Work

Multi-Omics Analysis and Validation of Cell Senescence-Related Genes Associated with Non-Alcoholic Fatty Liver Disease

Year: 2025

Type: article

Abstract: Objective: To assess causal links between senescence-related genes and non-alcoholic fatty liver disease (NAFLD) using summary-data Mendelian randomization (SMR) and colocalization analyses. Methods: Our study examined the relationship between senescence and NAFLD by integrating DNA methylation, gene expression, and protein quantitative trait loci (mQTL, eQTL, and pQTL) data. Summary statistics for NAFLD were sourced from a previous study (discovery) and the FinnGen database (replication), with additional cohorts for nonalcoholic steatohepatitis and liver fibrosis. Genetic variants near senescence-related genes were used as instrumental variables to assess causal relationships. Colocalization analysis was performed to confirm shared causal variants and liver-specific eQTL data were used for validation. Furthermore, we validated findings using cell and mouse models of NAFLD. Cell models were treated with oleic acid, and NAFLD mice were induced using a high-fat diet. Results: We identified 40 mQTLs, 9 eQTLs, and 3 pQTLs significantly linked to NAFLD in the discovery cohort. Multi-omics data highlighted three genes— S100A6, ENDOG , and TP53I3 —as potential causal contributors. Notably, S100A6 was confirmed at both the methylation sites (cg24155129 and cg01910639) and gene expression levels, with methylation at these CpG sites significant regulating its expression. Liver-specific validation revealed that ENDOG expression was negatively associated with NAFLD, consistent with findings in blood. Finally, differential expression of all three genes was confirmed in cell models, with S100A6 and ENDOG further validated in a mouse model. Conclusion: Our findings suggest that S100A6, ENDOG , and TP53I3 are associated with NAFLD, providing insights for further research into the disease’s underlying etiology. Keywords: cellular senescence, non-alcoholic fatty liver disease, causal inference, Mendelian randomization, colocalization

Source: Journal of Inflammation Research

DOI: 10.2147/jir.s525168