Putative Protein Biomarkers of Multiple Sclerosis

2014 ◽  
pp. 389-412
Keyword(s):  
Multiple Sclerosis ◽  
Protein Biomarkers ◽  
Putative Protein

scholarly journals Integrative biochemical, proteomics, and metabolomics cerebrospinal fluid biomarkers predict clinical conversion to multiple sclerosis

2021 ◽  
Author(s):  
Fay Probert ◽  
Tianrong Yeo ◽  
Yifan Zhou ◽  
Megan Sealey ◽  
Siddharth Arora ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cerebrospinal Fluid ◽  
Predictive Accuracy ◽  
Personalised Medicine ◽  
Clinically Isolated Syndrome ◽  
Oligoclonal Bands ◽  
Protein Biomarkers ◽  
Glucose Levels ◽  
Prognostic Accuracy ◽  
New Biomarkers

Abstract Eighty-five percent of multiple sclerosis cases begin with a discrete attack termed clinically isolated syndrome, but 37% of clinically isolated syndrome patients do not experience a relapse within 20 years of onset. Thus, the identification of biomarkers able to differentiate between individuals who are most likely to have a second clinical attack from those who remain in the clinically isolated syndrome stage is essential to apply a personalised medicine approach. We sought to identify biomarkers from biochemical, metabolic, and proteomic screens that predict clinically defined conversion from clinically isolated syndrome to multiple sclerosis and generate a multi-omics-based algorithm with higher prognostic accuracy than any currently available test. An integrative multi-variate approach was applied to the analysis of cerebrospinal fluid samples taken from 54 individuals at the point of clinically isolated syndrome with 2–10 years of subsequent follow-up enabling stratification into clinical converters and non-converters. Leukocyte counts were significantly elevated at onset in the clinical converters and predict occurrence of a second attack with 70% accuracy. Myo-inositol levels were significantly increased in clinical converters while glucose levels were decreased, predicting transition to multiple sclerosis with accuracies of 72% and 63%, respectively. Proteomics analysis identified 89 novel gene products related to conversion. The identified biochemical and protein biomarkers were combined to produce an algorithm with predictive accuracy of 83% for the transition to clinically defined multiple sclerosis, outperforming any individual biomarker in isolation including oligoclonal bands. The identified protein biomarkers are consistent with an exaggerated immune response, perturbed energy metabolism, and multiple sclerosis pathology in the clinical converter group. The new biomarkers presented provide novel insight into the molecular pathways promoting disease while the multi-omics algorithm provides a means to more accurately predict whether an individual is likely to convert to clinically defined multiple sclerosis.

scholarly journals Inflammation-related plasma and CSF biomarkers for multiple sclerosis

2020 ◽  
Vol 117 (23) ◽  
pp. 12952-12960 ◽  
Author(s):  
Jesse Huang ◽  
Mohsen Khademi ◽  
Lars Fugger ◽  
Örjan Lindhe ◽  
Lenka Novakova ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cerebrospinal Fluid ◽  
Neurological Diseases ◽  
Area Under The Curve ◽  
Csf Biomarkers ◽  
Healthy Controls ◽  
Protein Biomarkers ◽  
Neurofilament Light Chain ◽  
Diagnostic Efficacy ◽  
Neurofilament Light

Effective biomarkers for multiple sclerosis diagnosis, assessment of prognosis, and treatment responses, in particular those measurable in blood, are largely lacking. We have investigated a broad set of protein biomarkers in cerebrospinal fluid (CSF) and plasma using a highly sensitive proteomic immunoassay. Cases from two independent cohorts were compared with healthy controls and patients with other neurological diseases. We identified and replicated 10 cerebrospinal fluid proteins including IL-12B, CD5, MIP-1a, and CXCL9 which had a combined diagnostic efficacy similar to immunoglobulin G (IgG) index and neurofilament light chain (area under the curve [AUC] = 0.95). Two plasma proteins, OSM and HGF, were also associated with multiple sclerosis in comparison to healthy controls. Sensitivity and specificity of combined CSF and plasma markers for multiple sclerosis were 85.7% and 73.5%, respectively. In the discovery cohort, eotaxin-1 (CCL11) was associated with disease duration particularly in patients who had secondary progressive disease (PCSF< 4 × 10−5,Pplasma< 4 × 10−5), and plasma CCL20 was associated with disease severity (P= 4 × 10−5), although both require further validation. Treatment with natalizumab and fingolimod showed different compartmental changes in protein levels of CSF and peripheral blood, respectively, including many disease-associated markers (e.g., IL12B, CD5) showing potential application for both diagnosing disease and monitoring treatment efficacy. We report a number of multiple sclerosis biomarkers in CSF and plasma for early disease detection and potential indicators for disease activity. Of particular importance is the set of markers discovered in blood, where validated biomarkers are lacking.

Protein expression profiles in pediatric multiple sclerosis: potential biomarkers

2009 ◽  
Vol 15 (4) ◽  
pp. 455-464 ◽  
Author(s):  
KN Rithidech ◽  
L Honikel ◽  
M Milazzo ◽  
D Madigan ◽  
R Troxell ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Mass Spectrometry ◽  
Protein Expression ◽  
Expression Profiles ◽  
Low Frequency ◽  
Complement Factor ◽  
Protein Biomarkers ◽  
Two Dimensional Gel Electrophoresis ◽  
Pediatric Multiple Sclerosis ◽  
Proteomic Approach

The diagnosis of pediatric multiple sclerosis (MS) is challenging due to its low frequency and the overlap with other acquired childhood demyelinating disorders of the central nervous system. To identify potential protein biomarkers which could facilitate the diagnosis, we used two-dimensional gel electrophoresis (2-DE) in combination with mass spectrometry to identify proteins associated with pediatric MS. Plasma samples from nine children with MS and nine healthy subjects, matched in aggregate by age and gender, were analyzed for differences in their patterns of protein expression. We found 12 proteins that were significantly up regulated in the pediatric MS group: alpha-1-acid-glycoprotein 1, alpha-1-B-glycoprotein, transthyretin, apoliprotein-C-III, serum amyloid P component, complement factor-I, clusterin, gelsolin, hemopexin, kininogen-1, hCG1993037-isoform, and vitamin D-binding protein. These results show that 2-DE in combination with mass spectrometry is a highly sensitive technique for the identification of blood-based biomarkers. This proteomic approach could lead to a new panel of diagnostic and prognostic markers in pediatric MS.

Protein biomarkers for multiple sclerosis: semi-quantitative analysis of cerebrospinal fluid candidate protein biomarkers in different forms of multiple sclerosis

2012 ◽  
Vol 18 (8) ◽  
pp. 1081-1091 ◽  
Author(s):  
Timucin Avsar ◽  
Didem Korkmaz ◽  
Melih Tütüncü ◽  
N Onat Demirci ◽  
Sabahattin Saip ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cerebrospinal Fluid ◽  
Disease Process ◽  
Underlying Disease ◽  
Protein Biomarkers ◽  
Serum Samples ◽  
Neurofilament Light Chain ◽  
Neurofilament Light ◽  
Protein Levels ◽  
Clinical Subtype

Background: The complex pathogenesis of multiple sclerosis, combined with an unpredictable prognosis, requires identification of disease-specific diagnostic and prognostic biomarkers. Objective: To determine whether inflammatory proteins, such as neurofilament light chain, myelin oligodendrocyte glycoprotein and myelin basic protein, and neurodegenerative proteins, such as tau and glial fibrillary acidic protein, can serve as biomarkers for predicting the clinical subtype and prognosis of MS. Methods: Cerebrospinal fluid and serum samples were collected from patients with a diagnosis of clinically isolated syndrome ( n = 46), relapsing–remitting MS ( n = 67) or primary-progressive MS ( n = 22) along with controls having other non-inflammatory neurological disease ( n = 22). Western blot analyses were performed for the listed proteins. Protein levels were compared among different clinical subtypes using one-way analysis of variance analysis. The k-nearest neighbour algorithm was further used to assess the predictive use of these proteins for clinical subtype classification. Results: The results showed that each of tau, GFAP, MOG and NFL protein concentrations differed significantly ( p < 0.001) in multiple sclerosis clinical subtypes compared with the controls. Levels of the proteins also differed between the multiple sclerosis clinical subtypes, which may be associated with the underlying disease process. Classification studies revealed that these proteins might be useful for identifying multiple sclerosis clinical subtypes. Conclusions: We showed that select biomarkers may have potential in identifying multiple sclerosis clinical subtypes. We also showed that the predictive value of the prognosis increased when using a combination of the proteins versus using them individually.

scholarly journals CSF Chitinase 3–Like 2 Is Associated With Long-term Disability Progression in Patients With Progressive Multiple Sclerosis

2021 ◽  
Vol 8 (6) ◽  
pp. e1082
Author(s):  
Manuel Comabella ◽  
Jaume Sastre-Garriga ◽  
Eva Borras ◽  
Luisa M. Villar ◽  
Albert Saiz ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Binding Protein ◽  
Area Under The Curve ◽  
Shotgun Proteomics ◽  
Progressive Multiple Sclerosis ◽  
Disability Progression ◽  
Protein Biomarkers ◽  
Discovery Cohort

ObjectiveThis study aimed to identify long-term prognostic protein biomarkers associated with disease progression in patients with progressive multiple sclerosis (MS).MethodsCSF samples were collected from a discovery cohort of 28 patients with progressive MS who participated in a clinical trial with interferon beta. Patients were classified into high and low disability progression phenotypes according to numeric progression rates (NPR) and step-based progression rates (SPR) after a mean follow-up time of 12 years. Protein abundance was measured by shotgun proteomics. Selected proteins from the discovery cohort were quantified by parallel reaction monitoring in CSF samples from an independent validation cohort of 41 patients with progressive MS classified also into high and low disability progression phenotypes after a mean follow-up time of 7 years.ResultsOf 2,548 CSF proteins identified in the discovery cohort, 10 were selected for validation based on their association with long-term disability progression: SPATS2-like protein, chitinase 3–like 2 (CHI3L2), plasma serine protease inhibitor, metallothionein-3, phospholipase D4, beta-hexosaminidase, neurexophilin-1, adipocyte enhancer-binding protein 1, cathepsin L1, and lipopolysaccharide-binding protein. Only CHI3L2 was validated, and patients with high disability progression exhibited significantly higher CSF protein levels compared with patients with low disability progression (p = 0.03 for NPR and p = 0.02 for SPR). CHI3L2 levels showed good performance to discriminate between high and low disability progression in patients with progressive MS (area under the curve 0.73; sensitivity 90% and specificity 63%).ConclusionsAlthough further confirmatory studies are needed, we propose CSF CHI3L2 as a prognostic protein biomarker associated with long-term disability progression in patients with progressive MS.Classification of EvidenceThis study provides Class II evidence that high CSF CHI3L2 levels identified higher disability progression in patients with progressive MS.

Analysis of plasma protein biomarkers in childhood onset multiple sclerosis

2020 ◽  
Vol 348 ◽  
pp. 577359
Author(s):  
Ismail Solmaz ◽  
Engin Kocak ◽  
Ozan Kaplan ◽  
Mustafa Celebier ◽  
Banu Anlar
Keyword(s):  
Multiple Sclerosis ◽  
Plasma Protein ◽  
Protein Biomarkers ◽  
Childhood Onset
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