From proteomics to biomarker discovery in Alzheimer's disease

DEAD Box Helicase 24 Is Increased in the Brain in Alzheimer's Disease and AppN-LF Mice and Influences Presymptomatic Pathology

At the time of diagnosis, Alzheimer's disease (AD) patients already suffer from significant neuronal loss. The identification of proteins that influence disease progression before the onset of symptoms is thus an essential part of the development of new effective drugs and biomarkers. Here, we used an unbiased 18O labelling proteomics approach to identify proteins showing altered levels in the AD brain. We studied the relationship between the protein with the highest increase in hippocampus, DEAD box Helicase 24 (DDX24), and AD pathology. We visualised DDX24 in the human brain and in a mouse model for Aβ42-induced AD pathology-AppNL-F-and studied the interaction between Aβ and DDX24 in primary neurons. Immunohistochemistry in the AD brain confirmed the increased levels and indicated an altered subcellular distribution of DDX24. Immunohistochemical studies in AppNL-F mice showed that the increase of DDX24 starts before amyloid pathology or memory impairment is observed. Immunocytochemistry in AppNL-F primary hippocampal neurons showed increased DDX24 intensity in the soma, nucleus and nucleolus. Furthermore, siRNA targeting of DDX24 in neurons decreased APP and Aβ42 levels, and the addition of Aβ42 to the medium reduced DDX24. In conclusion, we have identified DDX24 as a protein with a potential role in Aβ-induced AD pathology.

Lipidomics and proteomics: An integrative approach for early diagnosis of dementia and Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder and considered to be responsible for majority of worldwide prevalent dementia cases. The number of patients suffering from dementia are estimated to increase up to 115.4 million cases worldwide in 2050. Hence, AD is contemplated to be one of the major healthcare challenge in current era. This disorder is characterized by impairment in various signaling molecules at cellular and nuclear level including aggregation of Aβ protein, tau hyper phosphorylation altered lipid metabolism, metabolites dysregulation, protein intensity alteration etc. Being heterogeneous and multifactorial in nature, the disease do not has any cure or any confirmed diagnosis before the onset of clinical manifestations. Hence, there is a requisite for early diagnosis of AD in order to downturn the progression/risk of the disorder and utilization of newer technologies developed in this field are aimed to provide an extraordinary assistance towards the same. The lipidomics and proteomics constitute large scale study of cellular lipids and proteomes in biological matrices at normal stage or any stage of a disease. The study involves high throughput quantification and detection techniques such as mass spectrometry, liquid chromatography, nuclear mass resonance spectroscopy, fluorescence spectroscopy etc. The early detection of altered levels of lipids and proteins in blood or any other biological matrices could aid in preventing the progression of AD and dementia. Therefore, the present review is designed to focus on the recent techniques and early diagnostic criteria for AD, revealing the role of lipids and proteins in this disease and their assessment through different techniques.

Diabetes and Its Cardiovascular Complications: Comprehensive Network and Systematic Analyses

Diabetes mellitus is a worldwide health problem that usually comes with severe complications. There is no cure for diabetes yet and the threat of these complications is what keeps researchers investigating mechanisms and treatments for diabetes mellitus. Due to advancements in genomics, epigenomics, proteomics, and single-cell multiomics research, considerable progress has been made toward understanding the mechanisms of diabetes mellitus. In addition, investigation of the association between diabetes and other physiological systems revealed potentially novel pathways and targets involved in the initiation and progress of diabetes. This review focuses on current advancements in studying the mechanisms of diabetes by using genomic, epigenomic, proteomic, and single-cell multiomic analysis methods. It will also focus on recent findings pertaining to the relationship between diabetes and other biological processes, and new findings on the contribution of diabetes to several pathological conditions.

Are Polyphenols Strong Dietary Agents Against Neurotoxicity and Neurodegeneration?

Life expectancy of most human populations has greatly increased as a result of factors including better hygiene, medical practice, and nutrition. Unfortunately, as humans age, they become more prone to suffer from neurodegenerative diseases and neurotoxicity. Polyphenols can be cheaply and easily obtained as part of a healthy diet. They present a wide range of biological activities, many of which have relevance for human health. Compelling evidence has shown that dietary phytochemicals, particularly polyphenols, have properties that may suppress neuroinflammation and prevent toxic and degenerative effects in the brain. The mechanisms by which polyphenols exert their action are not fully understood, but it is clear that they have a direct effect through their antioxidant activities. They have also been shown to modulate intracellular signaling cascades, including the PI3K-Akt, MAPK, Nrf2, and MEK pathways. Polyphenols also interact with a range of neurotransmitters, illustrating that these compounds can promote their health benefits in the brain through a direct, indirect, or complex action. We discuss whether polyphenols obtained from diet or food supplements are an effective strategy to prevent or treat neurodegeneration. We also discuss the safety, mechanisms of action, and the current and future relevance of polyphenols in clinical treatment of neurodegenerative diseases. As populations age, it is important to discuss the dietary strategies to avoid or counteract the effects of incurable neurodegenerative disorders, which already represent an enormous financial and emotional burden for health care systems, patients, and their families.

Green tea polyphenols and their potential role in health and disease

There is a growing body of evidence that plant polyphenols such as resveratrol, anthocyanins, catechins, and terpenes like taxol are effectively used in the treatment of chronic conditions including cancer, Alzheimer, Parkinsonism, diabetes, aging, etc. The link between oxidative stress and inflammation is well accepted. Thus, the mechanism of action of these natural products is partly believed to be through their significant antioxidant properties. The main constituent of green tea, with clinical significance, is epigallocatechin gallate (EGCG). It has been associated with antitumor, anti-Alzheimer, and anti-aging properties, improve redox status at the tissue level possibly preventing system level structural damage. This review focuses on EGCG and its potential therapeutic role in health and disease.

Systems biology approaches for discovering biomarkers for traumatic brain injury

The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates.

ELISA microarray technology as a high-throughput system for cancer biomarker validation

A large gap currently exists between the ability to discover potential biomarkers and the ability to assess the real value of these proteins for cancer screening. One major challenge in biomarker validation is the inherent variability in biomarker levels. This variability stems from the diversity across the human population and the considerable molecular heterogeneity between individual tumors, even those that originate from a single tissue. An additional challenge with cancer screening is that most cancers are rare in the general population, meaning that assay specificity must be very high. Otherwise, the number of false positives will be much greater than the number of true positives. Due to these challenges associated with biomarker validation, it is necessary to analyze thousands of samples in order to obtain a clear idea of the utility of a screening assay. Enzyme-linked immunosorbent assay (ELISA) microarray technology can simultaneously quantify levels of multiple proteins and, thus, has the potential to accelerate validation of protein biomarkers for clinical use. This review will discuss current ELISA microarray technology and potential advances that could help to achieve the reproducibility and throughput that are required to evaluate cancer biomarkers.

Recent technological developments in proteomics shed new light on translational research on diabetic microangiopathy

Diabetic microangiopathy has become a heavy social burden worldwide, but at present it is still difficult to predict and diagnose this ailment at an early stage. Various proteomics approaches have been applied to the pathophysiological study of diabetic microangiopathy. Conventional proteomics methods, including gel-based methods, exhibit limited sensitivity and robustness and have typically been used in high- or middle-abundance biomarker discovery. Clinical samples from patients with diabetic microangiopathy, such as biopsy samples, are minute in size. Therefore sample preparation, quantitative labelling and mass spectrometry technologies need to be optimized for low-abundance protein detection, multiple-sample processing and precision quantitation. In this review, we briefly introduce the recent technological developments in proteomics methods and summarize current proteomics-based, translational research on diabetic microangiopathy. Recent technological developments in proteomics tools may shed new light on the pathogenesis of diabetic microangiopathy and biomarkers and therapeutic targets related to this condition.

Identification of potential biomarkers from microarray experiments using multiple criteria optimization

Microarray experiments are capable of determining the relative expression of tens of thousands of genes simultaneously, thus resulting in very large databases. The analysis of these databases and the extraction of biologically relevant knowledge from them are challenging tasks. The identification of potential cancer biomarker genes is one of the most important aims for microarray analysis and, as such, has been widely targeted in the literature. However, identifying a set of these genes consistently across different experiments, researches, microarray platforms, or cancer types is still an elusive endeavor. Besides the inherent difficulty of the large and nonconstant variability in these experiments and the incommensurability between different microarray technologies, there is the issue of the users having to adjust a series of parameters that significantly affect the outcome of the analyses and that do not have a biological or medical meaning. In this study, the identification of potential cancer biomarkers from microarray data is casted as a multiple criteria optimization (MCO) problem. The efficient solutions to this problem, found here through data envelopment analysis (DEA), are associated to genes that are proposed as potential cancer biomarkers. The method does not require any parameter adjustment by the user, and thus fosters repeatability. The approach also allows the analysis of different microarray experiments, microarray platforms, and cancer types simultaneously. The results include the analysis of three publicly available microarray databases related to cervix cancer. This study points to the feasibility of modeling the selection of potential cancer biomarkers from microarray data as an MCO problem and solve it using DEA. Using MCO entails a new optic to the identification of potential cancer biomarkers as it does not require the definition of a threshold value to establish significance for a particular gene and the selection of a normalization procedure to compare different experiments is no longer necessary.

The neuropathological profile of mild cognitive impairment (MCI): a systematic review

Whether mild cognitive impairment (MCI) has a distinct neuropathological profile that reflects an intermediate state between no cognitive impairment and dementia is not clear. Identifying which biological events occur at the earliest stage of progressive disease and which are secondary to the neuropathological process is important for understating pathological pathways and for targeted disease prevention. Many studies have now reported on the neurobiology of this intermediate stage. In this systematic review, we synthesize current evidence on the neuropathological profile of MCI. A total of 162 studies were identified with varied definition of MCI, settings ranging from population to specialist clinics and a wide range of objectives. From these studies, it is clear that MCI is neuropathologically complex and cannot be understood within a single framework. Pathological changes identified include plaque and tangle formation, vascular pathologies, neurochemical deficits, cellular injury, inflammation, oxidative stress, mitochondrial changes, changes in genomic activity, synaptic dysfunction, disturbed protein metabolism and disrupted metabolic homeostasis. Determining which factors primarily drive neurodegeneration and dementia and which are secondary features of disease progression still requires further research. Standardization of the definition of MCI and reporting of pathology would greatly assist in building an integrated picture of the clinical and neuropathological profile of MCI.

Label-free quantitative LC-MS proteomics of Alzheimer's disease and normally aged human brains

Quantitative proteomics analysis of cortical samples of 10 Alzheimer's disease (AD) brains versus 10 normally aged brains was performed by following the accurate mass and time tag (AMT) approach with the high resolution LTQ Orbitrap mass spectrometer. More than 1400 proteins were identified and quantitated. A conservative approach of selecting only the consensus results of four normalization methods was suggested and used. A total of 197 proteins were shown to be significantly differentially abundant (p-values <0.05, corrected for multiplicity of testing) in AD versus control brain samples. Thirty-seven of these proteins were reported as differentially abundant or modified in AD in previous proteomics and transcriptomics publications. The rest to the best of our knowledge are new. Mapping of the discovered proteins with bioinformatic tools revealed significant enrichment with differentially abundant proteins of pathways and processes known to be important in AD, including signal transduction, regulation of protein phosphorylation, immune response, cytoskeleton organization, lipid metabolism, energy production, and cell death.

Gene expression profiling and therapeutic interventions in neurodegenerative diseases: a comprehensive study on potentiality and limits

INTRODUCTION

Neurodegenerative diseases are incurable debilitating disorders of the nervous system that affect approximately 30 million people worldwide. Despite profuse efforts attempting to define the molecular mechanisms underlying neurodegeneration, many aspects of these pathologies remain elusive. The novelty of their mechanisms represents a challenge to biology, to their related biomarkers identification and drug discovery. Because of their multifactorial aspects and complexity, gene expression analysis platforms have been extensively used to investigate altered pathways during degeneration and to identify potential biomarkers and drug targets.

AREAS COVERED

This work offers an overview of the gene expression profiling studies carried out on Alzheimer's disease, Huntington's disease, Parkinson's disease and prion disease specimens. Therapeutic approaches are also discussed.

EXPERT OPINION

Although many therapeutic approaches have been tested, some of them acting on several altered cellular pathways, no effective cures for these neurodegenerative diseases have been identified. Microarray technology must be associated with functional proteomics and physiology in an effort to identify specific and selective biomarkers and druggable targets, thus allowing the successful discovery of disease-modifying therapeutic treatments.

Proteomic research in psychiatry

Psychiatric disorders such as Alzheimer's disease, schizophrenia and mood disorders are severe and disabling conditions of largely unknown origin and poorly understood pathophysiology. An accurate diagnosis and treatment of these disorders is often complicated by their aetiological and clinical heterogeneity. In recent years proteomic technologies based on mass spectrometry have been increasingly used, especially in the search for diagnostic and prognostic biomarkers in neuropsychiatric disorders. Proteomics enable an automated high-throughput protein determination revealing expression levels, post-translational modifications and complex protein-interaction networks. In contrast to other methods such as molecular genetics, proteomics provide the opportunity to determine modifications at the protein level thereby possibly being more closely related to pathophysiological processes underlying the clinical phenomenology of specific psychiatric conditions. In this article we review the theoretical background of proteomics and its most commonly utilized techniques. Furthermore the current impact of proteomic research on diverse psychiatric diseases, such as Alzheimer's disease, schizophrenia, mood and anxiety disorders, drug abuse and autism, is discussed. Proteomic methods are expected to gain crucial significance in psychiatric research and neuropharmacology over the coming decade.

Alzheimer's disease biomarker discovery in symptomatic and asymptomatic patients: experimental approaches and future clinical applications

Alzheimer's disease (AD) is the most common form of dementia in the elderly. Current treatments for AD are not as effective as needed, nor is there any definitive antemortem diagnostic. Understanding the biological processes that occur during AD onset and/or progression will improve disease diagnosis and treatment. Recent applications of microarray technologies for analysis of messenger (m) RNA expression profiles have elucidated distinct changes in the brain as a function of AD dementia initiation and progression. However, mRNA analysis underestimates post-transcriptional modifications and therefore provides only a partial view of the molecular changes in the AD brain. Combining mRNA studies with protein expression analysis may provide a more global picture of the biological processes associated with AD dementia. Information gathered could lead to the development of select biological indices (biomarkers) for guiding AD diagnosis and therapy. We will provide a brief background on AD, followed by a review on the applications of microarray, proteomics, as well as microRNA expression profile analysis to develop novel diagnostic strategies that may be useful for the diagnosis AD and for monitoring disease progression. The availability of biomarkers that promote early disease diagnosis, particularly among asymptomatic patients, will lead to the application of personalized medicine in AD.

An entorhinal cortex sulcal pattern is associated with Alzheimer's disease

OBJECTIVES

Magnetic resonance (MRI) studies rely on sulcal boundaries to delineate the human entorhinal cortex (EC) and typically show that EC size is reduced in Alzheimer's disease (AD) and a predictor of future dementia. However, it is unknown if variations in the EC sulcal patterns are associated with AD. We classified the lateral EC sulcal boundary as either a rhinal or collateral pattern and tested the hypotheses that the rhinal pattern was (1) more common in AD and (2) associated with a smaller EC size.

EXPERIMENTAL DESIGN

MRI was used to determine the prevalence of the rhinal and collateral EC patterns in 421 subjects (212 AD, 107 old normal (ONL), and 102 young NL (YNL). Anatomical validation studies of normal subjects were conducted at postmortem in 34 brain hemispheres and in vivo with 21 MRI volume studies. EC pattern reliability was studied with MRI in both cross-sectional and longitudinal designs.

PRINCIPAL OBSERVATIONS

The rhinal pattern was more frequent in the right hemisphere in AD (47%) compared with ONL (28%, odds ratio = 2.25, P = 0.001). EC pattern was not related to ApoE genotype. The validations showed that the EC sulcal pattern was not associated with the neuronal number, surface area, or volume of the EC. In patients with antemortem MRI studied at postmortem it was equivalently determined, that EC patterns are reliably determined on MRI and do not change with the progressive atrophy of AD.

CONCLUSIONS

The data indicate that the right hemisphere rhinal pattern is over represented in AD as compared with control. However, in normal subjects the EC rhinal pattern is not associated with a diminished EC tissue size. It remains to be demonstrated if the right EC rhinal sulcus pattern association with AD reflects genetic or developmental influences.

The potential of proteomics for providing new insights into environmental impacts on human health

The effects of environmental chemicals have traditionally been detected by monitoring biomarkers of exposure or biomarkers of effect. Proteomics, the study of the complete profile of proteins in a given cell, tissue or biological system, is a new approach using a set of high-throughput methodologies with a wide dynamic range that makes possible the discovery of novel biomarkers. This article reviews the application of two-dimensional electrophoresis and mass-spectrometry methods to environmental toxicology. Emphasis is placed on the protein-expression signature approach and on identifying redox-based post-translational protein modifications. The methodological links between studies in sentinel organisms and humans are explored. Significant limitations and challenges are placed on this approach by the shortage of genome sequence data necessary for protein identification and the growing requirement for more stringent study design. Proteomics will continue to be an important toolkit to help address the growing environmental threat posed by nanoparticles and endocrine disrupting agents.

Proteomics in clinical interventions: achievements and limitations in biomarker development

Development of toxicological and clinical biomarkers for disease diagnosis, quantification of toxicant/drug responses and rapid patient care are major concerns in modern biology. Even after human genome sequencing, identification of specific molecular signatures for unambiguous correlation with toxicity and clinical interventions is a challenging task. Differential protein expression patterns and protein-protein interaction studies have started unraveling rigorous molecular explanation of multi-factorial and toxicant borne diseases. Proteome profiling is extensively used to investigate etiology of diseases, develop predictive biomarkers for toxicity and therapeutic interventions and potential strategies for treatment of complex and toxicant mediated diseases. In this review, achievements and limitations of proteomics in developing predictive biomarkers for toxicological and clinical interventions have been discussed.

Natural antisense transcripts of Alzheimer's disease associated genes

Natural antisense transcripts (NATs), also named endogenous antisense transcripts, are a class of genes whose role in controlling gene expression is becoming more and more relevant. NATs might play important roles in gene expression and translation regulation. Present work investigated the presence of NATs of Alzheimer's disease associated genes including PRESENILIN1, PRESENILIN2, BACE1, BACE2, APP, APOE, TAU (MAPT), PRION, alpha-SYNUCLEIN (SNCA), NICASTRIN, PEN2, APH1A, APH1B as well as CD147 (BASIGIN), and the results revealed that APP, BACE2, APH1A, TAU, CD147 and alpha-SYNUCLEIN contain natural antisense transcripts. These NATs were characterized according to the sense-antisense overlapping information and potential functional mechanisms were proposed. Present findings provide preliminary but important information about transcription regulation of AD associated genes, which would further our understanding of the gene expression regulation of AD, and also suggest a novel potential strategy for the therapy of AD.

Novel subtractive transcription-based amplification of mRNA (STAR) method and its application in search of rare and differentially expressed genes in AD brains

Background

Alzheimer's disease (AD) is a complex disorder that involves multiple biological processes. Many genes implicated in these processes may be present in low abundance in the human brain. DNA microarray analysis identifies changed genes that are expressed at high or moderate levels. Complementary to this approach, we described here a novel technology designed specifically to isolate rare and novel genes previously undetectable by other methods. We have used this method to identify differentially expressed genes in brains affected by AD. Our method, termed Subtractive Transcription-based Amplification of mRNA (STAR), is a combination of subtractive RNA/DNA hybridization and RNA amplification, which allows the removal of non-differentially expressed transcripts and the linear amplification of the differentially expressed genes.

Results

Using the STAR technology we have identified over 800 differentially expressed sequences in AD brains, both up- and down- regulated, compared to age-matched controls. Over 55% of the sequences represent genes of unknown function and roughly half of them were novel and rare discoveries in the human brain. The expression changes of nearly 80 unique genes were further confirmed by qRT-PCR and the association of additional genes with AD and/or neurodegeneration was established using an in-house literature mining tool (LitMiner).

Conclusion

The STAR process significantly amplifies unique and rare sequences relative to abundant housekeeping genes and, as a consequence, identifies genes not previously linked to AD. This method also offers new opportunities to study the subtle changes in gene expression that potentially contribute to the development and/or progression of AD.

Applying advances in neurogenetics to medical practice

The investigation of rare neurogenetic diseases is an example of how a translational science approach may lead to the delineation of complex genetic and biochemical pathways. Thisprocess comprises several intellectual stages. The first step involves the astute identification and clinical description of the unique phenotype, which may lead to obvious pathways or may reveal novel or unexpected mechanisms. As similar patients are identified, the establishment of databases detailing the clinical phenotype may serve to provide clues as to the genetic and biochemical characterization, and identification of the genetic mutation based on patient samples and animal or cellular models. Lastly, attempts to develop and apply therapies based on what has been learned about the biochemical and molecular bases of the disease enables intervention on the individual patient level. Several stages of discovery may overlap or be investigated simultaneously. As examples, this review discusses how this process of investigation has enabled progress in the delineation of several genetic and neurogenetic disorders, including Progeria syndrome, neurodegenerative diseases, muscular dystrophy, Rett syndrome and neurotransmitter disorders. This review attempts to summarize the transition from the bedside-to-bench-to-bedside as a model of bringing such discoveries into the clinical arena, and in doing so addresses the issues that may enhance, or complicate, such a path of discovery, as well as the impact such advances in genetics and genomics may have on the practice of clinical medicine and the role of the physician.

An integrated map of the murine hippocampal proteome based upon five mouse strains

With the advent of proteomics technologies it is possible to simultaneously demonstrate the expression of hundreds of proteins. The information offered by proteomics provides context-based understanding of cellular protein networks and has been proven to be a valuable approach in neuroscience studies. The mouse hippocampus has been a major target of analysis in the search for molecular correlates to neuronal information storage. Although human and rat hippocampal samples have been successfully subjected to proteomic profiling, no elaborate analysis providing the fundamental experimental basis for protein-expression studies in the mouse hippocampus has been carried out as yet. This led us to construct a master map generated from the individual hippocampal proteomes of five different mouse strains. A proteomic approach, based upon 2-DE coupled to MS (MALDI-TOF/TOF) has been chosen in an attempt to establish a comprehensive reference database of proteins expressed in the mouse hippocampus. 469 individual proteins, represented by 1156 spots displaying various functional states of the respective gene products were identified. Proteomic profiling of the hippocampus, a brain region with a pivotal role for neuronal information processing and storage may provide insight into the characteristics of proteins serving this highly sophisticated function.

Clinical proteomics: searching for better tumour markers with SELDI-TOF mass spectrometry

Recently, the focus of cancer research has expanded from genetic information in the human genome to protein expression analyses. Because this 'proteome' reflects the state of a cell, tissue or organism more accurately, much is expected from proteomics to yield better tumour markers for disease diagnosis and therapy monitoring. Some current proteomic technologies are particularly suitable for protein profiling in the search for new biomarkers. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry has been used frequently, highlighting many new proteins as biomarkers (e.g. for ovarian, breast, prostate and colorectal cancer). However, it is becoming increasingly recognized that reproducibility and validation of these biomarkers should be addressed carefully, as should their origin and identity. If these efforts are made, protein profiling can contribute to the better diagnosis of patients and the optimization of their treatment.

Biomarkers for neurodegenerative diseases

PURPOSE OF REVIEW

A major goal of current clinical research in neurodegenerative diseases is to improve early detection of disease and presymptomatic detection of neuronal dysfunction. We also need better tools to assess disease progression in this group of disorders. Currently, many potential disease-modifying therapies are being developed and evaluated at the preclinical stage, and will lead to clinical trials in the near future for which biomarkers are urgently needed. This review summarizes the field of biomarker research in the major neurodegenerative diseases.

RECENT FINDINGS

Many different approaches are being undertaken to identify biomarkers and include imaging, neurophysiological and cognitive testing in addition to newer technologies such as biochemical, proteomic, metabanomic and gene array profiling of tissue and biofluids from patients. Key recent findings in each of these areas are discussed.

SUMMARY

The ideal biomarker needs to be easy to quantify and measure, reproducible, not subject to wide variation in the general population and unaffected by co-morbid factors. For evaluation of therapies the biomarker needs to change linearly with disease progression and closely correlate with established clinico-pathological parameters of the disease. It is unlikely that any one biomarker will fulfil all these characteristics, and it is likely that more than one biomarker will be needed for early diagnosis and similarly for evaluation of disease progression for therapeutic trials. For example, the combination of more detailed clinical assessments encompassing specific cognitive and neurophysiological testing, in addition to imaging, biochemical and genomic profiling, is likely to be needed.

To be or not to be (inflamed) – is that the question in anti-inflammatory drug therapy of neurodegenerative disorders?

A sustained inflammatory reaction is present in acute (e.g. stroke) and chronic (e.g. Alzheimer's disease, Parkinson's disease and multiple sclerosis) neurodegenerative disorders. Inflammation, which is fostered by both residential glial cells and blood-circulating cells that infiltrate the diseased brain, probably starts as a time- and site-specific defense mechanism that could later evolve into a destructive and uncontrolled reaction. In this article, we review the crucial dichotomy of brain inflammation, where failure to resolve an acute beneficial response could lead to a vicious and anarchic state of chronic activation. The possible use of non-steroidal anti-inflammatory drugs for the management of neurodegenerative diseases is discussed in light of recent data demonstrating a neuroprotective role of local innate and adaptive immune responses. Novel therapeutic approaches must rely on potentiation of endogenous anti-inflammatory pathways, identification of early markers of neuronal deterioration and a combination treatment involving immune modulation and anti-inflammatory therapies.