Precision medicine in steatotic liver disease

Purpose of review Discuss advances in genomics, metabolomics, and proteomics in steatotic liver disease. Recent findings Common genetic variants in genes including PNPLA3 , TM6SF2 , and HSD17B13 are associated with risk of hepatic steatosis, metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-associated liver disease (ALD) cirrhosis, and hepatocellular carcinoma. In contrast, variants in other genes such as GCKR are strongly associated with steatosis but much more weakly associated with advanced liver disease. The cirrhosis-associated variants typically drive steatosis through reduction of lipid export from the liver, potentially highlighting this mechanism as a driver of fibrosis though not ruling out alternative pathways. Alterations in amino acids, lipids, bile acids, and other metabolites have been observed in both MASLD and ALD reflecting insulin resistance, altered bile acid metabolism, and increased fatty acid flux and de novo lipogenesis (for MASLD) or mitochondrial dysfunction (for ALD). Also seen are characteristic changes in serum/plasma protein levels reflecting fibrosis, systemic inflammation, and hepatic synthetic function are also seen with MASLD and ALD. Predictive models incorporating genomics, metabolomic, and proteomic biomarkers may improve upon existing clinical models, but nearly all studies on this topic have been retrospective or post hoc. Summary Genomics, metabolomics, proteomics, and multiomics may improve our understanding of disease pathophysiology. They may also have implications for clinical care, but further prospective studies are required to establish whether they provide sufficient benefit over clinical biomarkers to be routinely used.