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PNPLA3-I148M genetic variant rewires lipid metabolism to drive programmed cell death in human hepatocytes

GSE309786 Homo sapiens Expression profiling by high throughput sequencing 8 samples Submitted 2025/11/20 Platform GPL18573
Summary
Genetic variants in lipid metabolism influence the risk of developing metabolic dysfunction-associated steatotic liver disease (MASLD), cirrhosis, and end-stage liver disease (ESLD). The mechanisms by which these variants drive disease are poorly understood. Because of the PNPLA3-I148M variant's strong correlation with all stages of the MASLD spectrum and the lack of tractable therapeutic targets, we sought to understand its impact on cellular function and liver metabolism. Primary human hepatocytes (HAH) and iPSC-derived hepatocytes (iHeps) from healthy individuals possessing the PNPLA3-I148M mutation were characterized for changes in lipid metabolism, cellular stress, and survival. Using lipidomics, metabolomics, stable isotope tracing, and flux propensity analysis, we created a comprehensive metabolic profile of the changes associated with the PNPLA3-I148M variant. Functional analysis showed that the presence of the PNPLA3-I148M variant increased endoplasmic reticulum stress, mitochondrial dysfunction, and peroxisomal β-oxidation, ultimately leading to cell death via ferroptosis. Nutritional interventions, ferroptosis-specific inhibitors, and genetic approaches modulating GPX4 activity in PNPLA3-I148M HAH and iHeps decreased programmed cell death. Our findings indicate that therapies targeting ferroptosis in patients carrying the PNPLA3-I148M variant could affect the development of MASLD and ESLD and highlight the utility of iPSC-based models for the study of genetic contributions to hepatic disorders.
Published in
PNPLA3-I148M genetic variant rewires lipid metabolism to drive programmed cell death in human hepatocytes
Florentino RM, Animasahun O, Haep N et al. · JCI insight 2025 · PMID 41118258 · doi:10.1172/jci.insight.193805
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Also filed as BioProject PRJNA1363171 and SRA study SRP644312. Searching any of these in the dataset finder brings you back here.

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