Abstract
Identifying patients at higher risk for poor outcomes from nonalcoholic fatty liver disease (NAFLD) remains challenging. Metabolomics, the comprehensive measurement of small molecules in biological samples, has the potential to reveal novel noninvasive biomarkers. The aim of this study was to determine if serum metabolite profiles in patients with NAFLD associate with future liver-related events. We performed a retrospective single-center cohort study of 187 participants with biopsy-proven NAFLD. Metabolomic analysis was performed on serum using ultrahigh performance liquid chromatography/tandem mass spectrometry and gas chromatography/mass spectrometry. We identified liver-related events (variceal bleeding, ascites, spontaneous bacterial peritonitis, hepatic encephalopathy, hepatocellular carcinoma, hepatopulmonary or hepatorenal syndrome) by manual chart review between index biopsy (2007-2013) and April 1, 2018. Generalized linear models and Cox proportional hazards models were used to test the association of metabolites with liver-related events and time to first liver-related event, controlling for covariates and fibrosis stage. Over a mean ± SD follow-up of 6.9 ± 3.2 years, 11 participants experienced 22 liver-related events. Generalized linear models revealed 53 metabolites significantly associated with liver-related events (P < 0.05). In Cox proportional hazards modeling, 69 metabolites were significantly associated with time to future liver-related events (P < 0.05), seven of which met the false discovery rate threshold of 0.10: vitamin E metabolites gamma-carboxyethyl-hydroxychroman (gamma-CEHC) and gamma-CEHC glucuronide; primary bile acid metabolite taurochenodeoxycholate; serotonin metabolite 5-hydroxyindoleacetate; and lipid metabolites (i) 2-hydroxyglutarate, (ii) 3beta,17beta-diol disulfate 1, and (iii) eicosenoyl sphingomyelin. Conclusion: Metabolites of a primary bile acid, vitamin E, and serotonin were associated with future liver-related events. Our results suggest metabolite pathways may be useful for predicting which patients with NAFLD are at higher risk for hepatic decompensation.