Proteomic analysis of Alzheimer's disease cerebrospinal fluid from neuropathologically diagnosed subjects

Endosomal-Lysosomal and Autophagy Pathway in Alzheimer's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

The endosomal-lysosomal and autophagy (ELA) pathway may be implicated in the progression of Alzheimer's disease (AD); however, findings thus far have been inconsistent.

OBJECTIVE

To systematically summarize differences in endosomal-lysosomal and autophagy proteins in the cerebrospinal fluid (CSF) of people with AD and healthy controls (HC).

METHODS

Studies measuring CSF concentrations of relevant proteins in the ELA pathway in AD and healthy controls were included. Standardized mean differences (SMD) with 95% confidence intervals (CI) between AD and healthy controls in CSF concentrations of relevant proteins were meta-analyzed using random-effects models.

RESULTS

Of 2,471 unique studies, 43 studies were included in the systematic review and meta-analysis. Differences in ELA protein levels in the CSF between AD and healthy controls were observed, particularly in lysosomal membrane (LAMP-1: NAD/NHC = 348/381, SMD [95% CI] = 0.599 [0.268, 0.930], I2 = 72.8% ; LAMP-2: NAD/NHC = 401/510, SMD [95% CI] = 0.480 [0.134, 0.826], I2 = 78.7%) and intra-lysosomal proteins (GM2A: NAD/NHC = 390/420, SMD [95% CI] = 0.496 [0.039, 0.954], I2 = 87.7% ; CTSB: NAD/NHC = 485/443, SMD [95% CI] = 0.201 [0.029, 0.374], I2 = 28.5% ; CTSZ: NAD/NHC = 535/820, SMD [95% CI] = -0.160 [-0.305, -0.015], I2 = 24.0%) and in proteins involved in endocytosis (AP2B1:NAD/NHC = 171/205, SMD [95% CI] = 0.513 [0.259, 0.768], I2 = 27.4% ; FLOT1: NAD/NHC = 41/45, SMD [95% CI] = -0.489 [-0.919, -0.058], I2 <0.01). LC3B, an autophagy marker, also showed a difference (NAD/NHC = 70/59, SMD [95% CI] = 0.648 [0.180, 1.116], I2 = 38.3%)), but overall there was limited evidence suggesting differences in proteins involved in endosomal function and autophagy.

CONCLUSION

Dysregulation of proteins in the ELA pathway may play an important role in AD pathogenesis. Some proteins within this pathway may be potential biomarkers for AD.

Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics

Alzheimer's disease is biologically heterogeneous, and detailed understanding of the processes involved in patients is critical for development of treatments. CSF contains hundreds of proteins, with concentrations reflecting ongoing (patho)physiological processes. This provides the opportunity to study many biological processes at the same time in patients. We studied whether Alzheimer's disease biological subtypes can be detected in CSF proteomics using the dual clustering technique non-negative matrix factorization. In two independent cohorts (EMIF-AD MBD and ADNI) we found that 705 (77% of 911 tested) proteins differed between Alzheimer's disease (defined as having abnormal amyloid, n = 425) and controls (defined as having normal CSF amyloid and tau and normal cognition, n = 127). Using these proteins for data-driven clustering, we identified three robust pathophysiological Alzheimer's disease subtypes within each cohort showing (i) hyperplasticity and increased BACE1 levels; (ii) innate immune activation; and (iii) blood-brain barrier dysfunction with low BACE1 levels. In both cohorts, the majority of individuals were labelled as having subtype 1 (80, 36% in EMIF-AD MBD; 117, 59% in ADNI), 71 (32%) in EMIF-AD MBD and 41 (21%) in ADNI were labelled as subtype 2, and 72 (32%) in EMIF-AD MBD and 39 (20%) individuals in ADNI were labelled as subtype 3. Genetic analyses showed that all subtypes had an excess of genetic risk for Alzheimer's disease (all P > 0.01). Additional pathological comparisons that were available for a subset in ADNI suggested that subtypes showed similar severity of Alzheimer's disease pathology, and did not differ in the frequencies of co-pathologies, providing further support that found subtypes truly reflect Alzheimer's disease heterogeneity. Compared to controls, all non-demented Alzheimer's disease individuals had increased risk of showing clinical progression (all P < 0.01). Compared to subtype 1, subtype 2 showed faster clinical progression after correcting for age, sex, level of education and tau levels (hazard ratio = 2.5; 95% confidence interval = 1.2, 5.1; P = 0.01), and subtype 3 at trend level (hazard ratio = 2.1; 95% confidence interval = 1.0, 4.4; P = 0.06). Together, these results demonstrate the value of CSF proteomics in studying the biological heterogeneity in Alzheimer's disease patients, and suggest that subtypes may require tailored therapy.

A comprehensive systematic review of CSF proteins and peptides that define Alzheimer's disease

BACKGROUND

During the last two decades, over 100 proteomics studies have identified a variety of potential biomarkers in CSF of Alzheimer's (AD) patients. Although several reviews have proposed specific biomarkers, to date, the statistical relevance of these proteins has not been investigated and no peptidomic analyses have been generated on the basis of specific up- or down- regulation. Herein, we perform an analysis of all unbiased explorative proteomics studies of CSF biomarkers in AD to critically evaluate whether proteins and peptides identified in each study are consistent in distribution; direction change; and significance, which would strengthen their potential use in studies of AD pathology and progression.

METHODS

We generated a database containing all CSF proteins whose levels are known to be significantly altered in human AD from 47 independent, validated, proteomics studies. Using this database, which contains 2022 AD and 2562 control human samples, we examined whether each protein is consistently present on the basis of reliable statistical studies; and if so, whether it is over- or under-represented in AD. Additionally, we performed a direct analysis of available mass spectrometric data of these proteins to generate an AD CSF peptide database with 3221 peptides for further analysis.

RESULTS

Of the 162 proteins that were identified in 2 or more studies, we investigated their enrichment or depletion in AD CSF. This allowed us to identify 23 proteins which were increased and 50 proteins which were decreased in AD, some of which have never been revealed as consistent AD biomarkers (i.e. SPRC or MUC18). Regarding the analysis of the tryptic peptide database, we identified 87 peptides corresponding to 13 proteins as the most highly consistently altered peptides in AD. Analysis of tryptic peptide fingerprinting revealed specific peptides encoded by CH3L1, VGF, SCG2, PCSK1N, FBLN3 and APOC2 with the highest probability of detection in AD.

CONCLUSIONS

Our study reveals a panel of 27 proteins and 21 peptides highly altered in AD with consistent statistical significance; this panel constitutes a potent tool for the classification and diagnosis of AD.

A multivariate predictive modeling approach reveals a novel CSF peptide signature for both Alzheimer's Disease state classification and for predicting future disease progression

To determine if a multi-analyte cerebrospinal fluid (CSF) peptide signature can be used to differentiate Alzheimer’s Disease (AD) and normal aged controls (NL), and to determine if this signature can also predict progression from mild cognitive impairment (MCI) to AD, analysis of CSF samples was done on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. The profiles of 320 peptides from baseline CSF samples of 287 subjects over a 3–6 year period were analyzed. As expected, the peptide most able to differentiate between AD vs. NL was found to be Apolipoprotein E. Other peptides, some of which are not classically associated with AD, such as heart fatty acid binding protein, and the neuronal pentraxin receptor, also differentiated disease states. A sixteen-analyte signature was identified which differentiated AD vs. NL with an area under the receiver operating characteristic curve of 0.89, which was better than any combination of amyloid beta (1–42), tau, and phospho-181 tau. This same signature, when applied to a new and independent data set, also strongly predicted both probability and rate of future progression of MCI subjects to AD, better than traditional markers. These data suggest that multivariate peptide signatures from CSF predict MCI to AD progression, and point to potentially new roles for certain proteins not typically associated with AD.

Proteomics and metabolomics in ageing research: from biomarkers to systems biology

Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible 'biomarkers', which are predictors of one's biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying 'endophenotypes' in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.

Insights into the human brain proteome: Disclosing the biological meaning of protein networks in cerebrospinal fluid

Cerebrospinal fluid (CSF) is an excellent source of biological information regarding the nervous system, once it is in close contact and accurately reflects alterations in this system. Several studies have analyzed differential protein profiles of CSF samples between healthy and diseased human subjects. However, the pathophysiological mechanisms and how CSF proteins relate to diseases are still poorly known. By applying bioinformatics tools, we attempted to provide new insights on the biological and functional meaning of proteomics data envisioning the identification of putative disease biomarkers. Bioinformatics analysis of data retrieved from 99 mass spectrometry (MS)-based studies on CSF profiling highlighted 1985 differentially expressed proteins across 49 diseases. A large percentage of the modulated proteins originate from exosome vesicles, and the majority are involved in either neuronal cell growth, development, maturation, migration, or neurotransmitter-mediated cellular communication. Nevertheless, some diseases present a unique CSF proteome profile, which were critically analyzed in the present study. For instance, 48 proteins were found exclusively upregulated in the CSF of patients with Alzheimer's disease and are mainly involved in steroid esterification and protein activation cascade processes. A higher number of exclusively upregulated proteins were found in the CSF of patients with multiple sclerosis (76 proteins) and with bacterial meningitis (70 proteins). Whereas in multiple sclerosis, these proteins are mostly involved in the regulation of RNA metabolism and apoptosis, in bacterial meningitis the exclusively upregulated proteins participate in inflammation and antibacterial humoral response, reflecting disease pathogenesis. The exploration of the contribution of exclusively upregulated proteins to disease pathogenesis will certainly help to envision potential biomarkers in the CSF for the clinical management of nervous system diseases.

The aqueous phase of Alzheimer's disease brain contains assemblies built from ∼4 and ∼7 kDa Aβ species

INTRODUCTION

Much knowledge about amyloid β (Aβ) aggregation and toxicity has been acquired using synthetic peptides and mouse models, whereas less is known about soluble Aβ in human brain.

METHODS

We analyzed aqueous extracts from multiple AD brains using an array of techniques.

RESULTS

Brains can contain at least four different Aβ assembly forms including: (i) monomers, (ii) a ∼7 kDa Aβ species, and larger species (iii) from ∼30-150 kDa, and (iv) >160 kDa. High molecular weight species are by far the most prevalent and appear to be built from ∼7 kDa Aβ species. The ∼7 kDa Aβ species resist denaturation by chaotropic agents and have a higher Aβ42/Aβ40 ratio than monomers, and are unreactive with antibodies to Asp1 of Ab or APP residues N-terminal of Asp1.

DISCUSSION

Further analysis of brain-derived ∼7 kDa Aβ species, the mechanism by which they assemble and the structures they form should reveal therapeutic and diagnostic opportunities.

Arizona Study of Aging and Neurodegenerative Disorders and Brain and Body Donation Program

The Brain and Body Donation Program (BBDP) at Banner Sun Health Research Institute (http://www.brainandbodydonationprogram.org) started in 1987 with brain-only donations and currently has banked more than 1600 brains. More than 430 whole-body donations have been received since this service was commenced in 2005. The collective academic output of the BBDP is now described as the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND). Most BBDP subjects are enrolled as cognitively normal volunteers residing in the retirement communities of metropolitan Phoenix, Arizona. Specific recruitment efforts are also directed at subjects with Alzheimer's disease, Parkinson's disease and cancer. The median age at death is 82. Subjects receive standardized general medical, neurological, neuropsychological and movement disorders assessments during life and more than 90% receive full pathological examinations by medically licensed pathologists after death. The Program has been funded through a combination of internal, federal and state of Arizona grants as well as user fees and pharmaceutical industry collaborations. Subsets of the Program are utilized by the US National Institute on Aging Arizona Alzheimer's Disease Core Center and the US National Institute of Neurological Disorders and Stroke National Brain and Tissue Resource for Parkinson's Disease and Related Disorders. Substantial funding has also been received from the Michael J. Fox Foundation for Parkinson's Research. The Program has made rapid autopsy a priority, with a 3.0-hour median post-mortem interval for the entire collection. The median RNA Integrity Number (RIN) for frozen brain and body tissue is 8.9 and 7.4, respectively. More than 2500 tissue requests have been served and currently about 200 are served annually. These requests have been made by more than 400 investigators located in 32 US states and 15 countries. Tissue from the BBDP has contributed to more than 350 publications and more than 200 grant-funded projects.

Recent advances in quantitative neuroproteomics

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders.

Cerebrospinal fluid biomarkers of neuropathologically diagnosed Parkinson's disease subjects

OBJECTIVES

Parkinson's disease (PD) afflicts approximately 1-2% of the population over 50 years of age. No cures or effective modifying treatments exist and clinical diagnosis is currently confounded by a lack of definitive biomarkers. We sought to discover potential biomarkers in the cerebrospinal fluid (CSF) of neuropathologically confirmed PD cases.

METHODS

We compared postmortem ventricular CSF (V-CSF) from PD and normal control (NC) subjects using two-dimensional difference gel electrophoresis (2D-DIGE). Spots exhibiting a 1·5-fold or greater difference in volume between PD patients and controls were excised from the two-dimensional gels, subjected to tryptic digestion and identification of peptides assigned using mass spectrometric/data bank correlation methods.

RESULTS

Employing this strategy six molecules: fibrinogen, transthyretin, apolipoprotein E, clusterin, apolipoprotein A-1, and glutathione-S-transferase-Pi, were found to be different between PD and NC populations.

DISCUSSION

These molecules have been implicated in PD pathogenesis. Combining biomarker data from multiple laboratories may create a consensus panel of proteins that may serve as a diagnostic tool for this neurodegenerative disorder.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research.

Preparation of human cerebrospinal fluid for proteomics biomarker analysis

The analysis of the cerebrospinal fluid (CSF) proteome in recent years has resulted in a valuable repository of data for targeting and diagnosing a variety of diseases, such as Parkinson's disease, Alzheimer's disease, traumatic brain injury, and amyotrophic lateral sclerosis. Human ventricular CSF contains numerous proteins that are unique to CSF due in part to the interaction of the biofluid with the brain. This allows researchers to obtain information from a region that would otherwise be inaccessible except through invasive surgery or during autopsy. Characterization of the CSF proteome requires that strict care be taken so that sample integrity and fidelity are maintained to ensure data reproducibility. Standardized methods in sample collection, storage, preparation, analysis, and data mining must be used for meaningful information to be obtained. The following method describes a simple and robust approach for preparing CSF samples for analysis via reversed-phase liquid chromatography (RPLC) and mass spectrometry (MS).

Cerebrospinal fluid proteome of patients with acute Lyme disease

During acute Lyme disease, bacteria can disseminate to the central nervous system (CNS), leading to the development of meningitis and other neurologic symptoms. Here we have analyzed pooled cerebrospinal fluid (CSF) allowing a deep view into the proteome for patients diagnosed with early disseminated Lyme disease and CSF inflammation. Additionally, we analyzed individual patient samples and quantified differences in protein abundance employing label-free quantitative mass spectrometry-based methods. We identified 108 proteins that differ significantly in abundance in patients with acute Lyme disease from controls. Comparison between infected patients and control subjects revealed differences in proteins in the CSF associated with cell death localized to brain synapses and others that likely originate from brain parenchyma.

The cerebrospinal fluid proteome in HIV infection: change associated with disease severity

BACKGROUND

Central nervous system (CNS) infection is a nearly universal feature of untreated systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment.

RESULTS

After establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91 CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral therapy and correlated abundances of identified proteins a) within and between subjects, b) with all other proteins across the entire sample set, and c) with "external" CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) ≤ -0.3 and ≥0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with amyloid precursor protein as a central node.

CONCLUSIONS

Advanced CSF proteomic analysis enabled the identification of an array of novel protein changes across the spectrum of CNS HIV infection and disease. This initial analysis clearly demonstrated the value of contemporary state-of-the-art proteomic CSF analysis as a discovery tool in HIV infection with likely similar application to other neurological inflammatory and degenerative diseases.

Alzheimer's disease and non-demented high pathology control nonagenarians: comparing and contrasting the biochemistry of cognitively successful aging

The amyloid cascade hypothesis provides an economical mechanistic explanation for Alzheimer's disease (AD) dementia and correlated neuropathology. However, some nonagenarian individuals (high pathology controls, HPC) remain cognitively intact while enduring high amyloid plaque loads for decades. If amyloid accumulation is the prime instigator of neurotoxicity and dementia, specific protective mechanisms must enable these HPC to evade cognitive decline. We evaluated the neuropathological and biochemical differences existing between non-demented (ND)-HPC and an age-matched cohort with AD dementia. The ND-HPC selected for our study were clinically assessed as ND and possessed high amyloid plaque burdens. ELISA and Western blot analyses were used to quantify a group of proteins related to APP/Aβ/tau metabolism and other neurotrophic and inflammation-related molecules that have been found to be altered in neurodegenerative disorders and are pivotal to brain homeostasis and mental health. The molecules assumed to be critical in AD dementia, such as soluble or insoluble Aβ40, Aβ42 and tau were quantified by ELISA. Interestingly, only Aβ42 demonstrated a significant increase in ND-HPC when compared to the AD group. The vascular amyloid load which was not used in the selection of cases, was on the average almost 2-fold greater in AD than the ND-HPC, suggesting that a higher degree of microvascular dysfunction and perfusion compromise was present in the demented cohort. Neurofibrillary tangles were less frequent in the frontal cortices of ND-HPC. Biochemical findings included elevated vascular endothelial growth factor, apolipoprotein E and the neuroprotective factor S100B in ND-HPC, while anti-angiogenic pigment epithelium derived factor levels were lower. The lack of clear Aβ-related pathological/biochemical demarcation between AD and ND-HPC suggests that in addition to amyloid plaques other factors, such as neurofibrillary tangle density and vascular integrity, must play important roles in cognitive failure.

Proteomic study of the toxic effect of oligomeric Aβ1-42 in situ prepared from 'iso-Aβ1-42'

Alzheimer's disease (AD) is the most prevalent form of neurodegenerative disorders even so the exact pathomechanism is still unclear. Recently, it is widely accepted that amyloid-beta peptide (Aβ) toxicity is positively linked to Aβ oligomers, which may be responsible for the initiation of AD. For this reason, AD research requires well defined aggregation state and structure of Aβ. Precursor peptide 'iso-Aβ1-42' makes it possible to use Aβ1-42 with well- defined aggregation state for in vitro and in vivo experiments. The aim of this study was to identify protein expression changes from differentiated SH-SY5Y neuroblastoma cells after treatment with oligomeric Aβ1-42 prepared in situ from 'iso-Aβ1-42'. In our experiment, a cell viability assay revealed a strong and time-dependent toxic effect of oligomeric Aβ1-42 which was supported by dramatic morphological changes. Our proteomics study also revealed numerous significant protein expression changes (22 proteins down- and 25 proteins up-regulated) after comparison of the untreated and Aβ1-42-treated cell lysates by two-dimensional electrophoresis. From the functional classification of the identified proteins, we found deregulations of proteins involved in metabolic processes, cytoskeleton organisation and protein biosynthesis and a huge number of up-regulated stress proteins displayed oligomeric Aβ1-42-induced cell stress.

Developing predictive CSF biomarkers-a challenge critical to success in Alzheimer's disease and neuropsychiatric translational medicine

The need to develop effective treatments for Alzheimer's disease has been confounded by repeated clinical failures where promising new chemical entities that have been extensively characterized in preclinical models of Alzheimer's disease have failed to show efficacy in the human disease state. This has been attributed to: the selection of drug targets that have yet to be shown as causal to the disease as distinct from being the result of the disease process, a lack of congruence in the animal models of Alzheimer's disease, wild-type and transgenic, to the human disease, and the enrollment of patients in proof of concept clinical trials who are at too advanced a stage of the disease to respond to any therapeutic. The development of validated biomarkers that can be used for disease diagnosis and progression is anticipated to improve patient enrollment in clinical trials, to develop new animal models and to identify new disease targets for drug discovery. The present review assesses the status of current efforts in developing CSF biomarkers for Alzheimer's disease and briefly discusses the status of CSF biomarker efforts in schizophrenia, depression, Parkinson's disease and multiple sclerosis.