Metabolic alterations in multiple sclerosis and the impact of vitamin D supplementation

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Abstract

BACKGROUND. Our goal was to identify changes in the metabolome in multiple sclerosis (MS) and how vitamin D supplementation alters metabolic profiles in MS patients and healthy controls. METHODS. We applied global untargeted metabolomics to plasma from a cross-sectional cohort of age- and sex-matched MS patients and controls and a second longitudinal cohort of MS patients and healthy controls who received 5,000 IU cholecalciferol daily for 90 days. We applied partial least squares discriminant analysis, weighted correlation network analysis (WGCNA), and pathway analysis to the metabolomics data. Generalized estimating equations models were used to assess change in WGCNA-identified module scores or metabolite pathways with vitamin D supplementation. RESULTS. Utilizing multiple analytical techniques, we identified metabolic alterations in oxidative stress (γ-glutamyl amino acid, glutathione) and xenobiotic metabolism (benzoate, caffeine) in MS patients compared with healthy controls in the first cohort. In the vitamin D supplementation cohort, we identified two sets of metabolites altered differentially between MS patients and healthy controls with vitamin D supplementation. The first included markers of oxidative stress and protein oxidation (P = 0.006), while the second contained lysolipids and fatty acids (P = 0.03). CONCLUSIONS. Using metabolomics, we identified alterations in oxidative stress and xenobiotic metabolism in MS patients and subsequently demonstrated a reduction of oxidative stress markers with vitamin D supplementation in healthy controls but not in MS patients. We demonstrate the utility of metabolomics in identifying aberrant metabolic processes and in monitoring the ability of therapeutic interventions to correct these abnormalities.

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Bhargava, P., Fitzgerald, K. C., Calabresi, P. A., & Mowry, E. M. (2017). Metabolic alterations in multiple sclerosis and the impact of vitamin D supplementation. JCI Insight, 2(19). https://doi.org/10.1172/jci.insight.95302

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