Journal of Clinical InvestigationNeurosciencePeer-reviewed journal article
Bile acid metabolism is altered in multiple sclerosis and supplementation ameliorates neuroinflammation
Pavan BhargavaiD, Matthew D. SmithiD, Leah MischeiD, Emily Harrington, Kathryn C. FitzgeraldiD, Kyle A. MartiniD, Sol KimiD, Arthur Anthony Reyes, Jaime Gonzalez CardonaiD, Christina M. Volsko, Ajai K. TripathiiD, Sonal SinghiD, Kesava Varanasi, Hannah‐Noelle LordiD, Keya R MeyersiD, Michelle Taylor, Marjan GharagozlooiD, Elias S. SotirchosiD, Bardia NourbakhshiD, Ranjan DuttaiD, Ellen M. MowryiD, Emmanuelle L. WaubantiD, Peter A. CalabresiiD
Abstract
Multiple sclerosis (MS) is an inflammatory demyelinating disorder of the CNS. Bile acids are cholesterol metabolites that can signal through receptors on cells throughout the body, including the CNS and immune system. Whether bile acid metabolism is abnormal in MS is unknown. Using global and targeted metabolomic profiling, we identified lower levels of circulating bile acid metabolites in multiple cohorts of adult and pediatric MS patients compared to controls. In white matter lesions from MS brain tissue, we noted the presence of bile acid receptors on immune and glial cells. To mechanistically examine the implications of lower levels of bile acids in MS, we studied the in vitro effects of an endogenous bile acid - tauroursodeoxycholic acid (TUDCA) on astrocyte and microglial polarization. TUDCA prevented neurotoxic (A1) polarization of astrocytes and pro-inflammatory polarization of microglia in a dose-dependent manner. TUDCA supplementation in experimental autoimmune encephalomyelitis reduced severity of disease, based on behavioral and pathological measures. We demonstrate that bile acid metabolism is altered in MS; bile acid supplementation prevents polarization of astrocytes and microglia to neurotoxic phenotypes and ameliorates neuropathology in an animal model of MS. These findings identify dysregulated bile acid metabolism as a potential therapeutic target in MS.
- organism: human
- assay: metabolomics
- research focus: differential expression
- approach: statistical model
- Citations
- 237
- FWCI
- 18.22
- Field percentile
- top 1%
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