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Monogenic and Polygenic Risk in Common Liver Diseases: Implications for Clinical Care
Veeral Ajmera1, Daniel Q Huang2, Vincent L Chen3
1Division of Gastroenterology, University of California in San Diego, La Jolla, California.
Abstract:
The burden of chronic liver disease is rapidly increasing worldwide, driven primarily by metabolic dysfunction-associated steatotic liver disease, metabolic and alcohol-associated liver disease (MetALD), and alcohol-associated liver disease (ALD). Genetic predisposition contributes substantially to variability in disease onset, progression, and outcomes, and recent advances in genomic discovery have brought polygenic risk scores (PRSs) and targeted sequencing closer to clinical relevance. This review summarizes the role of genetic testing in clinical hepatology, including monogenic drivers of disease and the growing role of common variants and PRS. Specific populations, including patients with cryptogenic cirrhosis and lean metabolic dysfunction-associated steatotic liver disease, may be enriched for monogenic drivers of disease. In addition, patients with chronic liver disease may benefit from incorporation of genetic risk scores, including PNPLA3, TM6SF2, HSD17B13, and other key variants in determining risk for fibrosis progression and cirrhosis. Across metabolic dysfunction-associated steatotic liver disease and alcohol-associated liver disease, PRSs demonstrate modest improvements in predicting fibrosis progression and liver-related events, especially when integrated with clinical risk factors and comorbidities. However, their performance remains limited for population-level screening. Similarly, PRS alone has limited diagnostic accuracy for hepatocellular carcinoma and more complex models with clinical features and multiomic biomarkers are likely needed. Emerging therapies targeting PNPLA3 and HSD17B13 variants represent a paradigm shift toward genetically informed treatment. Yet challenges remain, including limited ancestral diversity in genomic datasets, pleiotropic effects of variants, cost-effectiveness, and the need for integration with other omics and electronic medical records. As evidence matures, combining genetic risk with clinical and environmental factors may enable more personalized approaches to prognostication and therapy in liver disease.
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