Metabolomics reveals lipid and amino acid signatures of disease severity in multiple sclerosis
Abstract
Objective: Plasma metabolomics offers insight into multiple sclerosis (MS) pathophysiology, but existing studies are limited by small sample sizes and incomplete clinical data.
Methods: We conducted plasma metabolomic profiling of 411 deeply phenotyped patients with MS and 46,443 controls, analyzing 162 metabolites in 30 biologically related metabolite groups. We characterized associations with MS diagnosis, disability, disease subtype, and inflammatory disease activity using regression and differential network enrichment analysis. We additionally examined 25 pre-diagnosis individuals whose samples were collected before their first demyelinating event.
Results: Fourteen of 30 metabolite groups were associated with MS after false discovery rate correction, with the strongest positive associations observed for atherogenic lipoproteins, glycine, cholines, and saturated fatty acids, and the strongest negative associations for aromatic amino acids, branched-chain amino acids, alanine, and citrate. Differential network enrichment analysis identified two dysregulated subnetworks encompassing amino acid and energy metabolism and lipid and lipoprotein metabolism. Five metabolite groups were negatively associated with disability: small high-density lipoprotein particles, histidine, branched-chain amino acids, albumin, and aromatic amino acids. The omega-6/omega-3 fatty acid ratio was significantly associated with recent relapse ( OR = 1.92, FDR- p = 0.030) and nominally associated…
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