Bioinformatics analysis of potential ferroptosis and non-alcoholic fatty liver disease biomarkers.

Abstract

Ferroptosis plays a crucial role in the development of non-alcoholic fatty liver disease (NAFLD). In this study, we aimed to use a comprehensive bioinformatics approach and experimental validation to identify and verify potential ferroptosis-related genes in NAFLD. We downloaded the microarray datasets for screening differentially expressed genes (DEGs) and identified the intersection of these datasets with ferroptosis-related DEGs from the Ferroptosis database. Subsequently, ferroptosis-related DEGs were obtained using SVM analysis; the LASSO algorithm was then used to identify six marker genes. Furthermore, the CIBERSORT algorithm was used to estimate the proportion of different types of immune cells. Subsequently, we constructed drug regulatory networks and ceRNA regulatory networks. We identified six genes as marker genes for NAFLD, demonstrating their robust diagnostic abilities. Subsequent functional enrichment analysis results revealed that these marker genes were associated with multiple diseases and play a key role in NAFLD via the regulation of immune response and amino acid metabolism, among other pathways. The expression of hepatic EGR1, IL-6, SOCS1, and NR4A1 was significantly downregulated in the NAFLD model. Our findings provide new insights and molecular clues for understanding and treating NAFLD. Further studies are needed to assess the diagnostic potential of these markers for NAFLD.