Hepatic Steatosis Is Associated With Adverse Molecular Signatures in Subjects Without Diabetes.
Academic Article
Overview
abstract
BACKGROUND AND AIMS: Exaggerated hepatic triglyceride accumulation (i.e., hepatic steatosis) represents a strong risk factor for type 2 diabetes mellitus and cardiovascular disease. Despite the clear association of hepatic steatosis with impaired insulin signaling, the precise molecular mechanisms involved are still under debate. We combined data from several metabolomics techniques to gain a comprehensive picture of molecular alterations related to the presence of hepatic steatosis in a diabetes-free sample (N = 769) of the population-based Study of Health in Pomerania. METHODS: Liver fat content (LFC) was assessed using MRI. Metabolome measurements of plasma and urine samples were done by mass spectrometry and nuclear magnetic resonance spectroscopy. Linear regression analyses were used to detect significant associations with either LFC or markers of hepatic damage. Possible mediations through insulin resistance, hypertriglyceridemia, and inflammation were tested. A predictive molecular signature of hepatic steatosis was established using regularized logistic regression. RESULTS: The LFC-associated atherogenic lipid profile, tightly connected to shifts in the phospholipid content, and a prediabetic amino acid cluster were mediated by insulin resistance. Molecular surrogates of oxidative stress and multiple associations with urine metabolites (e.g., indicating altered cortisol metabolism or phase II detoxification products) were unaffected in mediation analyses. Incorporation of urine metabolites slightly improved classification of hepatic steatosis. CONCLUSIONS: Comprehensive metabolic profiling allowed us to reveal molecular patterns accompanying hepatic steatosis independent of the known hallmarks. Novel biomarkers from urine (e.g., cortisol glucuronide) are worthwhile for follow-up in patients suffering from more severe liver impairment compared with our merely healthy population-based sample.
