Metabolomic Profiles Associated With Disease Severity in Multiple Sclerosis.

Authors

Fatemeh Siavoshi, Dimitrios C Ladakis, Larissa Jank, Blake E Dewey, Angeliki G Filippatou, Matthew D Smith, Jerry L Prince, Elias S Sotirchos, Shiv Saidha, Ellen M Mowry, Peter A Calabresi, Kathryn C Fitzgerald, Pavan Bhargava

Published in

Neurology(R) neuroimmunology & neuroinflammation. Volume 13. Issue 6. Pages e200664. Epub Oct 22, 2026.

Abstract

Sensitive, minimally invasive biomarkers that reflect functional decline in multiple sclerosis (MS) are still lacking. Untargeted metabolomic profiling allows unbiased discovery of circulating biomarkers and dysregulated biological pathways underlying MS onset and progression. We aimed to identify candidate circulating metabolite signatures correlated with clinical, imaging, and patient-reported outcomes in MS and to characterize the underlying metabolic pathways.
We conducted a cross-sectional analysis of untargeted circulating metabolomic profiles from 541 samples of 323 people with multiple sclerosis (PwMS), including both relapsing-remitting and progressive forms, detecting 332 metabolites. Associations between metabolite levels and outcomes, including clinical disability (Expanded Disability Status Scale), functional tests (walking speed, manual dexterity, and processing speed), Neuro-QoL patient-reported domains, optical coherence tomography-derived retinal layer thicknesses, and MRI-derived measures, were assessed using linear mixed-effects models adjusted for age, sex, race, treatment status, and MS subtype. To identify clusters of metabolites jointly linked to outcomes, we applied Hierarchical All-Against-All Association Analysis and weighted correlation network analysis. Pathway enrichment was also performed using Fast Gene Set Enrichment Analysis on ranked effect sizes based on the RaMP database, excluding pathways with fewer than 3 metabolites.
We identified multiple metabolites consistently associated with MS severity across clinical, patient-reported, and imaging domains. Metabolites such as p-cresol sulfate, p-cresol glucuronide, phenylacetylglutamine, and carnitine-derived species were linked to greater disease severity, whereas tryptophan betaine, ergothioneine, N-acetylcarnosine, and indolepropionate were associated with more favorable outcomes. Pathway analyses highlighted amino acid transport and metabolism, aromatic and branched-chain amino acid pathways, and solute carrier transporter systems, as well as bile acid, sphingolipid, and carnitine-related pathways linked to MS severity.
Comprehensive integration of metabolomic, clinical, and imaging data in PwMS highlights distinct metabolites and metabolic pathways associated with MS severity. These candidate metabolites warrant external validation in independent cohorts and provide a rationale for future biomarker discovery studies aimed at improving disease monitoring and management in MS.

PMID:
42912879
Bibliographic data and abstract were imported from PubMed on 24 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.