**4. Identification of a new plasma biomarker of AD using metabolomics technology**

Current metabolomics research involves the identification and quantification of hundreds to thousands of small-molecular-mass metabolites (<1,500 Daltons) in cells, tissues, or biological fluids. The aims of such studies are typically to understand new diagnosis biomarkers, to understand the mechanism of action of therapeutic compounds, and to uncover the pharma‐ codynamics and kinetic markers of drugs in patients and in preclinical in vivo and in vitro models (Wilcoxen et al., 2010). Lipidomics is one of the metabolomics approaches used to analyze lipid species in biological systems (Hu et al., 2009; Han et al., 2005; Han and Gross, 2003). Investigating lipid biochemistry using a lipidomics approach will not only provide insights into the specific roles of lipid molecular species in healthy individuals and patients but will also assist in identifying potential biomarkers for establishing preventive or thera‐ peutic approaches for human health (Hu et al., 2009,Wenk.,2005; Rosenson.,2010 ). Lipidomics has recently captured attention, owing to the well-recognized roles of lipids in numerous human diseases such as diabetes, obesity, atherosclerosis, and AD (Wenk et al., 2005; Watson., 2006; Steinberg,. 2005; Sato et al., 2010). In support of the hypothesis that lipid dysfunction plays an important role in AD pathogenesis, previous studies with post-mortem brain tissue samples have demonstrated altered lipidomes at the different stage of AD pathogenesis. For example, multiple classes of sphingolipids are altered not only at the late stage of the disease but also at the earliest clinically recognizable stage of AD. All major classes of phospholipids are ubiquitously decreased at the late stage of AD. Among these, the levels of plasmalogen (a major component in nerve tissue membranes counting for up to 85% of ethanolamine glycer‐ ophospholipid, or ∼30% of total phospholipids of these membranes) are gradually reduced as progress of AD severity (Han et al., 2011). Sato et al (2011) established a lipidomics method for comprehensive phospholipids evaluation that identified 31 phospholipids as AD biomarker candidates in human plasma using LC/MS (Satoet al., 2010). Moreover, additional studies have suggested that AD associates with other lipid metabolism pathways and lipid carrier proteins such as apoE (Bertram et al., 2008; Corder et al., 1993; Farrer et al., 1997; Strittmatter et al., 1993).

a specific involvement of miRNAs in pathogenetic signaling pathways associated with the AD process. Recent findings suggest that neuronal miRNA deregulation in response to an insult by Aβ may be an important factor contributing to the cascade of events leading to AD (Schonrock, et al., 2010). Of note, the upregulation of peripheral miRNAs in AD could contribute to the diminished plasma proteins reported to be predictive biomarkers for AD (Ray Set al., 2007). In addition, it has recently been reported that miRNAs can be detected in CSF: an altered regulation of miRNA expression in AD brains was paralleled by a modulation of miRNA levels in the CSF (Cogswell et al., 2008). These studies provide an initial hope that miRNAs could represent accessible biomarkers to support clinical diagnosis in the near future.

Candidate Bio-Markers of Alzheimer's Disease

http://dx.doi.org/10.5772/55069

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Disease modifying drugs are likely to be most effective in the earlier stages of AD, before neurodegeneration is too severe and widespread, so trials for this type of drug will need to include AD cases in the earlier stages of the disease. Validated biomarkers that could enable accurate identification of AD pathology at an early stage would be of great use (Hampel et al., 2011). Alternatively, baseline biomarker measurements can be used for enrichment and stratification in proof-of concept studies, as well as for supporting go/no-go decision making of phase III trials. Biomarkers should be used in all stages of drug development including phase I, phase II and phase III. They can be used to enhance inclusion and exclusion criteria, for stratification. Biomarkers can also be used as outcome markers to detect treatment effects. Particularly, if biomarkers are intended to be used as surrogate endpoints in pivotal studies, they must have been qualified to be a substitute for a clinical standard of truth and as such reasonably predict a clinical meaningful outcome. Finally, biomarkers can be used to identify adverse effects. Nevertheless there are several pitfalls to be faced in the interpretation of biomarker data in AD drug development, such as the fact that biomarkers may be nonspecific to AD, it may not be feasible to measure them in the appropriate system (i.e. the central nervous system) and the risk of over-interpreting biomarker data in phase II trials if statistical significance levels are not adjusted for multiple comparisons (Aisen, 2009). Failure to consider these issues could contribute to false conclusions and costly errors

Several promising drug candidates with disease-modifying effect, such as A*β* immunother‐ apy, secretase modulators, and tau aggregation inhibitors, have now reached the stage of being tested in clinical trials. The promise of disease-modifying therapy has created a need for biomarkers to enable the clinical identification of the disease at an early stage. Early diagnosis will be of great importance since disease-modifying drugs are likely to be most effective in the earlier stages of the disease, before neurodegeneration is too severe and widespread. A large number of studies have demonstrated that tests based on

**6. Timing and other influencing factors of biomarker use**

(Hampel et al., 2011; Hampel et al., 2004)

**7. Conclusion and future directions**

A very recent study by Sato et al (2011) were able to find a biomarker desmosterol that changes in AD compared with plasma from healthy elderly controls. They have shown that desmosterol plasma level and the desmosterol/cholesterol ratio in the same patients was significantly decreased. This study is the first report that plasma desmosterol levels are decreased in AD and MCI. And future studies are needed to confirm whether desmosterol could become an attractive plasma AD biomarker that could perhaps also be utilized for diagnosis and as well as for monitoring noninvasively the effect of future AD drugs on disease progression.

### **5. MicroRNAs as biomarkers for AD**

MicroRNAs (miRNAs) are a class of small, endogenous, noncoding RNA molecules that serve as posttranscriptional regulators of gene expression (Lee etal.,1993;Giannakakis etal.,2007). miRNAs are acquiring important and determinant roles in the regulation of brain gene transcription in health and disease: the fact that approximately 80% of the human brain genome is transcribed into RNA, but only about 2% of the genome is transcribed into protein, under‐ scores the potential of various levels of RNA signaling and epigenetic mechanisms to contrib‐ ute to physiological gene control (Makeyevetal., 2008). In the last few years, miRNAs have been emerging as important regulators of various aspects of neuronal development and dysfunction (Gao.,2007; Lukiw.,2007). The role of miRNAs in neurodegenerative diseases has been investigated using miRNA microarray profiling in brain tissue samples derived from patients and controls. Using miRNA expression profiling in cortex samples from a wellcharacterized clinicopathological series of elderly controls, MCI subjects and AD patients, Wang et al (2008) identified miR-107 to be specifically decreased early in the course of AD. Computational analyses predicted BACE1 mRNA as a target of miR-107 and correlative mRNA expression studies confirmed its role in regulating BACE1 expression. An independent miRNA profiling study by Hebert et al (2008) confirmed the importance of BACE1 regulation by miRNAs. The presence of a modulation of miRNA in regions of brain targeted by AD neuropathology was further demonstrated (Lukiw et al., 2008; Lukiw., 2009), thus suggesting a specific involvement of miRNAs in pathogenetic signaling pathways associated with the AD process. Recent findings suggest that neuronal miRNA deregulation in response to an insult by Aβ may be an important factor contributing to the cascade of events leading to AD (Schonrock, et al., 2010). Of note, the upregulation of peripheral miRNAs in AD could contribute to the diminished plasma proteins reported to be predictive biomarkers for AD (Ray Set al., 2007). In addition, it has recently been reported that miRNAs can be detected in CSF: an altered regulation of miRNA expression in AD brains was paralleled by a modulation of miRNA levels in the CSF (Cogswell et al., 2008). These studies provide an initial hope that miRNAs could represent accessible biomarkers to support clinical diagnosis in the near future.
