or inflammation.

**1. Introduction** 

(McPherson & Pincus, 2006).


### **The Leukocyte Count, Immature Granulocyte Count and Immediate Outcome in Head Injury Patients**

Arulselvi Subramanian, Deepak Agrawal, Ravindra Mohan Pandey, Mohita Nimiya and Venencia Albert *Jai Prakash Narayan Apex Trauma Centre, AIIMS India* 

#### **1. Introduction**

138 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

Zhang X, Zhou K, Wang R, Cui J, Lipton SA, Liao FF, Hu H, Zhang YW. (2007). Hypoxia-

Zipser BD, Johanson CE, Gonzalez L, Berzin TM, Tavares R, Hultte CM, Vitek MP,

Zlokovic BV, Martel CL, Matsubara E, McComb JG, Zhang G, McCluskey RT, Frangione

Zlokovic BV. (2005). Neurovascular mechanisms of Alzheimer's neurodegeneration.

β-amyloid generation. *J Biol Chem* 282:10873–10880.

*Acad Sci USA* 93:4229-4234.

*Trends Neurosci* 28:202-208.

Alzheimer's disease. Neurobiol Aging 2007;27:977-986.

inducible factor 1α (HIF-1α)-mediated hypoxia increases BACE1 expression and

Hovanesian V, Stopa EG. Microvascular injury and blood-brain barrier leakage in

B, Ghiso J. (1996). Glycoprotein 330/megalin: probable role in receptor-mediated transport of apolipoprotein J alone and in a complex with Alzheimer disease amyloid beta at the blood-brain and blood-cerebrospinal fluid barriers. *Proc Natl* 

> Proliferation and differentiation of hematopoietic stem cells into mature white blood cells (WBC) in the bone marrow, followed by release into the circulation of mature WBC, is an extremely regulated process (Metcalf, 2008). Differentiation and maturation of the hematopoietic cells into granulocytes, monocytes, lymphocytes, megakaryocytes and erythroid cells is influenced by soluble factors including growth factors and cytokines with the bone marrow stroma, and are mediated to a certain extent through an interaction of adhesion molecules. The synchronized production of leukocytes in bone marrow is crucial for innate and adaptive immunity**.** Leukocytes encompass several subtypes including neutrophils, lymphocytes, monocytes, eosinophils, and basophils, and play a vital role in innate and adaptive immunity against invading microorganisms. They are also involved in the pathogenesis of various acute and chronic diseases. The circulating numbers of leukocytes can be influenced by stress, infection, or inflammation.

> Mature neutrophils are ephemeral and localize rapidly to inflammatory sites where they deliver microbicidal activity. It takes about 14 days until it reaches the blood, of which the last 6-7 days are spent in maturation and storage pool. In less than a day after it arrives in the blood vessel, the neutrophil emigrates from the circulation in a random manner and enters the tissue. If not utilized in an inflammatory response, the neutrophils leave the body within a few days via secretions in bronchi, saliva, gastrointestinal tract and urine, or are destroyed by the reticuloendothelial system. The kinetics of eosinophils are similar to the neutrophils, they are stored in the bone marrow for several days after going through the different maturational stages. The half-life in the blood is approximately 18 hours before entering the tissues. Basophils have a life span similar to eosinophil; the maturation time in the marrow is about 7 days. Basophils circulate in the blood and are not normally found in the tissue. Monocytes share the same committed progenitor cell as neutrophils; they undergo maturation for a period of about 50-60 hours before being released in to the blood. Once monocytes enter the blood they leave randomly with a half-time of 8.4 hours. After monocytes leave the blood, they spend several months, or longer as tissue macrophages. (McPherson & Pincus, 2006).

The Leukocyte Count, Immature Granulocyte

associated with mortality risk in hospital patients.

found in patients with severe head injury (Rovlias & Kotsou, 2004).

al., 2006, Smith et al., 2003 as cited in Ruggiero et al., 2007).

causes systemic inflammation.

deep venous thrombosis.

Count and Immediate Outcome in Head Injury Patients 141

Raabe et al., 1999; Raabe and Seifert, 2000; Sheinberg et al., 1992 as cited in Rovlias & Kotsou, 2004). Also several studies have shown that hyperglycemia and leukocytosis are associated with a worse outcome, particularly during focal ischemia or hypoxia, which are frequently found in patients with severe head injury (De Salles et al., 1987; Graham et al.,1989; Zhuang et al., 1993 as cited in Rovlias & Kotsou, 2004). Although nonreactive pupils, Sub Arachnoid Hemorrhage, acute subdural and intracerebral haematoma hold clinical significance there are routine laboratory investigations which emerge to be

The complete blood count and leukocyte differential count are among the most frequently requested clinical laboratory tests. Leukocytosis, an increase in the number of circulating white blood cells, was first described by Virchow and Andral in the mid 19th century (Lawerence et al., 2007) is a common phenomenon in head injuries. High leukocyte count though nonspecific has been used more specifically as a prognostic indicator in myocardial infarction and as a predictor of plasma urinary oestrogen levels in women undergoing gonadotrophic treatment for infertility (Hughes, 1963, Cruichshank, 1970, 1972). Early trends in WBC alert the physician about the possibility of sepsis and allow prompt therapeutic response. Leukocytosis above a certain level could serve as a marker for bacterial infection despite the known physiologic leukocytosis following splenectomy (Toutouzas et al., 2002). Leukocytosis is also associated with a worse outcome, particularly during focal ischemia or hypoxia, which are frequently

Leukocyte (WBC) count is considered a biomarker of inflammatory processes that actively contribute to vascular injury and atherosclerosis (Mehta et al., 1998, Alexander, 1994, as cited in Ruggiero et al., 2007). Whether elevated WBC count directly contributes to cardiovascular disease and mortality (Coller, 2005, as cited in Ruggiero et al., 2007) or is merely a marker of negative cardiovascular risk profile remains controversial (Loimaala et

Injury educe a response from all cells of the immune system in which cytokines and other metabolic products of activated leukocytes can act either beneficially to provide for enhanced host resistance or deleteriously to depress the function of remote organs and

A nonspecific systemic inflammatory response occurs after both ischemic and hemorrhagic stroke, either as part of the process of brain damage or in response to complications such as

Inflammation alters normal leukocyte production by promoting granulopoiesis over lymphopoiesis, a response that supports the reactive neutrophilia following infection. Leukocytosis in trauma is due to neutrophilia, caused by neutrophil margination, and not due to increased marrow production or release of immature cells or bands. The phenomenon is short-lived, lasting only minutes to hours (Abramson & Beckz, 2000 as cited in Santucci et al., 2008). It is hypothesized that, patients with significant injury should have a higher degree of

Traumatic brain injury is associated with elevated serum levels of catecholamines (Clifton et al., 1981, Hortangl et al., 1980, Rosner et al., 1984 as cited in Gürkanlar et al., 2009). Catecholamines are responsible for the release of neutrophil stores while corticosteroids cause a decrease in the egress of neutrophils from the circulation. Catecholamines increase the leukocyte count by release of the marginated cells into the circulating pool. Corticosteroids increase the neutrophil count by releasing the cells from the storage pool in the bone marrow into the blood and by preventing egress from the circulation into these

leukocytosis compared to patients with minor injuries (Santucci et al., 2008).

#### **2. Leukocyte count and immature granulocyte count as prognostic marker for traumatic brain injury**

Traumatic Brain Injury persists to be a major health problem, and a recurrent cause of death and severe disability among a primarily young population. Worldwide, traumatic brain injury (TBI) is the single largest cause of death and disability following injury. Most TBI's are due to roadside accidents. According to WHO, by the year 2020, head trauma will be third largest killer in the developing world. The statistics from India are even more alarming. Studies show, on an average one person dies every six minutes, 70% of these being directly attributable to head and spinal trauma. The annual social costs of road accidents are estimated 3% of India's Gross Domestic Product (GDP). The accident rate of 35 per 1000 vehicles in India is also amongst the highest in the world (Ahmed et al., 2009). Traumatic brain injury (TBI) is also a major cause of disability, with survivors acquiring long-term cognitive, motor, behavioral or speech-language disabilities (Rutland-Brown, 2003, as cited in Namas et al., 2009). The various forms of traumatic injury therefore represent a pandemic disease that affects every nation in the world without regard for economic development, racial or religious predominance, or political ideology; this disease is acute in onset and often results in chronic, debilitating health problems affecting far beyond the individual victims (Kauvar & Wade, 2005, as cited in Namas et al., 2009).

Trauma acts as a trigger of a complex cascade of posttraumatic events that can be divided into a hemodynamic, metabolic, neuro-endocrine and immune responses leading to a multifocal pathophysiologic process (DeLong & Born, 2004, as cited in Namas et al., 2009). Inflammation is a a well-coordinated communication network operating at an intermediate time scale between neural and longer term endocrine processes which is necessary for the removal or reduction of challenges to the organism and subsequent restoration of homeostasis. (Vodovotz et al., 2008, as cited in Namas et al., 2009). Inflammation is necessary for the removal or reduction of challenges to the organism and subsequent restoration of homeostasis. (Nathan, 2002, as cited in Namas et al., 2009).

Although the inflammatory response is crucial in clearing invading organisms and offending agents and promoting tissue repair, these same responses carried out under a set of extreme conditions can also compromise healthy tissue and further exacerbate inflammation (Nathan, 2002, Jarrar, 1999, as cited in Namas et al., 2009). Thus, early identification of reliable prognostic factors for severely head-injured patients is of significance to both the practicing neurosurgeon and the clinical investigator. The ability to predict likely outcome in acutely admitted hospital patients can be beneficial in several ways. Risk assessment on the basis of laboratory investigations is also commonly used, but is usually applied in specific disease situations, and generally gives subjective assessments of risk. Several prognostic factors, such as age group, gender, pupillary reactivity, Glasgow Coma Scale (GCS) on admission, serum glucose level, total white blood cell counts, platelet counts, coagulation profile, computerised tomography (CT) scan, have been authenticated in various studies to predict outcome in adult traumatic brain injury patients.

A number of other variables have also been suggested to be important for determining the prognosis of patients with severe head injury. These include multimodality evoked potentials, electroencephalography, cerebral perfusion pressure, blood flow velocity on transcranial doppler, jugular venous oxygen saturation, brain tissue oxygenation, and specific serum biochemical markers such as creatine-kinase isoenzyme BB, neuronspecific enolase, and S-100B protein (Dings et al., 1996; Moulton et al., 1994; Nordby and Urdal, 1985;

Traumatic Brain Injury persists to be a major health problem, and a recurrent cause of death and severe disability among a primarily young population. Worldwide, traumatic brain injury (TBI) is the single largest cause of death and disability following injury. Most TBI's are due to roadside accidents. According to WHO, by the year 2020, head trauma will be third largest killer in the developing world. The statistics from India are even more alarming. Studies show, on an average one person dies every six minutes, 70% of these being directly attributable to head and spinal trauma. The annual social costs of road accidents are estimated 3% of India's Gross Domestic Product (GDP). The accident rate of 35 per 1000 vehicles in India is also amongst the highest in the world (Ahmed et al., 2009). Traumatic brain injury (TBI) is also a major cause of disability, with survivors acquiring long-term cognitive, motor, behavioral or speech-language disabilities (Rutland-Brown, 2003, as cited in Namas et al., 2009). The various forms of traumatic injury therefore represent a pandemic disease that affects every nation in the world without regard for economic development, racial or religious predominance, or political ideology; this disease is acute in onset and often results in chronic, debilitating health problems affecting far

**2. Leukocyte count and immature granulocyte count as prognostic marker** 

beyond the individual victims (Kauvar & Wade, 2005, as cited in Namas et al., 2009).

restoration of homeostasis. (Nathan, 2002, as cited in Namas et al., 2009).

Trauma acts as a trigger of a complex cascade of posttraumatic events that can be divided into a hemodynamic, metabolic, neuro-endocrine and immune responses leading to a multifocal pathophysiologic process (DeLong & Born, 2004, as cited in Namas et al., 2009). Inflammation is a a well-coordinated communication network operating at an intermediate time scale between neural and longer term endocrine processes which is necessary for the removal or reduction of challenges to the organism and subsequent restoration of homeostasis. (Vodovotz et al., 2008, as cited in Namas et al., 2009). Inflammation is necessary for the removal or reduction of challenges to the organism and subsequent

Although the inflammatory response is crucial in clearing invading organisms and offending agents and promoting tissue repair, these same responses carried out under a set of extreme conditions can also compromise healthy tissue and further exacerbate inflammation (Nathan, 2002, Jarrar, 1999, as cited in Namas et al., 2009). Thus, early identification of reliable prognostic factors for severely head-injured patients is of significance to both the practicing neurosurgeon and the clinical investigator. The ability to predict likely outcome in acutely admitted hospital patients can be beneficial in several ways. Risk assessment on the basis of laboratory investigations is also commonly used, but is usually applied in specific disease situations, and generally gives subjective assessments of risk. Several prognostic factors, such as age group, gender, pupillary reactivity, Glasgow Coma Scale (GCS) on admission, serum glucose level, total white blood cell counts, platelet counts, coagulation profile, computerised tomography (CT) scan, have been authenticated in various studies to predict outcome in adult

A number of other variables have also been suggested to be important for determining the prognosis of patients with severe head injury. These include multimodality evoked potentials, electroencephalography, cerebral perfusion pressure, blood flow velocity on transcranial doppler, jugular venous oxygen saturation, brain tissue oxygenation, and specific serum biochemical markers such as creatine-kinase isoenzyme BB, neuronspecific enolase, and S-100B protein (Dings et al., 1996; Moulton et al., 1994; Nordby and Urdal, 1985;

**for traumatic brain injury** 

traumatic brain injury patients.

Raabe et al., 1999; Raabe and Seifert, 2000; Sheinberg et al., 1992 as cited in Rovlias & Kotsou, 2004). Also several studies have shown that hyperglycemia and leukocytosis are associated with a worse outcome, particularly during focal ischemia or hypoxia, which are frequently found in patients with severe head injury (De Salles et al., 1987; Graham et al.,1989; Zhuang et al., 1993 as cited in Rovlias & Kotsou, 2004). Although nonreactive pupils, Sub Arachnoid Hemorrhage, acute subdural and intracerebral haematoma hold clinical significance there are routine laboratory investigations which emerge to be associated with mortality risk in hospital patients.

The complete blood count and leukocyte differential count are among the most frequently requested clinical laboratory tests. Leukocytosis, an increase in the number of circulating white blood cells, was first described by Virchow and Andral in the mid 19th century (Lawerence et al., 2007) is a common phenomenon in head injuries. High leukocyte count though nonspecific has been used more specifically as a prognostic indicator in myocardial infarction and as a predictor of plasma urinary oestrogen levels in women undergoing gonadotrophic treatment for infertility (Hughes, 1963, Cruichshank, 1970, 1972). Early trends in WBC alert the physician about the possibility of sepsis and allow prompt therapeutic response. Leukocytosis above a certain level could serve as a marker for bacterial infection despite the known physiologic leukocytosis following splenectomy (Toutouzas et al., 2002). Leukocytosis is also associated with a worse outcome, particularly during focal ischemia or hypoxia, which are frequently found in patients with severe head injury (Rovlias & Kotsou, 2004).

Leukocyte (WBC) count is considered a biomarker of inflammatory processes that actively contribute to vascular injury and atherosclerosis (Mehta et al., 1998, Alexander, 1994, as cited in Ruggiero et al., 2007). Whether elevated WBC count directly contributes to cardiovascular disease and mortality (Coller, 2005, as cited in Ruggiero et al., 2007) or is merely a marker of negative cardiovascular risk profile remains controversial (Loimaala et al., 2006, Smith et al., 2003 as cited in Ruggiero et al., 2007).

Injury educe a response from all cells of the immune system in which cytokines and other metabolic products of activated leukocytes can act either beneficially to provide for enhanced host resistance or deleteriously to depress the function of remote organs and causes systemic inflammation.

A nonspecific systemic inflammatory response occurs after both ischemic and hemorrhagic stroke, either as part of the process of brain damage or in response to complications such as deep venous thrombosis.

Inflammation alters normal leukocyte production by promoting granulopoiesis over lymphopoiesis, a response that supports the reactive neutrophilia following infection. Leukocytosis in trauma is due to neutrophilia, caused by neutrophil margination, and not due to increased marrow production or release of immature cells or bands. The phenomenon is short-lived, lasting only minutes to hours (Abramson & Beckz, 2000 as cited in Santucci et al., 2008). It is hypothesized that, patients with significant injury should have a higher degree of leukocytosis compared to patients with minor injuries (Santucci et al., 2008).

Traumatic brain injury is associated with elevated serum levels of catecholamines (Clifton et al., 1981, Hortangl et al., 1980, Rosner et al., 1984 as cited in Gürkanlar et al., 2009). Catecholamines are responsible for the release of neutrophil stores while corticosteroids cause a decrease in the egress of neutrophils from the circulation. Catecholamines increase the leukocyte count by release of the marginated cells into the circulating pool. Corticosteroids increase the neutrophil count by releasing the cells from the storage pool in the bone marrow into the blood and by preventing egress from the circulation into these

The Leukocyte Count, Immature Granulocyte

as cited in Briggs, 2009).

**2.2 Materials and method** 

excluded from the study.

Sysmex XE 2100 (Sysmex, Kobe, Japan).

**2.1 Aim** 

Count and Immediate Outcome in Head Injury Patients 143

Published studies agree that IG counts have a high specificity for infectious conditions (from 83% to 97%) but are accompanied by low sensitivity (between 35% and 40%) (Briggs et al., 2003, Ansari-Lari et al., 2003, as cited in Buttarello & Plebani, 2008). This low sensitivity means that this count is not indicated as a screening test for infection, even though a significant association exists between elevated IG counts and positive blood cultures (Buttarello & Plebani, 2008). The presence of low numbers of immature granulocytes is more reliably detected on automated hematology analyzers than using manual microscopy. Automated blood cell counters have undergone a formidable technological evolution owing to the introduction of new physical principles for cellular analysis and the progressive evolution of software, resulting in high number of cells being counted (Briggs et al., 2003, as cited in Briggs, 2009). This is because of the high number of cells counted and an increase of IG (>2%) can be useful in identifying infection even when not suspected (Briggs et al., 2003,

Our aim for this study was to correlate on admission leukocyte and immature granulocyte count (IG) with the severity of head injury (according to the Glasgow coma score), computed tomography findings and pupillary reaction in trauma patients with isolated head injuries. We also intended to determine the factors influencing the immediate clinical outcome (dead or alive) in isolated head injury patients. The acute-phase response due to trauma is characterized by a leukocytosis upon admission. Therefore, an increase in the white blood cell (WBC) count might serve as an additional diagnostic and prognostic indicator in head injury. Our goal was to demonstrate that a reliable prediction of outcome based on the admission day leukocyte and immature granulocyte count is of great clinical relevance. We aimed to develop a prognostic model with readily available traditional laboratory parameters for the selection of those trauma patients who are likely to progress towards an adverse outcome, in turn ensuring their optimum management.

For the purpose of this study retrospective analysis of case files of patients admitted with, non penetrating head injury (mild, moderate and severe) at a level I trauma centre for duration of two months (June - July 2008) was performed. Patients with brain death, penetrating injury, infection and possible diseases that may alter the white blood cell count (myocardial infarction, cerebral vascular accident, surgical procedures etc) were

Two ml of venous blood was collected in a disposable EDTA tubes, on the same day as clinical assessment or, for patients admitted to the hospital, as soon after assessment as possible, for the estimation of basic hemogram parameters and immature granulocyte count. The WBC and IG count was measured using a fully automated hematology analyzer,

The results of all the routinely done, laboratory investigations were documented in the institution computerised patient record system (CPRS). The patients clinical and laboratory

The XE-2100TM is a haematology analyser that, utilises the technology of fluorescence flow cytometry to quantitate the standard five part , immature granulocytes (metamyelocytes, myelocytes and promyelocytes), nucleated red blood cells (NRBC), reticulocyte count, immature reticulocyte fraction and "optical" fluorescent platelet

details were extracted from the CPRS and patient files, for the purpose of this study.

tissues (Boggs, 1967 as cited in Gürkanlar et al., 2009). Brain swelling occurring after head trauma is probably an inflammatory response due to tracerebral cytokine production and increased leukocyte adhesion as a result of a direct effect on vascular permeability and leucocyte activation (Dietrich et al., 2004, Fee et al., 2003, Gourin & Shackford, 1997, Juurlink, 2000, Lenzlinger, 2001 as cited in Gurkanlar et al., 2009). Another theory of leukocytosis after trauma can be explained as follows: In post traumatic injury, the cell body of the microglia becomes hypertrophic with long, branched and crennellated processes during the first 60 minutes post injury, as the blood brain barrier (BBB) opens at the time of the trauma and approaches closure at about 60 minutes post injury (Bednar et al., 1997 as cited in Gürkanlar et al., 2009). Microglia cells express class I and class II MHC antigens and these antigens could be presented to lymphocytes in the regional lymph nodes and trigger the activation of circulating lymphocytes in the central nervous system (Capps, 1896, Kakarieka, 1997, Neil-Dwyer & Cruickshank 1974, Rovlias & Kotsou, 2001 as cited in Gürkanlar et al., 2009). Microglia cells play a predominant role in the induction and maintenance of the immune response following head trauma (Czigner et al., 2007 as cited in Gürkanlar et al., 2009). An alternative mechanism by which leucocytes can be associated with cerebral damage is the traumatic rupture of microvessels followed by physical occlusion. The leucocytes are less deformable than the erythrocytes, and a greater pressure gradient is therefore required to force them through the capillaries with small diameter. Under conditions of reduced perfusion pressure, the capillaries may behave like a sieve and trap the leucocytes to increase the WBC count. After the entrapment, the leucocytes form a common area of contact with the endothelium and may not be dislodged even after the perfusion pressure returns to normal (Hallenbeck, 1986, Janoff, 1965, Suval, 1987, Yamakawa, 1987 as cited in Gürkanlar et al., 2009). The mechanical occlusion of the capillaries may become more evident as a result of the release of a number of cytotoxic chemicals that leads to increased leucocyte endothelial interactions (Harlan & Winn, 2007 as cited in Gürkanlar et al., 2009).

The presence of immature granulocytes (IG) in the peripheral blood may indicate bacterial sepsis, inflammation, trauma, cancer, steroid therapy or myeloproliferative diseases (Ansari-Lari et al., 2003, Briggs, 2003, 2009, Iddles, 2007.) They are also present in the later stages of pregnancy. In these cases, there is often an increased neutrophil count. Nevertheless neutrophils morphological abnormalities and automated left shift flags are notoriously unreliable as specific diagnostic features.

The measurement of the immature cells of the myeloid series, specifically "band" cells, is considered clinically useful for the diagnosis of infections, especially neonatal sepsis. Rodwell et al., 1988, Seebach et al., 1997 as cited in Buttarello & Plebani, 2008) Even though a morphologic definition of these cells exists, it is not universally accepted. (Cornbleet & Novak, 1995, as cited in Buttarello & Plebani, 2008). Immature granulocytes, normally absent from peripheral blood, are increased also in other conditions such as tissue necrosis, acute transplant rejection, surgical and orthopedic trauma. In these cases, the increase in immature granulocytes is accompanied by an increase in neutrophils, which are freed from the marginal pool and bone marrow. In some subjects, especially elderly people, neonates, and myelosuppressed patients, the increase in neutrophils may be absent, and in other conditions, such as sepsis, there can even be neutropenia. In these situations, the increase in IGs (>2%), even if isolated, can be useful for identifying an acute infection, even when not suspected (Briggs et al., 2003 as cited in Buttarello & Plebani, 2008).

Microscopic immature granulocytes counts has limits of imprecision and lack clinical sensitivity because these components are usually found in low concentrations (<10%). Published studies agree that IG counts have a high specificity for infectious conditions (from 83% to 97%) but are accompanied by low sensitivity (between 35% and 40%) (Briggs et al., 2003, Ansari-Lari et al., 2003, as cited in Buttarello & Plebani, 2008). This low sensitivity means that this count is not indicated as a screening test for infection, even though a significant association exists between elevated IG counts and positive blood cultures (Buttarello & Plebani, 2008). The presence of low numbers of immature granulocytes is more reliably detected on automated hematology analyzers than using manual microscopy. Automated blood cell counters have undergone a formidable technological evolution owing to the introduction of new physical principles for cellular analysis and the progressive evolution of software, resulting in high number of cells being counted (Briggs et al., 2003, as cited in Briggs, 2009). This is because of the high number of cells counted and an increase of IG (>2%) can be useful in identifying infection even when not suspected (Briggs et al., 2003, as cited in Briggs, 2009).

#### **2.1 Aim**

142 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

tissues (Boggs, 1967 as cited in Gürkanlar et al., 2009). Brain swelling occurring after head trauma is probably an inflammatory response due to tracerebral cytokine production and increased leukocyte adhesion as a result of a direct effect on vascular permeability and leucocyte activation (Dietrich et al., 2004, Fee et al., 2003, Gourin & Shackford, 1997, Juurlink, 2000, Lenzlinger, 2001 as cited in Gurkanlar et al., 2009). Another theory of leukocytosis after trauma can be explained as follows: In post traumatic injury, the cell body of the microglia becomes hypertrophic with long, branched and crennellated processes during the first 60 minutes post injury, as the blood brain barrier (BBB) opens at the time of the trauma and approaches closure at about 60 minutes post injury (Bednar et al., 1997 as cited in Gürkanlar et al., 2009). Microglia cells express class I and class II MHC antigens and these antigens could be presented to lymphocytes in the regional lymph nodes and trigger the activation of circulating lymphocytes in the central nervous system (Capps, 1896, Kakarieka, 1997, Neil-Dwyer & Cruickshank 1974, Rovlias & Kotsou, 2001 as cited in Gürkanlar et al., 2009). Microglia cells play a predominant role in the induction and maintenance of the immune response following head trauma (Czigner et al., 2007 as cited in Gürkanlar et al., 2009). An alternative mechanism by which leucocytes can be associated with cerebral damage is the traumatic rupture of microvessels followed by physical occlusion. The leucocytes are less deformable than the erythrocytes, and a greater pressure gradient is therefore required to force them through the capillaries with small diameter. Under conditions of reduced perfusion pressure, the capillaries may behave like a sieve and trap the leucocytes to increase the WBC count. After the entrapment, the leucocytes form a common area of contact with the endothelium and may not be dislodged even after the perfusion pressure returns to normal (Hallenbeck, 1986, Janoff, 1965, Suval, 1987, Yamakawa, 1987 as cited in Gürkanlar et al., 2009). The mechanical occlusion of the capillaries may become more evident as a result of the release of a number of cytotoxic chemicals that leads to increased leucocyte endothelial interactions

The presence of immature granulocytes (IG) in the peripheral blood may indicate bacterial sepsis, inflammation, trauma, cancer, steroid therapy or myeloproliferative diseases (Ansari-Lari et al., 2003, Briggs, 2003, 2009, Iddles, 2007.) They are also present in the later stages of pregnancy. In these cases, there is often an increased neutrophil count. Nevertheless neutrophils morphological abnormalities and automated left shift flags are notoriously

The measurement of the immature cells of the myeloid series, specifically "band" cells, is considered clinically useful for the diagnosis of infections, especially neonatal sepsis. Rodwell et al., 1988, Seebach et al., 1997 as cited in Buttarello & Plebani, 2008) Even though a morphologic definition of these cells exists, it is not universally accepted. (Cornbleet & Novak, 1995, as cited in Buttarello & Plebani, 2008). Immature granulocytes, normally absent from peripheral blood, are increased also in other conditions such as tissue necrosis, acute transplant rejection, surgical and orthopedic trauma. In these cases, the increase in immature granulocytes is accompanied by an increase in neutrophils, which are freed from the marginal pool and bone marrow. In some subjects, especially elderly people, neonates, and myelosuppressed patients, the increase in neutrophils may be absent, and in other conditions, such as sepsis, there can even be neutropenia. In these situations, the increase in IGs (>2%), even if isolated, can be useful for identifying an acute infection, even when not

Microscopic immature granulocytes counts has limits of imprecision and lack clinical sensitivity because these components are usually found in low concentrations (<10%).

(Harlan & Winn, 2007 as cited in Gürkanlar et al., 2009).

suspected (Briggs et al., 2003 as cited in Buttarello & Plebani, 2008).

unreliable as specific diagnostic features.

Our aim for this study was to correlate on admission leukocyte and immature granulocyte count (IG) with the severity of head injury (according to the Glasgow coma score), computed tomography findings and pupillary reaction in trauma patients with isolated head injuries. We also intended to determine the factors influencing the immediate clinical outcome (dead or alive) in isolated head injury patients. The acute-phase response due to trauma is characterized by a leukocytosis upon admission. Therefore, an increase in the white blood cell (WBC) count might serve as an additional diagnostic and prognostic indicator in head injury. Our goal was to demonstrate that a reliable prediction of outcome based on the admission day leukocyte and immature granulocyte count is of great clinical relevance. We aimed to develop a prognostic model with readily available traditional laboratory parameters for the selection of those trauma patients who are likely to progress towards an adverse outcome, in turn ensuring their optimum management.

#### **2.2 Materials and method**

For the purpose of this study retrospective analysis of case files of patients admitted with, non penetrating head injury (mild, moderate and severe) at a level I trauma centre for duration of two months (June - July 2008) was performed. Patients with brain death, penetrating injury, infection and possible diseases that may alter the white blood cell count (myocardial infarction, cerebral vascular accident, surgical procedures etc) were excluded from the study.

Two ml of venous blood was collected in a disposable EDTA tubes, on the same day as clinical assessment or, for patients admitted to the hospital, as soon after assessment as possible, for the estimation of basic hemogram parameters and immature granulocyte count. The WBC and IG count was measured using a fully automated hematology analyzer, Sysmex XE 2100 (Sysmex, Kobe, Japan).

The results of all the routinely done, laboratory investigations were documented in the institution computerised patient record system (CPRS). The patients clinical and laboratory details were extracted from the CPRS and patient files, for the purpose of this study.

The XE-2100TM is a haematology analyser that, utilises the technology of fluorescence flow cytometry to quantitate the standard five part , immature granulocytes (metamyelocytes, myelocytes and promyelocytes), nucleated red blood cells (NRBC), reticulocyte count, immature reticulocyte fraction and "optical" fluorescent platelet

The Leukocyte Count, Immature Granulocyte

considered as statistically significant.

**2.3 Results** 

non SAH group (p=0.04).

associated with a hopeless outcome.

Count and Immediate Outcome in Head Injury Patients 145

To find out the statistical correlation of various clinical factors with the immediate outcome (dead/ alive), firstly, chi square test was used to measure the statistical association of these factors in the binary form with the outcome, followed by a bivariate logistic regression to compute unadjusted odds ratio (95% confidence interval) of each of the separate factors with the outcome. Lastly all the factors were considered simultaneously in the stepwise multivariate logistic regression analysis with probability to enter as 0.05 and the probability to remove as 0.1. STATA 10.0 statistical software (STATA corporation, Texas, US) was used for data analysis. In this study p value < 0.05 is

A total of eighty patients were included in the study. The mean age was 33.5±13.9 years; there were 70 (87.5%) males. The head injury was mild (GCS 14-15) in 17(21.3%) patients, moderate (GCS 8-13) in 21(26.2%) patients and severe (GCS 3-7) in 42 patients (52.5%). The overall admission day mean± S.D. leukocyte count and median (IQR) immature granulocyte counts were 14,062 ± 5383 cells/cumm and 0.07 (0-1.54) cells/cumm respectively. Mortality rate of 28.8% (23) was observed in the study group during the course of their hospital stay. The mean WBC count was associated with the severity of head injury according to the GCS scores, pupillary reaction and CT scan findings and the results were tabulated (table 1). The head injury patients with low GCS scores (3-7) had higher mean WBC counts compared to moderate and mild head injury groups (p<0.001). Head injured patients with bilaterally absent pupillary reaction had higher mean WBC counts compared to unilaterally present and bilaterally present pupillary reaction groups (p<0.001). However, the mean WBC count between the unilaterally present and bilaterally present pupillary reaction groups was not significant (p<1.00). Statistically significant association was not observed between the mean WBC count and CT scan findings. The results of the comparison between the median IG count and the other variables are shown in table 2. The median IG count in the, CT scan findings, SAH group was significantly lower than groups with other CT scan findings the

To dichotomize the variables, cut-offs were derived for the WBC and the IG counts. The mean WBC count among the survivors and non survivors was 12,096 ± 3842 cells/cumm and 18,934±1172 cells/cumm respectively. Similarly, the median range IG count among the survivors and non survivors was 0.07 (0-0.26) cells/cumm and 0.13 (0-1.54) cells/cumm respectively. The mean value of WBC and IG count among survivors was taken as the cut off and variables were entered in to bivariate analysis to derive the significant factors.The mean value of WBC and IG count among survivors was taken as the cut off and variables were entered in to bivariate analysis to determine the significant independent role of these investigations in head injury patients. The results of bivariate and multivariate logistic regression are shown in table 3. The non survivors had high WBC counts (>12,096 cells/cumm, p<0.0001), severe head injury (GCS 3-7, p<0.001) and higher abnormal pupillary reaction (unilaterally present and bilaterally absent pupillary reaction, p<0.01) compared to the survivors. Multivariate logistic regression analysis to determine the correlation of each individual factor with mortality revealed only high WBC count [OR (95% CI): 4.9 (0.8-29.5)] and severe head injury (GCS 3-7) [OR (95% CI): 4.4 (0.9-21.2)] to be independent significant predictors of mortality. Bilaterally absent pupillary responses was not found to be statistically significant in predicting mortality, thus it should not always be

count. A hemolytic reagent causes disruption of mature WBC membranes, leaving bare nuclei, while immature myeloid cells with low cell membrane lipid content remain intact. A surfactant increases membrane permeability allowing a poly-methylene dye with high affinity for nucleic acid to enter the cells. When excited by a 633-nm laser beam, the stained cells emit fluorescence proportional to their content of nucleic acid. The combination of side scatter (inner complexity of the cell), forward scatter (volume) and fluorescence intensity of nucleated cells gives a concise but precise image of each cell detected in the peripheral blood. A well-defined physical description of the different leucocyte populations (clusters) is obtained. Immature granulocytes are recognized by their increased fluorescence emission compared with segmented neutrophils because they contain more RNA and DNA. The immature information (IMI) channel of the XE-2100 counts human progenitor cells (HPC). The reagents specifically affect the lipid components of the cell membranes; the membranes of mature cells, with a higher content of lipid are lysed while immature cells retain their membranes. In normal samples no intact cells are seen in the IMI area. The HPC has been shown to be an important parameter in the prediction of the apheresis yields of CD34+ cells in peripheral blood in patients undergoing progenitor cell mobilisation. It has been demonstrated that the use of peripheral blood HPC counts gives a more precise measurement of early cells than visual blast cell counts and allows a more quantitative assessment of the release of progenitor cells into the blood (Briggs et al., 1999).

The Sysmex XE 2100 automated analyzer can count immature granulocyte while performing the differential leukocyte (WBC) count, with notably lower imprecision [Coefficient Variance (CV) near 7%]. On comparison with microscopic examination or flow cytometry using Monoclonal antibody (MoAb) methods high accuracy was observed for the Sysmex XE 2100 automated analyzer (r between 0.78 and 0.96). (Briggs et al., 2003, Field et al., 2006 as cited in Buttarello & Plebani, 2008).

The corresponding computed tomography (CT) scan findings and pupillary reaction were extracted from the case files and analyzed. For purposes of analysis, pupillary reaction was noted as unilaterally present, bilaterally present or bilaterally absent reaction. The CT scan findings were recorded as subdural hemorrhage (SDH), extradural hemorrhage (EDH), intracerebral hemorrhage (ICH) and contusion and subarachnoid hemorrhage (SAH). The severity of head injury was graded according to the GCS as mild (GCS 14-15), moderate (GCS 8-13) and severe (GCS 3-7).

The WBC and IG counts were correlated with severity of head injury, pupillary reaction and CT scan findings (SDH, EDH, ICH and SAH). Death during the hospital stay was considered as the study immediate outcome and WBC count, IG count, pupillary reaction and severity of head injury were considered as its potential determinants.

Data was recorded on a predesigned proforma and managed on an excel spread sheet. Categorical variables such as pupillary reaction, severity of head injury (mild, moderate, severe), CT findings (SDH, SAH, EDH, ICH and contusion) and immediate outcome (dead/ alive) were summarized as frequency (%). Quantitative variables (WBC and IG counts) were summarized as mean±S.D (standard deviation) for normally distributed and median (Inter quartile range) for non-normally distributed variables Students's t-Test was used to compare mean values between two groups, while Wilcoxon rank sum test was used to compare median values between two groups. For the overall comparison of mean values between more than two groups, One Way Analysis Of Variance (ANOVA) followed by Bonferroni's correction in post-hoc analysis was applied.

To find out the statistical correlation of various clinical factors with the immediate outcome (dead/ alive), firstly, chi square test was used to measure the statistical association of these factors in the binary form with the outcome, followed by a bivariate logistic regression to compute unadjusted odds ratio (95% confidence interval) of each of the separate factors with the outcome. Lastly all the factors were considered simultaneously in the stepwise multivariate logistic regression analysis with probability to enter as 0.05 and the probability to remove as 0.1. STATA 10.0 statistical software (STATA corporation, Texas, US) was used for data analysis. In this study p value < 0.05 is considered as statistically significant.

#### **2.3 Results**

144 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

count. A hemolytic reagent causes disruption of mature WBC membranes, leaving bare nuclei, while immature myeloid cells with low cell membrane lipid content remain intact. A surfactant increases membrane permeability allowing a poly-methylene dye with high affinity for nucleic acid to enter the cells. When excited by a 633-nm laser beam, the stained cells emit fluorescence proportional to their content of nucleic acid. The combination of side scatter (inner complexity of the cell), forward scatter (volume) and fluorescence intensity of nucleated cells gives a concise but precise image of each cell detected in the peripheral blood. A well-defined physical description of the different leucocyte populations (clusters) is obtained. Immature granulocytes are recognized by their increased fluorescence emission compared with segmented neutrophils because they contain more RNA and DNA. The immature information (IMI) channel of the XE-2100 counts human progenitor cells (HPC). The reagents specifically affect the lipid components of the cell membranes; the membranes of mature cells, with a higher content of lipid are lysed while immature cells retain their membranes. In normal samples no intact cells are seen in the IMI area. The HPC has been shown to be an important parameter in the prediction of the apheresis yields of CD34+ cells in peripheral blood in patients undergoing progenitor cell mobilisation. It has been demonstrated that the use of peripheral blood HPC counts gives a more precise measurement of early cells than visual blast cell counts and allows a more quantitative assessment of the release of progenitor

The Sysmex XE 2100 automated analyzer can count immature granulocyte while performing the differential leukocyte (WBC) count, with notably lower imprecision [Coefficient Variance (CV) near 7%]. On comparison with microscopic examination or flow cytometry using Monoclonal antibody (MoAb) methods high accuracy was observed for the Sysmex XE 2100 automated analyzer (r between 0.78 and 0.96). (Briggs et al., 2003, Field et al., 2006

The corresponding computed tomography (CT) scan findings and pupillary reaction were extracted from the case files and analyzed. For purposes of analysis, pupillary reaction was noted as unilaterally present, bilaterally present or bilaterally absent reaction. The CT scan findings were recorded as subdural hemorrhage (SDH), extradural hemorrhage (EDH), intracerebral hemorrhage (ICH) and contusion and subarachnoid hemorrhage (SAH). The severity of head injury was graded according to the GCS as mild (GCS 14-15), moderate

The WBC and IG counts were correlated with severity of head injury, pupillary reaction and CT scan findings (SDH, EDH, ICH and SAH). Death during the hospital stay was considered as the study immediate outcome and WBC count, IG count, pupillary reaction

Data was recorded on a predesigned proforma and managed on an excel spread sheet. Categorical variables such as pupillary reaction, severity of head injury (mild, moderate, severe), CT findings (SDH, SAH, EDH, ICH and contusion) and immediate outcome (dead/ alive) were summarized as frequency (%). Quantitative variables (WBC and IG counts) were summarized as mean±S.D (standard deviation) for normally distributed and median (Inter quartile range) for non-normally distributed variables Students's t-Test was used to compare mean values between two groups, while Wilcoxon rank sum test was used to compare median values between two groups. For the overall comparison of mean values between more than two groups, One Way Analysis Of Variance (ANOVA) followed by Bonferroni's correction in post-hoc analysis was

and severity of head injury were considered as its potential determinants.

cells into the blood (Briggs et al., 1999).

as cited in Buttarello & Plebani, 2008).

(GCS 8-13) and severe (GCS 3-7).

applied.

A total of eighty patients were included in the study. The mean age was 33.5±13.9 years; there were 70 (87.5%) males. The head injury was mild (GCS 14-15) in 17(21.3%) patients, moderate (GCS 8-13) in 21(26.2%) patients and severe (GCS 3-7) in 42 patients (52.5%). The overall admission day mean± S.D. leukocyte count and median (IQR) immature granulocyte counts were 14,062 ± 5383 cells/cumm and 0.07 (0-1.54) cells/cumm respectively. Mortality rate of 28.8% (23) was observed in the study group during the course of their hospital stay. The mean WBC count was associated with the severity of head injury according to the GCS scores, pupillary reaction and CT scan findings and the results were tabulated (table 1). The head injury patients with low GCS scores (3-7) had higher mean WBC counts compared to moderate and mild head injury groups (p<0.001). Head injured patients with bilaterally absent pupillary reaction had higher mean WBC counts compared to unilaterally present and bilaterally present pupillary reaction groups (p<0.001). However, the mean WBC count between the unilaterally present and bilaterally present pupillary reaction groups was not significant (p<1.00). Statistically significant association was not observed between the mean WBC count and CT scan findings. The results of the comparison between the median IG count and the other variables are shown in table 2. The median IG count in the, CT scan findings, SAH group was significantly lower than groups with other CT scan findings the non SAH group (p=0.04).

To dichotomize the variables, cut-offs were derived for the WBC and the IG counts. The mean WBC count among the survivors and non survivors was 12,096 ± 3842 cells/cumm and 18,934±1172 cells/cumm respectively. Similarly, the median range IG count among the survivors and non survivors was 0.07 (0-0.26) cells/cumm and 0.13 (0-1.54) cells/cumm respectively. The mean value of WBC and IG count among survivors was taken as the cut off and variables were entered in to bivariate analysis to derive the significant factors.The mean value of WBC and IG count among survivors was taken as the cut off and variables were entered in to bivariate analysis to determine the significant independent role of these investigations in head injury patients. The results of bivariate and multivariate logistic regression are shown in table 3. The non survivors had high WBC counts (>12,096 cells/cumm, p<0.0001), severe head injury (GCS 3-7, p<0.001) and higher abnormal pupillary reaction (unilaterally present and bilaterally absent pupillary reaction, p<0.01) compared to the survivors. Multivariate logistic regression analysis to determine the correlation of each individual factor with mortality revealed only high WBC count [OR (95% CI): 4.9 (0.8-29.5)] and severe head injury (GCS 3-7) [OR (95% CI): 4.4 (0.9-21.2)] to be independent significant predictors of mortality. Bilaterally absent pupillary responses was not found to be statistically significant in predicting mortality, thus it should not always be associated with a hopeless outcome.

The Leukocyte Count, Immature Granulocyte

demonstrated by Rovlias & Kotsou.

patients such as blunt trauma victims.

**Variables Alive** 

WBC count >12,096

Head Injury

Pupillary reaction

Bilaterally and Unilaterally

**(n=57)** 

WBC count Cut off = 12,096 cells/cumm; IG count Cut off = 0.07 cells/cumm

Results of bivariate and multivariate logistic regression analysis

**Dead (n=23)** 

cells/cumm 26 (45.6) 21(91.3) 0.001 0.0001 12.5(2.6 - 58.4) **4.9 (0.8-29.5)** 

Severe 22(38.5) 20(86.9) 15.42 0.001 10.6 (2.8-39.9) **4.4 (0.9-21.2)** 

IG count > 0.07 cells/cumm 25(43.8) 14(60.8) 1.89 0.13 2.0 (0.7 -5.3) \_\_

absent(Abnormal) 12(21.0) 11(47.8) 5.73 0.01 3.43 (1.2- 9.6) \_\_

Table 3. Association of various factors with the death as outcome in head injured patients:

**χ2 Value**

**p value**  **Unadjusted odds ratio (95% CI)** 

**Adjusted odds ratio (95% CI)** 

**2.4 Discussion** 

Count and Immediate Outcome in Head Injury Patients 147

Few authors have studied the association between WBC count, outcome and head injury. Keskil et al illustrated in a study of 153 head trauma patients that WBC count exceeding 20 x 106/l was associated with poor clinical grade on admission and high mortality compared to those patients with normal or slightly above normal WBC counts (Keskil et al.,1994). Rovlias & Kotsou did a prospective analysis of 125 patients of severe head injury to study the prognostic significance of WBC counts in these patients. Patients with severe head injury had significantly higher white blood cell counts than did those with moderate or minor injury (p < 0.001). Among the patients with severe head injury, a significant relationship was found between WBC counts and Glasgow Coma Scale score, pupillary reaction, and presence of subarachnoid haemorrhage (p < 0.001). WBC counts were also found to be an independent significant predictor of outcome on multivariate analysis (Rovlias & Kotsou, 2001). Our results were concordant to that demonstrated by Rovlias & Kotsou. (Rovlias & Kotsou, 2001). Our results were concordant to that

Akin results were also seen in the study by Kan et al, wherein 146 children with Severe TBI were evaluated in attempt to establish the prognostic factors of severe TBI. They observed that a low coma score upon admission was independently associated with poor outcome, also the presence of diabetes insipidus within 3 days post-TBI (OR: 1.9), hyperglycemia (OR: 1.2), prolonged PT ratio (OR: 2.3) and leukocytosis (OR: 1.1) were associated with poorer outcome (Khan et al., 2009). In a study by Gurkanlar et al on 59 patients of head trauma, it was shown that WBC count exceeding 17.5x106/l had a predictive value for poor GCS score and long hospital stay. Similarly, CT progression was significantly seen in patients with moderate and severe head injury. Other studies in the literature were done on either trauma patients overall or on specific type of trauma


Table 1. Comparison of mean WBC counts in various Clinical parameters in Head Injury patients: Results of one way analysis of variance (ANOVA) and Bonferroni correction


Table 2. Median (Inter quartile range) Immature Granulocytes (IG) counts in head injury patients: Results of Kruskal-Wallis Test and overall comparison using one way ANOVA & Bonferroni correction

#### **2.4 Discussion**

146 Brain Injury – Pathogenesis, Monitoring, Recovery and Management

**WBC (Mean ± S.D.)**

17495.2 ± 4687.4 11114.2 ± 3557.7 9223.5 ± 1933.7

19533.3 ± 5884.8 13227.2 ± 6103.9 13071.9 ± 4458.2

11985.7 ± 4250.2

15878.9 ± 6878.1

14727.2 ± 5828.0

14063.6 ± 4582.7

**IG median (range)** 

0.85 (0-1.5) 0.05 (0-0.5) 0.07 (0-0.3)

0.05 (0-1.3) 0.09 (0-0.3) 0.07 (0-1.5)

0.08 (0-0.1) 0.08 (0-1.5) 0.04 (0-0.2)

0.08 (0-1.3)

Table 2. Median (Inter quartile range) Immature Granulocytes (IG) counts in head injury patients: Results of Kruskal-Wallis Test and overall comparison using one way ANOVA &

Table 1. Comparison of mean WBC counts in various Clinical parameters in Head Injury patients: Results of one way analysis of variance (ANOVA) and Bonferroni correction

**(n)** 

42 21 17

12 11 57

14 19 11

33

**Statistical Significance**

> F = 34.1; p = 0.0001

> F = 8.72; p = 0.0004

F = 1.46; p = 0.23

**Statistical Significance** 

> χ 2 = 3.48; p = 0.17

χ 2 = 0.4; p = 0.78

χ 2 = 9.68; p = 0.04

**Post Hoc Analysis p value** 

Severe vs. Moderate : 0.001 Severe vs. Mild : 0.001

B/L absent vs. U/L absent : 0.009 U/L absent vs. B/L present : 1.000 B/L absent vs. B/L present : 0.000

\_\_\_

**Post Hoc Analysis p value** 



SAH vs. EDH- p<0.05 SAH vs. SDH - p=0.05 SAH vs. ICH - p<0.05

**Variables Frequency**

**Head injury (HI)** Severe HI Moderate HI Mild HI

**Pupillary reaction** Bilaterally (B/L)

> absent Unilaterally (U/L) absent Bilaterally (B/L)

present

**CT scan finding** Extra Dural Hemorrhage (EDH) Sub Dural Hemorrhage (SDH) Sub Arachnoid Hemorrhage (SAH) Intra Cerebral Hemorrhage (ICH) and contusion

**Head injury(HI)** Severe HI Moderate HI Mild HI

**Pupillary reaction** 

**CT scan finding** 

(SAH)

Bilaterally (B/L) absent Unilaterally (U/L) absent Bilaterally (B/L) present

Extra Dural Hemorrhage (EDH) Sub Dural Hemorrhage (SDH) Sub Arachnoid Hemorrhage

Intra Cerebral Hemorrhage (ICH) and contusion

Bonferroni correction

**(n)**

42 21 17

12 11 57

14

19

11

33

**Variables Frequency**

Few authors have studied the association between WBC count, outcome and head injury. Keskil et al illustrated in a study of 153 head trauma patients that WBC count exceeding 20 x 106/l was associated with poor clinical grade on admission and high mortality compared to those patients with normal or slightly above normal WBC counts (Keskil et al.,1994). Rovlias & Kotsou did a prospective analysis of 125 patients of severe head injury to study the prognostic significance of WBC counts in these patients. Patients with severe head injury had significantly higher white blood cell counts than did those with moderate or minor injury (p < 0.001). Among the patients with severe head injury, a significant relationship was found between WBC counts and Glasgow Coma Scale score, pupillary reaction, and presence of subarachnoid haemorrhage (p < 0.001). WBC counts were also found to be an independent significant predictor of outcome on multivariate analysis (Rovlias & Kotsou, 2001). Our results were concordant to that demonstrated by Rovlias & Kotsou. (Rovlias & Kotsou, 2001). Our results were concordant to that demonstrated by Rovlias & Kotsou.

Akin results were also seen in the study by Kan et al, wherein 146 children with Severe TBI were evaluated in attempt to establish the prognostic factors of severe TBI. They observed that a low coma score upon admission was independently associated with poor outcome, also the presence of diabetes insipidus within 3 days post-TBI (OR: 1.9), hyperglycemia (OR: 1.2), prolonged PT ratio (OR: 2.3) and leukocytosis (OR: 1.1) were associated with poorer outcome (Khan et al., 2009). In a study by Gurkanlar et al on 59 patients of head trauma, it was shown that WBC count exceeding 17.5x106/l had a predictive value for poor GCS score and long hospital stay. Similarly, CT progression was significantly seen in patients with moderate and severe head injury. Other studies in the literature were done on either trauma patients overall or on specific type of trauma patients such as blunt trauma victims.


WBC count Cut off = 12,096 cells/cumm; IG count Cut off = 0.07 cells/cumm

Table 3. Association of various factors with the death as outcome in head injured patients: Results of bivariate and multivariate logistic regression analysis

The Leukocyte Count, Immature Granulocyte

reported (Bruegel et al., 2004).

Lari et al., 2003)

study.

Rovlias et al.

**3. Conclusion** 

had subarachnoid haemorrhage.

analyzer reducing the need for manual differentials.

Count and Immediate Outcome in Head Injury Patients 149

trials. There are no accredited external quality assessment schemes (EQAS) available for this parameter. Nevertheless, this instrument has internal quality control material available for this parameter and has been proven to be accurate, precise and highly suitable as a screening

Bruegel et al. analyzed immature granulocytes in 156 healthy donors by using IG count and IMI channel. Men and women showed comparable values for IGs with the highest value of 0.03 x109/l for men and 0.06 x109/l for women. No age dependency for the IG counts was

In the study to determine the usefulness of immature granulocyte measurement as a predictor of infection or positive blood culture. Blood samples from 102 infected and 69 non infected patients were analyzed using the Sysmex XE-2100 automated blood cell counter (Sysmex, Kobe, Japan). The percentage of immature granulocytes was found to be significantly higher (P < .001) in infected than in non infected patients and in patients with positive than patients with negative blood cultures (P = .005). Also, a percentage of immature granulocytes of > 3 was observed to be a very specific predictor of sepsis. On comparing the results of immature granulocyte measurement with total WBC count and absolute neutrophil count (ANC), receiver operating characteristic curves (ROC) showed that the percentage of immature granulocytes was a better predictor of infection than the WBC count and comparable to the ANC. They concluded that immature granulocyte measurements reflect a biologically and clinically relevant phenomenon but are not sensitive enough to be used as screening assays for prediction of infection or bacteremia. However, although infrequently encountered, a percentage of immature granulocytes of more than 3 might help expedite microbiologic laboratory evaluation of a subset of patients. (Ali Ansari-

In the present study, the role of admission WBC and IG count as prognostic determinants of mortality in isolated head injury patients was investigated. The study revealed that the mean WBC count was high in patients with severe (GCS 3-7) head injury and bilaterally absent pupillary reaction groups. The independent significant determinants of mortality due to head injury were high WBC count (>12,096 cells/cumm) and severe head injury (GCS 3-7). IG count was not found to be a potential determinant of mortality in this

We observed high WBC counts in the non survivors compared to the survivors and the difference was statistically significant (p<0.001). Similar results were observed by

We found that the IG count in patients with subdural haemorrhage, extradural hemorrhage, intracerebral hemorrhage and contusion was significantly higher than those patients who

Leukocytosis at initial examination is associated with adverse prognosis in trauma patients. High admission WBC count (>12,096 cells/cumm) and low GCS scores (3-7) portends a worse prognosis in isolated head trauma patients. Percentage of immature granulocytes correlates with CT findings (p=0.04) of Head injury patients, but its association with severity of injury and mortality is clinically insignificant. More prospective studies would be

Chang et al did a prospective analysis of 786 trauma victims and found ISS >15, GCS≤8 and white race to be associated with increase in white cell count. Their study included all trauma patients irrespective of the site of injury (Chang et al., 2003). WBC count as a laboratory marker has also been studied in blunt trauma patients to predict the severity of injury (Santucci et al., 2008).

Schnüriger et al conducted a study to ascertain the significance of serial white blood cell (WBC) counts in trauma patients with a suspected hollow viscus injury (HVI), on an overall study population of 5,950. A significant relationship between increasing Injury Severity Score and increasing WBC count on admission was found by linear regression and they concluded that WBC count elevation on admission is nonspecific and does not predict the presence of Hollow Viscus Injury (HVI) (Schnüriger et al., 2010).

Similarly, in the study done on 805 trauma patient, to test the diagnostic use of white blood cell (WBC) count in differentiating major from minor injuries. Paladino et al. concluded that WBC count was not a useful addition as a diagnostic indicator of major trauma in their study population (Paladino et al., 2010).

While the WBC had moderate discriminatory capability for serious injury, was not considered to be a reliable independent marker to rule in or out serious injury. Nevertheless, the use of WBC on presentation to the emergency department as an adjunct for making disposition decisions is recommended.

Rovlias & Kotsou observed that, WBC counts were significantly higher in those with an unfavorable outcome (p < 0.001) i.e. a high mean± S.D.WBC count of 18144.93±467/cumm was seen in patients with unfavourable outcome (severe disability, persistent vegetative state, dead) in contrast to a mean± S.D. WBC count of 13711.85±415.61/cumm in patients with a favourable outcome, i.e. good recovery, moderate disability (Rovlias & Kotsou, 2001). In another study, the mean WBC count was higher i.e. 21.1x106/l in patients with Glasgow outcome score (GOS) of one (death) and comparatively low i.e. 12.3x106/l when the GOS was five (good recovery) (Gürkanlar et al., 2009). Keskil et al showed in a prospective analysis, a low mortality rate (23%) in patients with WBC counts less than 20x106/l Compared to those with counts more than 20x106/l (mortality rate 96%) (Keskil et al., 1994). The present study showed that a high WBC count (>12,096 cells/cumm) [OR (95% CI): 4.9 (0.8-29.5)] and severe head injury (GCS 3-7) [OR (95% CI): 4.4 (0.9-21.2)] to be independent significant predictors of mortality.

Rangarajan et al. in their study designed to find out the factors influencing mortality in acutely injured trauma patients receiving massive blood transfusion (MBT). They observed a total leukocyte count (TLC) ≥ 10,000 cells/cubic mm, GCS ≤ 8, the presence of coagulopathy and major vascular surgery as four independent determinants of mortality in multivariate logistic regression analysis (Rangarajan et al., 2011).

Immature granulocyte count is a recently introduced parameter in the automated hematology analyzers that provides the number of promyelocytes, myelocytes and metamyelocytes in the peripheral blood. The presence of low numbers of immature granulocytes is more reliably detected on automated hematology analyzers than using manual microscopy (Ali Ansari-Lari et al., 2003; Briggs, 2003, 2009; Iddles et al., 2007). The performance analysis of the automated hematology analyzer for this parameter has been performed earlier (Walters & Garrity, 2000). The immature granulocyte parameter measured using Sysmex-2100 is presently used only for research purposes and in the context of clinical decision making requires more prospective

Chang et al did a prospective analysis of 786 trauma victims and found ISS >15, GCS≤8 and white race to be associated with increase in white cell count. Their study included all trauma patients irrespective of the site of injury (Chang et al., 2003). WBC count as a laboratory marker has also been studied in blunt trauma patients to predict the severity of injury

Schnüriger et al conducted a study to ascertain the significance of serial white blood cell (WBC) counts in trauma patients with a suspected hollow viscus injury (HVI), on an overall study population of 5,950. A significant relationship between increasing Injury Severity Score and increasing WBC count on admission was found by linear regression and they concluded that WBC count elevation on admission is nonspecific and does not predict the

Similarly, in the study done on 805 trauma patient, to test the diagnostic use of white blood cell (WBC) count in differentiating major from minor injuries. Paladino et al. concluded that WBC count was not a useful addition as a diagnostic indicator of major trauma in their

While the WBC had moderate discriminatory capability for serious injury, was not considered to be a reliable independent marker to rule in or out serious injury. Nevertheless, the use of WBC on presentation to the emergency department as an adjunct for making

Rovlias & Kotsou observed that, WBC counts were significantly higher in those with an unfavorable outcome (p < 0.001) i.e. a high mean± S.D.WBC count of 18144.93±467/cumm was seen in patients with unfavourable outcome (severe disability, persistent vegetative state, dead) in contrast to a mean± S.D. WBC count of 13711.85±415.61/cumm in patients with a favourable outcome, i.e. good recovery, moderate disability (Rovlias & Kotsou, 2001). In another study, the mean WBC count was higher i.e. 21.1x106/l in patients with Glasgow outcome score (GOS) of one (death) and comparatively low i.e. 12.3x106/l when the GOS was five (good recovery) (Gürkanlar et al., 2009). Keskil et al showed in a prospective analysis, a low mortality rate (23%) in patients with WBC counts less than 20x106/l Compared to those with counts more than 20x106/l (mortality rate 96%) (Keskil et al., 1994). The present study showed that a high WBC count (>12,096 cells/cumm) [OR (95% CI): 4.9 (0.8-29.5)] and severe head injury (GCS 3-7) [OR (95% CI): 4.4 (0.9-21.2)] to be independent significant predictors of

Rangarajan et al. in their study designed to find out the factors influencing mortality in acutely injured trauma patients receiving massive blood transfusion (MBT). They observed a total leukocyte count (TLC) ≥ 10,000 cells/cubic mm, GCS ≤ 8, the presence of coagulopathy and major vascular surgery as four independent determinants of mortality in multivariate

Immature granulocyte count is a recently introduced parameter in the automated hematology analyzers that provides the number of promyelocytes, myelocytes and metamyelocytes in the peripheral blood. The presence of low numbers of immature granulocytes is more reliably detected on automated hematology analyzers than using manual microscopy (Ali Ansari-Lari et al., 2003; Briggs, 2003, 2009; Iddles et al., 2007). The performance analysis of the automated hematology analyzer for this parameter has been performed earlier (Walters & Garrity, 2000). The immature granulocyte parameter measured using Sysmex-2100 is presently used only for research purposes and in the context of clinical decision making requires more prospective

presence of Hollow Viscus Injury (HVI) (Schnüriger et al., 2010).

study population (Paladino et al., 2010).

disposition decisions is recommended.

logistic regression analysis (Rangarajan et al., 2011).

(Santucci et al., 2008).

mortality.

trials. There are no accredited external quality assessment schemes (EQAS) available for this parameter. Nevertheless, this instrument has internal quality control material available for this parameter and has been proven to be accurate, precise and highly suitable as a screening analyzer reducing the need for manual differentials.

Bruegel et al. analyzed immature granulocytes in 156 healthy donors by using IG count and IMI channel. Men and women showed comparable values for IGs with the highest value of 0.03 x109/l for men and 0.06 x109/l for women. No age dependency for the IG counts was reported (Bruegel et al., 2004).

In the study to determine the usefulness of immature granulocyte measurement as a predictor of infection or positive blood culture. Blood samples from 102 infected and 69 non infected patients were analyzed using the Sysmex XE-2100 automated blood cell counter (Sysmex, Kobe, Japan). The percentage of immature granulocytes was found to be significantly higher (P < .001) in infected than in non infected patients and in patients with positive than patients with negative blood cultures (P = .005). Also, a percentage of immature granulocytes of > 3 was observed to be a very specific predictor of sepsis. On comparing the results of immature granulocyte measurement with total WBC count and absolute neutrophil count (ANC), receiver operating characteristic curves (ROC) showed that the percentage of immature granulocytes was a better predictor of infection than the WBC count and comparable to the ANC. They concluded that immature granulocyte measurements reflect a biologically and clinically relevant phenomenon but are not sensitive enough to be used as screening assays for prediction of infection or bacteremia. However, although infrequently encountered, a percentage of immature granulocytes of more than 3 might help expedite microbiologic laboratory evaluation of a subset of patients. (Ali Ansari-Lari et al., 2003)

In the present study, the role of admission WBC and IG count as prognostic determinants of mortality in isolated head injury patients was investigated. The study revealed that the mean WBC count was high in patients with severe (GCS 3-7) head injury and bilaterally absent pupillary reaction groups. The independent significant determinants of mortality due to head injury were high WBC count (>12,096 cells/cumm) and severe head injury (GCS 3-7). IG count was not found to be a potential determinant of mortality in this study.

We observed high WBC counts in the non survivors compared to the survivors and the difference was statistically significant (p<0.001). Similar results were observed by Rovlias et al.

We found that the IG count in patients with subdural haemorrhage, extradural hemorrhage, intracerebral hemorrhage and contusion was significantly higher than those patients who had subarachnoid haemorrhage.

### **3. Conclusion**

Leukocytosis at initial examination is associated with adverse prognosis in trauma patients. High admission WBC count (>12,096 cells/cumm) and low GCS scores (3-7) portends a worse prognosis in isolated head trauma patients. Percentage of immature granulocytes correlates with CT findings (p=0.04) of Head injury patients, but its association with severity of injury and mortality is clinically insignificant. More prospective studies would be

The Leukocyte Count, Immature Granulocyte

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required to evaluate the role of IG count as a marker of head injury in a larger study population, also to assess whether immature granulocyte measurements could be combined with other markers to create an algorithm with better diagnostic sensitivity or specificity.

#### **4. Acknowledgment**

We would like to thank Dr Kanchana Rangarajan, Senior Resident at the department of laboratory medicine, Trauma Center, AIIMS, for dedicated work and support. Mr Bhupender for helping in the statistical analysis of the study.

Prof. Dr. Mahesh Chandra Misra , Chief of Trauma Center for providing the ammenities and facilities, that made this study possible.

#### **5. References**


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We would like to thank Dr Kanchana Rangarajan, Senior Resident at the department of laboratory medicine, Trauma Center, AIIMS, for dedicated work and support. Mr

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**8** 

*India* 

**Animal Models of Retinal Ischemia** 

*Postgraduate Institute of Medical Education and Research, Chandigarh* 

Retinal ischemia is a frequent source of irreparable visual impairment and even loss of sight, affecting over a hundred million individuals in the world. It is associated with a wide range of clinical retinal disorders, like ischemic optic neuropathies, obstructive retinopathies, carotid occlusive disorders, diabetic retinopathy and glaucoma. Retinal ischemia occurs when the blood supply to retina is inadequate to meet the metabolic requirements of the retina. If treatment is not given to fix this imbalance, the outcome is irreversible, ischemic and apoptotic cascades resulting in cell death. Appropriate study models, particularly animal models, are necessary for further understanding the etiology, pathology, and evolution of retinal ischemia and also in order to help in the evaluation, development, and improvement of therapeutic strategies. Accordingly, quite a few *in-vivo* and *ex-vivo* mammalian models have been developed to study this syndrome. The rat models of retinal ischemia are frequently used, because the distribution of retinal and choroidal blood supply

The retina has been extensively used for the study of pathophysiology of ischemia and mechanism of damage triggered by ischemia and excitotoxicity. Compared to all the other tissues, retina has a higher metabolic rate; any disturbance in blood supply can have an effect on the supply of oxygen and the substrates leading to retinal ischemia. The retina has a dual blood supply. The photoreceptors and most of the outer plexiform layer (OPL) are nourished by choriocapillaries, while the inner retinal layers are nourished by the central retinal artery. The actual effects of retinal ischemia vary, depending on the position of the occlusion. It is clear that occlusion of the retinal artery leads to inner retinal ischemia only, but occlusion of ophthalmic artery leads to global retinal ischemia, as it supplies blood to

The retina of mammals is a functionally specialised tissue. It is capable of light detection and perception as well as processing and transmission of the information received to the central nervous system. It has two major elements – the neurosensory retina and the pigment epithelium (RPE). During the embryonic development, the RPE and neural development are

**1. Introduction** 

is quite similar to that in humans.

**2. Retinal architecture** 

Corresponding Author

 \*

the central retinal artery as well as choriocapillaries.

Gillipsie Minhas and Akshay Anand\*

*Neuroscience Research Lab, Department of Neurology* 

