Metabolomic Profiles Associated With Disease Severity in Multiple Sclerosis.
- 1Division of Neuroimmunology, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD.
- 2Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, MD; and.
- 3Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, MD.
Abstract
Background and objectives
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.Methods
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.Results
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.Discussion
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.
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BibTeX
@article{siavoshi2026metabolomic,
title = {{Metabolomic Profiles Associated With Disease Severity in Multiple Sclerosis.}},
author = {Fatemeh Siavoshi and Dimitrios C Ladakis and Larissa Jank and Blake E Dewey and Angeliki G Filippatou and Matthew D Smith and Jerry L Prince and Elias S Sotirchos and Shiv Saidha and Ellen M Mowry and Peter A Calabresi and Kathryn C Fitzgerald and Pavan Bhargava},
journal = {Neurology(R) neuroimmunology \& neuroinflammation},
year = {2026},
month = oct,
doi = {10.1212/nxi.0000000000200664},
url = {https://europepmc.org/article/MED/42912879},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Metabolomic Profiles Associated With Disease Severity in Multiple Sclerosis.
AU - Fatemeh Siavoshi
AU - Dimitrios C Ladakis
AU - Larissa Jank
AU - Blake E Dewey
AU - Angeliki G Filippatou
AU - Matthew D Smith
AU - Jerry L Prince
AU - Elias S Sotirchos
AU - Shiv Saidha
AU - Ellen M Mowry
AU - Peter A Calabresi
AU - Kathryn C Fitzgerald
AU - Pavan Bhargava
PY - 2026
DA - 2026/10/22
JO - Neurology(R) neuroimmunology & neuroinflammation
DO - 10.1212/nxi.0000000000200664
UR - https://europepmc.org/article/MED/42912879
AB - Background and objectives 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.Methods 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.Results 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.Discussion 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.
SN - 2332-7812
ER -