ArticleMultiple sclerosis and related disorders2022
Biomarker panel increases accuracy for identification of an MS relapse beyond sNfL.
Article in Multiple sclerosis and related disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- A framework for blood biomarker discovery in MS.Multiple sclerosis (Houndmills, Basingstoke, England) · 2026Review
- Serum neurofilament light chain as a biomarker of disease control in multiple sclerosis: a real-world cross-sectional analysis of therapeutic regimens.Journal of neurology · 2025Article
- Role of soluble biomarkers in treating multiple sclerosis and neuroinflammatory conditions.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025Review
- Serum Proteomics Distinguish Subtypes of NMO Spectrum Disorder and MOG Antibody-Associated Disease and Highlight Effects of B-Cell Depletion.Neurology(R) neuroimmunology & neuroinflammation · 2024Article
- Association of Dietary Retinol Intake and Serum Neurofilament Light Chain Levels: Results from NHANES 2013-2014.Nutrients · 2024Article
- A rapid review of differences in cerebrospinal neurofilament light levels in clinical subtypes of progressive multiple sclerosis.Frontiers in neurology · 2024Review
- Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis.Nature communications · 2023Article
- Current and Future Biomarkers in Multiple Sclerosis.International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
14 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundFor relapsing-remitting multiple sclerosis (RRMS), there is a need for biomarker development beyond clinical manifestations and MRI. Soluble neurofilament light chain (sNfL) has emerged as a biomarker for inflammatory activity in RRMS. However, there are limitations to the accuracy of sNfL in identifying relapses. Here, we sought to identify a panel of biomarkers that would increase the precision of distinguishing patients in relapse compared to sNfL alone.
methodsWe used a multiplex approach to measure levels of 724 blood proteins in two distinct RRMS cohorts. Multiple t-tests with covariate correction determined biomarkers that were differentially regulated in relapse and remission. Logistic regression models determined the accuracy of biomarkers to distinguish relapses from remission.
resultsThe discovery cohort identified 37 proteins differentially abundant in active RRMS relapse compared to remission. The verification cohort confirmed four proteins, including sNfL, were altered in active RRMS relapse compared to remission. Logistic regression showed that the 4-protein panel identified active relapse with higher accuracy (AUC = 0.87) than sNfL alone (AUC = 0.69).
conclusionOur studies confirmed that sNfL is elevated during relapses in RRMS patients. Furthermore, we identified three other blood proteins, uPA, hK8 and DSG3 that were altered during relapse. Together, these four biomarkers could be used to monitor disease activity in RRMS patients.
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