AMONG PATIENTS with multiple sclerosis (MS), distinct circulating metabolomic profiles have been linked to disease severity across clinical, patient-reported, and imaging measures, according to a new cross-sectional analysis, with gut microbiota-derived metabolites featuring prominently.
Researchers conducted a cross-sectional analysis of untargeted metabolomic profiles from 541 samples of 323 patients with MS, including relapsing-remitting and progressive forms, detecting 332 metabolites.
Associations with clinical disability (Expanded Disability Status Scale), walking speed, manual dexterity, processing speed, Neuro-QoL patient-reported domains, retinal layer thicknesses from optical coherence tomography and magnetic resonance imaging measures were assessed using linear mixed-effects models adjusted for age, sex, race, treatment status and MS subtype.
Metabolite clusters were identified using Hierarchical All-Against-All Association Analysis and weighted correlation network analysis, and pathway enrichment was performed using Fast Gene Set Enrichment Analysis based on the RaMP database.
Multiple significant clusters of metabolites were correlated with clinical, imaging, and patient-reported outcomes.
Gut microbiota-derived aromatic amino acid metabolites, including p-cresol glucuronide, p-cresol sulfate, phenylacetylglutamine and trimethylamine N-oxide, showed strong positive correlations with greater disability measures and lower peripapillary retinal nerve fibre layer thickness.
Carnitine-derived species were also linked to greater severity, whereas tryptophan betaine, ergothioneine, N-acetylcarnosine and indolepropionate were associated with more favourable outcomes.
Pathway analyses highlighted amino acid transport and metabolism, aromatic and branched-chain amino acid pathways, solute carrier transporter systems, and bile acid, sphingolipid and carnitine-related pathways.
These findings have highlighted distinct metabolites and metabolic pathways associated with MS severity, supporting integration of metabolomic profiles with clinical and imaging data in multiple sclerosis. The candidate metabolites warrant external validation in independent cohorts, and the cross-sectional design means causality cannot be inferred. This work provides a rationale for future biomarker discovery studies aimed at improving disease monitoring and management.
Reference
Siavoshi F et al. Metabolomic profiles associated with disease severity in multiple sclerosis. Neurology: Neuroimmunology & Neuroinflammation. 2026;13(6):e200664.
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