PNPLA3 gene in liver diseases
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Updated: Mar 23, 2026

Murine Precision-Cut Liver Slices as an Ex Vivo Model of Liver Biology
Published on: March 14, 2020
Eric Trépo1, Stefano Romeo2, Jessica Zucman-Rossi3
1Inserm, UMR-1162, Génomique Fonctionnelle des Tumeurs Solides, Equipe Labellisée Ligue Contre le Cancer, Institut Universitaire d'Hématologie, Paris, France; Department of Gastroenterology, Hepatopancreatology, and Digestive Oncology, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Experimental Gastroenterology, Université Libre de Bruxelles, Brussels, Belgium.
Abstract:
Genome-wide association studies (GWAS) in the field of liver diseases have revealed previously unknown pathogenic loci and generated new biological hypotheses. In 2008, a GWAS performed in a population-based sample study, where hepatic liver fat content was measured by magnetic spectroscopy, showed a strong association between a variant (rs738409 C>G p.I148M) in the patatin-like phospholipase domain containing 3 (PNPLA3) gene and nonalcoholic fatty liver disease. Further replication studies have shown robust associations between PNPLA3 and steatosis, fibrosis/cirrhosis, and hepatocellular carcinoma on a background of metabolic, alcoholic, and viral insults. The PNPLA3 protein has lipase activity towards triglycerides in hepatocytes and retinyl esters in hepatic stellate cells. The I148M substitution leads to a loss of function promoting triglyceride accumulation in hepatocytes. Although PNPLA3 function has been extensively studied, the molecular mechanisms leading to hepatic fibrosis and carcinogenesis remain unclear. This unsuspected association has highlighted the fact that liver fat metabolism may have a major impact on the pathophysiology of liver diseases. Conversely, alone, this locus may have limited predictive value with regard to liver disease outcomes in clinical practice. Additional studies at the genome-wide level will be required to identify new variants associated with liver damage and cancer to explain a greater proportion of the heritability of these phenotypes. Thus, incorporating PNPLA3 and other genetic variants in combination with clinical data will allow for the development of tailored predictive models. This attractive approach should be evaluated in prospective cohorts.
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