Multi-Omic Predictors of Steatohepatitis and Advanced Fibrosis in Children

Abstract

Metabolic dysregulation associated with gut microbial dysbiosis can influence the progression of nonalcoholic fatty liver disease (NAFLD) from hepatic steatosis to inflammation and subsequent fibrosis. Using a multi-omics approach, we identified microbiome-derived biochemicals and genes associated with progressive hepatic pathology and fibrosis in Latino children (N=241). Children with more severe liver pathology were dysbiotic and had increased gene content associated with lipopolysaccharide biosynthesis and lipid, amino acid and carbohydrate metabolism. These changes were driven by increases in Bacteroides and concomitant decreases of Akkermansia, Anaerococcus, Corynebacterium, and Finegoldia. Nontargeted mass spectrometry revealed perturbations in one-carbon metabolism, mitochondrial dysfunction, and increased oxidative stress in children with steatohepatitis and fibrosis. Random forests modeling of plasma metabolites were highly predictive of nonalcoholic steatohepatitis (NASH) (97% accuracy) and hepatic fibrosis, steatosis and lobular inflammation (93.8% accuracy), and can differentiate steatohepatitis from simple steatosis (90.0% accuracy). These metabolomic biomarkers of hepatic pathology provide insights for therapeutic targeting of bacterially-mediated and host pathways.