**Recent Progress in the Identification of Non-Invasive Biomarkers to Support the Diagnosis of Alzheimer's Disease in Clinical Practice and to Assist Human Clinical Trials**

Francois Bernier, Pavan Kumar, Yoshiaki Sato and Yoshiya Oda

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/60008

**1. Introduction**

Alzheimer's disease (AD) is a neurodegenerative disorder that manifests itself by progressive dementia accompanied by memory deterioration usually in elderlies and is becoming the public health crisis of the 21st century. Currently, there are an estimated 35 Million patients affected by the disease, and this number is expected to burgeon to 115 million by the year 2050 (WHO, 2012). In the United States alone, one patient is diagnosed with AD every 67 seconds according to the Alzheimer's Association website.

This situation is very alarming since Alzheimer's disease has been a graveyard for drug developers with an astonishing 99.6% of trials of potential Alzheimer's treatments aimed at preventing, curing or improving the symptoms of the disease failing or being discontinued from 2002 to 2014 [1]. Although there are FDA approved drugs available including acetylcho‐ line esterase inhibitors (donepezil, rivastigmine, galantamine) and the NMDA receptor antagonist memantine that have been useful in temporarily alleviating short-term memory problems or improving daily functions, they are ineffective in stopping disease progression.

AD is characterized by the presence of amyloid plaques in brain and it is hypothesized that the increase levels of toxic Amyloid beta oligomers and protofibrils leads to Tau neurofibrillary tangles formation, loss of synaptic connections and selective neuronal cell death in the brain (Figure 1) and this sequence of events is referred as the amyloid cascade hypothesis [2]. The amyloid plaques are mostly composed of amyloid-beta peptides (Abeta 40-42) thought to be

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

toxic once they self-aggregate and subsequently bind to a cell surface to disrupt neuronal signaling and cell viability [3]. It is initially thought that downstream to this event is the formation of neurofibrillary tangles composed of hyperphosphorylated Tau protein. Such hyperphosphorylation is an indicator of neuronal cell death in numerous neurodegenerative disorders or brain injuries [4, 5] indicating that both abnormal processes can take place independently [6]. Two key enzymes necessary for the cleavage of the Amyloid Precursor Protein (APP) to generate Amyloid-beta peptides are the gamma and beta-secretase. Accord‐ ing to the amyloid cascade, it is thought that developing Inhibitors of those enzymes would prevent amyloid formation and stop disease progression. Several companies have therefore been testing such inhibitors in human trials. Unfortunately, this has proven to be harder than anticipated. While Bace1 inhibitors trials outcomes are not yet known at the time of this writing, gamma-secretase inhibitors had disappointing results in late-stage trials where worsening of cognition was observed [7]. The reason for this is not totally clear, but the fact that gammasecretase is responsible for the cleavage of multiple substrates including NOTCH protein may have been a contributing factor.

**Figure 1.** Transmembrane APP protein can be cleaved by three proteases; Beta, Alpha, and Gamma-secretase. Cleavage by B-secretase and G-secretase produces Abeta peptides (mainly 40 and 42). Aggregation of Abeta peptides into toxic oligomers and protofibrils to brain cells is a critical event prior to Abeta plaques formation and disruption of neuronal function and cellular loss.

Other clinical approaches around the amyloid cascade are focusing on passive immunization using administered human monoclonal antibodies against the amyloid-beta peptides, oligom‐ ers, protofibrils or plaques [8-10]. Several advanced phase 2 and 3 trials are still ongoing (Table 1) but at least one phase 3 trial outcome, although it did not meet its endpoints has revealed that patients with the mild form of the disease seemed to respond better to treatment [11, 12].

Based on this data, it appears that it might be too late to stop disease progression in patient with mild-to-moderate to severe AD patients with anti-amyloid therapies, so companies are now focusing their efforts on testing those drugs, including beta-secretase inhibitors, in early Mild Cognitive Impairment patients (MCI) which are known to convert to AD more rapidly, especially if patients test positive for amyloid deposition using Positron Emission Tomography scans (PET) [13, 14]. It also comes as no surprise that companies developing these new therapies are now adding being positive on amyloid PET scan as entry criteria in recent clinical trials [15] (table1). Unfortunately, the cost of amyloid PET imaging is very expensive, and PET centers are not currently available worldwide [16-18]. Even if Amyloid-PET is proven to be useful to identify a target patient population, it is important to also develop a non-invasive biomarker that could either be singly used to identify amyloid positive patients or used as a first-line test before Amyloid PET imaging confirmation.


Source: Clinicaltrial.Gov and various press releases.

#### **Table 1.** Please add caption

toxic once they self-aggregate and subsequently bind to a cell surface to disrupt neuronal signaling and cell viability [3]. It is initially thought that downstream to this event is the formation of neurofibrillary tangles composed of hyperphosphorylated Tau protein. Such hyperphosphorylation is an indicator of neuronal cell death in numerous neurodegenerative disorders or brain injuries [4, 5] indicating that both abnormal processes can take place independently [6]. Two key enzymes necessary for the cleavage of the Amyloid Precursor Protein (APP) to generate Amyloid-beta peptides are the gamma and beta-secretase. Accord‐ ing to the amyloid cascade, it is thought that developing Inhibitors of those enzymes would prevent amyloid formation and stop disease progression. Several companies have therefore been testing such inhibitors in human trials. Unfortunately, this has proven to be harder than anticipated. While Bace1 inhibitors trials outcomes are not yet known at the time of this writing, gamma-secretase inhibitors had disappointing results in late-stage trials where worsening of cognition was observed [7]. The reason for this is not totally clear, but the fact that gammasecretase is responsible for the cleavage of multiple substrates including NOTCH protein may

**Figure 1.** Transmembrane APP protein can be cleaved by three proteases; Beta, Alpha, and Gamma-secretase. Cleavage by B-secretase and G-secretase produces Abeta peptides (mainly 40 and 42). Aggregation of Abeta peptides into toxic oligomers and protofibrils to brain cells is a critical event prior to Abeta plaques formation and disruption of neuronal

Other clinical approaches around the amyloid cascade are focusing on passive immunization using administered human monoclonal antibodies against the amyloid-beta peptides, oligom‐ ers, protofibrils or plaques [8-10]. Several advanced phase 2 and 3 trials are still ongoing (Table 1) but at least one phase 3 trial outcome, although it did not meet its endpoints has revealed that patients with the mild form of the disease seemed to respond better to treatment [11, 12]. Based on this data, it appears that it might be too late to stop disease progression in patient with mild-to-moderate to severe AD patients with anti-amyloid therapies, so companies are

have been a contributing factor.

226 Alzheimer's Disease - Challenges for the Future

function and cellular loss.

In this book chapter, we will review the recent progress in the development of non-invasive AD biomarkers that could be used for such purpose by various research groups with a focus on AD biomarkers our group recently identified in patients' plasma.

## **2. The diagnosis of Alzheimer' Disease and the need for non-invasive markers**

The disease is difficult to diagnose correctly even with the availability of cognitive tests and sophisticated Imaging technologies that include MRI, FDG-PET and Amyloid PET imaging. Currently, a diagnosis of probable AD is made using NINCDS-ADRDA criteria but this is usually possible when the condition has developed and progressed to a point where neuronal cell death and/or irreparable damages have already occurred [19]. While the accuracy of this test was thought to be around 80-90% when it was developed in the early 80's, it's accuracy, especially to diagnose patients at the early stage of the disease, is much lower which further complicates AD biomarker discovery.

The inability to correctly diagnose AD has also probably negatively affected the development of novel therapies aiming at stopping the amyloid cascade via gamma-secretase inhibitors as well passive immunization therapies using antibodies against abeta peptides or abeta plaques [7, 11]. The possible inclusion of patients suffering from non-AD dementia in those trials may have been a contributing factor to those failures.

As a result, research efforts have intensified exponentially in the recent years to identify and develop biomarkers that could be used for diagnosing AD early to support clinical practice and clinical drug development [20].

Much of these efforts have initially focus on looking at pathological changes of amyloid beta peptides, Abeta 40/42 in CSF as well as P-Tau and T-Tau and has eventually led to the development of a model that define Alzheimer's disease progression [6, 21, 22]. In that original model, gradual reduction in Abeta 42 is observed in CSF, presumably due to the aggregation of the peptide in brain and formation of plaques which is followed by gradual elevation of P-TAU and TAU in CSF, indicators of neuronal cell death or injury[23, 24]. The model was initially received with great interest because it described the temporal evolution of AD biomarkers in relation to each other and the onset and progression of clinical symptoms. However, emerging evidence appeared that challenges this model's assumptions. Refinements to the model now include indexing of individuals by the time rather than clinical symptom severity.; incorporation of inter-individual cognitive impairment variability in relation to AD pathophysiology progression; modifications to when some biomarkers changes sequentially appear; and acknowledgement that the two major proteinopathies in AD, amyloid beta (Abeta) and tau, might be initiated separately from one another in sporadic AD[6].

Although useful to assist clinical diagnosis of AD with enough sensitivity and specificity [23, 25], stiff barriers exist that prevent the comprehensive utilization of those markers by physi‐ cians and especially primary care doctors. Lumbar puncture, for example, that is required to collect CSF is still a delicate medical intervention in several developed countries and is also accompanied by increased frequency of headaches [26].The nature of the Amyloid peptides itself is also complicating the picture. Recent data have indeed shown that the Abeta 42 peptides are prone to stick to collection tubes and their detected concentration is affected by various parameters such as storage temperature, volume and thawing [27-29], probably explaining the frequent lack of correlation between labs using the same immunoassay kits.

Separately to CSF analysis, the research field has also developed a series of imaging approaches to assist clinical diagnosis such as Volumetric Magnetic Resonance Imaging (MRI) (to measure brain areas volume), FDG-PET and Amyloid PET imaging. Those are useful but currently provide only prognostic value to predict the likelihood to convert from MCI to AD [30, 31]. Amyloid PET tracers such as Pittsburgh Compound B and two new tracers, florbetapir-18 and flutemetamol-18, are approved as an *in vitro* diagnostic (IVD) but only to rule out possible AD pathology since a significant % of patients that test positive might never develop the disease [32]. Moreover, Positron Emission Tomography (PET) is very costly, and the scarcity of centers capable to handle this technology is still an issue in many countries. In UK, for example, only ~30 centers can perform this test, and the numbers are even lower in countries such as China [33]. These agents, although not reimbursed in US and other countries, are now proving useful to assist the development of novel drugs aiming to test the amyloid cascade hypothesis and are being used as enrollment criteria by several companies developing beta-secretase inhibitors as well as passive immunotherapies using anti-amyloid antibodies (Table 1). If these new therapies succeed, the availability of Amyloid-PET imaging as Companion Diagnostic (CDx) will still present the issues mentioned here as well as create additional economic burden on many healthcare systems. It is therefore accepted that having a first-line non-invasive diag‐ nostic blood test comparable to Amyloid PET imaging would be precious in the clinical setting and could be used in tandem to diagnose patients correctly.

## **3. Recent progress in AD biomarker discoveries**

#### **3.1. Amyloid beta peptides and TAU in blood**

The inability to correctly diagnose AD has also probably negatively affected the development of novel therapies aiming at stopping the amyloid cascade via gamma-secretase inhibitors as well passive immunization therapies using antibodies against abeta peptides or abeta plaques [7, 11]. The possible inclusion of patients suffering from non-AD dementia in those trials may

As a result, research efforts have intensified exponentially in the recent years to identify and develop biomarkers that could be used for diagnosing AD early to support clinical practice

Much of these efforts have initially focus on looking at pathological changes of amyloid beta peptides, Abeta 40/42 in CSF as well as P-Tau and T-Tau and has eventually led to the development of a model that define Alzheimer's disease progression [6, 21, 22]. In that original model, gradual reduction in Abeta 42 is observed in CSF, presumably due to the aggregation of the peptide in brain and formation of plaques which is followed by gradual elevation of P-TAU and TAU in CSF, indicators of neuronal cell death or injury[23, 24]. The model was initially received with great interest because it described the temporal evolution of AD biomarkers in relation to each other and the onset and progression of clinical symptoms. However, emerging evidence appeared that challenges this model's assumptions. Refinements to the model now include indexing of individuals by the time rather than clinical symptom severity.; incorporation of inter-individual cognitive impairment variability in relation to AD pathophysiology progression; modifications to when some biomarkers changes sequentially appear; and acknowledgement that the two major proteinopathies in AD, amyloid beta (Abeta)

Although useful to assist clinical diagnosis of AD with enough sensitivity and specificity [23, 25], stiff barriers exist that prevent the comprehensive utilization of those markers by physi‐ cians and especially primary care doctors. Lumbar puncture, for example, that is required to collect CSF is still a delicate medical intervention in several developed countries and is also accompanied by increased frequency of headaches [26].The nature of the Amyloid peptides itself is also complicating the picture. Recent data have indeed shown that the Abeta 42 peptides are prone to stick to collection tubes and their detected concentration is affected by various parameters such as storage temperature, volume and thawing [27-29], probably explaining the frequent lack of correlation between labs using the same immunoassay kits. Separately to CSF analysis, the research field has also developed a series of imaging approaches to assist clinical diagnosis such as Volumetric Magnetic Resonance Imaging (MRI) (to measure brain areas volume), FDG-PET and Amyloid PET imaging. Those are useful but currently provide only prognostic value to predict the likelihood to convert from MCI to AD [30, 31]. Amyloid PET tracers such as Pittsburgh Compound B and two new tracers, florbetapir-18 and flutemetamol-18, are approved as an *in vitro* diagnostic (IVD) but only to rule out possible AD pathology since a significant % of patients that test positive might never develop the disease [32]. Moreover, Positron Emission Tomography (PET) is very costly, and the scarcity of centers capable to handle this technology is still an issue in many countries. In UK, for example, only ~30 centers can perform this test, and the numbers are even lower in countries such as China [33]. These agents, although not reimbursed in US and other countries, are now proving useful to assist the development of novel drugs aiming to test the amyloid cascade hypothesis and

and tau, might be initiated separately from one another in sporadic AD[6].

have been a contributing factor to those failures.

and clinical drug development [20].

228 Alzheimer's Disease - Challenges for the Future

Given the apparent association between Abeta accumulation and increase of P-TAU and Tau in brain and CSF of AD patients, several studies have looked at the change of Abeta 40/42 ratio in serum and plasma as non-invasive AD marker. At least 14 studies including our own that examined the change in such ratio in AD have been conducted [34] but have produced mixed results. It is not clear why such discrepancy is observed, but several factors not only related to patient's selection but also to assays themselves and how samples were stored and handled are possible explanations. It should be noted that even the Alzheimer's Disease Neuroimaging Initiative study (ADNI) data could not link Abeta40/42 plasma ratios to clinical state [35].What further complicate the use of plasma Abeta as an AD marker is the fact that it is produced not only centrally but also in the periphery and the nature itself of the peptide which tend to stick to walls and aggregate on itself affect the epitopes available during ELISA assays [34, 36].

Recently, researchers have also looked at Abeta 1-17 as a possible diagnostic marker of AD. One report showed that free-to-cell bound ratio of Abeta 1-17 could discriminate Control, MCI and AD patients with high sensitivity and specificity [37]. Additionally, plasma BACE1 enzyme, one key enzyme essential for the generation of Abeta peptides as well as soluble APP beta (sAPPbeta) have been found to be elevated in one study in AD patients plasma [38]. Despite the challenge of reliably measure Abeta 1-42 in plasma, a group demonstrated that APP669-711 appeared to be an indicator of pathological change of Abeta1-42. Ratio of APP669-711 to Abeta1-42 (APP669-711/Abeta1-42) measured by MALDI-TOF mass spectra showed a very good correlation with PIB+ signal in brain, suggesting that this plasma biomarker could be developed as a surrogate marker of cerebral amyloid deposition[39].

As for Tau and P-Tau detection in blood, demonstrating association with AD has been very challenging [40], especially for P-TAU due to the presence of circulating phosphatases in blood [24, 41] and the fact that TAU/P-TAU is elevated in multiple types of dementia including brain injuries [42]. A recent paper reporting the increase of an enzyme-generated fragment of TAU in serum that is inversely associated with cognitive function [43] seems promising. Another recently developed assay using antibodies reacting to all TAU isoforms could show with greater sensitivity than usual EIA methods the elevation of total Tau in serum of patients suffering from severe brain ischemia [44].Another group described the finding of oligomeric form of TAU in AD patients platelets [45] providing 76% sensitivity and 80% specificity. Time will tell if these TAU assays will be useful as a screening tool to support AD diagnosis.

#### **3.2. Amyloid beta oligomers in blood**

Amyloid beta (Aβ), especially Aβ42 oligomers play a significant role in early Alzheimer's disease (AD) pathogenesis [46, 47].In fact, AD-associated inflammation has been thought to be a secondary response to the pathological lesions triggered by Aβ oligomers in the early stage of pathogenesis. Although several studies, including our own (unpublished) have shown an elevation of such oligomers in CSF [48-52], few studies have looked at the correlation between blood oligomers concentration. In one study, levels of plasma Aβ monomers, Aβ oligomers, and soluble tumor necrosis factor α receptors (sTNFRs) were evaluated by ELISA in 120 controls, 32 amnestic mild cognitive impairment (aMCI) patients, and 90 mild AD patients [53]. The study found that levels of Aβ oligomers were significantly increased by ~two fold in mild AD patients compared to levels in aMCI and healthy controls. Interestingly, plasma levels of sTNFR in aMCI and mild AD patients was elevated significantly compared to controls, and both sTNFR1 and sTNFR2 levels were associated with levels of Aβ oligomers in both aMCI and mild AD individuals. Interestingly, changes in Aβ oligomer concentrations and sTNFR levels correctly differentiated mild ADfrom healthy control subjects.

In a separate study [50], another group have demonstrated that their ELISA system using BAN50 can detect signals in 60% of serum samples and 80% of CSF samples obtained from non-demented subjects.


Although the levels of serum Abeta oligomers were reported to be unexpectedly high, the authors made the suggestion that the assay could be detecting non-pathological Abeta complexes associated with serum carrier proteins. Nonetheless, they did show a significant positive correlation with the levels obtained from matched CSF samples, suggesting that this assay system might be useful to support AD diagnosis.

## **4. Emerging blood-based AD biomarkers: Reproducibility of findings difficult**

Novel non-invasive AD biomarkers found in blood are emerging as being a composition of different proteins, metabolites or gene transcripts in blood cells or single analytes. In total, there are as many as 21 literature studies in recent years looking at blood-based proteins association with AD. While the studies varied in size, they all looked at more than 100 proteins and the total number of patients examined ranged from 14 to 961, the 2 largest cohorts being ADNI (566) and AIBL (961). Kiddle et al. have recently published a report where they tried to replicate the findings of those 21 studies that linked a total of 163 proteins to AD using Somalogic's SOMAscan proteomics technology. 94 of those 163 candidate AD biomarkers were assessed in a relatively large cohorts of 677 subjects [54]. Only 9 candidate protein biomarkers were actually found to be related to at least 1 AD-related phenotypes: Pancreatic prohormone, Granulocyte colony-stimulating factor, Clusterin, Complement C3, Complement C6, Insulinlike growth factor-binding protein 2, Alpha-1-antitrypsin, inter-alpha-trypsin inhibitor heavy chain H4 and C-C motif chemokine 18. The outcome of this extensive replication study illustrates well the difficulty the field has been facing when trying to confirm previous findings in different patient cohorts.

## **5. Protein panel assays in development**

**3.2. Amyloid beta oligomers in blood**

230 Alzheimer's Disease - Challenges for the Future

non-demented subjects.

**proteins panels (plasma)**

**Lipids (plasma)**

**Others**

**Genes, mRNAs. miRNAs**

**Table 2: summary of non-invasive AD biomarker candidates** 

**Table 2.** Summary of non-invasive AD biomarker candidates

Amyloid beta (Aβ), especially Aβ42 oligomers play a significant role in early Alzheimer's disease (AD) pathogenesis [46, 47].In fact, AD-associated inflammation has been thought to be a secondary response to the pathological lesions triggered by Aβ oligomers in the early stage of pathogenesis. Although several studies, including our own (unpublished) have shown an elevation of such oligomers in CSF [48-52], few studies have looked at the correlation between blood oligomers concentration. In one study, levels of plasma Aβ monomers, Aβ oligomers, and soluble tumor necrosis factor α receptors (sTNFRs) were evaluated by ELISA in 120 controls, 32 amnestic mild cognitive impairment (aMCI) patients, and 90 mild AD patients [53]. The study found that levels of Aβ oligomers were significantly increased by ~two fold in mild AD patients compared to levels in aMCI and healthy controls. Interestingly, plasma levels of sTNFR in aMCI and mild AD patients was elevated significantly compared to controls, and both sTNFR1 and sTNFR2 levels were associated with levels of Aβ oligomers in both aMCI and mild AD individuals. Interestingly, changes in Aβ oligomer concentrations

and sTNFR levels correctly differentiated mild ADfrom healthy control subjects.

In a separate study [50], another group have demonstrated that their ELISA system using BAN50 can detect signals in 60% of serum samples and 80% of CSF samples obtained from

**individual peptide/ protein (plasma,serum) comments reference** Abeta 40/42 ratio mixed results by various group (34) Abeta 1-17 free to bound cell ratio discriminate Control, MCI and AD (37) BACE1 enzyme, sAPPbeta elevated in plasma (38) APP669-711/Abeta1-42 significant correlation with brain amyloid deposition (PIB+) (39) TAU fragment level in serum inversely correlates with cognition deline (42) multiple TAU isoforms combination elevated in patients suffering from brain ischemia (43) Oligomeric TAU increase levels identified in platelets (44) Abeta oligomers (serum) higher in MCI and AD subjects, not detected in all samples (49, 52) sTNFr higher in MCI and AD subjects (52)

30 serum proteins combination set of several inflammatory and vascular related markers (54, 55) combined with clinical data 18 signalling plasma proteins combination can differentiate AD and C, predict MCI conversion to AD (56,57) (1 study could not reproduce this finding) Cortisol/VWF/oxidized LDL antibodies can distinguish AD and C with 80% accuracy (58)

10 lipids combination predicted phenoconversion from MCI to AD within 2-3 y (61) Ceramide/sphygomyelin elevation correlates with MMSE score (62) Desmosterol/Cholesterol decreased in MCI and AD, decrease % change in longitudinal cohorts (66,73) correlates with rate of cognitive decline

96 genes signature (blood) algorythm correctly predicts AD and discriminate Parkinson's Disease (CE mark test)) (75) 136 genes signature (blood) algorythm identify AD patients over Controls (CE mark test) (76) 48 genes signature (blood) identify AD patients over Controls with even more accuracy when combined with MRI (77) TOMM40 expression in blood potentially useful to monitor AD progression/severity (79) 98-5p,885-5p,483-3p,343-3p,191-5p,7d-5p Asian population (Serum) (131) Let-7g-5p,142-3p,15b-5p,301s-3p,545-3p,191-5p,7d-5p Caucasian population (Plasma) (120) 7f,1285,107,103a-3p,26b-5p,26a-5p,532-5p,151a-3p,161,7d,112,5010-3p Caucasian population (Whole blood cells) (135) miR-132,128,874,134,323-3p,382 Caucasian population (Plasma) (MCI correlation) (109) 9,29a,29b,34a,125b,146a Asian population (Plasma,CSF) (158)

Two retinal amyloid depositions scans detected after oral ingestion of curcumin tracer prior to eye scan using laser AAIC 2014

Impairment of smell detection ability association with brain region atrophy and prediction of conversion from MCI to AD AAIC 2014

found good correlation with PIB amyloid positivity and/AV-45 O2-05-05 ointment containing tracer applied to eye before laser scan O3-12-01 Various protein panel assays have been developed by several groups with the use of algorithms to predict AD correctly. This approach is based on the assumption that combining markers together will increase the power of the test to identify patients correctly. One assay, in particular, is looking at 30 serum proteins and has 80% sensitivity and 91% specificity for diagnosing AD [55].The set of proteins is composed of several inflammatory and vascular related markers and the assay, combined with clinical data, showed a correlation with neuropsychological test performance [56].

Another group identified a panel of 18 signaling plasma proteins that can differentiate AD and control with ~90% sensitivity and identify MCI patients likely to convert to AD within 2 years with 81% sensitivity [57]. However, these results could not be reproduced independently [58].Combination of 3 blood markers (cortisol, von Willebrand factor and oxidized LDL antibodies) was able to diagnose AD with 80% accuracy [59].Quantitative mass-spectrometrybased selective reaction monitoring (SRM) is also supporting the development of AD diag‐ nostic tests [60] by using isotopic tandem mass tag (TMT) technology to evaluate specific peptides derived from selected AD-related proteins. This approach, although very sound, is more difficult that one would think. In fact, when we tried in-house a similar technique called MRM (multiple reaction monitoring), we could not replicate several AD biomarker protein candidates discovered by other groups. Intriguingly, several peptides from the same protein showed changes in opposite directions (unpublished).

## **6. Plasma lipids as non-invasive AD biomarkers**

The disturbance of several lipid pathways in the brain, in particular in cholesterol biosynthesis has been associated with several brain disorders including AD [61].So it comes as a little surprise that this category of molecule changes in blood to be another rich source of potential AD biomarkers. In a recent study, 525 community-dwelling healthy participants, aged 70 and older were enrolled as part of 5 year's observation study. Over the course of the study, 74 patients developed either MCI or mild AD. Using a lipidomic approach, the authors identified and validated a set of 10 lipids from peripheral blood that predicted phenoconversion to either MCI or AD within 2-3 year period with over 90% accuracy [62]. To our knowledge, this study is the first report of blood-based marker panel that can detect preclinical AD with such accuracy although validation using other cohorts will be required before considering clinical use. As the authors pointed out, alteration of lipids found in the cell membrane may be sensitive markers of neurodegeneration in pre-clinical AD. Another study using shotgun lipidomics, compared AD with controls individuals and found a change of ceramide/sphingomyelin ratio in AD [63] and its elevation to correlate with Mini-Mental-State-Examination scores (MMSE). This small study (26 AD and 26 controls) needs to be replicated though. Interestingly, a separate group found that an increase in this ratio was associated with slower disease progression [64]. Analysis of a longitudinal cohort of AD and control samples showed that AD patients had diminished baseline levels of either phospholipids, phosphatidylcholines, sphingomyelin and sterols as opposed to controls although they could not confirm the lipid profile to be good prognostic panel for estimating the progression to AD [65].

Our group initially discovered plasma desmosterol, the precursor of cholesterol, a metabolite that was recently identified as an LXR and RORgamma agonist[66, 67], as a candidate AD plasma marker [68]. Desmosterol is an essential sterol with hormone-like activity and account for as much as 30% of all brain sterols during most species brain development [69, 70].Multiple activities of desmosterol have also been reported, and it is understood that disturbances of the cholesterol metabolism may contribute to neurodegeneration [71, 72].

In our first study, decreased levels of desmosterol were observed (p value< 0.05, fold change= 0.36) in AD plasma samples versus controls plasma as well as in CSF [68]. Other groups also reported a decrease of desmosterol in brain as well as CSF [73] in an independent study but not in plasma. The discrepancy was understood in-house after we determined that this was due to an incomplete separation of cholesterol-desmosterol peaks during Gas Chromatogra‐ phy (AAIC 2012 abstract). Interestingly, we also observed a decrease of desmosterol also in MCI and in particular, more pronounced in plasma of female AD patients plasma. This change of desmosterol in contrast was not affected by ApoE4 genotype. This finding was further validated and presented recently (AAIC 2013 abstract) using two large cohorts: a commercially available Caucasian sample set and a large Asian cohort. The Caucasian sample set consisted of a total of 109 patients (Control, MCI, and AD) and the large Asian cohort (n=401, 200 C and 201 AD) were both analyzed using LCMS. Our original data showing the association between decreased desmosterol/cholesterol ratio in AD and MCI was replicated in these cohorts. Data analysis showed that desmosterol level in plasma was found to be significantly different from AD and control groups with p-values 2.3E-14 and comparable AUC of ROC curve as initially found. High correlation between plasma desmosterol level and MMSE score was observed for these two large cohorts. As for novel AD candidate markers, we believe specificity should be investigated in other dementia types in order to understand the clinical usefulness of the marker and this work is currently on-going. In addition, the longitudinal analysis revealed that plasma Desmosterol/Cholesterol ratio (DES/CHO) in AD patients shows a significant decrease at follow-up intervals. The decline in plasma DES/CHO is larger in the AD group with rapid progression than in that with slow progression and the changes in plasma DES/CHO significantly correlated with changes in MMSE score.

Altogether, this data means that plasma DES/CHO decrease in AD patients may serve as a longitudinal surrogate marker associated with cognitive decline. This data, as well as an additional longitudinal cohort data analysis, is now in press at the time of this writing[74].

Very interestingly, a minor allele of an intronic SNP within DHCR24 gene (the gene coding for the protein responsible to convert desmosterol into cholesterol) was identified in a recent ADNI study and was associated with a lower average PiB PET uptake, a first generation imaging amyloid PET agent that is used to understand amyloid deposit load in AD brain [75].It is tempting to speculate that lower desmosterol levels in the brain (reflected as well in plasma and CSF) could be directly linked to higher amyloid deposition.

In order to further understand the utility of desmosterol as an AD biomarker, we collected patients plasma samples obtained through one of our ongoing AD clinical phase 2 trial, that were either positive or negative on Amyloid Pet scans (Flurbetamol) and data analysis is now ongoing. Possible outcome of this study could help patient stratification in further trials and lead to the development of a first line test prior to conducting more expensive PET imaging scans for patients enrolment in future trials or to the development of a stand-alone *in vitro* diagnostics.

## **7. Genes, mRNA, and miRNAs**

nostic tests [60] by using isotopic tandem mass tag (TMT) technology to evaluate specific peptides derived from selected AD-related proteins. This approach, although very sound, is more difficult that one would think. In fact, when we tried in-house a similar technique called MRM (multiple reaction monitoring), we could not replicate several AD biomarker protein candidates discovered by other groups. Intriguingly, several peptides from the same protein

The disturbance of several lipid pathways in the brain, in particular in cholesterol biosynthesis has been associated with several brain disorders including AD [61].So it comes as a little surprise that this category of molecule changes in blood to be another rich source of potential AD biomarkers. In a recent study, 525 community-dwelling healthy participants, aged 70 and older were enrolled as part of 5 year's observation study. Over the course of the study, 74 patients developed either MCI or mild AD. Using a lipidomic approach, the authors identified and validated a set of 10 lipids from peripheral blood that predicted phenoconversion to either MCI or AD within 2-3 year period with over 90% accuracy [62]. To our knowledge, this study is the first report of blood-based marker panel that can detect preclinical AD with such accuracy although validation using other cohorts will be required before considering clinical use. As the authors pointed out, alteration of lipids found in the cell membrane may be sensitive markers of neurodegeneration in pre-clinical AD. Another study using shotgun lipidomics, compared AD with controls individuals and found a change of ceramide/sphingomyelin ratio in AD [63] and its elevation to correlate with Mini-Mental-State-Examination scores (MMSE). This small study (26 AD and 26 controls) needs to be replicated though. Interestingly, a separate group found that an increase in this ratio was associated with slower disease progression [64]. Analysis of a longitudinal cohort of AD and control samples showed that AD patients had diminished baseline levels of either phospholipids, phosphatidylcholines, sphingomyelin and sterols as opposed to controls although they could not confirm the lipid

profile to be good prognostic panel for estimating the progression to AD [65].

cholesterol metabolism may contribute to neurodegeneration [71, 72].

Our group initially discovered plasma desmosterol, the precursor of cholesterol, a metabolite that was recently identified as an LXR and RORgamma agonist[66, 67], as a candidate AD plasma marker [68]. Desmosterol is an essential sterol with hormone-like activity and account for as much as 30% of all brain sterols during most species brain development [69, 70].Multiple activities of desmosterol have also been reported, and it is understood that disturbances of the

In our first study, decreased levels of desmosterol were observed (p value< 0.05, fold change= 0.36) in AD plasma samples versus controls plasma as well as in CSF [68]. Other groups also reported a decrease of desmosterol in brain as well as CSF [73] in an independent study but not in plasma. The discrepancy was understood in-house after we determined that this was due to an incomplete separation of cholesterol-desmosterol peaks during Gas Chromatogra‐ phy (AAIC 2012 abstract). Interestingly, we also observed a decrease of desmosterol also in

showed changes in opposite directions (unpublished).

232 Alzheimer's Disease - Challenges for the Future

**6. Plasma lipids as non-invasive AD biomarkers**

Because gene transcription and translation ultimately determine the production of proteins that regulate cells and tissue functions, several groups have been looking at molecular changes in AD vs Controls in blood components and circulating peripheral cells to identify biomarkers. Among these, one group looked at the expression of 96 different genes in blood. A whole genome analysis was conducted using oligonucleotide microarray and blood from a large clinical cohort consisting of AD patients and control healthy subjects. a. Gene analysis comparing the gene expression of 94 AD patients and 94 cognitive healthy controls was conducted, and a disease classifier algorithm developed [76].

Validation was conducted on an independent cohort consisting of 63 subjects that included 50% AD patients,40% aged-matched controls and 10% young healthy controls. The results showed the test to have an accuracy of 87% to predict AD pathology. Additionally, the algorithm also discriminated AD from Parkinson's disease in 24/27 patients (accuracy 89%).

Another group developed an alternate gene AD signature consisting of 136 different genes using 177 blood samples (90 AD patients and 87 controls) [77]. Signature validation was then later performed on a blinded independent cohort of 209 individuals (111 AD and 98 controls). Many of the genes included in the signature are found to be elevated during inflammation processes and apoptosis and have been associated with the amyloid cascade and tau pathol‐ ogy. In a follow-up validation study consisting of 164 patients.. This test performed relatively well and was able to identify AD patients (81.3% sensitivity) correctly and to exclude AD pathology (67.1% specificity). Both of these tests have won approval in Europe (CE Mark) as AD biomarker and are available to physicians but they still haven't been validated in large clinical cohorts such as the Alzheimer's Disease Neuroimaging Initiative (ADNI ½).

At least two other studies showed this transcriptome approach potential. In one study [78], a gene expression signature was discovered in a 156 patients cohorts consisting of AD and controls. The validation study confirmed the performance of the gene signature in a separate cohort composed of 26 AD, 26 healthy age-matched control and 118 mild MCI individuals classified as probable early AD subjects. The 48 genes signature accurately identified 70% of AD patients and when combined with MRI defined criteria, the accuracy went up to 85%.,. However, the authors indicated that these results have to be validated in other diseases or dementias.

The same group also looked at changes in gene expression in leukocytes and found alterations in blood seen mild cognitive impairment (MCI) and AD subjects indicating a peripheral response to pathology may occur very early [79].Noticeably, evidences for mitochondrial dysfunction indicated by a reduce expression of several respiratory complex I-V genes were observed, confirming changes previously seen in AD brain.

One novel single gene marker identified that is associated with AD is TOMM40 (translocase of outer mitochondrial membrane 40 homolog). The protein encoded by TOMM40 seems to transport proteins functionally to mitochondria. Risk Mutation in this gene has been found in several GWAS studies, and one group showed that its expression in blood may serve as an AD marker of disease severity and progression [80].

## **8. miRNAs**

Beside the existing proteomic, metabolomics and nucleic acid based markers, small RNAs (including miRNAs) are an upcoming class of circulating biomarkers that have resulted in clinical cohort consisting of AD patients and control healthy subjects. a. Gene analysis comparing the gene expression of 94 AD patients and 94 cognitive healthy controls was

Validation was conducted on an independent cohort consisting of 63 subjects that included 50% AD patients,40% aged-matched controls and 10% young healthy controls. The results showed the test to have an accuracy of 87% to predict AD pathology. Additionally, the algorithm also discriminated AD from Parkinson's disease in 24/27 patients (accuracy 89%). Another group developed an alternate gene AD signature consisting of 136 different genes using 177 blood samples (90 AD patients and 87 controls) [77]. Signature validation was then later performed on a blinded independent cohort of 209 individuals (111 AD and 98 controls). Many of the genes included in the signature are found to be elevated during inflammation processes and apoptosis and have been associated with the amyloid cascade and tau pathol‐ ogy. In a follow-up validation study consisting of 164 patients.. This test performed relatively well and was able to identify AD patients (81.3% sensitivity) correctly and to exclude AD pathology (67.1% specificity). Both of these tests have won approval in Europe (CE Mark) as AD biomarker and are available to physicians but they still haven't been validated in large

clinical cohorts such as the Alzheimer's Disease Neuroimaging Initiative (ADNI ½).

At least two other studies showed this transcriptome approach potential. In one study [78], a gene expression signature was discovered in a 156 patients cohorts consisting of AD and controls. The validation study confirmed the performance of the gene signature in a separate cohort composed of 26 AD, 26 healthy age-matched control and 118 mild MCI individuals classified as probable early AD subjects. The 48 genes signature accurately identified 70% of AD patients and when combined with MRI defined criteria, the accuracy went up to 85%.,. However, the authors indicated that these results have to be validated in other diseases or

The same group also looked at changes in gene expression in leukocytes and found alterations in blood seen mild cognitive impairment (MCI) and AD subjects indicating a peripheral response to pathology may occur very early [79].Noticeably, evidences for mitochondrial dysfunction indicated by a reduce expression of several respiratory complex I-V genes were

One novel single gene marker identified that is associated with AD is TOMM40 (translocase of outer mitochondrial membrane 40 homolog). The protein encoded by TOMM40 seems to transport proteins functionally to mitochondria. Risk Mutation in this gene has been found in several GWAS studies, and one group showed that its expression in blood may serve as an

Beside the existing proteomic, metabolomics and nucleic acid based markers, small RNAs (including miRNAs) are an upcoming class of circulating biomarkers that have resulted in

conducted, and a disease classifier algorithm developed [76].

234 Alzheimer's Disease - Challenges for the Future

observed, confirming changes previously seen in AD brain.

AD marker of disease severity and progression [80].

dementias.

**8. miRNAs**

many new findings. miRNAs belong to the class of non-coding regulatory RNA molecules of ∼22nt length that regulate gene expression post-transcriptionally by binding (in most cases) to the 3′ un-translated region (UTRs) of their targets [81-83]. It is estimated that ~5% genes in the human genome encode for miRNAs and a single miRNA can regulate multiple targets (sometimes in excess of 200) based primarily on the complementarity of the seed region (nt 2-8 of the miRNA) to target mRNA molecules [84]. MicroRNAs play regulatory roles in vital biological processes, including cell proliferation and growth, tissue differentiation, develop‐ ment, and cell death[85]. Interestingly, it has recently been demonstrated, that not only are miRNAs active in their cell of origin, but they can be exported/secreted out, and cause downregulation of target mRNAs in an alternate target cell [86]. It is this unique property of miRNAs of being present in intact and functional condition in circulating biofluids including CSF, plasma, serum, urine, tears and saliva, which makes them promising biomarker candidates. They are found enclosed in membrane-bound structures (exosomes, microvesicles etc.) [87, 88], and in some cases in "free" form, protected by RNA binding proteins like NPM1, HDL [86, 89] or Argonaute2 [90, 91]. Circulating miRNA signatures have been shown to identify different tumor types [92, 93] indicate staging and progression of the disease [94] and serve as prognostic markers [95, 96]. Recently, five miRNA based diagnostic tests have been made available for clinicians to prescribe (through Rosetta Genomics and Asuragen Inc). Although the first generation of tests requires tumor biopsies, there is now significant work in progress to eliminate the need for getting biopsies, and to be able to get answers from blood, urine or other readily available circulating fluids.

Although the potential of miRNAs as diagnostic markers has been consistently demonstrated in Oncology; recent publications in other areas like neurodegenerative disorders point to their expanding role [99]. In AD, for example, miRNA profiling experiments (in brain tissue) have resulted in the identification of many disease-specific miRNAs that have been confirmed independently in two or more studies [97]. For example, hsa-miR-106, hsa-miR-153 and hsamiR-101 have been shown to modulate APP [98-101], while BACE1 has been shown to be targeted by hsa-miRNA-29 and hsa-miR-107, linking miRNAs to regulation of amyloid production in AD brains [102]. Based on similar studies, researchers have focused on these disease-specific miRNAs to determine if differential levels are found in more-easily accessible biofluids like blood or CSF. Hsa-miR-29a/b including others was a disease-specific miRNA whose down-regulated levels in the serum of AD patients mimicked the expected downregulation in the brain tissue [103]. This is a more disease-focused approach, where only those miRNAs that have a known link to the illness is profiled for. However, the nature of circulating fluids, which allows all organs, tissues to be potential sources of biomarkers makes a simple correlation with only diseased focus biomarkers (miRNAs, in this case) hard. There is also now a confirmed presence of a selective gating mechanism that determines a particular profile of miRNAs to be exported out (in exosomes or protein bound). This was recently demonstrated in studies that showed that secreted miRNA profiles (from culture) were not in correlation with intra-cellular profiles. This could explain why higher level of a miRNA in an affected organ is not automatically associated with an increase in its plasma level [104, 105]. Another approach, still under the umbrella of disease-relevant miRNAs looks not at the disease etiology, but broadens the net and looks for all miRNAs known to be expressed in the tissue/ organ of interest. Hence for AD for examples, miRNAs known to be enriched in neurons and synapse destruction were focused on [109-111]. As a result, miR-132 and the miR-134 family of miRNAs were discovered which showed potential for differentiation between MCI and AD, and, in fact, could also predict 1-5 years in advance of a clinical diagnosis. Potential biomarkers like these could be instrumental in identifying the population which would respond best to therapy in the future, or at least identify the correct pool of patients who are MCI for example, but would advance to AD in the absence of any treatment. On the Neurodegeneration side, some focused miRNA analysis has uncovered candidates like miR-146a and miR-155 that were found in higher levels in brain tissue extra-cellular fluid (ECF) in AD patients [112]. Along with the recent report on let-7b that is being investigated as a TLR-7 ligand [113], these recent findings point towards the potential role of inflammation, which ultimately could lead to neurodegenerative disorders.

Without limiting the miRNA profiles to either disease etiology or organ/tissue of focus, unbiased-global profiling is another approach to biomarker research. This is now especially more feasible, considering the significant technological advancements that have allowed researchers to look at thousands of biomarkers using as little as 100 ul of blood, for example. Another reason, why an unbiased approach might be appealing to certain researchers is the potential of finding novel pathways that have so far not been implicated in the disease of interest, and this is especially true for complex, heterogeneous disorders like AD, where there is still a lot of work on going in trying to understand all the biology of the disease. Of course, on the flip-side, it is often difficult to explain the biological significance and connection of the novel biomarker for the illness. The problem is more severe for miRNAs, because it is not a simple miRNA-mRNA relationship, but rather a single miRNA, and hundreds of potential mRNA targets [114-116], which makes it even harder to predict connections to disease. To put this conundrum of multiple miRNA targets into a biological context, this publication proposed [117] that usually biologically meaningful targets of miRNAs were found to be enriched in specific pathways, or a network. The first un-biased miRNA study in blood (PBMCs) was done in 2007 [106] followed by a much-cited study by Cogswell et al.[107] that identified miRNAs differentially expressed in brain and CFS of AD/matched controls. In addition to some related pathways being implicated in neuronal differentiation and actin remodeling (through targets of miR-9 and 132), novel target pathways like brain insulin signaling and oxidative stress were identified. However, the surprise finding was the lack of correlation between CSF and brain profiles, which again hinted at a particular secretion mechanism that regulated the transfer of miRNAs from the cell. In addition, differentially expressed CSF miRNAa like miR-146b (thought to be involved in immune function) were found to be decreased in AD patients, suggesting an activated immune status, potentially offering insights into the role of inflam‐ mation in the disease.

Consistent with the global profiling approach, our group had published a novel AD signature that had >95% accuracy in determining AD status from matched controls [108]. It consisted of reduced levels of 7 miRNAs (hsa-let-7d-5p, hsa-let-7g-5p, hsa-miR-15b-5p, hsa-miR-142-3p, hsa-miR-191-5p, hsa-miR-301a-3p and hsa-miR-545-3p) which was further confirmed in an independent sample-set of 20 AD and 17 NC samples, To put a biological context to the organ of interest. Hence for AD for examples, miRNAs known to be enriched in neurons and synapse destruction were focused on [109-111]. As a result, miR-132 and the miR-134 family of miRNAs were discovered which showed potential for differentiation between MCI and AD, and, in fact, could also predict 1-5 years in advance of a clinical diagnosis. Potential biomarkers like these could be instrumental in identifying the population which would respond best to therapy in the future, or at least identify the correct pool of patients who are MCI for example, but would advance to AD in the absence of any treatment. On the Neurodegeneration side, some focused miRNA analysis has uncovered candidates like miR-146a and miR-155 that were found in higher levels in brain tissue extra-cellular fluid (ECF) in AD patients [112]. Along with the recent report on let-7b that is being investigated as a TLR-7 ligand [113], these recent findings point towards the potential role of inflammation, which ultimately could lead to

Without limiting the miRNA profiles to either disease etiology or organ/tissue of focus, unbiased-global profiling is another approach to biomarker research. This is now especially more feasible, considering the significant technological advancements that have allowed researchers to look at thousands of biomarkers using as little as 100 ul of blood, for example. Another reason, why an unbiased approach might be appealing to certain researchers is the potential of finding novel pathways that have so far not been implicated in the disease of interest, and this is especially true for complex, heterogeneous disorders like AD, where there is still a lot of work on going in trying to understand all the biology of the disease. Of course, on the flip-side, it is often difficult to explain the biological significance and connection of the novel biomarker for the illness. The problem is more severe for miRNAs, because it is not a simple miRNA-mRNA relationship, but rather a single miRNA, and hundreds of potential mRNA targets [114-116], which makes it even harder to predict connections to disease. To put this conundrum of multiple miRNA targets into a biological context, this publication proposed [117] that usually biologically meaningful targets of miRNAs were found to be enriched in specific pathways, or a network. The first un-biased miRNA study in blood (PBMCs) was done in 2007 [106] followed by a much-cited study by Cogswell et al.[107] that identified miRNAs differentially expressed in brain and CFS of AD/matched controls. In addition to some related pathways being implicated in neuronal differentiation and actin remodeling (through targets of miR-9 and 132), novel target pathways like brain insulin signaling and oxidative stress were identified. However, the surprise finding was the lack of correlation between CSF and brain profiles, which again hinted at a particular secretion mechanism that regulated the transfer of miRNAs from the cell. In addition, differentially expressed CSF miRNAa like miR-146b (thought to be involved in immune function) were found to be decreased in AD patients, suggesting an activated immune status, potentially offering insights into the role of inflam‐

Consistent with the global profiling approach, our group had published a novel AD signature that had >95% accuracy in determining AD status from matched controls [108]. It consisted of reduced levels of 7 miRNAs (hsa-let-7d-5p, hsa-let-7g-5p, hsa-miR-15b-5p, hsa-miR-142-3p, hsa-miR-191-5p, hsa-miR-301a-3p and hsa-miR-545-3p) which was further confirmed in an independent sample-set of 20 AD and 17 NC samples, To put a biological context to the

neurodegenerative disorders.

236 Alzheimer's Disease - Challenges for the Future

mation in the disease.

hundreds of potential miRNA target molecules, we enriched for mRNA molecules that were targeted by multiple miRNAs (at least 2) Some neurological canonical pathways identified included axonal guidance signaling, ephrin receptor signaling [109], actin cytoskeleton signaling[110], clathrin-mediated endocytosis signaling [111] and RhoA signaling [112]. These pathways, although diverse, show potential biological relationships with disease etiology [125]. Using an unbiased analysis approach, we removed the filter of neurological pathways in IPA, and got a list of pathways enriched for signature miRNA targets., A type II Diabetes Mellitus signaling canonical pathway was identified. This was interesting because there was also evidence from multiple GWAS studies indicating that SNPs in ApoE [113] Clu [114] and ABCA7 genes [115] were linked to AD biology. This was in addition to another report that linked lipid metabolism to both amyloid and tau pathology [61]. However, due to unclear outcomes after statin treatment in AD clinical trials, the role of lipid metabolism in AD pathogenesis remains to be elucidated [116]. In another global-approach driven study in serum, miRNAs were profiled from 50 AD and 50 matched control samples using nextgeneration sequencing [117] This was followed by a validation study using qRT-PCR in an independent cohort of 158 AD and 155 control populations. Amongst other signature miRNAs identified, miR-191-5p and let-7d-5p were identified to be down-regulated in AD patients. This was encouraging because it validated part of our miRNA signature in blood (serum) using a different profiling technology (NGS) as opposed to a hybridization-based technology (nCount‐ er: Nanostring) used by our group. This suggested that the signature had biological relevance and was not likely a profiling or normalization artifact, which often results in little validation rates of miRNA signatures.

Having previously established that the signature miRNAs could reliably differentiate AD from a matched control population NC, we investigated if lower levels of these miRNAs could be observed at earlier stages of dementia. To address this, a new set of samples containing 27 AD, 30 MCI, and 59 NC samples was obtained. All 7signature miRNAs were confirmed to be differentially expressed between the new cohort of 27 AD and 59 NC samples (internal data, not published). In addition, these miRNAs could reliably differentiate between MCI and NC samples. Meanwhile, no significant difference was observed between MCI and AD samples. To eliminate a potential normalization bias because of our choice of normalization strategy (geometric mean of ath-159a and hsa-miR-106), the data was normalized in two additional ways. The geometric mean of hsa-miR-16-5p and ath-miR-159a was used for normalization, given previous use of hsa-miR-16 as the miRNA of choice for normalization for plasma-based miRNA profiles [118, 119]. In addition, spike-in ath-159a was used in isolation to account for the possibility that normalization with endogenous control miRNAs might prevent detection of valid and meaningful biological variation. We observed no significant change in foldchanges or p –values for AD/NC and MCI/NC confirming that the signature was robust and not sensitive to different normalization strategies. Inter-site reproducibility was also investi‐ gated and an aliquot of total RNA was tested at another site by a different operator following the described protocol. Excellent correlations were observed for all 7-miRNA signatures, demonstrating the robustness of the entire assay workflow.

It was encouraging, that the same signature set of miRNAs that could differentiate AD from NC individuals was also downregulated in MCI patients. This suggested that these signature miRNAs were potentially related to early events in the disease and could be valuable for the early identification of AD/MCI patients for potential stratification in clinical studies. However, care should be exercised in how one interpret these findings. Patients that have been diagnosed as MCI are a heterogeneous population, which can have very diverse outcomes as a result of their MCI diagnosis. Some patients continue in the MCI phase or advance to more severe MCI states while, for others, conditions might deteriorate towards dementia. While some MCI patients go on to develop dementia linked to Frontal Temporal Lobe Dementia (FTLD) or Dementia with Lewy Bodies (DLB), a majority of patients develop dementia driven by pathophysiological processes attributed to Alzheimer's with a conversion rate of ~15-20% per year [120] So it is important to follow up with more studies to understand the course of progression for the MCI population tested, and evaluate if we can predict conversion of MCI to AD (for example) using this signature set of miRNAs. In addition to the specificity of any diagnostic signature for Alzheimer's disease, determining how early in disease etiology the biomarker in question changes is also critical. Archived samples are going back years before the actual diagnosis of MCI or AD would need to be accessed and processed to understand the timing of the biomarker aberration. For a biomarker signature to be valuable for a longi‐ tudinal evaluation, it is helpful to comprehend the variation and stability of the proposed biomarker across time. We observed an average coefficient of variation between 15 and 25% for 6 out of 7 miRNAs for eight healthy individuals across samples taken from multiple 6 month visits spread over 3-4 years (unpublished). This set of data indicates that the signature miRNAs are indeed stable across time in individuals, and are therefore promising candidates to evaluate in longitudinal samples from individual patients to understand at what point, these biomarkers start to change (in Alzheimer's progression, for example).

In another global, unbiased study, researchers looked at whole blood cells from Alzheimer's and age-matched control samples to discover diagnostic miRNA signatures. They utilized a next-generation-sequencing platform for profiling the miRNAs in a discovery cohort of 48 AD and 22 unaffected control samples, while the validation was done using qRT-PCR in a larger cohort of over 200 patients comprising not only of AD patients but also patients suffering from other CNS illnesses. They achieved a 12-miRNA signature, which had an accuracy of 93% to differentiate AD from matched control samples [121] The accuracy was significantly lower (74-78%) to distinguish AD from other CNS disorders. In another study, researchers looked at profiling serum samples from 22 AD and control samples, which comprised of 18 noninflammatory neurological disease controls (NINDCs) and eight inflammatory neurological disease controls (INDCs). Although they used an unbiased approach and did not restrict the number of miRNAs to disease-associated candidates, they only profiled the most abundantly expressed miRNAs (a panel of 192 miRNAs), and then followed up with qRT-PCR validation. MicroRNA-125b and miR-26b were found to be down-regulated in AD, and confirmed in CSF from the same patient population [122] Accuracy was determined to be 82% for differentiating between AD and NINDC cohorts. Although they had an FTD cohort (Frontotemporal Lobe Dementia), the number of patients was too small [10] to make significant conclusions about the specificity of the signature.

It was encouraging, that the same signature set of miRNAs that could differentiate AD from NC individuals was also downregulated in MCI patients. This suggested that these signature miRNAs were potentially related to early events in the disease and could be valuable for the early identification of AD/MCI patients for potential stratification in clinical studies. However, care should be exercised in how one interpret these findings. Patients that have been diagnosed as MCI are a heterogeneous population, which can have very diverse outcomes as a result of their MCI diagnosis. Some patients continue in the MCI phase or advance to more severe MCI states while, for others, conditions might deteriorate towards dementia. While some MCI patients go on to develop dementia linked to Frontal Temporal Lobe Dementia (FTLD) or Dementia with Lewy Bodies (DLB), a majority of patients develop dementia driven by pathophysiological processes attributed to Alzheimer's with a conversion rate of ~15-20% per year [120] So it is important to follow up with more studies to understand the course of progression for the MCI population tested, and evaluate if we can predict conversion of MCI to AD (for example) using this signature set of miRNAs. In addition to the specificity of any diagnostic signature for Alzheimer's disease, determining how early in disease etiology the biomarker in question changes is also critical. Archived samples are going back years before the actual diagnosis of MCI or AD would need to be accessed and processed to understand the timing of the biomarker aberration. For a biomarker signature to be valuable for a longi‐ tudinal evaluation, it is helpful to comprehend the variation and stability of the proposed biomarker across time. We observed an average coefficient of variation between 15 and 25% for 6 out of 7 miRNAs for eight healthy individuals across samples taken from multiple 6 month visits spread over 3-4 years (unpublished). This set of data indicates that the signature miRNAs are indeed stable across time in individuals, and are therefore promising candidates to evaluate in longitudinal samples from individual patients to understand at what point, these

biomarkers start to change (in Alzheimer's progression, for example).

the specificity of the signature.

238 Alzheimer's Disease - Challenges for the Future

In another global, unbiased study, researchers looked at whole blood cells from Alzheimer's and age-matched control samples to discover diagnostic miRNA signatures. They utilized a next-generation-sequencing platform for profiling the miRNAs in a discovery cohort of 48 AD and 22 unaffected control samples, while the validation was done using qRT-PCR in a larger cohort of over 200 patients comprising not only of AD patients but also patients suffering from other CNS illnesses. They achieved a 12-miRNA signature, which had an accuracy of 93% to differentiate AD from matched control samples [121] The accuracy was significantly lower (74-78%) to distinguish AD from other CNS disorders. In another study, researchers looked at profiling serum samples from 22 AD and control samples, which comprised of 18 noninflammatory neurological disease controls (NINDCs) and eight inflammatory neurological disease controls (INDCs). Although they used an unbiased approach and did not restrict the number of miRNAs to disease-associated candidates, they only profiled the most abundantly expressed miRNAs (a panel of 192 miRNAs), and then followed up with qRT-PCR validation. MicroRNA-125b and miR-26b were found to be down-regulated in AD, and confirmed in CSF from the same patient population [122] Accuracy was determined to be 82% for differentiating between AD and NINDC cohorts. Although they had an FTD cohort (Frontotemporal Lobe Dementia), the number of patients was too small [10] to make significant conclusions about

While there is a lot of activities, excitement, and hope for a non-invasive, specific, cost effective and quantitative biomarker for early detection of Alzheimer's, there has also been a concerning lack of concordance reported amongst individual studies trying to reproduce previous signatures for Alzheimer's (Fig. 2). This is true for miRNA signatures for other diseases as well. A number of unique, independent signatures, especially for Oncology have been reported previously [123] but most of them remained un-validated or never progressed to the clinic stage. There are several reasons for this. Throughout the process of miRNA profiling and subsequent validation, there are steps in which individual biases get introduced, which are unique to each profiling method. The choice of starting material, be it plasma, serum, whole blood cells, PBMC's, or even exosomes from the blood impact signature profiles. The extraction method is another source of variation, as evidenced by the recent retraction[124], where it was reported that Trizol based preparations were susceptible to non-uniform extraction biases depending on initial concentration of certain miRNAs (with particular GC content profiles) in the sample. Gender, ethnicity, age [125] are some other factors that are known to affect miRNA profiles. Hence if one study utilized a defined cohort of patients that were Caucasian in ethnicity, while another group tried to replicate the signature in a cohort that was mixed with Hispanic or African American patient samples, concordance between the two studies could be compromised There has also been considerable concern about presence of blood-cell derived miRNAs that are found in the plasma fraction, occurring because of hemolysis of blood cells during plasma preparation [126, 127]. Hence, subtle differences in plasma preparation methods could impact plasma signatures significantly. Platelet contamination during plasma preparation is another source of potential discordance [128]. Even in our study, we have observed center to center variation and now more work needs to be done in identifying the source of variation, be it plasma handling leading to platelet contamination from some centers, or the effect of platelet activation leading to microparticle shedding, which also could impact the miRNA signature performance.

Post sample preparation, the choice of profiling platform utilized for discovery and validation has a significant effect on miRNA levels. A study compared biases in miRNA profiling across hybridization-based array platforms and a Next Generation Sequencing (NGS) platform [129] AU-rich miRNAs were detected with higher sensitivity using NGS based platforms; while GCrich miRNAs were preferably detected using Hybridization based array platforms. Within a NGS platform itself, biases for certain miRNAs exist, that are driven by sequence (3`nt) and secondary structure at the ligation site [130] of individual miRNAs and adapters, affecting ligase enzyme efficiency during the library construction step. What further compounds the issue is that typically after discovery using a high-throughput platform, miRNA signatures are usually validated using qPCR based methods, which adds their bias to the analysis. Stem loop RT-PCR primers, that are often the "gold standard" for miRNA detection only bind to the 3' 8-10 nt of the miRNA in question, and hence are susceptible to stable secondary structures at the 3' end of miRNAs that inhibit efficient primer initiation in the typical temperature range of reverse transcription (37° to 42°C). Alternatively, with the LNA (modified primers using Locked Nucleic Acid modifications to increase the Tm of smaller sized primers to accommo‐ date size limitations of miRNAs method, polyadenylation is used to elongate the short miRNA sequence, followed by RT-qPCR detection. Due to substrate preferences and secondary structures at the 3' end of the miRNA, certain miRNAs are better substrates than others for this first step, causing a bias. A recent analysis published in Nature captured the variability in miRNA profiling platforms [131]. They evaluated up to 12 profiling platforms using standar‐ dized sample sets. The platforms were PCR, hybridization or sequencing based. As expected, the PCR-based platforms resulted in higher sensitivity, although sometimes at a cost of accuracy and specificity. Metrics tested included reproducibility, dynamic range performance, accuracy, accuracy at lower RNA input, sensitivity, sensitivity at a lower RNA input specificity and cross assay reactivity. The lower volume metrics were designed to address applications like detection of circulating miRNAs from body fluids, where the concentrations of miRNAs are typically very small. Although differences were expected between platforms, what was surprising was the extent of discordance observed between platforms. The average validation rate between any two platforms was as low as 54%. This labors the point, that it is paramount to profile and validate using two different platforms to confirm potential signature miRNAs in order to eliminate platform artifacts. Moreover, lastly, the multiple normalization strategies that are used for circulating miRNA analysis further reduce concordance between independent studies. Because of a lack of a well-established and accepted normalization miRNA candidate (a GAPDH equivalent for miRNAs), there have been a variety of strategies utilized and have been previously reviewed [132, 133]. Each approach makes certain assumptions, and it is important to consider those when comparing different miRNA profiling studies. Given these above mentioned sources of variation, it is not surprising that multiple studies which started in 2007, where miRNAs were profiled using microarray technologies (that modified mRNA based strategies to work with the much shorter miRNAs) to today, where you have the next generation of technologies that have been built keeping miRNAs in mind, the miRNA profiles are significantly different. Furthermore, there have been constant additions/subtractions and even sequence edits to the miRBASE registry over the years, which have an impact on profiling platforms, since they have to modify probes in order to accommodate these changes. With the recent discovery and advancement in technologies to look at exosomes, another dimension of complexity has been added, where one can distinguish exosome encapsulated fractions and truly cell-free fractions, further reducing concordance between studies. Hence it is important to maintain very standard protocols, and then follow through with them till the end of the study, including multiple validations with many independent cohorts of samples taken from different centers, ethnicities and ages.

The last 3-4 years have seen the beginning of the utilization of circulating miRNAs in the neurodegenerative disorders domain, and it is still a maturing field. The potential of miRNAs to provide a cost effective, non-invasive, accurate and sensitive diagnostic assay resulting in a positive impact on patient health is undeniable, but care needs to be exercised in interpre‐ tation of these signatures in the absence of thorough validation. Furthermore, significant work detailing how these novel biomarkers tie into disease etiology is a must to increase confidence and understand the reason behind biomarker modulation due to illness or subsequent treatment.

Recent Progress in the Identification of Non-Invasive Biomarkers to Support the Diagnosis of Alzheimer's Disease… http://dx.doi.org/10.5772/60008 241

**Figure 2.** Snapshot of current circulating miRNA signatures# for Alzheimer's Disease

## **9. New non-invasive biomarkers on the horizon**

sequence, followed by RT-qPCR detection. Due to substrate preferences and secondary structures at the 3' end of the miRNA, certain miRNAs are better substrates than others for this first step, causing a bias. A recent analysis published in Nature captured the variability in miRNA profiling platforms [131]. They evaluated up to 12 profiling platforms using standar‐ dized sample sets. The platforms were PCR, hybridization or sequencing based. As expected, the PCR-based platforms resulted in higher sensitivity, although sometimes at a cost of accuracy and specificity. Metrics tested included reproducibility, dynamic range performance, accuracy, accuracy at lower RNA input, sensitivity, sensitivity at a lower RNA input specificity and cross assay reactivity. The lower volume metrics were designed to address applications like detection of circulating miRNAs from body fluids, where the concentrations of miRNAs are typically very small. Although differences were expected between platforms, what was surprising was the extent of discordance observed between platforms. The average validation rate between any two platforms was as low as 54%. This labors the point, that it is paramount to profile and validate using two different platforms to confirm potential signature miRNAs in order to eliminate platform artifacts. Moreover, lastly, the multiple normalization strategies that are used for circulating miRNA analysis further reduce concordance between independent studies. Because of a lack of a well-established and accepted normalization miRNA candidate (a GAPDH equivalent for miRNAs), there have been a variety of strategies utilized and have been previously reviewed [132, 133]. Each approach makes certain assumptions, and it is important to consider those when comparing different miRNA profiling studies. Given these above mentioned sources of variation, it is not surprising that multiple studies which started in 2007, where miRNAs were profiled using microarray technologies (that modified mRNA based strategies to work with the much shorter miRNAs) to today, where you have the next generation of technologies that have been built keeping miRNAs in mind, the miRNA profiles are significantly different. Furthermore, there have been constant additions/subtractions and even sequence edits to the miRBASE registry over the years, which have an impact on profiling platforms, since they have to modify probes in order to accommodate these changes. With the recent discovery and advancement in technologies to look at exosomes, another dimension of complexity has been added, where one can distinguish exosome encapsulated fractions and truly cell-free fractions, further reducing concordance between studies. Hence it is important to maintain very standard protocols, and then follow through with them till the end of the study, including multiple validations with many independent cohorts of samples taken from

The last 3-4 years have seen the beginning of the utilization of circulating miRNAs in the neurodegenerative disorders domain, and it is still a maturing field. The potential of miRNAs to provide a cost effective, non-invasive, accurate and sensitive diagnostic assay resulting in a positive impact on patient health is undeniable, but care needs to be exercised in interpre‐ tation of these signatures in the absence of thorough validation. Furthermore, significant work detailing how these novel biomarkers tie into disease etiology is a must to increase confidence and understand the reason behind biomarker modulation due to illness or subsequent

different centers, ethnicities and ages.

240 Alzheimer's Disease - Challenges for the Future

treatment.

Despite the promising collection of novel blood-based biomarkers as we just described, there is still a possibility to unravel additional novel non-invasive biomarkers for AD and MCI in other accessible body matrices. The human retina shares many features with the brain, including embryological origin, anatomical (ex. Microvasculature bed) and important physiological characteristics such as blood-tissue barrier [134] So researchers have looked at the possibility that the retina may offer an easily accessible and non-invasive way of examining human brain pathology. As it turned out, it is becoming evident that amyloid is also accumu‐ lating in the eyes and that this landmark event could be detected by relatively straightforward eye examinations according to data derived from multiple research trials data presented during the summer of 2014 at the Alzheimer's Association International Conference held in Copenhagen.. Data from independent studies showed that the level of beta-amyloid detected in the eye was significantly correlated with the level of beta-amyloid deposition in the brain and allowed researchers to accurately identify patients with Alzheimer's in the studies.

In the first study looking at healthy patients from the Australian Imaging, Biomarker and Lifestyle Flagship Stud Preliminary data from the first 40 participants showed that amyloid levels detected in the retina using an orally administered curcumin supplement were signifi‐ cantly correlated with brain amyloid levels, as shown by PiB PET imaging. In addition, Retinal Amyloid Imaging (RAI) differentiated participants with AD from those without AD with 100% sensitivity and 80.6% specificity. Furthermore, longitudinal data showed a 3.5% elevation on average in retinal amyloid signal during a 3.5-month period, suggesting that the technique may be used as a means of monitoring response to therapy.

The second separate phase 2 studies included 20 individuals with probable mild to moderate AD and 20 healthy, age-matched control participants. In this study, participants had a small proprietary molecule applied to the eye in the form of a sterile ophthalmic ointment. The compound was left to diffuse into the eye overnight and the next day the eye was scanned with the laser and results computed. As in the first study, all 40 participants also underwent PET amyloid brain imaging but this time with Amyvid PET agent. The test was capable to distinguish individuals with Alzheimer's from healthy control participants with 85% sensi‐ tivity and 95% specificity significantly and as in the first study, amyloid levels in the lens significantly correlated with PET imaging results.

Given the rapidity and simplicity of the diagnostic test (5 minutes) it is easy to understand how revolutionary this would be for the medical field as it could be used by general practi‐ tioners and specialists at point-of-care in hospitals and offices. Time will tell if it could also be used to monitor disease progression and monitor efficacy of new anti-Alzheimer's drug in development (Alzheimer's Association International Conference (AAIC) 2014. Abstracts O2-05-05 and O3-13-01).

## **10. Impairment of odor detection as early AD diagnostic**

It is becoming evident that as AD sets in, impairment of the olfaction system in its ability to correctly distinguish odors appears to be an early phenomenon that could predict cognitive impairment at an early stage (AAIC 2014, in Copenhagen). In two studies, the decreased ability to identify various defined odors was significantly associated with loss of neuronal cells function and progression to Alzheimer's disease as measured by a variety of cognitive tests.

Imaging data from one study revealed that a smaller hippocampus and a thinner entorhinal cortex accompanied by higher levels of brain amyloid were linked to worsening of smell identification abilities and memory after adjusting for parameters that includes age, gender, and an estimate of cognitive reserve(AAIC 2014).

A separate study conducted at Columbia University Medical Center looked at odor Identifi‐ cation deficits association with Transition from Mild Cognitive Impairment to Alzheimer's. Researchers investigated a multi-ethnic sample of 1037 non-demented elderly people in New York City, (average age of 80.7) and assessed their olfaction abilities in a variety of ways at three time periods. 109 people developed dementia (101=Alzheimer's and eight non-AD dementia) a significant incapacity to correctly identify odors was found to be associated with the early development of dementia in those patients.

Although further large-scale studies will be required to confirm these results it is encouraging for the medical practice field that such relatively inexpensive test may be used one day to detect early stage of AD and those at risk of cognitive decline.

## **11. Urine**

cantly correlated with brain amyloid levels, as shown by PiB PET imaging. In addition, Retinal Amyloid Imaging (RAI) differentiated participants with AD from those without AD with 100% sensitivity and 80.6% specificity. Furthermore, longitudinal data showed a 3.5% elevation on average in retinal amyloid signal during a 3.5-month period, suggesting that the technique

The second separate phase 2 studies included 20 individuals with probable mild to moderate AD and 20 healthy, age-matched control participants. In this study, participants had a small proprietary molecule applied to the eye in the form of a sterile ophthalmic ointment. The compound was left to diffuse into the eye overnight and the next day the eye was scanned with the laser and results computed. As in the first study, all 40 participants also underwent PET amyloid brain imaging but this time with Amyvid PET agent. The test was capable to distinguish individuals with Alzheimer's from healthy control participants with 85% sensi‐ tivity and 95% specificity significantly and as in the first study, amyloid levels in the lens

Given the rapidity and simplicity of the diagnostic test (5 minutes) it is easy to understand how revolutionary this would be for the medical field as it could be used by general practi‐ tioners and specialists at point-of-care in hospitals and offices. Time will tell if it could also be used to monitor disease progression and monitor efficacy of new anti-Alzheimer's drug in development (Alzheimer's Association International Conference (AAIC) 2014. Abstracts

It is becoming evident that as AD sets in, impairment of the olfaction system in its ability to correctly distinguish odors appears to be an early phenomenon that could predict cognitive impairment at an early stage (AAIC 2014, in Copenhagen). In two studies, the decreased ability to identify various defined odors was significantly associated with loss of neuronal cells function and progression to Alzheimer's disease as measured by a variety of cognitive tests.

Imaging data from one study revealed that a smaller hippocampus and a thinner entorhinal cortex accompanied by higher levels of brain amyloid were linked to worsening of smell identification abilities and memory after adjusting for parameters that includes age, gender,

A separate study conducted at Columbia University Medical Center looked at odor Identifi‐ cation deficits association with Transition from Mild Cognitive Impairment to Alzheimer's. Researchers investigated a multi-ethnic sample of 1037 non-demented elderly people in New York City, (average age of 80.7) and assessed their olfaction abilities in a variety of ways at three time periods. 109 people developed dementia (101=Alzheimer's and eight non-AD dementia) a significant incapacity to correctly identify odors was found to be associated with

**10. Impairment of odor detection as early AD diagnostic**

may be used as a means of monitoring response to therapy.

significantly correlated with PET imaging results.

and an estimate of cognitive reserve(AAIC 2014).

the early development of dementia in those patients.

O2-05-05 and O3-13-01).

242 Alzheimer's Disease - Challenges for the Future

There are very few reports describing the discovery of any AD-related urine biomarker, and the few that are reported and published have met the AD research field with controversy. One of them is called NTP (Neural Thread Protein), a membrane-associated phosphoprotein that made the headlines in 2007 when a company called Nymox Corporation got an EIA kit CE approved in Europe for the diagnosis of AD using urine samples. Although Nymox claimed the utility of the test, one blinded study conducted in the Czech Republic by a reference lab using the Nymox test found that when compared to the diagnosis established by NINCDS-ADRDA for AD, the test appeared to have low sensitivity and specificity. Very recently, two studies evaluating the levels of NTP in urine were published [135, 136]. In the first study, levels of NTP in AD, PD, and Healthy participants were evaluated (AD (49, PD (20), HC (22) using Nymox AlzhemAlert test. AD patients had significantly higher levels of NTP than HC and that those of PD. Although the authors concluded that urine NTP could be used as a promising biomarker of AD, it should be noted that there was an age difference among participants that could potentially affect this interpretation. Average age for each group was as follows: AD (72.2+/-7.5), PD (66.4 +/- 8.8), Control (64.1+/-6.8).

In a second separate recent study [137], NTP levels were compared in relation to age in HC volunteers divided into 5 groups (20-29, 30-39,40-49,50-59 and >=60) using a different test called 7c Gold..It is not clear as to why the levels detected in this study are in ng/ml range as opposed to the ug/ml range for the Nymox Kit since both studies were conducted on Asian patients. The authors concluded though that urine levels of NTP increase with age significantly which might explain the controversy around NTP as an AD biomarker.

## **12. Conclusion**

#### **12.1. Hurdles to blood-based AD biomarker development**

Replicating candidate blood biomarker findings has been the biggest challenge of the research field [138]. Several pre-analytical components factors are likely to make discoveries very challenging: choice of anticoagulant (EDTA, Heparin), addition of protease inhibitors, needle size, order of blood draw, processing time, storage condition, freeze/thaw cycles and centri‐ fugation procedures are just a few parameters that can affect drastically the detection of several analytes [128, 138]. Longitudinal analysis from the same patient is essential to find early markers, but the success of this approach highly depends on analyte stability during >10 years storage. Blood is also a constantly changing matrix where components levels are affected by multiple factors such as diet, lifestyle, circadian changes and other co-morbidities, especially in an elderly population such as Alzheimer's Disease patients which quite frequently suffers from other diseases where inflammation is implicated such as diabetes, rheumatoid arthritis and cardiovascular diseases [139].Further complicating discoveries is the fact that several patients have mixed dementias such as Vascular Dementia, Fronto Temporal Lobe Dementia (FTLD) and Dementia with Lewy-body (DLB) making it difficult to identify a particular marker. Importantly, the integrity of the blood-brain barrier and its impact on AD-related biomarkers might differ from patient to patient based on genetics and other factors [140].Another less discussed parameter that we found that is crucial for the discovery of true AD blood biomarkers is the definition of healthy controls. We realized talking to clinical physicians in Japan, US, and EU that in many instances, healthy elderly control samples are obtained from caregivers or spouses living with the patients. This is a particular concern since epidemiological studies have demonstrated that living with an AD patient increases the risk to develop the disease by six-fold [141]. The reason is not exactly known but contributing factors such as exposure to pollutants (air, water, contaminants in food, etc) and pathogens [142, 143] by the patient and the spouse for several years living in the same environment may play a role. We also heard through interviews with clinicians that several healthy control samples are obtained from patients who went to a clinic after complaining of some abnormal‐ ities that were later ruled out as not being related to dementia. The inclusion of such patient samples in the control group category may also contribute to the difficulty of identifying a true AD biomarker.

While co-morbidities cannot be avoided when comparing AD and control groups, it is important to the research field to agree on standard practices to ensure reproducibility of data and that careful selection of healthy controls be conducted before doing any comparisons. At least, initiatives like the Blood-Based Biomarker Interest Group and the release of FDA guidelines for the analytical validation of assays that meet GCP/GLP will hopefully lead to the adoption of robust standards for the research field that applies to the analysis of proteins, metabolites, lipids and miRNAs in serum and plasma to control for precision, analytical accuracy and dilution linearity.

One more important point for the successful development and adoption of blood-based AD biomarkers is to understand the relationship with the disease as AD is essentially a brain disorder with little manifestation of illness in the peripheral system. Such understanding of the biomarker, its function, and its contribution to the illness state is essential to promote the confirmation by peers. Moreover, such clarification could lead to the discovery of even better biomarkers that could be used to detect the disease at an even earlier state or lead to the identification of novel drug targets. Such functional identification as much as the validation is critical to promote the verification of novel candidate biomarker in exploratory studies that are part of sponsored clinical trials.

In conclusion, blood tests or other non-invasive tests as biomarkers for AD are appealing as they could be applied to many uses such as patient screening, disease prognosis, diagnosis and aid to support clinical trial development. The development of such markers will be greatly facilitated once we fully understand what is causing sporadic AD in the first place and after more comprehensive studies will be able to look at correlation between endophenotypic changes in the brain using imaging technologies and the candidate biomarkers.

## **Author details**

in an elderly population such as Alzheimer's Disease patients which quite frequently suffers from other diseases where inflammation is implicated such as diabetes, rheumatoid arthritis and cardiovascular diseases [139].Further complicating discoveries is the fact that several patients have mixed dementias such as Vascular Dementia, Fronto Temporal Lobe Dementia (FTLD) and Dementia with Lewy-body (DLB) making it difficult to identify a particular marker. Importantly, the integrity of the blood-brain barrier and its impact on AD-related biomarkers might differ from patient to patient based on genetics and other factors [140].Another less discussed parameter that we found that is crucial for the discovery of true AD blood biomarkers is the definition of healthy controls. We realized talking to clinical physicians in Japan, US, and EU that in many instances, healthy elderly control samples are obtained from caregivers or spouses living with the patients. This is a particular concern since epidemiological studies have demonstrated that living with an AD patient increases the risk to develop the disease by six-fold [141]. The reason is not exactly known but contributing factors such as exposure to pollutants (air, water, contaminants in food, etc) and pathogens [142, 143] by the patient and the spouse for several years living in the same environment may play a role. We also heard through interviews with clinicians that several healthy control samples are obtained from patients who went to a clinic after complaining of some abnormal‐ ities that were later ruled out as not being related to dementia. The inclusion of such patient samples in the control group category may also contribute to the difficulty of identifying a true

While co-morbidities cannot be avoided when comparing AD and control groups, it is important to the research field to agree on standard practices to ensure reproducibility of data and that careful selection of healthy controls be conducted before doing any comparisons. At least, initiatives like the Blood-Based Biomarker Interest Group and the release of FDA guidelines for the analytical validation of assays that meet GCP/GLP will hopefully lead to the adoption of robust standards for the research field that applies to the analysis of proteins, metabolites, lipids and miRNAs in serum and plasma to control for precision, analytical

One more important point for the successful development and adoption of blood-based AD biomarkers is to understand the relationship with the disease as AD is essentially a brain disorder with little manifestation of illness in the peripheral system. Such understanding of the biomarker, its function, and its contribution to the illness state is essential to promote the confirmation by peers. Moreover, such clarification could lead to the discovery of even better biomarkers that could be used to detect the disease at an even earlier state or lead to the identification of novel drug targets. Such functional identification as much as the validation is critical to promote the verification of novel candidate biomarker in exploratory studies that

In conclusion, blood tests or other non-invasive tests as biomarkers for AD are appealing as they could be applied to many uses such as patient screening, disease prognosis, diagnosis and aid to support clinical trial development. The development of such markers will be greatly facilitated once we fully understand what is causing sporadic AD in the first place and after more comprehensive studies will be able to look at correlation between endophenotypic

changes in the brain using imaging technologies and the candidate biomarkers.

AD biomarker.

accuracy and dilution linearity.

244 Alzheimer's Disease - Challenges for the Future

are part of sponsored clinical trials.

Francois Bernier1 , Pavan Kumar2 , Yoshiaki Sato1 and Yoshiya Oda1,2\*

\*Address all correspondence to: yoshiya\_oda@eisai.com

1 Eisai Co., Ltd., Tokodai, Tsukuba, Ibaraki, Japan

2 Eisai IncAndover, MA, USA

## **References**


[24] Cummings JL. Biomarkers in Alzheimer's disease drug development. Alzheimers Dement. 2011 May;7(3):e13-44.

[11] Salloway S, Sperling R, Fox NC, Blennow K, Klunk W, Raskind M, et al. Two phase 3 trials of bapineuzumab in mild-to-moderate Alzheimer's disease. N Engl J Med. 2014

[12] Doody RS, Thomas RG, Farlow M, Iwatsubo T, Vellas B, Joffe S, et al. Phase 3 trials of solanezumab for mild-to-moderate Alzheimer's disease. N Engl J Med. 2014 Jan

[13] Grimmer T, Wutz C, Drzezga A, Forster S, Forstl H, Ortner M, et al. The usefulness of amyloid imaging in predicting the clinical outcome after two years in subjects

[14] Okello A, Koivunen J, Edison P, Archer HA, Turkheimer FE, Nagren K, et al. Conver‐ sion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET

[15] Weiner MW. Commentary on "Biomarkers in Alzheimer's disease drug develop‐ ment." The view from Alzheimer's Disease Neuroimaging Initiative. Alzheimers De‐

[16] Mitka M. PET imaging for Alzheimer disease: are its benefits worth the cost? JAMA.

[17] Lorenzi M, Donohue M, Paternico D, Scarpazza C, Ostrowitzki S, Blin O, et al. En‐ richment through biomarkers in clinical trials of Alzheimer's drugs in patients with

[18] High-tech scan reveals protein in the brain linked to Alzheimer's disease. A special form of PET scanning offers a more certain diagnosis for some, but at a steep out-of-

[19] McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical di‐ agnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheim‐

[20] Tanne JH. US scientists discuss early detection and treatment of Alzheimer's disease.

[21] Jack CR, Jr., Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypo‐ thetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lan‐

[22] Fjell AM, Walhovd KB. Neuroimaging results impose new views on Alzheimer's dis‐

[23] Blennow K. Biomarkers in Alzheimer's disease drug development. Nat Med. 2010

ease--the role of amyloid revised. Mol Neurobiol. 2012 Feb;45(1):153-72.

mild cognitive impairment. Neurobiol Aging. 2010 Aug;31(8):1443-51, 51 e1.

pocket cost. Harv Mens Health Watch. 2014 Feb;18(7):6.

er's Disease. Neurology. 1984 Jul;34(7):939-44.

with mild cognitive impairment. Curr Alzheimer Res. 2013 Jan;10(1):82-5.

study. Neurology. 2009 Sep 8;73(10):754-60.

ment. 2011 May;7(3):e45-7.

2013 Mar 20;309(11):1099-100.

BMJ. 2012;344:e1068.

Nov;16(11):1218-22.

cet Neurol. 2010 Jan;9(1):119-28.

Jan 23;370(4):322-33.

246 Alzheimer's Disease - Challenges for the Future

23;370(4):311-21.


[49] Herskovits AZ, Locascio JJ, Peskind ER, Li G, Hyman BT. A Luminex assay detects amyloid beta oligomers in Alzheimer's disease cerebrospinal fluid. PLoS One. 2013;8(7):e67898.

[37] Perez-Grijalba V, Pesini P, Allue JA, Sarasa L, Montanes M, Lacosta AM, et al. Abe‐ ta1-17 is a Major Amyloid-beta Fragment Isoform in Cerebrospinal Fluid and Blood with Possible Diagnostic Value in Alzheimer's Disease. J Alzheimers Dis. 2014 Jul 24.

[38] Wu G, Sankaranarayanan S, Wong J, Tugusheva K, Michener MS, Shi X, et al. Char‐ acterization of plasma beta-secretase (BACE1) activity and soluble amyloid precursor proteins as potential biomarkers for Alzheimer's disease. J Neurosci Res. 2012 Dec;

[39] Kaneko N, Nakamura A, Washimi Y, Kato T, Sakurai T, Arahata Y, et al. Novel plas‐ ma biomarker surrogating cerebral amyloid deposition. Proc Jpn Acad Ser B Phys Bi‐

[40] Noguchi-Shinohara M, Hamaguchi T, Nozaki I, Sakai K, Yamada M. Serum tau pro‐ tein as a marker for the diagnosis of Creutzfeldt-Jakob disease. J Neurol. 2011 Aug;

[41] Blennow K, Hampel H, Weiner M, Zetterberg H. Cerebrospinal fluid and plasma bio‐

[42] Neselius S, Zetterberg H, Blennow K, Marcusson J, Brisby H. Increased CSF levels of phosphorylated neurofilament heavy protein following bout in amateur boxers.

[43] Neselius S, Zetterberg H, Blennow K, Randall J, Wilson D, Marcusson J, et al. Olym‐ pic boxing is associated with elevated levels of the neuronal protein tau in plasma.

[44] Randall J, Mortberg E, Provuncher GK, Fournier DR, Duffy DC, Rubertsson S, et al. Tau proteins in serum predict neurological outcome after hypoxic brain injury from

[45] Neumann K, Farias G, Slachevsky A, Perez P, Maccioni RB. Human platelets tau: a potential peripheral marker for Alzheimer's disease. J Alzheimers Dis. 2011;25(1):

[46] Upadhaya AR, Lungrin I, Yamaguchi H, Fandrich M, Thal DR. High-molecular weight Abeta oligomers and protofibrils are the predominant Abeta species in the native soluble protein fraction of the AD brain. J Cell Mol Med. 2012 Feb;16(2):287-95.

[47] Yoshiike Y, Chui DH, Akagi T, Tanaka N, Takashima A. Specific compositions of amyloid-beta peptides as the determinant of toxic beta-aggregation. J Biol Chem.

[48] Savage MJ, Kalinina J, Wolfe A, Tugusheva K, Korn R, Cash-Mason T, et al. A sensi‐ tive abeta oligomer assay discriminates Alzheimer's and aged control cerebrospinal

cardiac arrest: results of a pilot study. Resuscitation. 2013 Mar;84(3):351-6.

markers in Alzheimer disease. Nat Rev Neurol. 2010 Mar;6(3):131-44.

90(12):2247-58.

248 Alzheimer's Disease - Challenges for the Future

258(8):1464-8.

103-9.

ol Sci. 2014;90(9):353-64.

PLoS One. 2013;8(11):e81249.

Brain Inj. 2013;27(4):425-33.

2003 Jun 27;278(26):23648-55.

fluid. J Neurosci. 2014 Feb 19;34(8):2884-97.


ease. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring. 2014; (in press).

[75] Swaminathan S, Shen L, Risacher SL, Yoder KK, West JD, Kim S, et al. Amyloid path‐ way-based candidate gene analysis of [(11)C]PiB-PET in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Brain Imaging Behav. 2012 Mar;6(1):1-15.

[61] Di Paolo G, Kim TW. Linking lipids to Alzheimer's disease: cholesterol and beyond.

[62] Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat

[63] Han X, Rozen S, Boyle SH, Hellegers C, Cheng H, Burke JR, et al. Metabolomics in early Alzheimer's disease: identification of altered plasma sphingolipidome using

[64] Mielke MM, Haughey NJ, Bandaru VV, Weinberg DD, Darby E, Zaidi N, et al. Plas‐ ma sphingomyelins are associated with cognitive progression in Alzheimer's disease.

[65] Oresic M, Hyotylainen T, Herukka SK, Sysi-Aho M, Mattila I, Seppanan-Laakso T, et al. Metabolome in progression to Alzheimer's disease. Transl Psychiatry. 2011;1:e57.

[66] Spann NJ, Garmire LX, McDonald JG, Myers DS, Milne SB, Shibata N, et al. Regulat‐ ed accumulation of desmosterol integrates macrophage lipid metabolism and inflam‐

[67] Hu X, Wang Y, Hao LY, Liu X, Lesch CA, Sanchez BM, et al. Sterol metabolism con‐ trols T(H)17 differentiation by generating endogenous RORgamma agonists. Nat

[68] Sato Y, Suzuki I, Nakamura T, Bernier F, Aoshima K, Oda Y. Identification of a new plasma biomarker of Alzheimer's disease using metabolomics technology. J Lipid

[69] Jansen LA. Ethical concerns relating to the detection and treatment of ovarian cancer.

[70] Jansen M, Wang W, Greco D, Bellenchi GC, di Porzio U, Brown AJ, et al. What dic‐ tates the accumulation of desmosterol in the developing brain? FASEB J. 2013 Mar;

[71] Vance JE. Dysregulation of cholesterol balance in the brain: contribution to neurode‐

[72] Karasinska JM, Hayden MR. Cholesterol metabolism in Huntington disease. Nat Rev

[73] Popp J, Meichsner S, Kolsch H, Lewczuk P, Maier W, Kornhuber J, et al. Cerebral and extracerebral cholesterol metabolism and CSF markers of Alzheimer's disease. Bio‐

[74] Sato Y, Bernier F, Yamanaka Y, Aoshima K, Oda Y, Ingelsson M, et al. Reduced plas‐ ma desmosterol/cholesterol and longitudinal cognitive decline in Alzheimer's dis‐

generative diseases. Dis Model Mech. 2012 Nov;5(6):746-55.

Nat Rev Neurosci. 2011 May;12(5):284-96.

shotgun lipidomics. PLoS One. 2011;6(7):e21643.

matory responses. Cell. 2012 Sep 28;151(1):138-52.

J Alzheimers Dis. 2011;27(2):259-69.

Chem Biol. 2015 Feb;11(2):141-7.

Gynecol Oncol. 2002 Jan;84(1):1-3.

Neurol. 2011 Oct;7(10):561-72.

chem Pharmacol. 2013 Jul 1;86(1):37-42.

Res. 2012 Mar;53(3):567-76.

27(3):865-70.

Med. 2014 Apr;20(4):415-8.

250 Alzheimer's Disease - Challenges for the Future


[101] Patel N, Hoang D, Miller N, Ansaloni S, Huang Q, Rogers JT, et al. MicroRNAs can regulate human APP levels. Mol Neurodegener. 2008;3:10.

[87] Gallo A, Tandon M, Alevizos I, Illei GG. The majority of microRNAs detectable in serum and saliva is concentrated in exosomes. PLoS One. 2012;7(3):e30679.

[88] Michael A, Bajracharya SD, Yuen PS, Zhou H, Star RA, Illei GG, et al. Exosomes from human saliva as a source of microRNA biomarkers. Oral Dis. 2010 Jan;16(1):34-8. [89] Wang D, Qiu C, Zhang H, Wang J, Cui Q, Yin Y. Human microRNA oncogenes and tumor suppressors show significantly different biological patterns: from functions to

[90] Arroyo JD, Chevillet JR, Kroh EM, Ruf IK, Pritchard CC, Gibson DF, et al. Argo‐ naute2 complexes carry a population of circulating microRNAs independent of vesi‐

[91] Turchinovich A, Weiz L, Langheinz A, Burwinkel B. Characterization of extracellular

[92] Xu J, Wu C, Che X, Wang L, Yu D, Zhang T, et al. Circulating microRNAs, miR-21, miR-122, and miR-223, in patients with hepatocellular carcinoma or chronic hepatitis.

[93] Roth P, Wischhusen J, Happold C, Chandran PA, Hofer S, Eisele G, et al. A specific miRNA signature in the peripheral blood of glioblastoma patients. J Neurochem.

[94] Malumbres R, Sarosiek KA, Cubedo E, Ruiz JW, Jiang X, Gascoyne RD, et al. Differ‐ entiation stage-specific expression of microRNAs in B lymphocytes and diffuse large

[95] Dong Y, Wu WK, Wu CW, Sung JJ, Yu J, Ng SS. MicroRNA dysregulation in colorec‐

[96] Li J, Wang Y, Yu W, Chen J, Luo J. Expression of serum miR-221 in human hepatocel‐ lular carcinoma and its prognostic significance. Biochem Biophys Res Commun. 2011

[97] Delay C, Hebert SS. MicroRNAs and Alzheimer's Disease Mouse Models: Current In‐ sights and Future Research Avenues. Int J Alzheimers Dis. 2011;2011:894938.

[98] Long JM, Ray B, Lahiri DK. MicroRNA-153 physiologically inhibits expression of amyloid-beta precursor protein in cultured human fetal brain cells and is dysregulat‐ ed in a subset of Alzheimer disease patients. J Biol Chem. 2012 Sep 7;287(37):

[99] Long JM, Lahiri DK. MicroRNA-101 downregulates Alzheimer's amyloid-beta pre‐ cursor protein levels in human cell cultures and is differentially expressed. Biochem

[100] John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS. Human MicroRNA tar‐

tal cancer: a clinical perspective. Br J Cancer. 2011 Mar 15;104(6):893-8.

cles in human plasma. Proc Natl Acad Sci U S A. 2011 Mar 22;108(12):5003-8.

circulating microRNA. Nucleic Acids Res. 2011 Sep 1;39(16):7223-33.

targets. PLoS One. 2010;5(9).

252 Alzheimer's Disease - Challenges for the Future

Mol Carcinog. 2011 Feb;50(2):136-42.

B-cell lymphomas. Blood. 2009 Apr 16;113(16):3754-64.

Biophys Res Commun. 2011 Jan 28;404(4):889-95.

gets. PLoS Biol. 2004 Nov;2(11):e363.

2011 Aug;118(3):449-57.

Mar 4;406(1):70-3.

31298-310.


[128] Cheng HH, Yi HS, Kim Y, Kroh EM, Chien JW, Eaton KD, et al. Plasma processing conditions substantially influence circulating microRNA biomarker levels. PLoS One. 2013;8(6):e64795.

[115] Hollingworth P, Harold D, Sims R, Gerrish A, Lambert JC, Carrasquillo MM, et al. Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are as‐

[116] McGuinness B, Passmore P. Can statins prevent or help treat Alzheimer's disease? J

[117] Tan L, Yu JT, Tan MS, Liu QY, Wang HF, Zhang W, et al. Genome-wide serum mi‐ croRNA expression profiling identifies serum biomarkers for Alzheimer's disease. J

[118] McDermott AM, Kerin MJ, Miller N. Identification and validation of miRNAs as en‐ dogenous controls for RQ-PCR in blood specimens for breast cancer studies. PLoS

[119] Chen ZH, Zhang GL, Li HR, Luo JD, Li ZX, Chen GM, et al. A panel of five circulat‐ ing microRNAs as potential biomarkers for prostate cancer. Prostate. 2012 Sep

[120] Dickerson BC, Wolk DA. Biomarker-based prediction of progression in MCI: Com‐ parison of AD signature and hippocampal volume with spinal fluid amyloid-beta

[121] Leidinger P, Backes C, Deutscher S, Schmitt K, Mueller SC, Frese K, et al. A blood based 12-miRNA signature of Alzheimer disease patients. Genome Biol.

[122] Galimberti D, Villa C, Fenoglio C, Serpente M, Ghezzi L, Cioffi SM, et al. Circulating miRNAs as Potential Biomarkers in Alzheimer's Disease. J Alzheimers Dis. 2014 Jul

[123] Jarry J, Schadendorf D, Greenwood C, Spatz A, van Kempen LC. The validity of cir‐ culating microRNAs in oncology: five years of challenges and contradictions. Mol

[124] Kim YK, Yeo J, Kim B, Ha M, Kim VN. Short structured RNAs with low GC content are selectively lost during extraction from a small number of cells. Mol Cell. 2012 Jun

[125] Zhang X, Azhar G, Wei JY. The expression of microRNA and microRNA clusters in

[126] Kirschner MB, Edelman JJ, Kao SC, Vallely MP, van Zandwijk N, Reid G. The Impact of Hemolysis on Cell-Free microRNA Biomarkers. Front Genet. 2013;4:94.

[127] Blondal T, Jensby Nielsen S, Baker A, Andreasen D, Mouritzen P, Wrang Teilum M, et al. Assessing sample and miRNA profile quality in serum and plasma or other bio‐

sociated with Alzheimer's disease. Nat Genet. 2011 May;43(5):429-35.

Alzheimers Dis. 2010;20(3):925-33.

Alzheimers Dis. 2014;40(4):1017-27.

and tau. Front Aging Neurosci. 2013;5:55.

the aging heart. PLoS One. 2012;7(4):e34688.

fluids. Methods. 2013 Jan;59(1):S1-6.

One. 2013;8(12):e83718.

15;72(13):1443-52.

254 Alzheimer's Disease - Challenges for the Future

2013;14(7):R78.

29;46(6):893-5.

Oncol. 2014 Jun;8(4):819-29.

7.


## **New Frontiers in Alzheimer's Disease Diagnosis**

Franc Llorens, Sabine Nuhn, Christoph Peter, Inga Zerr and Katharina Stoeck

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/59652

## **1. Introduction**

[142] Honjo K, van Reekum R, Verhoeff NP. Alzheimer's disease and infection: do infec‐ tious agents contribute to progression of Alzheimer's disease? Alzheimers Dement.

[143] Itzhaki RF, Wozniak MA, Appelt DM, Balin BJ. Infiltration of the brain by pathogens causes Alzheimer's disease. Neurobiol Aging. 2004 May-Jun;25(5):619-27.

2009 Jul;5(4):348-60.

256 Alzheimer's Disease - Challenges for the Future

Alzheimer´s disease (AD) is the most prevalent form of dementia accounting for 60-70% of all cases worldwide. As the world's population ages the incidence of AD is expected to increase rapidly turning into a global epidemic disease with incalculable sociologi‐ cal and economic consequences. In 2006, the prevalence of AD worldwide was calculated in 26.6 million and it is estimated that by 2050 current prevalence will be triplicated or quadruplicated, affecting 1 out of 85 persons worldwide [1, 2]. An accurate diagnosis and a timely detection are critical for improving the physical, clinical, emotional and financial impacts of the disease. However, this aim is far to be achieved and several studies indicate that less than 35 percentage of people living with AD or related dementias are correctly diagnosed [3, 4]. As a consequence, between 18% and 67% of the dementia patients are treated with a potentially inappropriate medication [5].

In this dramatic scenario, new technical, methodological and notional approaches are explored in order to overcome the inherent limitations in AD clinical diagnosis. Indeed, the identifica‐ tion of reliable diagnostic tools in AD remains impeded by the clinical, neuropathological and molecular overlap existing between AD and other types of dementia such as Mild Cognitive Impairment (MCI), or mixed forms of dementia, such as Vascular Dementia (VaD), Fronto‐ temporal Lobar Degeneration (FTLD) or Lewy Body Dementia (LBD), and by the high AD heterogeneity according to disease onset, progression and duration [6-8].

Since the complexity of this scenario impairs the use of current diagnostic tools for a correct data interpretation, in the recent years, new strategies such as the integrated and combined use of neuropsychological profiles, imaging and biological fluids biomarkers have been developed, improving current diagnosis classification [9-11] and predicting the conversion from MCI to AD [12, 13].

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

Despite recent solid advances in the topic, up to date, no single diagnostic tool or combination of diagnostic tools can unequivocally confirm AD diagnosis. Indeed absolute confirmation and definite AD diagnostic still requires histopathologic analysis on the post-mortem brain certifying the presence of the pathologic disease hallmarks such as β-amyloid plaques and neurofibrillary tangles.

Since AD is a progressive disease and no treatment is available to recover neuronal integrity, the inaccuracy of AD early diagnosis and prognosis makes early therapeutic intervention difficult and impedes the prevention of neurodegeneration and cognitive dysfunction.

Identification of disease specific clinical, imaging and biochemical-based tools at early stages will help to greater extent to an early treatment which may restrain the disease progression. Additionally, a thorough understanding of the role of biomarkers in AD disease and their modulated levels in AD patients will facilitate the comprehension of their role in AD etiopa‐ thology and would help to establish a link between diagnostic and therapeutic fields. There‐ fore, the ultimate goal is to develop early and reliable diagnosis methods to establish an appropriate and prompt treatment. Indeed this aspect is imperative to maximize the efficiency of potential therapies and decrease symptomatology before pathological changes spread throughout the brain and massive death of neurons has already occurred. Finally, it should also be taken into consideration that the development of successful epidemiological risk assessment and diagnosis programs, including a routinely monitoring of disease progression, will need to be established through the development of new methodologies and protocols at low cost and with non-invasive approaches.

The present chapter summarizes the most recent findings in the field of AD, including neuropsychological profiles and brain and biological fluids biomarkers, which are currently paving the way for new focused approaches in AD diagnosis and prognosis.

## **2. Diagnostic criteria/Clinical and research criteria**

According to the International Classification of Diseases (ICD-10) and the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association (DSM IV) dementia is defined as a a worsening of cognitive function from a preexisting individual level. The major symptom is decline in memory and should be followed by at least one dysfunction in another major cognitive core skill, severe enough to impair a person's ability to perform everyday activities. The cognitive impairments should be irreversible and not be attributable to e.g. a delirium or another psychiatric disorder and must be present for at least 6 month.

Moreover, the German Society of Psychiatry, Psychotherapy and Neurology (DGPPN) as well as the German Neurological Society (DGN) refer to a subtle change in personality and behavior in the process of dementia [14]. The criteria of the American National Institute of Neurological and Communicative Disorders and Stroke/Alzheimer's disease and Related Disorders Association (NINCDS/ADRDA) are more often referred to in the literature, which differentiate the degree of diagnostic accuracy in "possible" or "probable dementia" [15, 16].

Based on the latter, commonly accepted dementia criteria, a "probable Alzheimer's dementia" (AD dementia) is diagnosed by signs of dementia on clinical examination and neuropsycho‐ logical tests whereby the memory impairment should be followed by another deficit in an additional cognitive skill. In alternative there is impairment in two cognitive skills with a recognized progression and without evidence of a reduced consciousness.

Despite recent solid advances in the topic, up to date, no single diagnostic tool or combination of diagnostic tools can unequivocally confirm AD diagnosis. Indeed absolute confirmation and definite AD diagnostic still requires histopathologic analysis on the post-mortem brain certifying the presence of the pathologic disease hallmarks such as β-amyloid plaques and

Since AD is a progressive disease and no treatment is available to recover neuronal integrity, the inaccuracy of AD early diagnosis and prognosis makes early therapeutic intervention difficult and impedes the prevention of neurodegeneration and cognitive dysfunction.

Identification of disease specific clinical, imaging and biochemical-based tools at early stages will help to greater extent to an early treatment which may restrain the disease progression. Additionally, a thorough understanding of the role of biomarkers in AD disease and their modulated levels in AD patients will facilitate the comprehension of their role in AD etiopa‐ thology and would help to establish a link between diagnostic and therapeutic fields. There‐ fore, the ultimate goal is to develop early and reliable diagnosis methods to establish an appropriate and prompt treatment. Indeed this aspect is imperative to maximize the efficiency of potential therapies and decrease symptomatology before pathological changes spread throughout the brain and massive death of neurons has already occurred. Finally, it should also be taken into consideration that the development of successful epidemiological risk assessment and diagnosis programs, including a routinely monitoring of disease progression, will need to be established through the development of new methodologies and protocols at

The present chapter summarizes the most recent findings in the field of AD, including neuropsychological profiles and brain and biological fluids biomarkers, which are currently

According to the International Classification of Diseases (ICD-10) and the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association (DSM IV) dementia is defined as a a worsening of cognitive function from a preexisting individual level. The major symptom is decline in memory and should be followed by at least one dysfunction in another major cognitive core skill, severe enough to impair a person's ability to perform everyday activities. The cognitive impairments should be irreversible and not be attributable to e.g. a delirium or another psychiatric disorder and must be present for at least 6 month.

Moreover, the German Society of Psychiatry, Psychotherapy and Neurology (DGPPN) as well as the German Neurological Society (DGN) refer to a subtle change in personality and behavior in the process of dementia [14]. The criteria of the American National Institute of Neurological and Communicative Disorders and Stroke/Alzheimer's disease and Related Disorders Association (NINCDS/ADRDA) are more often referred to in the literature, which differentiate

the degree of diagnostic accuracy in "possible" or "probable dementia" [15, 16].

paving the way for new focused approaches in AD diagnosis and prognosis.

**2. Diagnostic criteria/Clinical and research criteria**

neurofibrillary tangles.

258 Alzheimer's Disease - Challenges for the Future

low cost and with non-invasive approaches.

The age at onset should range between 40 and 90 years and other reasons for the cognitive decline, e.g. treatable causes, should have been carefully ruled out in the diagnostic work up.

The clinical criteria of a "possible Alzheimer's dementia" comprise a dementia syndrome of untypical clinical presentation or duration in absence of other recognizable factors causative of dementia, or if there is a progressive cognitive deficit without a recognized underlying cause.

Exclusion criteria are referred to as sudden onset, focal neurological signs (hemiparesis, hemianopsia) at onset as well as early appearance of gait disorders or epileptic fits.

This categorization is kept according to different revisions of the NINCDS/ADRDA-criteria [16, 17]. Additionally, next to deficits in episodic memory, detection of specific biomarkers in the cerebrospinal fluid (CSF) and imaging (Magnetic Resonance Imaging (MRI) and/or Emission Computed Tomography (PET) is suggested which can increase sensitivity of AD diagnosis.

Further supporting results are, e.g., a progressive worsening of specific cognitive function, disabling in all-day activities, and occurrence of behavioral changes, a positive family history of AD (especially if neuropathologically confirmed), a normal CSF result (basic analysis) and unspecific electroencephalogram (EEG) changes.

A diagnosis of AD is compatible with plateaus during disease course, side symptoms as depression, aggressive behavior, paranoia etc., neurological symptoms in progressed disease state (myoclonus, gait problems, epileptic fits) and a normal Computerized Tomography (CT) scan [14].

While both terminologies: "probable AD", "possible AD" are proposed for the clinical setting, a third category of "probable and possible AD" was suggested for research purposes. Recent research criteria for clinical AD diagnosis include next to mnestic deficits an occurrence of deficits in non-mnestic function, e.g., language, visual-spatial orientation, executive function. Furthermore, an early diagnosis of AD is proposed already during prodromal stages of dementia, which refer to the clinical picture of a mild cognitive impairment (MCI) [18].

A MCI is a recognized risk factor for AD. Yet, there are presently no commonly agreed criteria [14]. According to international consensus criteria, MCI is considered a condition between normal and demented, a worsening of cognitive function (on self-observation or observation by others) that can be demonstrated on neuropsychological tests, a worsening of cognitive function during an observational time period during disease as well as conserved or only minimally impaired dysfunction in complex all-day activities [19]. The difference between MCI and dementia is based mostly on well-functioning in all-day activities. Standard meas‐ urements for cognitive function comprise 1-1.5 standard deviation below the age- and education-matched age group and a mini-mental status test of 24 or above points [18, 20].

The prevalence and conversion rates are variable according to the distinct examination setting. In the clinical setting the annual conversion rate from MCI to AD has been calculated at around 10 percent [14, 21].

At present 4 different MCI subtypes are characterized: amnestic single domain, amnestic multiple domains, non-amnestic single domain and non-amnestic multiple domains [20], whereas the probability to develop AD is highest in MCI with memory deficits [14, 21].

## **3. Neuropsychological profiles**

### **3.1. The neuropsychological profile of AD**

AD is generally characterized by a slowly progressive preclinical (pre-symptomatical) state over several years, an approximately 1-2 years lasting pre-dementia phase until development of dementia, which can be categorized into 3 states (mild, medium, severe) [22, 23].

The progressive cognitive deficits hereby parallel neuropathological changes in the brain, whereby cognitive deficits vary individually. The degree of disease severeness refers to cognition and life skills, whereby transition of states can merge. A mild dementia is considered when complex tasks cannot be performed anymore, but an independent life organisation is still possible. A medium-state dementia is referred to if an independent life organisation is impaired but possible with help and observation of family and care-givers. In severe dementia constant guidance and help is required, an independent life organisation is not possible anymore.

At early stages of AD deficits are predominantly characterized by impairment of declarative memory, visual-spatial orientation and lexical-semantic language. Emotionally, in social contacts as well as in personality, patients with AD appear normal for a long period of time ("facade"). They tend to trivialize their deficits. When they recognize cognitive dysfunction, AD patients often describe themselves to be more forgetful without further specification.

*Memory impairment* (representative brain areas: hippocampus, gyrus parahippocampalis and adjusted temporomedial areas) affects the ability to encode and recapitulate novel memory contents for a longer period of time, whereas the short time memory and the working memory are mostly unaffected in early stages. The procedural memory often keeps unaffected. In the clinical setting progressive memory deficits often appear in forgetfulness of novel information, in repetitive phrases, difficulties in maintaining complex tasks (strands), e.g. forgetting where the keys/money have been stored, which can lead to paranoid reactions. Neuropsychological characterisations are a slow learning curve, rapid forgetfulness, recency-effects due to deficits in encoding, impaired and prolonged memorising, intrusions and a reduced discriminationability, non-profit of context cues as well as deficits in orientation in time [22].

In further disease progression according to a time-associated gradient (first in- last out) also long term memories (semantic and biographical memory) are impaired, with affection of identity and personality in medium and severe AD stages [23].

urements for cognitive function comprise 1-1.5 standard deviation below the age- and education-matched age group and a mini-mental status test of 24 or above points [18, 20].

The prevalence and conversion rates are variable according to the distinct examination setting. In the clinical setting the annual conversion rate from MCI to AD has been calculated at around

At present 4 different MCI subtypes are characterized: amnestic single domain, amnestic multiple domains, non-amnestic single domain and non-amnestic multiple domains [20], whereas the probability to develop AD is highest in MCI with memory deficits [14, 21].

AD is generally characterized by a slowly progressive preclinical (pre-symptomatical) state over several years, an approximately 1-2 years lasting pre-dementia phase until development

The progressive cognitive deficits hereby parallel neuropathological changes in the brain, whereby cognitive deficits vary individually. The degree of disease severeness refers to cognition and life skills, whereby transition of states can merge. A mild dementia is considered when complex tasks cannot be performed anymore, but an independent life organisation is still possible. A medium-state dementia is referred to if an independent life organisation is impaired but possible with help and observation of family and care-givers. In severe dementia constant guidance and help is required, an independent life organisation is not possible

At early stages of AD deficits are predominantly characterized by impairment of declarative memory, visual-spatial orientation and lexical-semantic language. Emotionally, in social contacts as well as in personality, patients with AD appear normal for a long period of time ("facade"). They tend to trivialize their deficits. When they recognize cognitive dysfunction, AD patients often describe themselves to be more forgetful without further specification.

*Memory impairment* (representative brain areas: hippocampus, gyrus parahippocampalis and adjusted temporomedial areas) affects the ability to encode and recapitulate novel memory contents for a longer period of time, whereas the short time memory and the working memory are mostly unaffected in early stages. The procedural memory often keeps unaffected. In the clinical setting progressive memory deficits often appear in forgetfulness of novel information, in repetitive phrases, difficulties in maintaining complex tasks (strands), e.g. forgetting where the keys/money have been stored, which can lead to paranoid reactions. Neuropsychological characterisations are a slow learning curve, rapid forgetfulness, recency-effects due to deficits in encoding, impaired and prolonged memorising, intrusions and a reduced discrimination-

ability, non-profit of context cues as well as deficits in orientation in time [22].

of dementia, which can be categorized into 3 states (mild, medium, severe) [22, 23].

10 percent [14, 21].

260 Alzheimer's Disease - Challenges for the Future

anymore.

**3. Neuropsychological profiles**

**3.1. The neuropsychological profile of AD**

Deficits of the *visual-spatial orientation* (representative brain areas: parietal lobes) are often associates with important all-day activities: writing, calculating, reading the clock, getting dressed or basic orientation in space. This can overlap with memory deficits and deficits in planning skills. Firstly affected are untrained complex skills, e.g., drawing, clock drawing (mispositioning of the minute hand, confusion of hour/minute hand), reading street maps, orientation in unknown buildings, filling in documents. Drawings can show simplifications, repetitions, altered angles, "closing-in" and loss of perspective. Well established and trained skills, e.g., reading, signing a paper, getting dressed, are mainly affected in medium disease stage. A sensitive parameter that can be valuable in early AD diagnosis but also as a parameter of disease progression is clock reading as a trained skill [24, 25].

Deficits in visual-spatial orientation with massive impairment in complex visual awareness are the main characteristic and leading symptom of the *posterior cortical atrophy* (affected brain region: atrophy of the parietal and occipital lobe). The posterior cortical atro‐ phy is a recognised variant of AD with early onset, early visual agnosia and prosopag‐ nosia, whereas memory is less impaired in the beginning [23]. Depending on the affected projection system (occipital-parietal or occipital-temporal) problems of analysing visualspatial information: e.g., space, depth, movement, position and orientation (dorsal visual route/"where-system") or problems in analysing of shapes/structures, colours, objects, faces and complex space-topographical scenes (ventral visual route/"what system") can occur. Both systems are tightly connected [26, 27].

Affection of *language* (affected brain region: Wernicke area) is characterized by initial difficul‐ ties in finding the right words, which is compensated by strategies of avoidance and para‐ phrases as well as by difficulties in naming of less frequently used objects. The patients tend to make semantic-superior and semantic-associative mistakes (dog=animal, pyramid=Egypt or also volcano=vesuvius). Syntax, articulation and prosody are unaffected.

Material that they read is less often understood, the understanding of complex facts or contents in the figurative sense (collocations) is declining. Verbal fluency is reduced, whereas the semantic is more affected than the phonematic [28]. During disease, language becomes progressively poor of content, stays however relatively fluent with difficulties in word finding as well as with imprecise, diffuse and less informative comments, drifting from topic, talking cross purposes and setting phrases. This results in abrupt sentences, mistakes of syntax, phonematic paraphrases and in problems of speech comprehension for simple comments. In the final stages a total loss of speech occurs [23].

Next to the 3 main symptoms, disturbances in *executive function* (affected brain region: prefrontal cortex) appear. Executive functions comprise: problem solving thinking, monitor‐ ing, planning and conducting of complex tasks, working memory, cognitive fluidity and flexibility. Besides a reduced word fluidity and flexibility also abilities in planning can be impaired early. Especially the so-called set-shifting abilities, that require a permanent shift in alertness, are affected at early stages [29].

*Attention* is tightly associated with executive function. This is especially required in complex tasks. Deficits in attention initially present very discretely, e.g. in dual task-questions (pre‐ frontal cortex, anterior cingulum).

During disease progression, also alertness is impaired which presence of a more rapid exhaustion.

During medium stages all components of attention are majorly affected [22]. Last but not least, apraxia (affected brain region: parietal lobe) and agnosia (affected brain region: occipital lobe and both basal temporal neocortex) can occur already during early and middle stages of dementia. Simple movements are not possible any longer, inaccurate moves cannot be corrected, this can present as, e.g., body-part-as object-mistakes (ideomotoric apraxia), impairment of planning and conducting of sequential tasks (ideatoric apraxia), recognition of line drawing is inhibited.

Cognitive-related *impairment of all-day activities* affects complex instrumental skills in early stages of dementia, e.g. using new instruments, filling in written documents, later on using familiar devices and basal all-day abilities deteriorate progressively.

*Psychiatric side symptoms* such as anxiety, agitation, excitability, aggressive behaviour or paranoia are not frequently present in early stages, but appear more often in middle and late stages of disease. There is a higher vulnerability for states of disorientation already in the preclinical stage, e.g. after hospital admissions, drug intolerance, malnutrition. Also depres‐ sive mood changes as well as reduction of daily activities are considered early signs [23].

*Depression* is the most frequent psychiatric side symptom and accounts for about 30% of the patients, especially during early disease stage and here from the degree of presentation rather mild. However, depression is considered a main psychiatric disease in the elderly. In general, depressed patients can articulate their symptoms more precisely; they can manage their allday activities in a better way and demonstrate during neuropsychological testing self-doubts and complain about deficits in concentration. The mood is continuously suppressed and a lack of motivation is more exhibited.

The onset of cognitive deterioration is more distinct in patients with depression, whereas in patients with AD this occurs more gradually. The deficits can affect the whole spectrum of cognition, whereby executive dysfunction (predominantly flexibility) and problems with attention dominate. However, also memory deficits are described [30]. In detailed observation of single tasks aspects, e.g. in recalls of wordlists, primacy more than recency effects are shown, and recall is generally better.

While demented patients guess more often and describe things, depressed patients react with omissions and hesitant answers. Orientation is widely intact and confabulation, aphasic and apractic elements don't occur [22, 31].

#### **3.2. The neuropsychological examination**

impaired early. Especially the so-called set-shifting abilities, that require a permanent shift in

*Attention* is tightly associated with executive function. This is especially required in complex tasks. Deficits in attention initially present very discretely, e.g. in dual task-questions (pre‐

During disease progression, also alertness is impaired which presence of a more rapid

During medium stages all components of attention are majorly affected [22]. Last but not least, apraxia (affected brain region: parietal lobe) and agnosia (affected brain region: occipital lobe and both basal temporal neocortex) can occur already during early and middle stages of dementia. Simple movements are not possible any longer, inaccurate moves cannot be corrected, this can present as, e.g., body-part-as object-mistakes (ideomotoric apraxia), impairment of planning and conducting of sequential tasks (ideatoric apraxia), recognition of

Cognitive-related *impairment of all-day activities* affects complex instrumental skills in early stages of dementia, e.g. using new instruments, filling in written documents, later on using

*Psychiatric side symptoms* such as anxiety, agitation, excitability, aggressive behaviour or paranoia are not frequently present in early stages, but appear more often in middle and late stages of disease. There is a higher vulnerability for states of disorientation already in the preclinical stage, e.g. after hospital admissions, drug intolerance, malnutrition. Also depres‐ sive mood changes as well as reduction of daily activities are considered early signs [23].

*Depression* is the most frequent psychiatric side symptom and accounts for about 30% of the patients, especially during early disease stage and here from the degree of presentation rather mild. However, depression is considered a main psychiatric disease in the elderly. In general, depressed patients can articulate their symptoms more precisely; they can manage their allday activities in a better way and demonstrate during neuropsychological testing self-doubts and complain about deficits in concentration. The mood is continuously suppressed and a lack

The onset of cognitive deterioration is more distinct in patients with depression, whereas in patients with AD this occurs more gradually. The deficits can affect the whole spectrum of cognition, whereby executive dysfunction (predominantly flexibility) and problems with attention dominate. However, also memory deficits are described [30]. In detailed observation of single tasks aspects, e.g. in recalls of wordlists, primacy more than recency effects are shown,

While demented patients guess more often and describe things, depressed patients react with omissions and hesitant answers. Orientation is widely intact and confabulation, aphasic and

familiar devices and basal all-day abilities deteriorate progressively.

alertness, are affected at early stages [29].

frontal cortex, anterior cingulum).

262 Alzheimer's Disease - Challenges for the Future

line drawing is inhibited.

of motivation is more exhibited.

and recall is generally better.

apractic elements don't occur [22, 31].

exhaustion.

Major tasks and aims of a neuropsychological examination comprise 1) determination and quantification of impaired cognitive function and resources as well as their consequences for maintaining all-day life, 2) assessment on changes of cognitive dysfunctions in progressive or reversible disease conditions, 3) differential diagnosis and securing of diagnosis as well as 4) evaluation of therapeutic benefits.

An important detail of the examination is a thorough interview with exploration of the clinical history, self-observation and observation of others, orientation, current mood situation (psychiatric side symptoms), as well as observation of behaviour during both interview and test situation. A final judgement is built from the test results with reference to emotional and motivational processes, a qualitative mistake analysis, and observation of behaviour during tests and interview, the resulting information derived from the interview and an evaluation of all-day competences during course of disease.

Neuropsychological testing represents an essential diagnostic tool in dementia diagnosis. It should be thoroughly performed and comprise the essential key competences. An "overtest‐ ing" should be avoided. In general, the choice of tests should orientate according to the individual differential diagnosis that is being questioned, the capacity of the individual patient and the time that is available.

Consecutively, a choice of test procedures is presented, that have been established in dementia diagnosis. As some of them cannot be administered solely for securing the diagnosis, a combination of several test procedures should be used.

For assessment of cognitive deficits in AD both screening methods as well as standardized psychometric tests are applied. Presumably, the most practical screening test in the clinical setting is the MMSE (Mini-Mental-State-Examination) according to Folstein et al. [32]. It comprises the examination of orientation in time and space, retentiveness and memory, attention and working memory, language (reading, writing, naming, speech comprehension, reading and meaning comprehension) as well as visual-spatial competences. The test takes usually approximately 10-12 minutes, the analysis results from a simple summation of points. At maximum 30 points can be achieved. The specificity ranges at 87 percent and the sensitivity at 82 percent [33]. However screening tests- as the mentioned MMSE- are only suitable, using cut off levels, for overviewing and determining severity of the dementia and for follow-up during disease course.

The MMSE is not acceptably sensitive in early onset dementia and does not allow, amongst other due to missing age and education correction, a satisfactory differentiation between "healthy" and "ill". For quantification of disease severity standard values of interpretation are provided, that can vary easily. Alternatively also CDR (Clinical Dementia Rating) or GDS (Global Deterioration Scale) can be applied. A general drop in points of around 3 MMSE points per year substantiates the suspected diagnosis of AD [34].

The *DemTect (Dementia Detection Test),* likewise a screening test, focuses more precisely on Alzheimer-specific impairments with its task of word-list learning and delayed recall. Furthermore it comprises more tasks on executive functions (working memory, word fluidity and cognitive flexibility). At maximum 18 points can be obtained. The DemTect is economic in time (8-12 minutes), it encloses a rough age correction (< 60 / ≥ 60 years) and presents with a high sensitivity for early stage AD and MCI [35].

After introduction in 1986 in the USA from the *Consortium to Establish a Registry for AD*, the newly established *CERAD test battery* has received great acceptance also in German-speaking countries. This novel neuropsychiatric testing tool has developed into a standardized dementia test procedure which aims to decipher cognitive dysfunction typical of AD [34, 36]. Analysed skills are: semantic fluidity (naming animals), naming of black and white drawings, verbal compliance and retentiveness (word list), delayed recall and recognition as well as constructive praxis (to copy something) and figural memory. The test battery also includes the MMSE. The results of a huge multicentre-validation study performed in German-speaking countries (n=1100), show that the variables: verbal fluidity, word list, memory, recall of wordlist, discrimination ability and recall of constructive praxis majorly contributed to the discrimina‐ bility from healthy elderly persons to AD patients with a sensitivity of 87 percent and a specificity of 98 percent. Severe differences in profiles of AD patients, patients with vascular dementia and mixed dementia could not be obtained. A better discrimination was attained between AD patients, patients with depression and mild impairments. Both patients with depression and MCI ranged between Healthy and AD [36, 37].

To trace better on subcortical dysfunction, since 2005 additional tasks were included that aim to quantify on cognitive processing speed and flexibility (Trail making test A and B) as well as phonematic word fluidity tasks (words with initial letter "s") (CERAD-Plus). The whole test duration ranges between 30-45 minutes. The raw score are age- and education-matched (school and professional education) and also gender-matched. They are designated as z-levels as a measure of deviation to normal. The CERAD-Plus test battery allows a qualitative assessment on cognitive ability, on evaluation of disease severity and a follow up on repeated testing.

However, at present a parallel test version is not available, thus it is recommended to use an alternative test for memorising word lists when test intervals are on short-term. In suspicion of other underlying dementia causes further psychometric tests can be applied.

As an additional screening instrument for calculation of disease severity and for follow-up, the *clock-drawing test* is often recommended [38]. Next to visual-spatial abilities the test requires abilities in planning and semantic memory. The assessment includes, e.g. the integrity of the clock face, the presence of the clock hands, problems of drawing and conceptual difficulties. The sensitivity accounts for 90 percent, the specificity ranges at 56 percent. A qualitative evaluation is reasonable as well as the observation while drawing the clock face. In a qualitative feature analysis for securing the AD diagnosis in differentiation to patients with depression and healthy subjects (n=205, patients of a memory clinic) only errors occurred solely in patients with AD (with exception of one): in disorganised stereograms, only one clock-hand, mixing of numbers (1-12 with 12-24), mixing of minutes- and clock-hands, false or altered order of numbers and inability to write numbers [39].

In mind of the low specificity of the clock drawing test, Schmidtke et al. suggest an additional *clock reading test* with respect that it doesn't require higher executive function. The clock reading test is culture-, language-, education- and gender-independent, however shows a slight age-effect. It is easy to use and quickly analysable by a simple point system. Both in AD and LBD abnormalities are detected early and in comparison to healthy persons the sensitivity ranges at 82 percent, the specificity at 70 percent [24, 25].

In suspicion of an *apractic dysfunction*, a corresponding examination is informally possible, while allowing the patient to mimic easy gestures or mimic using distinct utensils (e.g. hammer, saw and scissors). As long as the patient is unable to perform the movements according to verbal request, one should allow him (to exclude problems with language comprehension) to imitate the demanded movements. For assessment of an ideatoric apraxia the patient is asked, e.g. to prepare a letter for shipment.

In order to examine *all-day competences* there are different tests available, e.g. the ADL-/ IADLscale (Activities of Daily Living /Instrumental Activities of Daily Living), the Bayer-ADL-scale (Bayer Activities of Daily Living) or the FAQ (Functional Activities Questionnaire) which evaluate distinct functions partially very detailed. These tests are completed in general by relatives or by the interviewer [40-42]. Hereby, the FAQ has proven more sensitive compared to the IADL (85% to 57%) in the differentiation of "demented" and "normal". The specificity ranged at 81 percent [42].

Psychiatric side symptoms, e.g*. depression*, are assessed early during the neuropsychiatric interview. As needed additional depression scales can be used, e.g. the Geriatric Depression scale (GDS) or the Beck Depression Inventar (BDI), that are available also in short profile [43]. The input of depression scales depends on each situation and on the cognitive capacity of the patient. It should not lead to extend the usual time of the whole neuropsychiatric test situation.

## **4. Diagnostic imaging methods in AD**

### **4.1. Computerized Tomography (CT)**

Furthermore it comprises more tasks on executive functions (working memory, word fluidity and cognitive flexibility). At maximum 18 points can be obtained. The DemTect is economic in time (8-12 minutes), it encloses a rough age correction (< 60 / ≥ 60 years) and presents with

After introduction in 1986 in the USA from the *Consortium to Establish a Registry for AD*, the newly established *CERAD test battery* has received great acceptance also in German-speaking countries. This novel neuropsychiatric testing tool has developed into a standardized dementia test procedure which aims to decipher cognitive dysfunction typical of AD [34, 36]. Analysed skills are: semantic fluidity (naming animals), naming of black and white drawings, verbal compliance and retentiveness (word list), delayed recall and recognition as well as constructive praxis (to copy something) and figural memory. The test battery also includes the MMSE. The results of a huge multicentre-validation study performed in German-speaking countries (n=1100), show that the variables: verbal fluidity, word list, memory, recall of wordlist, discrimination ability and recall of constructive praxis majorly contributed to the discrimina‐ bility from healthy elderly persons to AD patients with a sensitivity of 87 percent and a specificity of 98 percent. Severe differences in profiles of AD patients, patients with vascular dementia and mixed dementia could not be obtained. A better discrimination was attained between AD patients, patients with depression and mild impairments. Both patients with

To trace better on subcortical dysfunction, since 2005 additional tasks were included that aim to quantify on cognitive processing speed and flexibility (Trail making test A and B) as well as phonematic word fluidity tasks (words with initial letter "s") (CERAD-Plus). The whole test duration ranges between 30-45 minutes. The raw score are age- and education-matched (school and professional education) and also gender-matched. They are designated as z-levels as a measure of deviation to normal. The CERAD-Plus test battery allows a qualitative assessment on cognitive ability, on evaluation of disease severity and a follow up on repeated testing.

However, at present a parallel test version is not available, thus it is recommended to use an alternative test for memorising word lists when test intervals are on short-term. In suspicion

As an additional screening instrument for calculation of disease severity and for follow-up, the *clock-drawing test* is often recommended [38]. Next to visual-spatial abilities the test requires abilities in planning and semantic memory. The assessment includes, e.g. the integrity of the clock face, the presence of the clock hands, problems of drawing and conceptual difficulties. The sensitivity accounts for 90 percent, the specificity ranges at 56 percent. A qualitative evaluation is reasonable as well as the observation while drawing the clock face. In a qualitative feature analysis for securing the AD diagnosis in differentiation to patients with depression and healthy subjects (n=205, patients of a memory clinic) only errors occurred solely in patients with AD (with exception of one): in disorganised stereograms, only one clock-hand, mixing of numbers (1-12 with 12-24), mixing of minutes- and clock-hands, false or altered order of

of other underlying dementia causes further psychometric tests can be applied.

a high sensitivity for early stage AD and MCI [35].

264 Alzheimer's Disease - Challenges for the Future

depression and MCI ranged between Healthy and AD [36, 37].

numbers and inability to write numbers [39].

Computerized Tomography (CT) is helpful in the detection of atrophy as well as other focal processes in brain and spinal cord, however it is not sufficient to substantiate AD diagnosis. Based on the low tissue contrast in comparison to magnetic resonance imgaging (MRI), CT serves well in the diagnostic classification of dementia syndromes. Advantages compared to MRI include a shorter time of investigation, low costs and a broad distribution [44]. In addition, CT allows an uncomplicated monitoring of critically ill patients.

With progressing age, brain volume decreases due to dying neurons and decline in water content. The annual atrophy rate ranges at around 0.24 % of total brain volume and is visible by the expansion of the ventricular system [45].

In AD, patients show a progressive brain atrophy in advancing disease which lies above the age matched population. This is demonstrated by enlargement of sulci and a dilatation of the ventricular system. Hereby, the dilatation of the ventricular system points to a subcortical tissue loss whereas the enlargement of the outer CSF interspaces points to cortical tissue loss [46]. The senso-motoric and the primary-visual cortex stay unaffected.

#### **4.2. Magnetic Resonance Imaging (MRI)**

MRI allows a high-contrast presentation of neuro-anatomical structures, pathological proc‐ esses as well as of functional changes in brain activity. With progressive age a higher exchange rate of fluids exists between the ventricular system and the brain parenchyma. This is visible in T2- and Fluid-attenuated inversion recovery (FLAIR)-sequences by signal alterations in the ependyma of the anterior horns [47]. Intermittent, subcortical and central signal increases in the white matter (white-matter-lesions) increase with progressive age. Additionally brain iron accumulation can be detected in basal ganglia by increasing signal changes in T2-sequences.

Already in early AD stages MRI can display brain atrophy patterns. These can predominamtly be located in the medial temporal lobe, in the hippocampus and the gyrus parahippocampalis. Also, the entorhinal cortex, the amygdala, basal ganglia as well as thalamus and the parietal cortex can be involved [44]. An important role in the early detection of AD plays the Nucleus basalis Meynert. The voxel-based morphometry (VBM) reduces the weaknesses of predomi‐ nantly investigator-dependent manual volumetry [48]. Modern computer techniques allow the spatial recognition of specific brain regions or the whole brain [49]. Hereby the volume of the typically affected brain region is exactly displayed and is comparable to that of other control groups. The majority of published studies show that patients with a MCI present with a smaller hippocampal volume than healthy controls and patients with AD have a smaller hippocampal volume in comparison to patients with MCI [50]. Patients with MCI hold an elevated risk for the development of AD [51]. Typical AD changes can also occur after brain trauma and longlasting epilepsy.

Functional MRI (fMRI) has the potential to demonstrate cerebral blood flow as well as oxygen use of certain brain areas in response to specific stimuli or while processing certain cognitive tasks.

Due to the inherent magnetic properties of blood, represented by hemoglobin and deoxyhe‐ moglobin, different patterns of activiation are visible [44].

Despite of the high spatial resolution, this method presents with a high sensitivity for minor head movements. Studies of AD patients show a decrease of activitiy in the hippocampus, the parahippocampal areas as well as in the parietal and pre-frontal cortex in comparison to healthy control groups. Furthermore, fMRI is useful in monitoring of medical treatment in AD patients.

#### **4.3. Emission computed tomography (SPECT and PET)**

Imaging via single photon emission computed tomography (SPECT) and positron emission computed tomography (PET) allows the detection of local hemodynamic and metabolic dysfunction. After intravenous injection of a radioactive tracer and uptake in brain, the tracer localizes at the region of regional acitivity and images are taken. As the tracers often have short radioactive half life, the radioactive decay (emission of positrons) can be measured.

SPECT imaging shows the regional cerebral blood flow (rCBF) at rest by the regional uptake of glucose as an expression of neuronal activity. Hereby functional abnormalities can already be detected before symptom onset. The tracers 99mTc-HMPAO and 99mTc-ECD are mostly used in clinical practise. Due to their lipophilic character the tracers reach the cells in the first minutes after injection proportionately to rCBF [52]. The typical SPECT image in AD is characterized by a reduced rCBF in the medial and superior temporal lobes as well as in the posterior cingulum and precuneus without a reduced striatal DAT-binding [53]. Due to a very low spatial resolution of SPECT the diagnostic accuracy is lower than PET [54]. However applica‐ tion can be meaningful in clinical practise in order to differentiate other dementia causes.

PET imaging illustatrates a regional dysfunction of glucose metabolism via application of 18F-FDG. Patients with AD demonstrate here, according to SPECT, a typical nuclide-distribution pattern of neuronal loss. Over 85 % of PET diagnosed AD patients could be neuropathologi‐ cally verified [53]. At early AD disease stage and before symptom onset, a temporoparietal metabolic dysfunction is visible by voxel-based (volumetric pixel) analysis. Also patients with a genetic risk for development of AD show early decreases in signal activity [55]. As PET is the most efficient method for diagnostic verification of an AD, it has meanwhile established to a standard tool in dementia research [56].

For further diagnostic approaches the tracer 11C-PIB was developed, which allows detection and distribution of Aß-plaques *in vivo* [57]. Next to an efficient diagnostic procedure and early disease recognition the dimension of AD dementia can be illustrated.

## **5. Biomarkers in peripheral tissues**

ventricular system. Hereby, the dilatation of the ventricular system points to a subcortical tissue loss whereas the enlargement of the outer CSF interspaces points to cortical tissue loss

MRI allows a high-contrast presentation of neuro-anatomical structures, pathological proc‐ esses as well as of functional changes in brain activity. With progressive age a higher exchange rate of fluids exists between the ventricular system and the brain parenchyma. This is visible in T2- and Fluid-attenuated inversion recovery (FLAIR)-sequences by signal alterations in the ependyma of the anterior horns [47]. Intermittent, subcortical and central signal increases in the white matter (white-matter-lesions) increase with progressive age. Additionally brain iron accumulation can be detected in basal ganglia by increasing signal changes in T2-sequences.

Already in early AD stages MRI can display brain atrophy patterns. These can predominamtly be located in the medial temporal lobe, in the hippocampus and the gyrus parahippocampalis. Also, the entorhinal cortex, the amygdala, basal ganglia as well as thalamus and the parietal cortex can be involved [44]. An important role in the early detection of AD plays the Nucleus basalis Meynert. The voxel-based morphometry (VBM) reduces the weaknesses of predomi‐ nantly investigator-dependent manual volumetry [48]. Modern computer techniques allow the spatial recognition of specific brain regions or the whole brain [49]. Hereby the volume of the typically affected brain region is exactly displayed and is comparable to that of other control groups. The majority of published studies show that patients with a MCI present with a smaller hippocampal volume than healthy controls and patients with AD have a smaller hippocampal volume in comparison to patients with MCI [50]. Patients with MCI hold an elevated risk for the development of AD [51]. Typical AD changes can also occur after brain trauma and long-

Functional MRI (fMRI) has the potential to demonstrate cerebral blood flow as well as oxygen use of certain brain areas in response to specific stimuli or while processing certain cognitive

Due to the inherent magnetic properties of blood, represented by hemoglobin and deoxyhe‐

Despite of the high spatial resolution, this method presents with a high sensitivity for minor head movements. Studies of AD patients show a decrease of activitiy in the hippocampus, the parahippocampal areas as well as in the parietal and pre-frontal cortex in comparison to healthy control groups. Furthermore, fMRI is useful in monitoring of medical treatment in AD

Imaging via single photon emission computed tomography (SPECT) and positron emission computed tomography (PET) allows the detection of local hemodynamic and metabolic dysfunction. After intravenous injection of a radioactive tracer and uptake in brain, the tracer

moglobin, different patterns of activiation are visible [44].

**4.3. Emission computed tomography (SPECT and PET)**

[46]. The senso-motoric and the primary-visual cortex stay unaffected.

**4.2. Magnetic Resonance Imaging (MRI)**

266 Alzheimer's Disease - Challenges for the Future

lasting epilepsy.

tasks.

patients.

Biomarkers are used as indicators of normal and pathogenic processes in a broad range of tissues, especially in peripheral tissues, which facilitates the accessibility of testing samples with minimal invasive methods. Despite substantial progress has been made in the area of biomarker development to confirm the diagnosis at early-clinical AD stages, less is known about the potential role of biomarkers in peripheral tissues in the prediction of AD [58]. Since it has been demonstrated for decades the existence of biochemical changes in the brain preceding the clinical AD onset (up to 20 years in advance) [59, 60] it is suggested that these changes may be also indirectly reflected in biological fluids. However, no tests are currently available to confirm an early AD diagnosis prior to clinical or symptomatic manifestations. The ongoing standardization efforts and quality control programs in biomarkers analysis, the development of tests in fully automated instruments, the combined detection of the wellestablished core biomarkers, the discovery of new regulated molecules improving current sensibility and sensitivity and the analysis of novel promising biomarkers in large independent cohorts will boost biomarker´s performance and facilitate the introduction of new AD diagnosis and prognosis tests in biological fluids in clinical routine.

#### **5.1. CSF**

CSF is the prime target among biological fluids in the search of specific biomarkers related to neurological disorders. The easy accessibility to this biofluid and its singular biophysicchemical characteristics make CSF ideal for biomarkers investigation. On one hand, CSF is not a very complex fluid, being composed of a restricted amount of metabolites [61], which facilitates technical screening for regulated molecules. On the other hand, the direct contact between CSF and the extracellular space of the brain puts CSF in a valuable position to be considered as a potential indicator of the pathological processes occurring in the brain during different disease stages. This last aspect has not been analysed in depth since real comparisons and correlations are cumbersome and can only be formally made when using CSF and brain tissues from the same patients and the same disease stages.

The performance of CSF biomarkers as a diagnostic tool has greatly improved in parallel with the improvement of detection methodologies such as new generation proteomic technologies and high-throughput transcriptomic methodologies (deep-sequencing, microarrays and quantitative PCR panels), which eased and expanded the possibilities to measure full expres‐ sion signature in a single assay enabling the inference of networks and biological functions associated to deregulated datasets. Indeed, current data indicate the existence of deregulated levels of proteins, peptides, small RNAs, mitochondrial DNA and a broad range of metabolites in the CSF of AD samples. In addition new outcomes are expected from worldwide undergoing large longitudinal studies in very-well defined cohorts [62].

#### *5.1.1. Protein biomarkers*

In recent years, a number of reports have exploited proteomic techniques to study the levels of selected proteins and peptides in the CSF of healthy and diseased individuals. Current data indicate that proteins and peptides such as β-amyloid (Aβ1-42/Aβ42 and Aβ1-40/Aβ40), total tau and phosphorylated tau (p-tau) meet the criteria to discriminate AD from individuals suffering from other types of dementias, as well as from healthy individuals and are considered as the core AD biomarkers [63]. According to different studies these biomarkers meet the consensus recommendations on AD biomarkers that should have >80% sensitivity and >80% specificity [64]. Importantly, core AD biomarkers molecules correlate with neuropathological hallmarks of AD, such as the presence of extracellular amyloid plaques (Aβ peptides), axonal degeneration (tau protein) and neuronal tangles (p-tau).

Three main observations unveil the clinical relevance of these molecules. Firstly, their appro‐ priate sensibility and sensitivity have been successfully validated by independent large-scale multicentre studies [65-69], although these studies also point out that biomarkers measure‐ ments present significant inter-laboratory variations [70]. Secondly, Aβ42, tau and p-tau have been validated as predictors of AD in patients with MCI [71-74]. Lastly, longitudinal studies indicate that, at least, Tau and Aβ42 in CSF reflect the underlying disease state in early clinical and late stages of AD.

### *5.1.1.1. Aβ peptides*

**5.1. CSF**

268 Alzheimer's Disease - Challenges for the Future

CSF is the prime target among biological fluids in the search of specific biomarkers related to neurological disorders. The easy accessibility to this biofluid and its singular biophysicchemical characteristics make CSF ideal for biomarkers investigation. On one hand, CSF is not a very complex fluid, being composed of a restricted amount of metabolites [61], which facilitates technical screening for regulated molecules. On the other hand, the direct contact between CSF and the extracellular space of the brain puts CSF in a valuable position to be considered as a potential indicator of the pathological processes occurring in the brain during different disease stages. This last aspect has not been analysed in depth since real comparisons and correlations are cumbersome and can only be formally made when using CSF and brain

The performance of CSF biomarkers as a diagnostic tool has greatly improved in parallel with the improvement of detection methodologies such as new generation proteomic technologies and high-throughput transcriptomic methodologies (deep-sequencing, microarrays and quantitative PCR panels), which eased and expanded the possibilities to measure full expres‐ sion signature in a single assay enabling the inference of networks and biological functions associated to deregulated datasets. Indeed, current data indicate the existence of deregulated levels of proteins, peptides, small RNAs, mitochondrial DNA and a broad range of metabolites in the CSF of AD samples. In addition new outcomes are expected from worldwide undergoing

In recent years, a number of reports have exploited proteomic techniques to study the levels of selected proteins and peptides in the CSF of healthy and diseased individuals. Current data indicate that proteins and peptides such as β-amyloid (Aβ1-42/Aβ42 and Aβ1-40/Aβ40), total tau and phosphorylated tau (p-tau) meet the criteria to discriminate AD from individuals suffering from other types of dementias, as well as from healthy individuals and are considered as the core AD biomarkers [63]. According to different studies these biomarkers meet the consensus recommendations on AD biomarkers that should have >80% sensitivity and >80% specificity [64]. Importantly, core AD biomarkers molecules correlate with neuropathological hallmarks of AD, such as the presence of extracellular amyloid plaques (Aβ peptides), axonal

Three main observations unveil the clinical relevance of these molecules. Firstly, their appro‐ priate sensibility and sensitivity have been successfully validated by independent large-scale multicentre studies [65-69], although these studies also point out that biomarkers measure‐ ments present significant inter-laboratory variations [70]. Secondly, Aβ42, tau and p-tau have been validated as predictors of AD in patients with MCI [71-74]. Lastly, longitudinal studies indicate that, at least, Tau and Aβ42 in CSF reflect the underlying disease state in early clinical

tissues from the same patients and the same disease stages.

large longitudinal studies in very-well defined cohorts [62].

degeneration (tau protein) and neuronal tangles (p-tau).

*5.1.1. Protein biomarkers*

and late stages of AD.

Aβ42 along with Aβ40 is secreted into the extracellular space and biological fluids, including CSF, as consequence of the proteolytic activity of proteinases on the Amyloid precursor protein (APP). Both peptides are found in senile plaques but their intracellular production, aggregation rates and proposed pathogenic functions are significantly distinct [75-77].

A consistent decrease in Aβ42 levels has been observed in the CSF of patients suffering from AD in several studies [78-80] but also in Subcortical White-matter Dementia (SWD) [81] and in Down Syndrome (DS) [82]. Reduced Aβ42 levels in AD are suggested to reflect either sequestration of Aβ42 in senile plaques, since Aβ42 CSF levels inversely correlate with the presence of senile plaques [83], or due to non-detectable Aβ42 oligomers in the assay, although alternative explanations may be plausible. In FTD, Aβ42 levels are significantly lower than in control samples, but higher than in AD cases [81, 84]. Aβ42 sensitivity and specificity in AD samples ranges from 78 to 100% (mean 85,6%) and from 67 to 100% (mean 88,5%), respectively [78]. A recent meta-analysis of 50 analytical studies indicates that CSF Aβ42 concentrations are significantly lower in AD when compared to MCI, FTD, PD and VaD but only moderately lower when compared to LBD [85].

Contrary to what is observed with Aβ42, Aβ40 and Aβ38 levels are not altered in the CSF of AD patients [79, 86, 87], but a significant decrease in Aβ40 levels is observed in FTLD when compared to AD and control cases [88]. In addition, Aβ40 levels, and more markedly Aβ38 levels, are decreased in FTD when compared to control samples [89].

A growing body of evidence suggests the superior performance of Aβ42/Aβ40 ratio when compared to Aβ42 alone using different analytic assays [79, 90, 91]. Importantly Aβ42/Aβ40 ratio is able to predict the conversion from MCI patients to AD when compared to cognitively stable MCI patients and MCI patients who developed other forms of dementia [79]. Aβ42/Aβ40 ratio is also able to discriminate better AD from VaD, LBD and non-AD dementia than Aβ42 alone and equally AD from FTD and non-AD dementia than the combination of Aβ42, p-tau and total tau [92]. Multiple studies also show an increased sensitivity and specificity in the use of Aβ ratio when compared to Aβ42/tau ratio, although the performance of combined biomarker analysis in AD diagnosis and prognosis is still a matter under discussion [93-96].

In addition to the regulated levels of monomeric Aβ species in the CSF of AD patients, encouraging observations have been reported in the potential diagnostic and prognostic role of BACE1, one of the main enzymes involved in the pathological cleave of the APP. Several independent observations indicate the presence of higher BACE1 levels and activity in the CSF of MCI and AD samples when compared to controls [97-100]. BACE1 activity is also increased in CJD samples [101] suggesting common pathological mechanisms among both diseases. Importantly, BACE1 correlate with classical AD biomarker's profile, brain atrophy in AD cases [102] and ApoE4 genotype [99], the latter being associated with an increased Aβ peptide *ex vivo* production [103]. In addition, specific BACE1 inhibitors dramatically reduce the presence of Aβ peptides in the CSF of AD patients [104] pointing out for a direct correlation between brain Aβ peptide processing and Aβ CSF levels.

#### *5.1.1.2. Aβ oligomers*

Recent studies demonstrated the presence of increased levels of Aβ oligomeric species in the CSF of AD patients when compared to controls using a broad range of methodological approaches [105-110]. Indeed, the analysis of individual Aβ oligomeric species is gaining experimental momentum due to their potential specific role in AD pathogenesis. Aβ40 oligomers levels are found to be increased in the CSF of AD patients at different disease severity stages, and a combined analysis of Aβ40 oligomers and monomeric Aβ42 greatly improved sensitivity and specificity to 95% and 90%, respectively [108]. Although the pathogenic role of Aβ40 in AD is still under discussion Aβ40 deposits have been reported both in control and AD brains [111, 112]. Aβ40-positive senile plaques with amyloid core are frequently associated with microglia in contrast to Aβ42-positive plaques [111], suggesting a role of microglia in the generation and aggregation of Aβ40 species in diseased brain. However, the different ability of Aβ fibrils and oligomers to react with microglia suggests a more complex scenario [113].

Aβ42 oligomers are increased in the CSF of AD patients [114] and the ratio of Aβ oligomers to Aβ42 is significantly elevated in AD patients [115]. Interestingly, the increased levels of Aβ42 oligomers in the CSF of MCI and AD samples may explain decreased levels of monomeric Aβ42. The recent development of the protein misfolding cyclic amplification assay (PMCA), based on the seeding activity of Aβ oligomers catalysing the polymerization of the monomeric Aβ, permits the discrimination of AD samples from other neurodegenerative non-degenera‐ tive neurological diseases with a sensitivity of 90% and specificity of 92% [109]. The use of Aβ-PMCA as a prognostic tool for detection of MCI still needs to be established. Importantly, detection of Aβ oligomers in the CSF is highly dependent on the native or disaggregated state of these oligomers [114, 116].

The finding that regulated levels of Aβ oligomer species are present in the CSF of AD patients' biofluids has a tremendous translational interest, since growing evidences indicate that soluble Aβ oligomers rather than aggregated Aβ plaques are more likely to be the main pathogenic agents of disease [117-119]. Consequently, preliminary data indicate that the analysis of Aβ oligomers, combined with levels of soluble Aβ peptides, may be relevant disease predictors and valuable tools for the analysis of AD progression.

#### *5.1.1.3. Tau*

The levels of total tau in the CSF, contrary to Aβ42 levels, increase with age [120]. Increments in tau levels have also been described in the CSF of AD and MCI patients in a broad range of several studies [121, 122] ranging from moderate to severe depending on the methodology and cohort used [78]. It is believed that deregulated tau may be reflecting the neuronal and axonal damage present in brain tissue and, as a consequence, the presence of increased tau levels is not a specific event for AD. Accordingly, transient tau increments have been also reported in acute stroke [123], and the most increased tau levels are observed in prion diseases such as in CJD, where massive neuronal cell death is present [124, 125]. Higher CSF tau is also associated with smaller brain volume in individuals with AD [126]. On the other hand, neurological diseases with minor neuronal loss and other dementias such as VaD, LBD and alcoholic dementia reflect minor or no significant changes in the levels of tau protein in the CSF, and tauopathies such as FTD also present inconsistent data [121, 127, 128].

A meta-analysis from different studies comparing tau levels in different dementia samples found that, although tau levels in AD are significantly increased when compared to controls, tau concentrations are moderately elevated in LBD, FTLD and VaD impeding a clear stratifi‐ cation between disease groups. Nevertheless, tau levels are useful to differentiate VaD from stroke [129] and, as expected, only CJD is characterized by extremely increased tau values, resulting in a sensitivity and specificity over 90% [130].

The improved performance of tau when analysed together with other AD biomarkers has been widely demonstrated [131, 132]. The combined use of Aβ42 and tau discriminates better between controls and AD and is very useful to predict MCI progression [69, 133]. A recent study also showed that decreased Aβ42 and increased tau levels are able to discriminate LBD from PD patients in spite of both being synucleopathies [134]. In the same line of evidences, combination of α-synuclein levels and Aβ42/tau ratios improves the diagnostic accuracy of PD [135].

A broad range of studies also demonstrated the helpfulness of the combined analysis of tau with non-AD core biomarkers. Assessment of tau and neuronal thread protein raises specificity and sensitivity for AD when compared to the individual analysis of both proteins [136]. Similarly, integrated analysis of tau and the regional cerebral blood flow in the posterior cingulate cortex discriminates MCI progressing to AD from non-progressive MCI [137]. The combined analysis of tau is also valuable for discriminating other diseases besides AD. As an example, the merged analysis of tau and midbrain-to-pons atrophy is reported to be useful for early identification of progressive supranuclear palsy (PSP), discriminating PSP cases from controls and patients suffering from corticobasal syndrome (CBS) and FTD [138].

#### *5.1.1.4. Phospho-tau*

*5.1.1.2. Aβ oligomers*

270 Alzheimer's Disease - Challenges for the Future

of these oligomers [114, 116].

*5.1.1.3. Tau*

and valuable tools for the analysis of AD progression.

Recent studies demonstrated the presence of increased levels of Aβ oligomeric species in the CSF of AD patients when compared to controls using a broad range of methodological approaches [105-110]. Indeed, the analysis of individual Aβ oligomeric species is gaining experimental momentum due to their potential specific role in AD pathogenesis. Aβ40 oligomers levels are found to be increased in the CSF of AD patients at different disease severity stages, and a combined analysis of Aβ40 oligomers and monomeric Aβ42 greatly improved sensitivity and specificity to 95% and 90%, respectively [108]. Although the pathogenic role of Aβ40 in AD is still under discussion Aβ40 deposits have been reported both in control and AD brains [111, 112]. Aβ40-positive senile plaques with amyloid core are frequently associated with microglia in contrast to Aβ42-positive plaques [111], suggesting a role of microglia in the generation and aggregation of Aβ40 species in diseased brain. However, the different ability of Aβ fibrils and oligomers to react with microglia suggests a more complex scenario [113].

Aβ42 oligomers are increased in the CSF of AD patients [114] and the ratio of Aβ oligomers to Aβ42 is significantly elevated in AD patients [115]. Interestingly, the increased levels of Aβ42 oligomers in the CSF of MCI and AD samples may explain decreased levels of monomeric Aβ42. The recent development of the protein misfolding cyclic amplification assay (PMCA), based on the seeding activity of Aβ oligomers catalysing the polymerization of the monomeric Aβ, permits the discrimination of AD samples from other neurodegenerative non-degenera‐ tive neurological diseases with a sensitivity of 90% and specificity of 92% [109]. The use of Aβ-PMCA as a prognostic tool for detection of MCI still needs to be established. Importantly, detection of Aβ oligomers in the CSF is highly dependent on the native or disaggregated state

The finding that regulated levels of Aβ oligomer species are present in the CSF of AD patients' biofluids has a tremendous translational interest, since growing evidences indicate that soluble Aβ oligomers rather than aggregated Aβ plaques are more likely to be the main pathogenic agents of disease [117-119]. Consequently, preliminary data indicate that the analysis of Aβ oligomers, combined with levels of soluble Aβ peptides, may be relevant disease predictors

The levels of total tau in the CSF, contrary to Aβ42 levels, increase with age [120]. Increments in tau levels have also been described in the CSF of AD and MCI patients in a broad range of several studies [121, 122] ranging from moderate to severe depending on the methodology and cohort used [78]. It is believed that deregulated tau may be reflecting the neuronal and axonal damage present in brain tissue and, as a consequence, the presence of increased tau levels is not a specific event for AD. Accordingly, transient tau increments have been also reported in acute stroke [123], and the most increased tau levels are observed in prion diseases such as in CJD, where massive neuronal cell death is present [124, 125]. Higher CSF tau is also associated with smaller brain volume in individuals with AD [126]. On the other hand, neurological diseases with minor neuronal loss and other dementias such as VaD, LBD and alcoholic Similarly to total tau, p-tau levels are increased in AD samples, although higher variability on its specificity and sensibility is reported when compared to the non-phosphorylated tau form [78, 127]. Several considerations should be done in this regard.

On one hand, the number of studies analysing p-tau levels is not as large as those performed for its non-phosphorylated form. In addition, sensitivity and sensibility may depend on the analysed phosphorylation site, although sensitivity for AD seems equal for at least the three main epitopes used in clinical diagnosis [139]. Importantly, results from a meta-analysis study indicate that tau phosphorylated at the Threonine 181 levels are able to discriminate AD from other dementias and MCI [140].

On the other hand, the utility of p-tau in the differential AD diagnosis against other neurode‐ generative diseases is advantageous over total tau since p-tau levels reflect AD pathogenesis [141]. Indeed, p-tau levels in the CSF may reflect the levels of tau phosphorylation in AD brains. Tau is more increased in the CSF of sCJD patients than in AD, while p-tau is only modestly increased in sCJD [142]. In addition, tau levels are increased in neurological diseases such as in acute ischemic stroke, while p-tau levels remains unaltered [123]. Indeed, tau phosphory‐ lation is physiologically regulated during several biological processes such as neuronal development, while tau levels usually remain more stable. Therefore, a direct correlation between total tau and p-tau levels cannot be established, and several lines of evidence indicate that p-tau levels are differently regulated, not only in AD, but also in other neurodegenerative diseases. In this regard, the main tau kinase, Glycogen synthase kinase 3 (GSK3) is assumed to be hyperactivated in AD brain, inducing pathogenic tau hyperphosphorylation, aggregation and formation of the intracellular NFTs. Although a direct correlation between GSK3 activity and tangle formation in AD is still under discussion [143], GSK3 levels and activity are markedly reduced in sCJD brain [144]. Thus, the distinct regulation of tau phosphorylation in the brain of AD and CJD, may explain the different p-tau/tau ratios observed in both diseases, which permits a differential diagnosis [145].

Recently it has been observed that patients suffering from rpAD present highly increased ptau levels in the CSF [146] when compared to controls and classical AD patients. Since it is estimated that rpAD may be accounting for 10-30% of all AD cases, it is urgently needed to establish if lack of disease stratification may lead to misinterpretation of p-tau analysis between rapidly progressive and classical AD forms. In this regard, a combination of high CSF tau without proportionally elevated p-tau-181 is associated with a faster rate of cognitive decline [147]. In this regard, longitudinal studies indicates that a combination of low Aβ42 and high tau and p-tau levels is highly predictive of MCI progression and cognitive decline rate [74, 148].

#### *5.1.1.5. Inflammatory cytokines*

A common feature in the Central Nervous System of neurodegenerative diseases is the presence of chronic neuroinflammation associated with an exacerbated gliosis [149]. The role of a chronic and sustained inflammation in neurodegeneration is still a matter of debate as neuroinflammation has been suggested to play both detrimental and protective functions depending on disease stage, brain region, activation of anti-inflammatory mechanisms and cellular milieu among others [150]. Besides these considerations point out a critical role of neuroinflammation in the molecular mechanisms linked to AD pathology [151] and a broad range of inflammatory cytokines and immune response mediators are increased in the CSF of AD patients. A correlation between inflammatory markers and biomarkers of neurodegener‐ ation has been described [152], and consequently, neurodegenerative disorders with high inflammatory chronic profiles such as prion diseases [153] present higher inflammatoryrelated deregulations in the CSF [154, 155]. However, the specific inflammatory profile observed in different types of dementia and at different disease stages indicates that inflam‐ matory biomarkers could be used as surrogate markers for AD diagnosis and prognosis.

The anti-inflammatory cytokine TGFβ–1 is consistently upregulated in AD cases [156, 157]. Interestingly, during the progression from MCI to AD, a pro-inflammatory state is proposed since MCI patients who progressed to AD showed higher TNFα and lower TGFβ–1 and Aβ42 levels than control individuals or those non progressing to AD [158]. These data are in agreement with increased levels of the acute-phase C-reactive protein (CRP) and IL-6 in the CSF of MCI patients when compared to AD patients, indicating that inflammatory mechanisms are already progressing even before changes in core AD biomarkers such as Aβ42 and tau can be detected in the CSF [159].

In relation to this, a comparative analysis between Amnestic Mild Cognitive Impairment (aMCI) and MS patients indicated that pro-inflammatory cytokines and CD45+ lymphocytes are present in the same levels in both diseases. Taking into account that MS can be considered the most representative neuroinflammatory disease, these observations indicate that inflam‐ matory mechanisms may be crucial for AD etiopathology.

In this regard, the pro-inflammatory cytokine osteopontin (OPN), also known as the secreted phosphoprotein 1 (SPP1) and involved in macrophage recruitment to inflam‐ matory sites and cytokine production [160], is also elevated in the CSF of AD pa‐ tients and in MCI patients developing AD. OPN levels correlate with cognitive decline and with increased levels in early disease phases [161, 162]. OPN has also been found elevated in the CSF during attacks of MS [163].

In addition, the major acute-phase protein SAP (Serum amyloid P component) has lower levels in MCI patients who progressed to AD than in those who did not progress to AD [164], suggesting that low SAP levels are linked to an increased risk of progression to AD.

Alternative promising inflammatory-biomarkers have been proposed. On one hand, lipocalin 2, whose levels are decreased in the CSF of MCI and AD patients and increased in brain regions with associated AD pathology [165]. On the other hand, the astrocytic marker YKL-40, has been reported to be increased in AD at early stages of the disease [166-169] and in FTD and aMCI patients [166]. In addition YKL-40 levels correlate positively with the classical core biomarkers tau and p-tau [166].

#### *5.1.1.6. MicroRNAs*

lation is physiologically regulated during several biological processes such as neuronal development, while tau levels usually remain more stable. Therefore, a direct correlation between total tau and p-tau levels cannot be established, and several lines of evidence indicate that p-tau levels are differently regulated, not only in AD, but also in other neurodegenerative diseases. In this regard, the main tau kinase, Glycogen synthase kinase 3 (GSK3) is assumed to be hyperactivated in AD brain, inducing pathogenic tau hyperphosphorylation, aggregation and formation of the intracellular NFTs. Although a direct correlation between GSK3 activity and tangle formation in AD is still under discussion [143], GSK3 levels and activity are markedly reduced in sCJD brain [144]. Thus, the distinct regulation of tau phosphorylation in the brain of AD and CJD, may explain the different p-tau/tau ratios observed in both diseases,

Recently it has been observed that patients suffering from rpAD present highly increased ptau levels in the CSF [146] when compared to controls and classical AD patients. Since it is estimated that rpAD may be accounting for 10-30% of all AD cases, it is urgently needed to establish if lack of disease stratification may lead to misinterpretation of p-tau analysis between rapidly progressive and classical AD forms. In this regard, a combination of high CSF tau without proportionally elevated p-tau-181 is associated with a faster rate of cognitive decline [147]. In this regard, longitudinal studies indicates that a combination of low Aβ42 and high tau and p-tau levels is highly predictive of MCI progression and cognitive decline rate [74, 148].

A common feature in the Central Nervous System of neurodegenerative diseases is the presence of chronic neuroinflammation associated with an exacerbated gliosis [149]. The role of a chronic and sustained inflammation in neurodegeneration is still a matter of debate as neuroinflammation has been suggested to play both detrimental and protective functions depending on disease stage, brain region, activation of anti-inflammatory mechanisms and cellular milieu among others [150]. Besides these considerations point out a critical role of neuroinflammation in the molecular mechanisms linked to AD pathology [151] and a broad range of inflammatory cytokines and immune response mediators are increased in the CSF of AD patients. A correlation between inflammatory markers and biomarkers of neurodegener‐ ation has been described [152], and consequently, neurodegenerative disorders with high inflammatory chronic profiles such as prion diseases [153] present higher inflammatoryrelated deregulations in the CSF [154, 155]. However, the specific inflammatory profile observed in different types of dementia and at different disease stages indicates that inflam‐ matory biomarkers could be used as surrogate markers for AD diagnosis and prognosis.

The anti-inflammatory cytokine TGFβ–1 is consistently upregulated in AD cases [156, 157]. Interestingly, during the progression from MCI to AD, a pro-inflammatory state is proposed since MCI patients who progressed to AD showed higher TNFα and lower TGFβ–1 and Aβ42 levels than control individuals or those non progressing to AD [158]. These data are in agreement with increased levels of the acute-phase C-reactive protein (CRP) and IL-6 in the CSF of MCI patients when compared to AD patients, indicating that inflammatory mechanisms

which permits a differential diagnosis [145].

272 Alzheimer's Disease - Challenges for the Future

*5.1.1.5. Inflammatory cytokines*

microRNAs (miRNA) are endogenous small non-coding RNAs (20-22 nucleotides) that are involved in post-transcriptional gene regulation by targeting mRNAs for cleavage or transla‐ tional repression [170]. miRNAs have emerged as key regulators of various aspects of neuronal development and dysfunction. Deregulated small RNA signatures, especially miRNAs, have been observed in the brain of a broad range of neurodegenerative diseases such as AD, PD, HD or ALS [171, 172] and experimental evidences ascribe a functional role to miRNAs in the pathogenic molecular mechanisms leading to neurodegeneration [173-175]. With the advent of high-throughput technologies, full transcriptomic signatures can be provided not only from tissues, but also from samples with small amounts of starting material such as biological fluids and associated exosomes [176-178]. In this regard, more than 100 circulating miRNAs are deregulated in pathological conditions [179] and some of them have been proposed as potential biomarkers for disease diagnosis and prognosis, mainly in cancer and neurodegenerative diseases. Regarding the levels of circulating miRNAs in AD, several studies already reported changes when compared to control samples. A recent pilot study in two different cohorts showed that hsa-miR-27a-3p expression is reduced in the CSF of AD patients [180]. Decreased levels of this miRNA correlate with high tau and low Aβ amyloid levels. A second study analysed a selected group of miRNA candidates and observed that miRNAs 34a, 125b and 146a levels were significantly lower in the CSF of AD patients when compared to control cases, while the levels of the miRNAs 29a and 29b were significantly higher [181]. In an independent study low levels of miRNA-146a were also detected in the CSF of AD patients [182]. In this regard the expression of miRNA-146a is increased in AD [183] and CJD brains [184], in AD mice models [185] and in scrapie mice [184]. miRNA-146a expression in AD mice models also correlates with senile plaque density and synaptic pathology [185]. This miRNA is induced by the interleukin IL-1β, modulating the expression of IL-6 and the cyclooxygenase COX-2 and acting as a negative regulator of the astrocyte-mediated inflammatory response [186, 187]. In addition miRNA-146a negatively regulates TLR signalling to prevent exacerbated inflamma‐ tion, thus, it seems to play a key role in the modulation of the neuropathology associated to chronic inflammation in neurodegenerative diseases. Whether the regulation of miRNAs in CSF is a consequence of neuronal cell damage or a modulated pathogenic response is still a matter of discussion.

In summary, all preliminary studies argue for the presence of deregulated levels of miRNAs in the CSF of AD patients with potential translational value. Exclusion of blood contamination effects, standardization of the assays, together with cross-disease and technical validation in larger cohorts need to be carried out to assess the potential role of miRNAs signatures as specific diagnostic and prognosis biomarker tool in AD and to define new diagnostic thera‐ peutic opportunities related to the miRNA field.

#### *5.1.1.7. Mitochondrial DNA*

A pioneering study demonstrated that asymptomatic patients at risk of AD and symptomatic AD patients exhibit a significant decrease in the levels of circulating cell-free mtDNA in the CSF [188]. Data were generated by qPCR and digital droplet PCR and validated in an inde‐ pendent cohort of patients. Interestingly, this decrease is disease-specific, as mtDNA levels in the CSF of FTLD patients remain unchanged. Since decreased levels of mtDNA precede the appearance of the classical AD biomarkers such as Aβ42, mtDNA is an excellent potential preclinical AD biomarker. Further studies in larger cohorts including rpAD and CJD samples will determinate the clinical use of mtDNA analysis as a prognosis AD biomarker.

#### *5.1.1.8. Metabolic profile*

The use of analytic technologies such as Nuclear magnetic resonance and Liquid chromatog‐ raphy–mass spectrometry to analyse the metabolic signatures of biological fluids deserves special attention [189]. The metabolic profile in human CSF samples of AD patients and agematched healthy controls unveils the presence of a significant presence of deregulated metabolites in AD cases [190]. Among them, higher corticols levels are found in AD cases, which correlate with AD progression and severity. In addition, the same study proved that combined analysis of different metabolites may increase sensitivity and specificity above 80%.

A second metabolic profile study identified the deregulated metabolic pathways in the CSF of MCI and AD patients [191]. The number of altered pathways increased with disease severity. Among them, Krebs cycle was significantly affected in MCI and cholesterol and sphingolipids transport was altered in AD. A high percentage of altered pathways in the CSF were also deregulated in plasma from the same individuals (30% in MCI and 60% in AD, respectively). Deregulated pathways performing the best disease discrimination were biosynthesis and metabolism of cortisone and prostaglandin 2.

Finally, a third study using metabolomics in the CSF of MCI and AD patients demonstrated the presence of elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillyl‐ mandelic acid, xanthosine and glutathione levels in AD patients and elevated 5-HIAA, MET, hypoxanthine and other metabolites in MCI patients when compared to healthy controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways [192], showing a partial overlap between MCI and AD.

Metabolomics is a promising tool for AD diagnosis indicating a slightly lower or similar performance when compared to classical AD biomarkers such as tau and Aβ42 depending on the study. Further analysis in large independent cohorts, technical updates as well as a combination of metabolic profiling with classical or alternative biomarkers will define the potential use of high throughput metabolic analysis in the AD diagnostic field. Besides, metabolite signatures may help to unveil the progression mechanisms and pathways leading to different dementia stages.

#### **5.2. Blood**

146a levels were significantly lower in the CSF of AD patients when compared to control cases, while the levels of the miRNAs 29a and 29b were significantly higher [181]. In an independent study low levels of miRNA-146a were also detected in the CSF of AD patients [182]. In this regard the expression of miRNA-146a is increased in AD [183] and CJD brains [184], in AD mice models [185] and in scrapie mice [184]. miRNA-146a expression in AD mice models also correlates with senile plaque density and synaptic pathology [185]. This miRNA is induced by the interleukin IL-1β, modulating the expression of IL-6 and the cyclooxygenase COX-2 and acting as a negative regulator of the astrocyte-mediated inflammatory response [186, 187]. In addition miRNA-146a negatively regulates TLR signalling to prevent exacerbated inflamma‐ tion, thus, it seems to play a key role in the modulation of the neuropathology associated to chronic inflammation in neurodegenerative diseases. Whether the regulation of miRNAs in CSF is a consequence of neuronal cell damage or a modulated pathogenic response is still a

In summary, all preliminary studies argue for the presence of deregulated levels of miRNAs in the CSF of AD patients with potential translational value. Exclusion of blood contamination effects, standardization of the assays, together with cross-disease and technical validation in larger cohorts need to be carried out to assess the potential role of miRNAs signatures as specific diagnostic and prognosis biomarker tool in AD and to define new diagnostic thera‐

A pioneering study demonstrated that asymptomatic patients at risk of AD and symptomatic AD patients exhibit a significant decrease in the levels of circulating cell-free mtDNA in the CSF [188]. Data were generated by qPCR and digital droplet PCR and validated in an inde‐ pendent cohort of patients. Interestingly, this decrease is disease-specific, as mtDNA levels in the CSF of FTLD patients remain unchanged. Since decreased levels of mtDNA precede the appearance of the classical AD biomarkers such as Aβ42, mtDNA is an excellent potential preclinical AD biomarker. Further studies in larger cohorts including rpAD and CJD samples will

The use of analytic technologies such as Nuclear magnetic resonance and Liquid chromatog‐ raphy–mass spectrometry to analyse the metabolic signatures of biological fluids deserves special attention [189]. The metabolic profile in human CSF samples of AD patients and agematched healthy controls unveils the presence of a significant presence of deregulated metabolites in AD cases [190]. Among them, higher corticols levels are found in AD cases, which correlate with AD progression and severity. In addition, the same study proved that combined analysis of different metabolites may increase sensitivity and specificity above 80%.

A second metabolic profile study identified the deregulated metabolic pathways in the CSF of MCI and AD patients [191]. The number of altered pathways increased with disease severity. Among them, Krebs cycle was significantly affected in MCI and cholesterol and sphingolipids

determinate the clinical use of mtDNA analysis as a prognosis AD biomarker.

matter of discussion.

274 Alzheimer's Disease - Challenges for the Future

*5.1.1.7. Mitochondrial DNA*

*5.1.1.8. Metabolic profile*

peutic opportunities related to the miRNA field.

Despite the description of altered levels of several molecules in the blood levels of several molecules in the blood of AD patients as AD clinical biomarkers. Direct analysis in blood or blood-derived serum or plasma samples presents a broad range of advantages over CSF analysis. Blood extraction is minimally invasive and sample is easily collected, processed and stored over time. However, variations in the levels of blood metabolites may be reflecting a broad spectrum of changes not directly related to the neurodegenerative process. In addition, the dynamic range of the changes are lower than in CSF obtaining, most of the times, incon‐ sistent data. Additionally, contrary to CSF, blood is a very complex fluid composed of different types of metabolites and cell types that present significant oscillations in response to external factors not related to pathogenic events. The analysis of specific blood cells could be an alternative approach to link potential biomarkers levels with AD pathology, being a field under intense study.

#### *5.2.1. Protein biomarkers*

The core CSF AD biomarkers present minimal alterations in plasma. Aβ40 levels are higher in AD than in controls, although a high overlap is observed between groups. No changes have been observed for Aβ42, and Aβ40 and both Aβ40 and Aβ42 levels showed no association with cognitive decline [86]. Albeit some partial overlap between groups, tau levels in plasma are increased in AD when compared to control and MCI patients. Interestingly, tau levels cannot differentiate non-progressive from AD progressive MCI patients and there is a lack of correlation between CSF and plasma tau levels [193].

High-throughputs proteomic studies have tried to report the complex deregulated signatures between control and AD samples. A 2D-Mass spectrometry-based study detected a deregu‐ lated set of proteins in AD plasma complement factor H precursor and α-2-macroglobulin, which were validated and correlated with disease severity [194]. Independent multi-analyte profiling studies also demonstrated the presence of deregulated levels of proteins in MCI and AD samples when compared to controls both in serum and plasma. Among them some hits are related to AD pathogenesis such as the apoE [195, 196] as well as a broad range of inflam‐ matory mediators [196, 197]. In an array-based ELISA study, 18 signalling proteins were able to distinguish AD from control samples with high accuracy (90%) and to predict MCI to AD progression [198], although the validation of this dataset has been ambiguous [199, 200]. The observation of a high variability between independent analyses indicates that further valida‐ tions by independent methodologies in different cohorts need to be performed before resolving the clinical relevance of high-throughput blood-based analysis.

Alternative plasma biomarkers include the brain-reactive autoantibodies, present in sera irrespective of the presence of any pathology. This finding led to the analysis of the potential AD-specific autoantibody signature, which has been suggested to possess diagnostic value due to its ability to distinguish AD cases from controls, PD and breast cancer samples [201].

#### *5.2.2. microRNAs*

miRNA signature from CSF is only slightly more stable when compared to serum, suggesting that both biofluids are appropriate for the screening analysis of small RNAs [202]. Therefore, several studies addressed the potential deregulated miRNA signature in blood-derived AD samples. Using a microarray and qPCR validation approach the miR-125b, miR-23a and miR-26b were downregulated in the serum of AD cases when compared to non-inflammatory and inflammatory neurological controls and to FTD cases [203]. miR-125b presented the best accuracy discriminating AD from other groups. The same study observed that miR-125b and miR-26b levels were also diminished in the CSF of AD patients. An independent validation study was able to replicate downregulation of miR-125b in AD serum [204].

In a different approach, using RNA-sequencing and qPCR validation, downregulated levels of the miR-98-5p, miR-885-5p, miR-483-3p, miR-342-3p, miR-191-5p and let-7d-5p in the serum of AD cases were reported. The miR-342-3p showed the best sensitivity and specificity and correlated with cognitive decline [205]. However, downregulated levels of miR-342-3p in biological fluids are also a common hallmark in cancer [206]. Using a similar approach a 12 blood-based miRNA signatures was suggested to discriminate AD patients from controls and samples from patients suffering from different neurodegenerative diseases with high diag‐ nostic accuracies [207]. Nonetheless, the different sample origin impedes a formal comparison between disease group's studies. The analysis of peripheral blood mononuclear cells identified upregulated levels of miR-34a, miR-181b in AD cells [208].

Despite the promising future of miRNA as biomarkers tools of clinical relevance, several considerations needs to be done. Lack of validation among current available studies, even when using similar platform, indicates that sample collection and methodology needs further standardization. In addition, high-throughput data need to be cross-validated in longitudinal studies using different cohorts and selected miRNAs validated in multicentre studies. Under these conditions miRNA in blood-related samples may serve as prognostic and diagnostic through the analysis of miRNA signatures alone or combined with the analysis of classical AD biomarkers.

## **6. Conclusion**

High-throughputs proteomic studies have tried to report the complex deregulated signatures between control and AD samples. A 2D-Mass spectrometry-based study detected a deregu‐ lated set of proteins in AD plasma complement factor H precursor and α-2-macroglobulin, which were validated and correlated with disease severity [194]. Independent multi-analyte profiling studies also demonstrated the presence of deregulated levels of proteins in MCI and AD samples when compared to controls both in serum and plasma. Among them some hits are related to AD pathogenesis such as the apoE [195, 196] as well as a broad range of inflam‐ matory mediators [196, 197]. In an array-based ELISA study, 18 signalling proteins were able to distinguish AD from control samples with high accuracy (90%) and to predict MCI to AD progression [198], although the validation of this dataset has been ambiguous [199, 200]. The observation of a high variability between independent analyses indicates that further valida‐ tions by independent methodologies in different cohorts need to be performed before resolving

Alternative plasma biomarkers include the brain-reactive autoantibodies, present in sera irrespective of the presence of any pathology. This finding led to the analysis of the potential AD-specific autoantibody signature, which has been suggested to possess diagnostic value due to its ability to distinguish AD cases from controls, PD and breast cancer samples [201].

miRNA signature from CSF is only slightly more stable when compared to serum, suggesting that both biofluids are appropriate for the screening analysis of small RNAs [202]. Therefore, several studies addressed the potential deregulated miRNA signature in blood-derived AD samples. Using a microarray and qPCR validation approach the miR-125b, miR-23a and miR-26b were downregulated in the serum of AD cases when compared to non-inflammatory and inflammatory neurological controls and to FTD cases [203]. miR-125b presented the best accuracy discriminating AD from other groups. The same study observed that miR-125b and miR-26b levels were also diminished in the CSF of AD patients. An independent validation

In a different approach, using RNA-sequencing and qPCR validation, downregulated levels of the miR-98-5p, miR-885-5p, miR-483-3p, miR-342-3p, miR-191-5p and let-7d-5p in the serum of AD cases were reported. The miR-342-3p showed the best sensitivity and specificity and correlated with cognitive decline [205]. However, downregulated levels of miR-342-3p in biological fluids are also a common hallmark in cancer [206]. Using a similar approach a 12 blood-based miRNA signatures was suggested to discriminate AD patients from controls and samples from patients suffering from different neurodegenerative diseases with high diag‐ nostic accuracies [207]. Nonetheless, the different sample origin impedes a formal comparison between disease group's studies. The analysis of peripheral blood mononuclear cells identified

Despite the promising future of miRNA as biomarkers tools of clinical relevance, several considerations needs to be done. Lack of validation among current available studies, even when using similar platform, indicates that sample collection and methodology needs further

study was able to replicate downregulation of miR-125b in AD serum [204].

upregulated levels of miR-34a, miR-181b in AD cells [208].

the clinical relevance of high-throughput blood-based analysis.

*5.2.2. microRNAs*

276 Alzheimer's Disease - Challenges for the Future

The use of combined analysis of current AD diagnostic tools is gaining experimental momen‐ tum due to its demonstrated value as a better prognostic and diagnostic tool when compared to individual assessments. As most promising candidates, CSF markers as well as methods of in vivo neuroimaging have been identified. Among them, we can find structural MRI, 18F-FDG-PET and novel in vivo amyloid-PET imaging [209, 210]. In longitudinal studies it was shown that with the help of these biomarkers AD could be diagnosed already in mild symptomatic states with high accuray allowing a predictability of its development [210]. Investigations of patients with genetic AD have demonstrated already 15 years prior to the onset of dementia significant pathological alterations in distinct biomarkers [211, 212].

Although these results are only assignable in a limited way to sporadic AD, the latter study provides impressive evidence on the long preclinical course of AD.

Current diagnostic concepts should therefore apply not at first when AD dementia has developed, but support explicitly the application of biomarkers at distinct stages of AD as it was shown that biomarkers become positive already at early and presymptomatic stages [213, 214].

In conclusion, differential diagnosis of a dementia syndrom requires esides clinical history and neuropsychological testing, analysis of metabolites in biological fluids as well as imaging methods. All these diagnostic approaches will not only allow an explanation towards the underlying cause of dementia but will also be useful in monitoring disease treatment and progression. The detection of AD at an early stage is hereby essential, as a further disease progression can be influenced positively by early initiation of treatment.

Integration of data generated during the last decades should be used to build up a worldwide rational algorithm based in the use of standardized, economically affordable methodologies and easily accessible samples.

#### **Nomenclature**

AD: Alzheimer's disease, rpAD: rapidly progressive Alzheimer's disease, CJD: Creutzfeldt-Jakob disease, aMCI: Amnestic Mild Cognitive Impairment, MCI: Mild cognitive impairment, FTLD: Frontotemporal Lobe Degeneration, FTD: Frontotemporal Dementia, CSF: Cerebrospi‐ nal Fluid, PD: Parkinson Disease, HD: Huntington Disease, ELISA: Enzyme-Linked Immuno‐ Sorbent Assay, MS: Multiple Sclerosis, SWD: Subcortical White-matter Dementia, MMSE: Mini–mental state examination, APP: Amyloid precursor protein, DS: Down Syndrome, CRP: C-reactive protein, PSP: progressive supranuclear palsy, CBS: corticobasal syndrome; NINCDS/ADRDA: American National Institute of Neurological and Communicative Disor‐ ders and Stroke /Alzheimer's disease and Related Disorders Association; DGPPN: German Society of Psychiatry, Psychotherapy and Neurology; DGN: German Neurological Society; MRI: Magnetic Resonance Imaging, PET: Emission Computed Tomography; SPECT: single photon emission computed tomography; EEG: Electroencephalogram; CT; Computerized Tomography; CDR: Clinical Dementia Rating; GDS: Global Deterioration Scale; ADL-/IADL: Activities of Daily Living /Instrumental Activities of Daily Living; VBM: voxel-based morph‐ ometry; FLAIR; Fluid-attenuated inversion recovery; rCBF: regional cerebral blood flow.

## **Acknowledgements**

The study was supported by the EU grants JPND-DEMTEST (Biomarker based diagnosis of rapid progressive dementias-optimization of diagnostic protocols, 01ED1201A) and PRIORI‐ TY (Protecting the food chain from prions, FP7-KBBE-2007-2A) and by funds from the Federal Ministry of Health (grant no. 1369-341] and from the German Center for Neurodegenerative Diseases (DZNE).

## **Author details**

Franc Llorens1,2, Sabine Nuhn1 , Christoph Peter1 , Inga Zerr1,2 and Katharina Stoeck1

1 Department of Neurology, Clinical Dementia Center, University Medical School, Georg-August University, Göttingen, Germany

2 German Center for Neurodegenerative Diseases (DZNE) – Göttingen, Germany

## **References**


[4] Boustani M, Peterson B, Hanson L, Harris R, Lohr KN. Screening for dementia in pri‐ mary care: a summary of the evidence for the U.S. Preventive Services Task Force. *Ann Intern Med* 2003 Jun 3;138:927-937.

C-reactive protein, PSP: progressive supranuclear palsy, CBS: corticobasal syndrome; NINCDS/ADRDA: American National Institute of Neurological and Communicative Disor‐ ders and Stroke /Alzheimer's disease and Related Disorders Association; DGPPN: German Society of Psychiatry, Psychotherapy and Neurology; DGN: German Neurological Society; MRI: Magnetic Resonance Imaging, PET: Emission Computed Tomography; SPECT: single photon emission computed tomography; EEG: Electroencephalogram; CT; Computerized Tomography; CDR: Clinical Dementia Rating; GDS: Global Deterioration Scale; ADL-/IADL: Activities of Daily Living /Instrumental Activities of Daily Living; VBM: voxel-based morph‐ ometry; FLAIR; Fluid-attenuated inversion recovery; rCBF: regional cerebral blood flow.

The study was supported by the EU grants JPND-DEMTEST (Biomarker based diagnosis of rapid progressive dementias-optimization of diagnostic protocols, 01ED1201A) and PRIORI‐ TY (Protecting the food chain from prions, FP7-KBBE-2007-2A) and by funds from the Federal Ministry of Health (grant no. 1369-341] and from the German Center for Neurodegenerative

1 Department of Neurology, Clinical Dementia Center, University Medical School, Georg-

[1] Hebert LE, Scherr PA, Bienias JL, Bennett DA, Evans DA. Alzheimer disease in the US population: prevalence estimates using the 2000 census. *Arch Neurol* 2003 Aug;

[2] Brookmeyer R, Johnson E, Ziegler-Graham K, Arrighi HM. Forecasting the global

[3] Boise L, Neal MB, Kaye J. Dementia assessment in primary care: results from a study in three managed care systems. *J Gerontol A Biol Sci Med Sci* 2004 Jun;59:M621-M626.

burden of Alzheimer's disease. *Alzheimers Dement* 2007 Jul;3:186-191.

, Inga Zerr1,2 and Katharina Stoeck1

, Christoph Peter1

2 German Center for Neurodegenerative Diseases (DZNE) – Göttingen, Germany

**Acknowledgements**

278 Alzheimer's Disease - Challenges for the Future

Diseases (DZNE).

**Author details**

**References**

Franc Llorens1,2, Sabine Nuhn1

60:1119-1122.

August University, Göttingen, Germany


[31] Beblo T. Neuropsychologie der Depression. In: Lautenbacher S, ed. Göttingen: Hog‐ refe, 2006.

[17] Dubois B, Feldman HH, Jacova C, et al. Research criteria for the diagnosis of Alz‐ heimer's disease: revising the NINCDS-ADRDA criteria. *Lancet Neurol* 2007 Aug;

[18] Albert MS, Dekosky ST, Dickson D, et al. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's dis‐

[19] Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment--beyond contro‐ versies, towards a consensus: report of the International Working Group on Mild

[20] Petersen RC. Clinical practice. Mild cognitive impairment. *N Engl J Med* 2011 Jun

[21] Loewenstein D. Assessment of Alzheimer´s Disease. Handbook on the Neuropsy‐

[22] Jahn T. Neuropsychologie der Demenz. Lautenbacher S, Gauggel (Hrsg.): Neuropsy‐

[23] Schmidtke K. Otto, M. Demenzen. Wallesch, CW, Förstl, H (Hrsg.) Thieme,

[24] Schmidtke K, Olbrich S. The Clock Reading Test: validation of an instrument for the diagnosis of dementia and disorders of visuo-spatial cognition. *Int Psychogeriatr* 2007

[25] Schmidtke K. Neuropsychologische Untersuchung bei Patienten mit Demenzver‐

[26] Tsai PH, Teng E, Liu C, Mendez MF. Posterior cortical atrophy: evidence for discrete syndromes of early-onset Alzheimer's disease. *Am J Alzheimers Dis Other Demen* 2011

[27] Groh-Bordin C. Störungen der Visuellen Raumwahrnehmung und Raumkognition. In: Kerkhoff G, ed. Sturm, W. et al. (Hrsg.): Lehrbuch der Klinischen Neuropsycholo‐

[28] Monsch AU, Bondi MW, Butters N, Salmon DP, Katzman R, Thal LJ. Comparisons of verbal fluency tasks in the detection of dementia of the Alzheimer type. *Arch Neurol*

[29] Engel S. Kognitives Screening. In: Mück A LFR, ed. Demenzerkrankungen. Deutsch‐

[30] Beblo T. Neuropsychologie affektiver Störungen. Neuropsychologie psychischer

Störungen. 2. Auflage Lautenbacher, S, Gauggel, S (Hrsg.). 2010:211-218.

ease. *Alzheimers Dement* 2011 May;7:270-279.

Cognitive Impairment. *J Intern Med* 2004 Sep;256:240-246.

chology of Aging and Dementia. Springer, 2013:271-280.

chologie psychischer Störungen. Springer, 2010:360-381.

dacht. In: Hüll M, ed., 26 ed Nervenheilkunde, 2007:651-658.

er Ärzte-Verlag Mahlberg R, Gutzmann (Hrsg.). 2009.

6:734-746.

280 Alzheimer's Disease - Challenges for the Future

9;364:2227-2234.

2012:203-227.

Apr;19:307-321.

Aug;26:413-418.

gie, Springer, 2009:500-512.

1992 Dec;49:1253-1258.


[60] Davies L, Wolska B, Hilbich C, et al. A4 amyloid protein deposition and the diagno‐ sis of Alzheimer's disease: prevalence in aged brains determined by immunocyto‐ chemistry compared with conventional neuropathologic techniques. *Neurology* 1988 Nov;38:1688-1693.

[45] de Leon MJ, George AE, Golomb J, et al. Frequency of hippocampal formation atro‐ phy in normal aging and Alzheimer's disease. *Neurobiol Aging* 1997 Jan;18:1-11.

[46] Wallesch C. Demenzen. 2., überarbeitete und erweiterte Auflage. Stuttgart: Thieme (Referenzreihe Neurologie Herausgegeben von G. Deuschl, H.C. Diener, H.C. Hopf).,

[47] Reiser M. Radiologie. 3., vollst. überarb. u. erw. Aufl. In: et al, ed. Stuttgart: Thieme

[48] Kinkingnehun S, Sarazin M, Lehericy S, Guichart-Gomez E, Hergueta T, Dubois B. VBM anticipates the rate of progression of Alzheimer disease: a 3-year longitudinal

[49] Thompson PM, Hayashi KM, de Zubicaray GI, et al. Mapping hippocampal and ven‐

[50] Becker JT, Davis SW, Hayashi KM, et al. Three-dimensional patterns of hippocampal

[51] Apostolova LG, Steiner CA, Akopyan GG, et al. Three-dimensional gray matter atro‐ phy mapping in mild cognitive impairment and mild Alzheimer disease. *Arch Neurol*

[52] Farid K, Caillat-Vigneron N, Sibon I. Is brain SPECT useful in degenerative dementia

[53] Mosconi L, Berti V, Glodzik L, Pupi A, De SS, de Leon MJ. Pre-clinical detection of Alzheimer's disease using FDG-PET, with or without amyloid imaging. *J Alzheimers*

[54] Matsuda H. Cerebral blood flow and metabolic abnormalities in Alzheimer's disease.

[55] Duran FL, Zampieri FG, Bottino CC, Buchpiguel CA, Busatto GF. Voxel-based inves‐ tigations of regional cerebral blood flow abnormalities in Alzheimer's disease using a

[56] Herholz K, Carter SF, Jones M. Positron emission tomography imaging in dementia.

[57] Morris JC, Roe CM, Grant EA, et al. Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease. *Arch*

[58] Blennow K, Zetterberg H, Fagan AM. Fluid biomarkers in Alzheimer disease. *Cold*

[59] Price JL, Morris JC. Tangles and plaques in nondemented aging and "preclinical"

single-detector SPECT system. *Clinics (Sao Paulo)* 2007 Aug;62:377-384.

tricular change in Alzheimer disease. *Neuroimage* 2004 Aug;22:1754-1766.

atrophy in mild cognitive impairment. *Arch Neurol* 2006 Jan;63:97-101.

2012.

(Duale Reihe)., 2011.

282 Alzheimer's Disease - Challenges for the Future

2007 Oct;64:1489-1495.

*Dis* 2010;20:843-854.

*Ann Nucl Med* 2001 Apr;15:85-92.

*Neurol* 2009 Dec;66:1469-1475.

*Br J Radiol* 2007 Dec;80 Spec No 2:S160-S167.

*Spring Harb Perspect Med* 2012 Sep;2:a006221.

Alzheimer's disease. *Ann Neurol* 1999 Mar;45:358-368.

study. *Neurology* 2008 Jun 3;70:2201-2211.

diagnosis? *J Comput Assist Tomogr* 2011 Jan;35:1-3.


[87] Schoonenboom NS, Mulder C, Van Kamp GJ, et al. Amyloid beta 38, 40, and 42 spe‐ cies in cerebrospinal fluid: more of the same? *Ann Neurol* 2005 Jul;58:139-142.

[73] Hansson O, Zetterberg H, Buchhave P, Londos E, Blennow K, Minthon L. Associa‐ tion between CSF biomarkers and incipient Alzheimer's disease in patients with mild

[74] Snider BJ, Fagan AM, Roe C, et al. Cerebrospinal fluid biomarkers and rate of cogni‐ tive decline in very mild dementia of the Alzheimer type. *Arch Neurol* 2009 May;

[75] Hartmann T, Bieger SC, Bruhl B, et al. Distinct sites of intracellular production for Alzheimer's disease A beta40/42 amyloid peptides. *Nat Med* 1997 Sep;3:1016-1020. [76] Hampel H, Shen Y, Walsh DM, et al. Biological markers of amyloid beta-related

[77] Hoshi M, Sato M, Matsumoto S, et al. Spherical aggregates of beta-amyloid (amylos‐ pheroid) show high neurotoxicity and activate tau protein kinase I/glycogen syn‐

[78] Blennow K. Cerebrospinal fluid protein biomarkers for Alzheimer's disease. *NeuroRx*

[79] Hansson O, Zetterberg H, Buchhave P, et al. Prediction of Alzheimer's disease using the CSF Abeta42/Abeta40 ratio in patients with mild cognitive impairment. *Dement*

[80] Vanmechelen E, Vanderstichele H, Hulstaert F, et al. Cerebrospinal fluid tau and be‐ ta-amyloid(1-42) in dementia disorders. *Mech Ageing Dev* 2001 Nov;122:2005-2011.

[81] Sjogren M, Minthon L, Davidsson P, et al. CSF levels of tau, beta-amyloid(1-42) and GAP-43 in frontotemporal dementia, other types of dementia and normal aging. *J*

[82] Tamaoka A, Sekijima Y, Matsuno S, Tokuda T, Shoji S, Ikeda SI. Amyloid beta pro‐ tein species in cerebrospinal fluid and in brain from patients with Down's syndrome.

[83] Strozyk D, Blennow K, White LR, Launer LJ. CSF Abeta 42 levels correlate with amy‐ loid-neuropathology in a population-based autopsy study. *Neurology* 2003 Feb

[84] Riemenschneider M, Wagenpfeil S, Diehl J, et al. Tau and Abeta42 protein in CSF of patients with frontotemporal degeneration. *Neurology* 2002 Jun 11;58:1622-1628. [85] Tang W, Huang Q, Wang Y, Wang ZY, Yao YY. Assessment of CSF Abeta as an aid to discriminating Alzheimer's disease from other dementias and mild cognitive impair‐

[86] Mehta PD, Pirttila T, Mehta SP, Sersen EA, Aisen PS, Wisniewski HM. Plasma and cerebrospinal fluid levels of amyloid beta proteins 1-40 and 1-42 in Alzheimer dis‐

ment: A meta-analysis of 50 studies. *J Neurol Sci* 2014 Jul 15.

mechanisms in Alzheimer's disease. *Exp Neurol* 2010 Jun;223:334-346.

thase kinase-3beta. *Proc Natl Acad Sci U S A* 2003 May 27;100:6370-6375.

cognitive impairment: a follow-up study. *Lancet Neurol* 2006 Mar;5:228-234.

66:638-645.

284 Alzheimer's Disease - Challenges for the Future

2004 Apr;1:213-225.

*Geriatr Cogn Disord* 2007;23:316-320.

*Neural Transm* 2000;107:563-579.

*Ann Neurol* 1999 Dec;46:933.

ease. *Arch Neurol* 2000 Jan;57:100-105.

25;60:652-656.


[113] Ferrera D, Mazzaro N, Canale C, Gasparini L. Resting microglia react to Abeta42 fi‐ brils but do not detect oligomers or oligomer-induced neuronal damage. *Neurobiol Aging* 2014 May 29.

[100] Zetterberg H, Andreasson U, Hansson O, et al. Elevated cerebrospinal fluid BACE1 activity in incipient Alzheimer disease. *Arch Neurol* 2008 Aug;65:1102-1107.

[101] Holsinger RM, Lee JS, Boyd A, Masters CL, Collins SJ. CSF BACE1 activity is in‐ creased in CJD and Alzheimer disease versus (corrected) other dementias. *Neurology*

[102] Ewers M, Cheng X, Zhong Z, et al. Increased CSF-BACE1 activity associated with de‐ creased hippocampus volume in Alzheimer's disease. *J Alzheimers Dis*

[103] Ye S, Huang Y, Mullendorff K, et al. Apolipoprotein (apo) E4 enhances amyloid beta peptide production in cultured neuronal cells: apoE structure as a potential thera‐

[104] Menting KW, Claassen JA. beta-secretase inhibitor; a promising novel therapeutic

[105] Fukumoto H, Tokuda T, Kasai T, et al. High-molecular-weight beta-amyloid oligom‐ ers are elevated in cerebrospinal fluid of Alzheimer patients. *FASEB J* 2010 Aug;

[106] Santos AN, Ewers M, Minthon L, et al. Amyloid-beta oligomers in cerebrospinal flu‐ id are associated with cognitive decline in patients with Alzheimer's disease. *J Alz‐*

[107] Holtta M, Hansson O, Andreasson U, et al. Evaluating amyloid-beta oligomers in cerebrospinal fluid as a biomarker for Alzheimer's disease. *PLoS One* 2013;8:e66381.

[108] Gao CM, Yam AY, Wang X, et al. Abeta40 oligomers identified as a potential bio‐ marker for the diagnosis of Alzheimer's disease. *PLoS One* 2010;5:e15725.

[109] Salvadores N, Shahnawaz M, Scarpini E, Tagliavini F, Soto C. Detection of misfolded Abeta oligomers for sensitive biochemical diagnosis of Alzheimer's disease. *Cell Rep*

[110] Pitschke M, Prior R, Haupt M, Riesner D. Detection of single amyloid beta-protein aggregates in the cerebrospinal fluid of Alzheimer's patients by fluorescence correla‐

[111] Fukumoto H, Asami-Odaka A, Suzuki N, Iwatsubo T. Association of A beta 40-posi‐ tive senile plaques with microglial cells in the brains of patients with Alzheimer's disease and in non-demented aged individuals. *Neurodegeneration* 1996 Mar;5:13-17.

[112] Gravina SA, Ho L, Eckman CB, et al. Amyloid beta protein (A beta) in Alzheimer's disease brain. Biochemical and immunocytochemical analysis with antibodies specif‐ ic for forms ending at A beta 40 or A beta 42(43). *J Biol Chem* 1995 Mar

peutic target. *Proc Natl Acad Sci U S A* 2005 Dec 20;102:18700-18705.

drug in Alzheimer's disease. *Front Aging Neurosci* 2014;6:165.

2006 Aug 22;67:710-712.

2011;25:373-381.

286 Alzheimer's Disease - Challenges for the Future

24:2716-2726.

*heimers Dis* 2012;29:171-176.

2014 Apr 10;7:261-268.

31;270:7013-7016.

tion spectroscopy. *Nat Med* 1998 Jul;4:832-834.


[140] Tang W, Huang Q, Yao YY, Wang Y, Wu YL, Wang ZY. Does CSF p-tau help to dis‐ criminate Alzheimer's disease from other dementias and mild cognitive impairment? A meta-analysis of the literature. *J Neural Transm* 2014 May 10.

[126] Fagan AM, Head D, Shah AR, et al. Decreased cerebrospinal fluid Abeta(42) corre‐ lates with brain atrophy in cognitively normal elderly. *Ann Neurol* 2009 Feb;

[127] Zetterberg H, Blennow K, Hanse E. Amyloid beta and APP as biomarkers for Alz‐

[128] Andreasen N, Vanmechelen E, Van d, V, et al. Cerebrospinal fluid tau protein as a biochemical marker for Alzheimer's disease: a community based follow up study. *J*

[129] Kaerst L, Kuhlmann A, Wedekind D, Stoeck K, Lange P, Zerr I. Cerebrospinal fluid biomarkers in Alzheimer's disease, vascular dementia and ischemic stroke patients: a

[130] van Harten AC, Kester MI, Visser PJ, et al. Tau and p-tau as CSF biomarkers in de‐

[131] De R, V, Galloni E, Marcon M, et al. Analysis of combined CSF biomarkers in AD di‐

[132] Holtzman DM. CSF biomarkers for Alzheimer's disease: current utility and potential

[133] Sunderland T, Linker G, Mirza N, et al. Decreased beta-amyloid1-42 and increased tau levels in cerebrospinal fluid of patients with Alzheimer disease. *JAMA* 2003 Apr

[134] Kaerst L, Kuhlmann A, Wedekind D, Stoeck K, Lange P, Zerr I. Using cerebrospinal fluid marker profiles in clinical diagnosis of dementia with Lewy bodies, Parkinson's

[135] Parnetti L, Farotti L, Eusebi P, et al. Differential role of CSF alpha-synuclein species,

[136] Kahle PJ, Jakowec M, Teipel SJ, et al. Combined assessment of tau and neuronal thread protein in Alzheimer's disease CSF. *Neurology* 2000 Apr 11;54:1498-1504.

[137] Okamura N, Arai H, Maruyama M, et al. Combined Analysis of CSF Tau Levels and ((123)I)Iodoamphetamine SPECT in Mild Cognitive Impairment: Implications for a

Novel Predictor of Alzheimer's Disease. *Am J Psychiatry* 2002 Mar;159:474-476.

[138] Borroni B, Malinverno M, Gardoni F, et al. A combination of CSF tau ratio and mid‐ saggital midbrain-to-pons atrophy for the early diagnosis of progressive supranu‐

[139] Hampel H, Buerger K, Zinkowski R, et al. Measurement of phosphorylated tau epito‐ pes in the differential diagnosis of Alzheimer disease: a comparative cerebrospinal

tau, and Abeta42 in Parkinson's Disease. *Front Aging Neurosci* 2014;6:53.

mentia: a meta-analysis. *Clin Chem Lab Med* 2011 Mar;49:353-366.

disease, and Alzheimer's disease. *J Alzheimers Dis* 2014;38:63-73.

heimer's disease. *Exp Gerontol* 2010 Jan;45:23-29.

*Neurol Neurosurg Psychiatry* 1998 Mar;64:298-305.

critical analysis. *J Neurol* 2013 Nov;260:2722-2727.

future use. *Neurobiol Aging* 2011 Dec;32 Suppl 1:S4-S9.

clear palsy. *J Alzheimers Dis* 2010;22:195-203.

fluid study. *Arch Gen Psychiatry* 2004 Jan;61:95-102.

agnosis. *Clin Lab* 2014;60:629-634.

23;289:2094-2103.

65:176-183.

288 Alzheimer's Disease - Challenges for the Future


[168] Craig-Schapiro R, Perrin RJ, Roe CM, et al. YKL-40: a novel prognostic fluid biomark‐ er for preclinical Alzheimer's disease. *Biol Psychiatry* 2010 Nov 15;68:903-912.

[154] Stoeck K, Bodemer M, Zerr I. Pro- and anti-inflammatory cytokines in the CSF of pa‐ tients with Creutzfeldt-Jakob disease. *J Neuroimmunol* 2006 Mar;172:175-181.

[155] Stoeck K, Bodemer M, Ciesielczyk B, et al. Interleukin 4 and interleukin 10 levels are elevated in the cerebrospinal fluid of patients with Creutzfeldt-Jakob disease. *Arch*

[156] Swardfager W, Lanctot K, Rothenburg L, Wong A, Cappell J, Herrmann N. A metaanalysis of cytokines in Alzheimer's disease. *Biol Psychiatry* 2010 Nov 15;68:930-941.

[157] Rota E, Bellone G, Rocca P, Bergamasco B, Emanuelli G, Ferrero P. Increased intra‐ thecal TGF-beta1, but not IL-12, IFN-gamma and IL-10 levels in Alzheimer's disease

[158] Tarkowski E, Andreasen N, Tarkowski A, Blennow K. Intrathecal inflammation pre‐ cedes development of Alzheimer's disease. *J Neurol Neurosurg Psychiatry* 2003 Sep;

[159] Schuitemaker A, Dik MG, Veerhuis R, et al. Inflammatory markers in AD and MCI patients with different biomarker profiles. *Neurobiol Aging* 2009 Nov;30:1885-1889.

[160] Wang KX, Denhardt DT. Osteopontin: role in immune regulation and stress respons‐

[161] Comi C, Carecchio M, Chiocchetti A, et al. Osteopontin is increased in the cerebrospi‐ nal fluid of patients with Alzheimer's disease and its levels correlate with cognitive

[162] Sun Y, Yin XS, Guo H, Han RK, He RD, Chi LJ. Elevated osteopontin levels in mild cognitive impairment and Alzheimer's disease. *Mediators Inflamm* 2013;2013:615745.

[163] Bornsen L, Khademi M, Olsson T, Sorensen PS, Sellebjerg F. Osteopontin concentra‐ tions are increased in cerebrospinal fluid during attacks of multiple sclerosis. *Mult*

[164] Verwey NA, Schuitemaker A, van der Flier WM, et al. Serum amyloid p component as a biomarker in mild cognitive impairment and Alzheimer's disease. *Dement Geriatr*

[165] Naude PJ, Nyakas C, Eiden LE, et al. Lipocalin 2: novel component of proinflamma‐

[166] Alcolea D, Carmona-Iragui M, Suarez-Calvet M, et al. Relationship Between beta-Secretase, Inflammation and Core Cerebrospinal Fluid Biomarkers for Alzheimer's

[167] Perrin RJ, Craig-Schapiro R, Malone JP, et al. Identification and validation of novel cerebrospinal fluid biomarkers for staging early Alzheimer's disease. *PLoS One*

tory signaling in Alzheimer's disease. *FASEB J* 2012 Jul;26:2811-2823.

*Neurol* 2005 Oct;62:1591-1594.

290 Alzheimer's Disease - Challenges for the Future

74:1200-1205.

patients. *Neurol Sci* 2006 Apr;27:33-39.

es. *Cytokine Growth Factor Rev* 2008 Oct;19:333-345.

decline. *J Alzheimers Dis* 2010;19:1143-1148.

Disease. *J Alzheimers Dis* 2014 Jan 1;42:157-167.

*Scler* 2011 Jan;17:32-42.

2011;6:e16032.

*Cogn Disord* 2008;26:522-527.


[197] O'Bryant SE, Xiao G, Barber R, et al. A serum protein-based algorithm for the detec‐ tion of Alzheimer disease. *Arch Neurol* 2010 Sep;67:1077-1081.

[183] Lukiw WJ, Zhao Y, Cui JG. An NF-kappaB-sensitive micro RNA-146a-mediated in‐ flammatory circuit in Alzheimer disease and in stressed human brain cells. *J Biol*

[184] Lukiw WJ, Dua P, Pogue AI, Eicken C, Hill JM. Upregulation of micro RNA-146a (miRNA-146a), a marker for inflammatory neurodegeneration, in sporadic Creutz‐ feldt-Jakob disease (sCJD) and Gerstmann-Straussler-Scheinker (GSS) syndrome. *J*

[185] Li YY, Cui JG, Hill JM, Bhattacharjee S, Zhao Y, Lukiw WJ. Increased expression of miRNA-146a in Alzheimer's disease transgenic mouse models. *Neurosci Lett* 2011 Jan

[186] Iyer A, Zurolo E, Prabowo A, et al. MicroRNA-146a: a key regulator of astrocyte-

[187] Boldin MP, Taganov KD, Rao DS, et al. miR-146a is a significant brake on autoim‐ munity, myeloproliferation, and cancer in mice. *J Exp Med* 2011 Jun 6;208:1189-1201.

[188] Podlesniy P, Figueiro-Silva J, Llado A, et al. Low cerebrospinal fluid concentration of mitochondrial DNA in preclinical Alzheimer disease. *Ann Neurol* 2013 Nov;

[189] Schlotterbeck G, Ross A, Dieterle F, Senn H. Metabolic profiling technologies for bio‐ marker discovery in biomedicine and drug development. *Pharmacogenomics* 2006 Oct;

[190] Czech C, Berndt P, Busch K, et al. Metabolite profiling of Alzheimer's disease cere‐

[191] Trushina E, Dutta T, Persson XM, Mielke MM, Petersen RC. Identification of altered metabolic pathways in plasma and CSF in mild cognitive impairment and Alzheim‐

[192] Kaddurah-Daouk R, Zhu H, Sharma S, et al. Alterations in metabolic pathways and

[193] Zetterberg H, Wilson D, Andreasson U, et al. Plasma tau levels in Alzheimer's dis‐

[194] Hye A, Lynham S, Thambisetty M, et al. Proteome-based plasma biomarkers for Alz‐

[195] Hu WT, Holtzman DM, Fagan AM, et al. Plasma multianalyte profiling in mild cog‐ nitive impairment and Alzheimer disease. *Neurology* 2012 Aug 28;79:897-905.

[196] Doecke JD, Laws SM, Faux NG, et al. Blood-based protein biomarkers for diagnosis

mediated inflammatory response. *PLoS One* 2012;7:e44789.

er's disease using metabolomics. *PLoS One* 2013;8:e63644.

networks in Alzheimer's disease. *Transl Psychiatry* 2013;3:e244.

*Chem* 2008 Nov 14;283:31315-31322.

3;487:94-98.

292 Alzheimer's Disease - Challenges for the Future

74:655-668.

7:1055-1075.

*Toxicol Environ Health A* 2011;74:1460-1468.

brospinal fluid. *PLoS One* 2012;7:e31501.

ease. *Alzheimers Res Ther* 2013;5:9.

heimer's disease. *Brain* 2006 Nov;129:3042-3050.

of Alzheimer disease. *Arch Neurol* 2012 Oct;69:1318-1325.


**Section 4**
