ArticleMolecular & cellular proteomics : MCP2016
Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis.
Article in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Predictors of Multiple Sclerosis After Clinically Isolated Syndrome: A Systematic Review and Meta-Analysis.European journal of neurology · 2026Pooled it
- Comprehensive Meta-Analysis of Differentially Expressed Proteins in Cerebrospinal Fluid Associated with Multiple Sclerosis.International journal of molecular sciences · 2025Pooled it
- Multiple Sclerosis: Pathogenesis Mechanism and Biomarkers.Central nervous system agents in medicinal chemistry · 2025Review
- Machine learning model base on metabolomics and proteomics to predict cognitive impairment in Parkinson's disease.NPJ Parkinson's disease · 2024Article
- Identification of brain-enriched proteins in CSF as biomarkers of relapsing remitting multiple sclerosis.Clinical proteomics · 2024Article
- The Non-Targeted Lipidomic-Based Classifier Reveals Two Candidate Biomarkers for Ischemic Stroke in Hypertensive Individuals.Risk management and healthcare policy · 2024Article
- Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis.The Cochrane database of systematic reviews · 2023Review
- Cellular and Molecular Evidence of Multiple Sclerosis Diagnosis and Treatment Challenges.Journal of clinical medicine · 2023Review
- A combination of molecular and clinical parameters provides a new strategy for high-grade serous ovarian cancer patient management.Journal of translational medicine · 2022Article
- An Update on Diagnostic Laboratory Biomarkers for Multiple Sclerosis.Current neurology and neuroscience reports · 2022Review
- A Scoping Review on Body Fluid Biomarkers for Prognosis and Disease Activity in Patients with Multiple Sclerosis.Journal of personalized medicine · 2022Article
- Proteomics in Multiple Sclerosis: The Perspective of the Clinician.International journal of molecular sciences · 2022Review
- Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer.Cancers · 2020Review
- Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis.Clinical proteomics · 2020Article
- CSF-PR 2.0: An Interactive Literature Guide to Quantitative Cerebrospinal Fluid Mass Spectrometry Data from Neurodegenerative Disorders.Molecular & cellular proteomics : MCP · 2017Article
- Targeted proteomics in urinary extracellular vesicles identifies biomarkers for diagnosis and prognosis of prostate cancer.Oncotarget · 2017Article
- Biomarkers of multiple sclerosis: current findings.Degenerative neurological and neuromuscular disease · 2017Review
- Multiple sclerosis: Glial cell activation - Biomarker advances and their translational significance.Science progressReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-β-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.
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Registered trials
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