A combined dataset of human cerebrospinal fluid proteins identified by multi-dimensional chromatography and tandem mass spectrometry

Biomarkers for cognitive impairment in Parkinson disease

Cognitive impairment, including dementia, is commonly seen in those afflicted with Parkinson disease (PD), particularly at advanced disease stages. Pathologically, PD with dementia (PD-D) is most often associated with the presence of cortical Lewy bodies, as is the closely related dementia with Lewy bodies (DLB). Both PD-D and DLB are also frequently complicated by the presence of neurofibrillary tangles and amyloid plaques, features most often attributed to Alzheimer disease. Biomarkers are urgently needed to differentiate among these disease processes and predict dementia in PD as well as monitor responses of patients to new therapies. A few clinical assessments, along with structural and functional neuroimaging, have been utilized in the last few years with some success in this area. Additionally, a number of other strategies have been employed to identify biochemical/molecular biomarkers associated with cognitive impairment and dementia in PD, e.g. targeted analysis of candidate proteins known to be important to PD pathogenesis and progression in cerebrospinal fluid or blood. Finally, interesting results are emerging from preliminary studies with unbiased and high throughput genomic, proteomic and metabolomic techniques. The current findings and perspectives of applying these strategies and techniques are reviewed in this article, together with potential areas of advancement.

Quantitative proteomics and metabolomics analysis of normal human cerebrospinal fluid samples

The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.

Quantitative proteomics and metabolomics analysis of normal human cerebrospinal fluid samples

The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.

General overview: biomarkers in neuroscience research

Biomarkers are in demand for disease diagnosis, treatment response monitoring, and development of novel therapeutics. Biomarker discovery in neuroscience is challenging due to absence of robust molecular correlates and the interpatient heterogeneity that characterizes neuropsychiatric disorders. Because of the complexity of these disorders, a panel of biomarkers derived from different platforms will be required to precisely reflect disease-related alterations. Animal models of psychiatric phenotypes as well as -omics and imaging methodologies are important tools for biomarker discovery. However, the limitations of current research concerning sample handling and collection, candidate biomarker validation, and a lack of interdisciplinary approaches need to be addressed. Ultimately, the coordinated effort of relevant stakeholders including researchers, physicians, and funding organizations together with standardization initiatives will be vital to overcome the present challenges and to advance personalized health care using sensitive and specific biomarkers.

Quest for new genomic and proteomic biomarkers in neurology

The possibility of identifying novel biomarkers for neurodegenerative diseases has been greatly enhanced with recent advances in genomics and proteomics. Novel technologies have the potential to hasten the development of new biomarkers useful as predictors of disease etiology and outcome, as well as responsiveness to therapy. Disease-modifying new therapies are very much needed in modern approaches to treatment of neurodegenerative diseases. Current progress in the field encounters a degree of skepticism about the reliability of genomic and proteomic data and its relevance for clinical applications. Standard operating procedures covering sample collection, methodology and statistical analysis need to be fully developed and strictly adhered to in order to assure reproducible and clinically relevant results. Previous studies involving patients with neurodegenerative diseases show promise in using genomic and proteomic approaches for development of new biomarkers. Confirmation of any novel biomarker in multiple independent patient cohorts and correlation of the improvement in biomarker endpoint with clinical improvement in longitudinal patient studies remains crucial for future successful application. We propose that a combination of approaches in biomarker discovery may in the end lead to identification of promising candidates at DNA, RNA, protein and small molecule level.

Identification of novel biomarker candidates by proteomic analysis of cerebrospinal fluid from patients with moyamoya disease using SELDI-TOF-MS

Background

Moyamoya disease (MMD) is an uncommon cerebrovascular condition with unknown etiology characterized by slowly progressive stenosis or occlusion of the bilateral internal carotid arteries associated with an abnormal vascular network. MMD is a major cause of stroke, specifically in the younger population. Diagnosis is based on only radiological features as no other clinical data are available. The purpose of this study was to identify novel biomarker candidate proteins differentially expressed in the cerebrospinal fluid (CSF) of patients with MMD using proteomic analysis.

Methods

For detection of biomarkers, CSF samples were obtained from 20 patients with MMD and 12 control patients. Mass spectral data were generated by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) with an anion exchange chip in three different buffer conditions. After expression difference mapping was undertaken using the obtained protein profiles, a comparative analysis was performed.

Results

A statistically significant number of proteins (34) were recognized as single biomarker candidate proteins which were differentially detected in the CSF of patients with MMD, compared to the control patients (p < 0.05). All peak intensity profiles of the biomarker candidates underwent classification and regression tree (CART) analysis to produce prediction models. Two important biomarkers could successfully classify the patients with MMD and control patients.

Conclusions

In this study, several novel biomarker candidate proteins differentially expressed in the CSF of patients with MMD were identified by a recently developed proteomic approach. This is a pilot study of CSF proteomics for MMD using SELDI technology. These biomarker candidates have the potential to shed light on the underlying pathogenesis of MMD.

Mass spectrometry-based proteomics in biomedical research: emerging technologies and future strategies

In recent years, the technology and methods widely available for mass spectrometry (MS)-based proteomics have increased in power and potential, allowing the study of protein-level processes occurring in biological systems. Although these methods remain an active area of research, established techniques are already helping answer biological questions. Here, this recent evolution of MS-based proteomics and its applications are reviewed, including standard methods for protein and peptide separation, biochemical fractionation, quantitation, targeted MS approaches such as selected reaction monitoring, data analysis and bioinformatics. Recent research in many of these areas reveals that proteomics has moved beyond simply cataloguing proteins in biological systems and is finally living up to its initial potential – as an essential tool to aid related disciplines, notably health research. From here, there is great potential for MS-based proteomics to move beyond basic research, into clinical research and diagnostics.

Using 'omics' to define pathogenesis and biomarkers of Parkinson's disease

Although great effort has been put forth to uncover the complex molecular mechanisms exploited in the pathogenesis of Parkinson's disease, a satisfactory explanation remains to be discovered. The emergence of several -omics techniques, transcriptomics, proteomics and metabolomics, have been integral in confirming previously identified pathways that are associated with dopaminergic neurodegeneration and subsequently Parkinson's disease, including mitochondrial and proteasomal function and synaptic neurotransmission. Additionally, these unbiased techniques, particularly in the brain regions uniquely associated with the disease, have greatly enhanced our ability to identify novel pathways, such as axon-guidance, that are potentially involved in Parkinson's pathogenesis. A comprehensive appraisal of the results obtained by different -omics has also reconfirmed the increase in oxidative stress as a common pathway likely to be critical in Parkinson's development/progression. It is hoped that further integration of these techniques will yield a more comprehensive understanding of Parkinson's disease etiology and the biological pathways that mediate neurodegeneration.

Quantitative proteomic analysis of oligodendrogliomas with and without 1p/19q deletion

Approximately 50-80% of oligodendrogliomas demonstrate a combined loss of chromosome 1p and 19q. Chromosome 1p/19q deletion, appearing early in tumorigenesis, is associated with improved clinical outcomes, including response to chemotherapy and radiation. Although many hypotheses have been proposed, the molecular mechanisms underlying improved clinical outcomes with 1p/19q deletion in oligodendrogliomas have not been characterized fully. To investigate the molecular differences between oligodendrogliomas, we employed an unbiased proteomic approach using microcapillary liquid chromatography mass spectrometry, along with a quantitative technique called isotope-coded affinity tags, on patient samples of grade II oligodendrogliomas. Following conventional biochemical separation of pooled tumor tissue from five samples of undeleted and 1p/19q deleted grade II oligodendrogliomas into nuclei-, mitochondria-, and cytosol-enriched fractions, relative changes in protein abundance were quantified. Among the 442 total proteins identified, 163 nonredundant proteins displayed significant changes in relative abundance in at least one of the three fractions between oligodendroglioma with and without 1p/19q deletion. Bioinformatic analyses of differentially regulated proteins supported the potential importance of metabolism and invasion/migration to the codeleted phenotype. A subset of altered proteins, including the pro-invasive extracellular matrix protein BCAN, was further validated by Western blotting as candidate markers for the more aggressive undeleted phenotype. These studies demonstrate the utility of proteomic analysis to identify candidate biological motifs and molecular mechanisms that drive differential malignancy related to 1p19q phenotypes. Future analysis of larger patient samples are warranted to further refine biomarker panels to predict biological behavior and assist in the identification of deleted gene products that define the 1p/19q phenotype.

Establishing the proteome of normal human cerebrospinal fluid

Background

Knowledge of the entire protein content, the proteome, of normal human cerebrospinal fluid (CSF) would enable insights into neurologic and psychiatric disorders. Until now technologic hurdles and access to true normal samples hindered attaining this goal.

Methods and Principal Findings

We applied immunoaffinity separation and high sensitivity and resolution liquid chromatography-mass spectrometry to examine CSF from healthy normal individuals. 2630 proteins in CSF from normal subjects were identified, of which 56% were CSF-specific, not found in the much larger set of 3654 proteins we have identified in plasma. We also examined CSF from groups of subjects previously examined by others as surrogates for normals where neurologic symptoms warranted a lumbar puncture but where clinical laboratory were reported as normal. We found statistically significant differences between their CSF proteins and our non-neurological normals. We also examined CSF from 10 volunteer subjects who had lumbar punctures at least 4 weeks apart and found that there was little variability in CSF proteins in an individual as compared to subject to subject.

Conclusions

Our results represent the most comprehensive characterization of true normal CSF to date. This normal CSF proteome establishes a comparative standard and basis for investigations into a variety of diseases with neurological and psychiatric features.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Characterization of the human plasma phosphoproteome using linear ion trap mass spectrometry and multiple search engines

Major plasma protein families play different roles in blood physiology and hemostasis and in immunodefense. Other proteins in plasma can be involved in signaling as chemical messengers or constitute biological markers of the status of distant tissues. In this respect, the plasma phosphoproteome holds potentially relevant information on the mechanisms modulating these processes through the regulation of protein activity. In this work we describe for the first time a collection of phosphopeptides identified in human plasma using immunoaffinity separation of the seven major serum protein families from other plasma proteins, SCX fractionation, and TiO(2) purification prior to LC-MS/MS analysis. One-hundred and twenty-seven phosphosites in 138 phosphopeptides mapping 70 phosphoproteins were identified with FDR < 1%. A high-confidence collection of phosphosites was obtained using a combined search with the OMSSA, SEQUEST, and Phenyx search engines.

Proteomic and metabolomic strategies to investigate HIV-associated neurocognitive disorders

Diagnosing neurodegenerative diseases, monitoring their progression and assessing responses to treatments will all be aided by the identification of molecular markers of different stages of pathology. Protein biomarkers for HIV-associated neurocognitive disorders that have been discovered using proteomics include complement C3, soluble superoxide dismutase and a prostaglandin synthase. Metabolomics has not yet been widely used for biomarker discovery, but early work shows that it has great potential.

In-depth exploration of cerebrospinal fluid by combining peptide ligand library treatment and label-free protein quantification

Cerebrospinal fluid (CSF) is the biological fluid in closest contact with the brain and thus contains proteins of neural cell origin. Hence, CSF is a biochemical window into the brain and is particularly attractive for the search for biomarkers of neurological diseases. However, as in the case of other biological fluids, one of the main analytical challenges in proteomic characterization of the CSF is the very wide concentration range of proteins, largely exceeding the dynamic range of current analytical approaches. Here, we used the combinatorial peptide ligand library technology (ProteoMiner) to reduce the dynamic range of protein concentration in CSF and unmask previously undetected proteins by nano-LC-MS/MS analysis on an LTQ-Orbitrap mass spectrometer. This method was first applied on a large pool of CSF from different sources with the aim to better characterize the protein content of this fluid, especially for the low abundance components. We were able to identify 1212 proteins in CSF, and among these, 745 were only detected after peptide library treatment. However, additional difficulties for clinical studies of CSF are the low protein concentration of this fluid and the low volumes typically obtained after lumbar puncture, precluding the conventional use of ProteoMiner with large volume columns for treatment of patient samples. The method has thus been optimized to be compatible with low volume samples. We could show that the treatment is still efficient with this miniaturized protocol and that the dynamic range of protein concentration is actually reduced even with small amounts of beads, leading to an increase of more than 100% of the number of identified proteins in one LC-MS/MS run. Moreover, using a dedicated bioinformatics analytical work flow, we found that the method is reproducible and applicable for label-free quantification of series of samples processed in parallel.

Proteomics of brain extracellular fluid (ECF) and cerebrospinal fluid (CSF)

Mass spectrometry has become the gold standard for the identification of proteins in proteomics. In this review, I will discuss the available literature on proteomic experiments that analyze human cerebrospinal fluid (CSF) and brain extracellular fluid (ECF), mostly obtained by cerebral microdialysis. Both materials are of high diagnostic value in clinical neurology, for example, in cerebrovascular disorders like stroke, neurodegenerative diseases like Alzheimer's Disease, Parkinson's Disease, amyotrophic lateral sclerosis (ALS), traumatic brain injury and cerebral infectious and inflammatory disease, such as multiple sclerosis. Moreover, there are standard procedures for sampling. In a number of studies in recent years, biomarkers have been proposed in CSF and ECF for improved diagnosis or to control therapy, based on proteomics and mass spectrometry. I will also discuss the needs for a transition of research-based experimental screening with mass spectrometry to fast and reliable diagnostic instrumentation for clinical use.

Glycoproteomics in neurodegenerative diseases

Protein glycosylation regulates protein function and cellular distribution. Additionally, aberrant protein glycosylations have been recognized to play major roles in human disorders, including neurodegenerative diseases. Glycoproteomics, a branch of proteomics that catalogs and quantifies glycoproteins, provides a powerful means to systematically profile the glycopeptides or glycoproteins of a complex mixture that are highly enriched in body fluids, and therefore, carry great potential to be diagnostic and/or prognostic markers. Application of this mass spectrometry-based technology to the study of neurodegenerative disorders (e.g., Alzheimer's disease and Parkinson's disease) is relatively new, and is expected to provide insight into the biochemical pathogenesis of neurodegeneration, as well as biomarker discovery. In this review, we have summarized the current understanding of glycoproteins in biology and neurodegenerative disease, and have discussed existing proteomic technologies that are utilized to characterize glycoproteins. Some of the ongoing studies, where glycoproteins isolated from cerebrospinal fluid and human brain are being characterized in Parkinson's disease at different stages versus controls, are presented, along with future applications of targeted validation of brain specific glycoproteins in body fluids.

Elucidating novel mechanisms of brain injury following subarachnoid hemorrhage: an emerging role for neuroproteomics

Subarachnoid hemorrhage (SAH) is a devastating neurological injury associated with significant patient morbidity and death. Since the first demonstration of cerebral vasospasm nearly 60 years ago, the preponderance of research has focused on strategies to limit arterial narrowing and delayed cerebral ischemia following SAH. However, recent clinical and preclinical data indicate a functional dissociation between cerebral vasospasm and neurological outcome, signaling the need for a paradigm shift in the study of brain injury following SAH. Early brain injury may contribute to poor outcome and early death following SAH. However, elucidation of the complex cellular mechanisms underlying early brain injury remains a major challenge. The advent of modern neuroproteomics has rapidly advanced scientific discovery by allowing proteome-wide screening in an objective, nonbiased manner, providing novel mechanisms of brain physiology and injury. In the context of neurosurgery, proteomic analysis of patient-derived CSF will permit the identification of biomarkers and/or novel drug targets that may not be intuitively linked with any particular disease. In the present report, the authors discuss the utility of neuroproteomics with a focus on the roles for this technology in understanding SAH. The authors also provide data from our laboratory that identifies high-mobility group box protein-1 as a potential biomarker of neurological outcome following SAH in humans.

Proteomics in human Parkinson's disease research

During the last decades, considerable advances in the understanding of specific mechanisms underlying neurodegeneration in Parkinson's disease have been achieved, yet neither definite etiology nor unifying sequence of molecular events has been formally established. Current unmet needs in Parkinson's disease research include exploring new hypotheses regarding disease susceptibility, occurrence and progression, identifying reliable diagnostic, prognostic and therapeutic biomarkers, and translating basic research into appropriate disease-modifying strategies. The most popular view proposes that Parkinson's disease results from the complex interplay between genetic and environmental factors and mechanisms believed to be at work include oxidative stress, mitochondrial dysfunction, excitotoxicity, iron deposition and inflammation. More recently, a plethora of data has accumulated pinpointing an abnormal processing of the neuronal protein alpha-synuclein as a pivotal mechanism leading to aggregation, inclusions formation and degeneration. This protein-oriented scenario logically opens the door to the application of proteomic strategies to this field of research. We here review the current literature on proteomics applied to Parkinson's disease research, with particular emphasis on pathogenesis of sporadic Parkinson's disease in humans. We propose the view that Parkinson's disease may be an acquired or genetically-determined brain proteinopathy involving an abnormal processing of several, rather than individual neuronal proteins, and discuss some pre-analytical and analytical developments in proteomics that may help in verifying this concept.

Cerebrospinal fluid proteomics reveals potential pathogenic changes in the brains of SIV-infected monkeys

The HIV-1-associated neurocognitive disorder occurs in approximately one-third of infected individuals. It has persisted in the current era of antiretroviral therapy, and its study is complicated by the lack of biomarkers for this condition. Since the cerebrospinal fluid is the most proximal biofluid to the site of pathology, we studied the cerebrospinal fluid in a nonhuman primate model for HIV-1-associated neurocognitive disorder. Here we present a simple and efficient liquid chromatography-coupled mass spectrometry-based proteomics approach that utilizes small amounts of cerebrospinal fluid. First, we demonstrate the validity of the methodology using human cerebrospinal fluid. Next, using the simian immunodeficiency virus-infected monkey model, we show its efficacy in identifying proteins such as alpha-1-antitrypsin, complement C3, hemopexin, IgM heavy chain, and plasminogen, whose increased expression is linked to disease. Finally, we find that the increase in cerebrospinal fluid proteins is linked to increased expression of their genes in the brain parenchyma, revealing that the cerebrospinal fluid alterations identified reflect changes in the brain itself and not merely leakage of the blood-brain or blood-cerebrospinal fluid barriers. This study reveals new central nervous system alterations in lentivirus-induced neurological disease, and this technique can be applied to other systems in which limited amounts of biofluids can be obtained.

Identification of glycoproteins in human cerebrospinal fluid

Human cerebrospinal fluid (CSF), which circulates within the ventricles of the brain and the subarachnoid space of the central nervous system (CNS), is an excellent source for proteomic discovery of biomarkers in neurodegenerative disorders, including Alzheimer's and Parkinson's disease. Protein glycosylation is an abundant and biologically significant posttranslational modification. Glycoproteins, commonly associated with membrane and secreted proteins, are highly enriched in body fluids, including CSF. Focusing on glycoproteins also improves the dynamic range of proteomic profiling of the CSF, where low abundance proteins are difficult to identify because of the CSF's enormous complexity. As an ongoing process to define the human CSF proteome, we have recently employed a complementary proteomic approach, with integrated lectin affinity column and hydrazide chemistry, for CSF glycoprotein identification. This investigation has revealed many proteins of low abundance that are related to the CNS structurally and/or functionally. This review centers on the technical details involved in various steps in sample preparation as well as proteomic analysis of CSF glycoproteins.

Brain-specific proteins decline in the cerebrospinal fluid of humans with Huntington disease

We integrated five sets of proteomics data profiling the constituents of cerebrospinal fluid (CSF) derived from Huntington disease (HD)-affected and -unaffected individuals with genomics data profiling various human and mouse tissues, including the human HD brain. Based on an integrated analysis, we found that brain-specific proteins are 1.8 times more likely to be observed in CSF than in plasma, that brain-specific proteins tend to decrease in HD CSF compared with unaffected CSF, and that 81% of brain-specific proteins have quantitative changes concordant with transcriptional changes identified in different regions of HD brain. The proteins found to increase in HD CSF tend to be liver-associated. These protein changes are consistent with neurodegeneration, microgliosis, and astrocytosis known to occur in HD. We also discuss concordance between laboratories and find that ratios of individual proteins can vary greatly, but the overall trends with respect to brain or liver specificity were consistent. Concordance is highest between the two laboratories observing the largest numbers of proteins.

Biomarkers of Alzheimer's disease

Although a battery of neuropsychological tests is often used in making a clinical diagnosis of Alzheimer's disease (AD), definitive diagnosis still relies on pathological evaluation at autopsy. The identification of AD biomarkers may allow for a less invasive and more accurate diagnosis as well as serve as a predictor of future disease progression and treatment response. Importantly, biomarkers may also allow for the identification of individuals who are already developing the underlying pathology of AD such as plaques and tangles yet who are not yet demented, i.e. "preclinical" AD. Attempts to identify biomarkers have included fluid and imaging studies, with a number of candidate markers showing significant potential. More recently, better reagent availability and novel methods of assessment have further spurred the search for biomarkers of AD. This review will discuss promising fluid and imaging markers to date.

Biomarker discovery in neurodegenerative diseases: a proteomic approach

Biomarkers for neurodegenerative disorders are essential to facilitate disease diagnosis, ideally at early stages, monitor disease progression, and assess response to existing and future treatments. Application of proteomics to the human brain, cerebrospinal fluid and plasma has greatly hastened the unbiased and high-throughput searches for novel biomarkers. There are many steps critical to biomarker discovery, whether for neurodegenerative or other diseases, including sample preparation, protein/peptide separation and identification, as well as independent confirmation and validation. In this review we have summarized current proteomics technologies involved in discovery of biomarkers for neurodegenerative diseases, practical considerations and limitations of several major aspects, as well as the current status of candidate biomarkers revealed by proteomics for Alzheimer and Parkinson diseases.

Proteomic identification of proteins in the human brain: Towards a more comprehensive understanding of neurodegenerative disease

Proteomics has revealed itself as a powerful tool in the identification and determination of proteins and their biological significance. More recently, several groups have taken advantage of the high-throughput nature of proteomics in order to gain a more in-depth understanding of the human brain. In turn, this information has provided researchers with invaluable insight into the potential pathways and mechanisms involved in the pathogenesis of several neurodegenerative disorders, e.g., Alzheimer and Parkinson disease. Furthermore, these findings likely will improve methods to diagnose disease and monitor disease progression as well as generate novel targets for therapeutic intervention. Despite these advances, comprehensive understanding of the human brain proteome remains challenging, and requires development of improved sample enrichment, better instrumentation, and innovative analytic techniques. In this review, we will focus on the most recent progress related to identification of proteins in the human brain under normal as well as pathological conditions, mainly Alzheimer and Parkinson disease, their potential application in biomarker discovery, and discuss current advances in protein identification aimed at providing a more comprehensive understanding of the brain.

Analysis of the experimental detection of central nervous system-related genes in human brain and cerebrospinal fluid datasets

Large-scale and high-throughput proteomics experiments of specific samples provide substantial amounts of identified proteins and peptides, which increasingly find their way into centralized, public data repositories. These data typically have potential beyond the analyses performed by the original authors, and can therefore provide considerable added value by being reused for specific, unexplored enquiries. We here reanalyze two CNS-related proteomics datasets, one from the HUPO's Brain Proteome Project, and one from a comprehensive analysis of cerebrospinal fluid in light of the expression of specific splice isoforms from CNS-related genes. We also evaluate the empirically observed peptides of interest against predictions of their proteotypic character.

PRIDE: new developments and new datasets

The PRIDE (http://www.ebi.ac.uk/pride) database of protein and peptide identifications was previously described in the NAR Database Special Edition in 2006. Since this publication, the volume of public data in the PRIDE relational database has increased by more than an order of magnitude. Several significant public datasets have been added, including identifications and processed mass spectra generated by the HUPO Brain Proteome Project and the HUPO Liver Proteome Project. The PRIDE software development team has made several significant changes and additions to the user interface and tool set associated with PRIDE. The focus of these changes has been to facilitate the submission process and to improve the mechanisms by which PRIDE can be queried. The PRIDE team has developed a Microsoft Excel workbook that allows the required data to be collated in a series of relatively simple spreadsheets, with automatic generation of PRIDE XML at the end of the process. The ability to query PRIDE has been augmented by the addition of a BioMart interface allowing complex queries to be constructed. Collaboration with groups outside the EBI has been fruitful in extending PRIDE, including an approach to encode iTRAQ quantitative data in PRIDE XML.

Endogeneous peptide profiling of cerebrospinal fluid by MALDI-TOF mass spectrometry: Optimization of magnetic bead-based peptide capture and analysis of preanalytical variables

Cerebrospinal fluid (CSF) perfuses the brain and spinal cord. CSF contains peptides and proteins important for brain physiology and potentially also relevant to brain pathology. High-throughput endogeneous peptide profiling by MS is an emerging approach for disease diagnosis and biomarker discovery. A magnetic bead-based method for off-line serum peptide capture coupled to MALDI-TOF-MS has been introduced recently. In this study, we optimize the peptide capture method for profiling of CSF and investigate the effect of a number of preanalytical variables. The CSF profiles contain ∼100 reliably detected peptides at m/z 800-4000 with reproducible ion intensities (average 7% CV). The investigated preanalytical variables include: time at room temperature (RT) before storage, storage temperature, freeze-thawing cycles, and blood contamination. The CSF peptidome (<20 kDa) is relatively stable and can withstand a few hours at RT and several freeze-thaw cycles. Several peptides sensitive to storage at -20°C, including Cystatin C, were assigned based on mass or identified by MS/MS. Hemoglobin α and β chains were detected in blood contaminated samples, at levels invisible to the eye (0.01%). These peptides may be used for quality control in a MALDI-TOF-MS screening strategy to select high quality samples for in-depth proteomics analysis in disease studies.

Clinical proteomics in neurodegenerative diseases

Investigation of the human specimens is an essential element for understanding the pathogenesis of neurodegenerative disorders, such as Alzheimer's disease, Parkinson's disease, and multiple sclerosis. The studies hold promise for identifying biomarkers for diagnosis and prognosis, elucidating disease mechanisms, and accelerating the development of new strategies for therapeutic intervention. Here, we review proteomics studies of human brain samples in light of recent advances of mass spectrometry, focusing on the general strategies for experimental design and analysis (e.g., sample pooling and replication, selection of proteomics platforms, and false discovery rate in data processing), because quantitative analysis of clinical samples is confounded by a number of variables, including genetic differences, antemortem and postmortem factors, and experimental errors. Diverse proteomics platforms are also discussed with respect to sensitivity, throughput, and accuracy. Regarding the enormous complexity of the human brain and the limitation of current proteomics technologies, it may be more practical to analyze a subset of proteome in a functional context, in order to facilitate the identification of important disease-related proteins in the substantial noise reflecting biological and technical variances.

Proteomics Identification of Proteins in Human Cortex Using Multidimensional Separations and MALDI Tandem Mass Spectrometer

It is essential to characterize the proteome of various regions of human brain because most, if not all, neurodegenerative diseases are region-specific. Here we report an in-depth proteomics identification of proteins extracted from the frontal cortex, a region playing a critical role in cognitive function. The integrated proteomics analytical flow consisted of biochemical fractionation, strong cation exchange chromatography, reverse phase liquid chromatography, and MALDI-TOF/TOF mass spectrometric analysis. In total, 812 proteins were confidently identified with two or more peptides. These proteins demonstrated diverse isoelectric points and molecular weights and are involved in several molecular functions, including protein binding, catalytic activity, transport, structure, and signal transduction. A number of proteins known to be associated with neurodegenerative diseases were also identified. Detailed characterization of these proteins will supply the necessary information to appropriately interpret proteins associated with aging and/or age-related neurodegenerative diseases. Finally 140 proteins found in the cortical proteome were present in the proteome of cerebrospinal fluid, providing tissue-specific candidates for biomarker discovery in body fluid.

Proteomics of human cerebrospinal fluid - the good, the bad, and the ugly

The development of MALDI ESI in the late 1980s has revolutionized the biological sciences and facilitated the emergence of a new discipline called proteomics. Application of proteomics to human cerebrospinal fluid (CSF) has greatly hastened the advancement of characterizing the CSF proteome as well as revealing novel protein biomarkers that are diagnostic of various neurological diseases. While impressive progressions have been made in this field, it has become increasingly clear that proteomics results generated by various laboratories are highly variable. The underlying issues are vast, including limitations and complications with heterogeneity of patients/testing subjects, experimental design, sample processing, as well as current proteomics technology. Accordingly, this review not only summarizes the current status of characterization of the human CSF proteome and biomarker discovery for major neurodegenerative disorders, i.e., Alzheimer's disease and Parkinson's disease, but also addresses a few essential caveats involved in several steps of CSF proteomics that may contribute to the variable/contradicting results reported by different laboratories. The potential future directions of CSF proteomics are also discussed with this analysis.