Targeted proteomics of cerebrospinal fluid in treatment naïve multiple sclerosis patients identifies immune biomarkers of clinical phenotypes.

Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Original Publication: London : Nature Publishing Group, copyright 2011-

Biomarkers*/cerebrospinal fluid ; Multiple Sclerosis*/cerebrospinal fluid ; Multiple Sclerosis*/immunology ; Proteomics*/methods; Humans ; Male ; Female ; Adult ; Middle Aged ; Phenotype ; Cytokines/cerebrospinal fluid ; Magnetic Resonance Imaging ; Cross-Sectional Studies

Multiple sclerosis (MS) is an inflammatory demyelinating disease with heterogeneous clinical presentations and variable long-term disability accumulation. There are currently no standard criteria to accurately predict disease outcomes. In this study we investigated the cross-sectional relationship between disease phenotype and immune-modulating cytokines and chemokines in cerebrospinal fluid (CSF). We analyzed CSF from 20 DMT-naïve MS patients using Olink Proteomics' Target 96 Inflammation panel and correlated the resulting analytes with respect to (1) disease subtype, (2) patient age and sex, (3) extent of clinical disability, and (4) MRI segmental brain volumes. We found that intrathecal IL-4 correlated with higher Expanded Disability Status Scale (EDSS) scores and longer 25-foot walk times, and CD8A correlated with decreased thalamic volumes and longer 9-hole peg test times. Male sex was associated with higher FGF-19 expression, and Tumefactive MS with elevated CCL4. Several inflammatory markers were correlated with older age at the time of LP. Finally, higher intrathecal IL-33 correlated with increased MS lesion burden and multi-compartment brain atrophy. This study confirms immune heterogeneity underlying CSF profiles in MS, but also identifies several inflammatory protein biomarkers that may be of use for predicting clinical outcomes in future algorithms.
(© 2024. The Author(s).)

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UL1 TR001453 United States TR NCATS NIH HHS; grant #UL1-TR001453 SPARK grant from the UMass Center for Clinical and Translational Science

Keywords: Age; Cerebrospinal fluid (CSF); Expanded Disability Status Scale (EDSS); Multiple sclerosis (MS); Targeted proteomics

0 (Biomarkers)
0 (Cytokines)

Date Created: 20240918 Date Completed: 20240918 Latest Revision: 20240922

20250114

PMC11411093

10.1038/s41598-024-67769-1

39294186