Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis.

Background: Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to serve as potential biomarkers. Our work will contribute to the in-depth study of the functions of extracellular proteins and the discovery of disease biomarkers. Methods: MS expression profiling data of the human brain was downloaded from the Gene Expression Omnibus (GEO). Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases. GO and KEGG were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the CSF of MS patients. ROC curve and survival analysis were used to evaluate the diagnostic and prognostic ability of key EP-DEGs. Results: We screened 133 EP-DEGs from DEGs. EP-DEGs were enriched in the collagen-containing extracellular matrix, signaling receptor activator activity, immune-related pathways, and PI3K-Akt signaling pathway. The PPI network of EP-DEGs had 85 nodes and 185 edges. We identified 4 key extracellular proteins IL17A, IL2, CD44, IGF1, and 16 extracellular proteins that interacted with IL17A. We clinically verified that IL17A levels decreased, but Del-1 and resolvinD1 levels increased. The diagnostic accuracy of Del-1 (AUC: 0.947) was superior to that of IgG (AUC: 0.740) with a sensitivity of 82.4% and a specificity of 100%. High Del-1 levels were significantly associated with better relapse-free and progression-free survival. Conclusion: IL17A, IL2, CD44, and IGF1 may be key extracellular proteins in the pathogenesis of MS. IL17A, Del-1, and resolvinD1 may co-regulate the development of MS and Del-1 is a potential biomarker of MS. We used bioinformatics methods to explore the biomarkers of MS and validated the results in clinical samples. The study provides a theoretical and experimental basis for revealing the pathogenesis of MS and improving the diagnosis and prognosis of MS.

Peripheral Blood Biomarkers CXCL12 and TNFRSF13C Associate with Cerebrospinal Fluid Biomarkers and Infiltrating Immune Cells in Alzheimer Disease.

Neuroinflammation-induced neurodegeneration and immune cell infiltration are two features of Alzheimer disease (AD). This study aimed to identify potential peripheral biomarkers that interact with cerebrospinal fluid (CSF) and infiltrating immune cells in AD. Blood and CSF data were downloaded from the Alzheimer's disease Neuroimaging Initiative database. We identified differentially expressed genes (DEGs) in AD and assessed infiltrating immune cells using the Immune Cell Abundance Identifier (ImmuCellAI) algorithm. Blood-brain barrier (BBB) and immune-related genes were identified from medical databases, and common genes were used to construct a protein-protein interaction network (PPI). Potential biomarkers reflecting the clinical features of AD were screened using Pearson correlations and logistic regression analysis. We identified 210 DEGs in the AD group. ImmuCellAI indicated that blood samples from patients with AD had a higher abundance of exhausted T (Tex; 0.196 vs. 0.132) and induced regulatory T (iTreg; 0.180 vs. 0.137) cells than controls. Thirty-two genes overlapped between the BBB and immune-related genes, and 27 genes in the PPI network were associated with eight pathways, including the cytokine-cytokine receptor interaction pathway (hsa04060) and the chemokine signaling pathway (hsa04062). Pearson correlations showed that five genes were associated with the CSF biomarkers, Aß, total, and phosphorylated tau. Logistics analysis showed that the B cell-associated genes, CXCL12 and TNFRSF13C, were independent risk factors for AD diagnosis. Peripheral CXCL12 and TNFRSF13C genes that correlated with immune cell infiltration in AD might serve as easily accessible biomarkers for the early diagnosis of AD.

Altered levels of CSF proteins in patients with FTD, presymptomatic mutation carriers and non-carriers.

BACKGROUND: The clinical presentations of frontotemporal dementia (FTD) are diverse and overlap with other neurological disorders. There are, as of today, no biomarkers in clinical practice for diagnosing the disorders. Here, we aimed to find protein markers in cerebrospinal fluid (CSF) from patients with FTD, presymptomatic mutation carriers and non-carriers. METHODS: Antibody suspension bead arrays were used to analyse 328 proteins in CSF from patients with behavioural variant FTD (bvFTD, n = 16) and progressive primary aphasia (PPA, n = 13), as well as presymptomatic mutation carriers (PMC, n = 16) and non-carriers (NC, n = 8). A total of 492 antibodies were used to measure protein levels by direct labelling of the CSF samples. The findings were further examined in an independent cohort including 13 FTD patients, 79 patients with Alzheimer's disease and 18 healthy controls. RESULTS: We found significantly altered protein levels in CSF from FTD patients compared to unaffected individuals (PMC and NC) for 26 proteins. The analysis show patterns of separation between unaffected individuals and FTD patients, especially for those with a clinical diagnosis of bvFTD. The most statistically significant differences in protein levels were found for VGF, TN-R, NPTXR, TMEM132D, PDYN and NF-M. Patients with FTD were found to have higher levels of TN-R and NF-M, and lower levels of VGF, NPTXR, TMEM132D and PDYN, compared to unaffected individuals. The main findings were reproduced in the independent cohort. CONCLUSION: In this pilot study, we show a separation of FTD patients from unaffected individuals based on protein levels in CSF. Further investigation is required to explore the CSF profiles in larger cohorts, but the results presented here has the potential to enable future clinical utilization of these potential biomarkers within FTD.

Bioinformatics to Tackle the Biological Meaning of Human Cerebrospinal Fluid Proteome.

Cerebrospinal fluid (CSF) is a source of valuable information concerning brain disorders. The technical advances of high-throughput omics platforms to analyze body fluids can generate a huge amount of data, whose translation to biological meaning is a challenge. Several bioinformatic tools have emerged to help handling this data into systems biology comprehensively. Herein, we describe a step-by-step tutorial for CSF proteome data analysis in the set of neurodegenerative diseases using (1) ClueGO+CluePedia tool to perform cluster-based analysis envisioning the characterization of the biological processes dysregulated in neurodegenerative diseases including Alzheimer's and Parkinson's diseases; (2) Cytoscape to map disease-specific proteins; (3) SecretomeP to inquire the secretion pathway of CSF proteins; and (4) STRING to identify biological processes modulated by secreted CSF proteins based on protein-protein interaction analysis. This step-by-step guide might help researchers to better characterize disease pathogenesis and to identify putative disease biomarkers.

Plasmatic Signature of Disease by Differential Scanning Calorimetry (DSC).

Differential scanning calorimetry (DSC) has been used for several decades to characterize thermal stability of macromolecules such as proteins and DNA. It allows to determine the denaturation temperature and enthalpy of individual domains of proteins, thus giving new insights into their domain organization and ligand interaction. Over the past decade, it has been shown that this technique can also be used to study biofluids such as plasma or cerebrospinal fluid to obtain denaturation profiles. An increasing number of studies demonstrated that such profiles obtained from patients were significantly different from profiles obtained using biofluids of healthy individuals. This opens interesting perspectives for new diagnostics and monitoring tools for a large number of diseases. Nevertheless, the extensive studies of plasma samples from patients with different pathologies as well as the development of standardized methods of data analysis are necessary to reach the promising diagnostic potential of this methodology. Using plasma samples from healthy individuals and glioblastoma patients, we outline the steps necessary to obtain a plasmatic calorimetric profile with VP-DSC instrument and describe a cluster analysis of obtained data.

Proteomes of Paired Human Cerebrospinal Fluid and Plasma: Relation to Blood-Brain Barrier Permeability in Older Adults.

The systems-level relationship between the proteomes of cerebrospinal fluid (CSF) and plasma has not been comprehensively described so far. Recently developed shotgun proteomic workflows allow for deeper characterization of the proteomes from body fluids in much larger sample size. We deployed state-of-the-art mass spectrometry-based proteomics in paired CSF and plasma samples volunteered by 120 elders with and without cognitive impairment to comprehensively characterize and examine compartmental proteome differences and relationships between both body fluids. We further assessed the influence of blood-brain barrier (BBB) integrity and tested the hypothesis that BBB breakdown can be identified from CSF and plasma proteome alterations in nondemented elders. We quantified 790 proteins in CSF and 422 proteins in plasma, and 255 of the proteins were identified in both compartments. Pearson's statistics determined 28 proteins with associated levels between CSF and plasma. BBB integrity as defined with the CSF/serum albumin index influenced 76 CSF/plasma protein ratios. In least absolute shrinkage and selection operator models, CSF and plasma proteins improved identification of BBB impairment. In conclusion, we provide here a first comprehensive draft map of interacting human CSF and plasma proteomes, in view of their complex and dynamic compositions, and influence of the BBB.

Orthologous proteins of experimental de- and remyelination are differentially regulated in the CSF proteome of multiple sclerosis subtypes.

OBJECTIVE: Here, we applied a multi-omics approach (i) to examine molecular pathways related to de- and remyelination in multiple sclerosis (MS) lesions; and (ii) to translate these findings to the CSF proteome in order to identify molecules that are differentially expressed among MS subtypes. METHODS: To relate differentially expressed genes in MS lesions to de- and remyelination, we compared transcriptome of MS lesions to transcriptome of cuprizone (CPZ)-induced de- and remyelination. Protein products of the overlapping orthologous genes were measured within the CSF by quantitative proteomics, parallel reaction monitoring (PRM). Differentially regulated proteins were correlated with molecular markers of inflammation by using MesoScale multiplex immunoassay. Expression kinetics of differentially regulated orthologous genes and proteins were examined in the CPZ model. RESULTS: In the demyelinated and remyelinated corpus callosum, we detected 1239 differentially expressed genes; 91 orthologues were also differentially expressed in MS lesions. Pathway analysis of these orthologues suggested that the TYROBP (DAP12)-TREM2 pathway, TNF-receptor 1, CYBA and the proteasome subunit PSMB9 were related to de- and remyelination. We designed 129 peptides representing 51 orthologous proteins, measured them by PRM in 97 individual CSF, and compared their levels between relapsing (n = 40) and progressive MS (n = 57). Four proteins were differentially regulated among relapsing and progressive MS: tyrosine protein kinase receptor UFO (UFO), TIMP-1, apolipoprotein C-II (APOC2), and beta-2-microglobulin (B2M). The orthologous genes/proteins in the mouse brain peaked during acute remyelination. UFO, TIMP-1 and B2M levels correlated inversely with inflammation in the CSF (IL-6, MCP-1/CCL2, TARC/CCL17). APOC2 showed positive correlation with IL-2, IL-16 and eotaxin-3/CCL26. CONCLUSIONS: Pathology-based multi-omics identified four CSF markers that were differentially expressed in MS subtypes. Upregulated TIMP-1, UFO and B2M orthologues in relapsing MS were associated with reduced inflammation and reflected reparatory processes, in contrast to the upregulated orthologue APOC2 in progressive MS that reflected changes in lipid metabolism associated with increased inflammation.

Minimal disseminated disease evaluation and outcome in trilateral retinoblastoma.

Trilateral retinoblastoma (TRb) presents a management challenge, since intracranial tumours are seldom times resectable and quickly disseminate. However, there are no risk factors to predict the final outcome in each patient. OBJECTIVE: To evaluate minimal disseminated disease (MDD) in the bone marrow (BM) and the cerebrospinal fluid (CSF) at diagnosis and during follow-up and reviewing its potential impact in the outcome of patients with TRb. METHODS AND ANALYSIS: We evaluated MDD in five patients with TRb, detecting the mRNA of CRX and/or GD2, in samples from BM and CSF, obtained at diagnosis, follow-up and relapse. RESULTS: Treatment involved intensive systemic chemotherapy in four patients, one did not receive this treatment and died of progression of the disease. Two patients underwent stem cell rescue. Three patients had leptomeningeal relapse and died. One patient remains disease-free for 84 months. RB1 mutations were identified in the five patients, all of them were null mutations. At diagnosis, one patient had tumour cells in the CSF, and none had the BM involved. Only one case of four presented MDD during follow-up in the CSF, without concomitant detection in the BM. On leptomeningeal relapse, no case had MDD in the BM. In all these cases, cells in the CSF were positive for GD2 and/or CRX. CONCLUSION: CSF dissemination always concluded in the death of the patient, without concomitant systemic dissemination denoting the importance of increasing treatment directed to the CSF compartment. The MDD presence could indicate a forthcoming relapse.

Proteomic studies in the discovery of cerebrospinal fluid biomarkers for amyotrophic lateral sclerosis.

INTRODUCTION: Amyotrophic lateral sclerosis (ALS) is a progressive degenerative motor neuron disease, which usually leads to death within a few years. The diagnosis is mainly based on clinical symptoms and there is a need for ALS-specific biomarkers to make an early and precise diagnosis, for development of disease-modifying drugs and to gain new insights into pathophysiology. Areas covered: In the present review, we summarize studies using mass spectrometric (MS) approaches to identify protein alterations in the cerebrospinal fluid (CSF) of ALS patients. In total, we identified 11 studies fulfilling our criteria by searching in the PubMed database using the keywords 'ALS' and 'CSF' combined with 'proteome', 'proteomic', 'mass spectrometry' or 'protein biomarker'. Ten proteins were differently regulated in ALS CSF compared to controls in at least 2 studies. We will discuss the relevance of the identified proteins regarding the frequency of identification, extent of alteration and brain-specificity. Expert commentary: Most of the identified CSF biomarker candidates are irreproducible or mainly blood-derived. We assign the missing success of CSF proteomic studies in biomarker discovery to a lack of sensitivity, unsuitable normalization, low quality assurance and variations originating from sample preparation. These issues must be improved in future proteomic studies in CSF.

Major depressive disorder: insight into candidate cerebrospinal fluid protein biomarkers from proteomics studies.

INTRODUCTION: Major Depressive Disorder (MDD) is the leading cause of global disability, and an increasing body of literature suggests different cerebrospinal fluid (CSF) proteins as biomarkers of MDD. The aim of this review is to summarize the suggested CSF biomarkers and to analyze the MDD proteomics studies of CSF and brain tissues for promising biomarker candidates. Areas covered: The review includes the human studies found by a PubMed search using the following terms: 'depression cerebrospinal fluid biomarker', 'major depression biomarker CSF', 'depression CSF biomarker', 'proteomics depression', 'proteomics biomarkers in depression', 'proteomics CSF biomarker in depression', and 'major depressive disorder CSF'. The literature analysis highlights promising biomarker candidates and demonstrates conflicting results on others. It reveals 42 differentially regulated proteins in MDD that were identified in more than one proteomics study. It discusses the diagnostic potential of the biomarker candidates and their association with the suggested pathologies. Expert commentary: One ultimate goal of finding biomarkers for MDD is to improve the diagnostic accuracy to achieve better treatment outcomes; due to the heterogeneous nature of MDD, using bio-signatures could be a good strategy to differentiate MDD from other neuropsychiatric disorders. Notably, further validation studies of the suggested biomarkers are still needed.

Elucidation of the complex metabolic profile of cerebrospinal fluid using an untargeted biochemical profiling assay.

We sought to determine the molecular composition of human cerebrospinal fluid (CSF) and identify the biochemical pathways represented in CSF to understand the potential for untargeted screening of inborn errors of metabolism (IEMs). Biochemical profiles for each sample were obtained using an integrated metabolomics workflow comprised of four chromatographic techniques followed by mass spectrometry. Secondarily, we wanted to compare the biochemical profile of CSF with those of plasma and urine within the integrated mass spectrometric-based metabolomic workflow. Three sample types, CSF (N=30), urine (N=40) and EDTA plasma (N=31), were analyzed from retrospectively collected pediatric cohorts of equivalent age and gender characteristics. We identified 435 biochemicals in CSF representing numerous biological and chemical/structural families. Sixty-three percent (273 of 435) of the biochemicals detected in CSF also were detected in urine and plasma, another 32% (140 of 435) were detected in either plasma or urine, and 5% (22 of 435) were detected only in CSF. Analyses of several metabolites showed agreement between clinically useful assays and the metabolomics approach. An additional set of CSF and plasma samples collected from the same patient revealed correlation between several biochemicals detected in paired samples. Finally, analysis of CSF from a pediatric case with dihydropteridine reductase (DHPR) deficiency demonstrated the utility of untargeted global metabolic phenotyping as a broad assessment to screen samples from patients with undifferentiated phenotypes. The results indicate a single CSF sample processed with an integrated metabolomics workflow can be used to identify a large breadth of biochemicals that could be useful for identifying disrupted metabolic patterns associated with IEMs.

Prospective phenotyping of NGLY1-CDDG, the first congenital disorder of deglycosylation.

PURPOSE: The cytosolic enzyme N-glycanase 1, encoded by NGLY1, catalyzes cleavage of the ß-aspartyl glycosylamine bond of N-linked glycoproteins, releasing intact N-glycans from proteins bound for degradation. In this study, we describe the clinical spectrum of NGLY1 deficiency (NGLY1-CDDG). METHODS: Prospective natural history protocol. RESULTS: In 12 individuals ages 2 to 21 years with confirmed, biallelic, pathogenic NGLY1 mutations, we identified previously unreported clinical features, including optic atrophy and retinal pigmentary changes/cone dystrophy, delayed bone age, joint hypermobility, and lower than predicted resting energy expenditure. Novel laboratory findings include low cerebral spinal fluid (CSF) total protein and albumin and unusually high antibody titers toward rubella and/or rubeola following vaccination. We also confirmed and further quantified previously reported findings noting that decreased tear production, transient transaminitis, small feet, a complex hyperkinetic movement disorder, and varying degrees of global developmental delay with relatively preserved socialization are the most consistent features. CONCLUSION: Our prospective phenotyping expands the clinical spectrum of NGLY1-CDDG, offers prognostic information, and provides baseline data for evaluating therapeutic interventions.Genet Med 19 2, 160-168.

In-Depth Cerebrospinal Fluid Quantitative Proteome and Deglycoproteome Analysis: Presenting a Comprehensive Picture of Pathways and Processes Affected by Multiple Sclerosis.

In the current study, we conducted a quantitative in-depth proteome and deglycoproteome analysis of cerebrospinal fluid (CSF) from relapsing-remitting multiple sclerosis (RRMS) and neurological controls using mass spectrometry and pathway analysis. More than 2000 proteins and 1700 deglycopeptides were quantified, with 484 proteins and 180 deglycopeptides significantly changed between pools of RRMS and pools of controls. Approximately 300 of the significantly changed proteins were assigned to various biological processes including inflammation, extracellular matrix organization, cell adhesion, immune response, and neuron development. Ninety-six significantly changed deglycopeptides mapped to proteins that were not found changed in the global protein study. In addition, four mapped to the proteins oligo-myelin glycoprotein and noelin, which were found oppositely changed in the global study. Both are ligands to the nogo receptor, and the glycosylation of these proteins appears to be affected by RRMS. Our study gives the most extensive overview of the RRMS affected processes observed from the CSF proteome to date, and the list of differential proteins will have great value for selection of biomarker candidates for further verification.

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

Proteomics-based technologies in the discovery of biomarkers for multiple sclerosis in the cerebrospinal fluid.

Multiple Sclerosis is the most common non-traumatic disorder of the central nervous system and is generally regarded as an immune-mediated disorder that occurs in young adults. Since cerebrospinal fluid is in close contact with the extracellular surface of the brain, it is of great interest to examine possible biomarkers for multiple sclerosis. Proteomic studies of cerebrospinal fluid samples represent an important step towards a better understanding of the disease and may lead to the identification of clinically useful markers. Methodological advances in proteomics allowed the comparison of the protein content in different cerebrospinal fluid samples, using gel or liquid-based approaches coupled with mass spectrometry. In this paper, we discuss the advantages and limitations of the strategies employed and the potential biomarkers for multiple sclerosis identified so far using proteomics-based approaches.

[A diagnostic model of cerebrospinal protein fingerprint pattern for brain metastases of non-small cell lung cancer].

OBJECTIVE: To establish a diagnostic model of protein fingerprint pattern in the cerebrospinal fluid (CSF) for non-small-cell lung cancer (NSCLC) patients with brain metastases. METHODS: The CSF samples were obtained from 29 NSCLC patients with brain metastasis, 23 non-tumor patients and 10 early-stage NSCLC patients without brain metastases for analysis of the protein expression profiles using surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). The data were then analyzed by Biomarker Wizard software, and the tree analysis patterns were generated using the decision-tree model in Biomarker Patterns software. The diagnostic model was tested for its clinical application. RESULTS: Five protein peaks were identified showing differential expression between patients with brain metastases and those without brain metastases. Combination of the 3 protein peaks (m/z: 8698.00, 1215.32 and 1245.70) could discriminate these two samples with a sensitivity of 100.00% (29/29) and a specificity of 100.00% (23/23). Five proteins were differentially expressed between the NSCLC patients with brain metastases and the non-tumor patients. With one protein peak (m/z: 6050.00), these two samples could be discriminated with a sensitivity of 90.00% (9/10) and a specificity of 78.26% (18/23). CONCLUSION: The established diagnostic model of CSF protein fingerprint pattern provides high sensitivity and specificity in the diagnosis of NSCLC with brain metastasis.

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.

[CSF biomarkers: proteomics investigations and clinical applications in neurodegenerative disorders]. / Les marqueurs biologiques protéiques du liquide céphalorachidien: caractéristiques et implications cliniques dans les démences.

Given the current developments of therapeutic strategies in the field of neurodegenerative disorders, exact diagnosis, especially at an early stage, is becoming increasingly crucial for optimal patient care. Importantly, the new diagnosis criteria of dementia include functional imagery as well as CSF biomarkers. Proteomics investigations of these CSF biomarkers have produced quite promising results. The interest of CSF analysis resides in the anatomical and pathophysiological characteristics of this fluid. In this article, we will review current proteomics investigations of CSF which have led to the discovery and validation of biomarkers, mainly in the field of neurodegenerative disorders in Alzheimer's disease.

Matching of oligoclonal immunoglobulin transcriptomes and proteomes of cerebrospinal fluid in multiple sclerosis.

We describe a method for correlating the immunoglobulin (Ig) proteomes with the B cell transcriptomes in human fluid and tissue samples, using multiple sclerosis as a paradigm. Oligoclonal Ig bands and elevated numbers of clonally expanded B cells in the cerebrospinal fluid (CSF) are diagnostic hallmarks of multiple sclerosis. Here we compared the Ig transcriptomes of B cells with the corresponding Ig proteomes in CSF samples from four subjects with multiple sclerosis. We created individual Ig transcriptome databases that contained the subject-specific mutations introduced by V(D)J recombination and somatic hypermutation and then searched the CSF for corresponding characteristic peptides by mass spectrometry. In each sample, the Ig transcriptomes and proteomes strongly overlapped, showing that CSF B cells indeed produce the oligoclonal Ig bands. This approach can be applied to other organ-specific diagnostic fluid or tissue samples to compare the Ig transcripts of local B cells with the corresponding antibody proteomes of individual subjects.

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.