Exploring the pathogenesis of nonalcoholic fatty liver disease complicated by atherosclerosis via bioinformatics

Abstract

This study aimed to explore the common differentially expressed genes (DEGs) between atherosclerosis (AS) and nonalcoholic fatty liver disease (NAFLD) through bioinformatics. The GSE89632 and GSE100927 datasets from the open-source GEO database were selected for analysis in this study. DEGs between the control and disease groups were identified from the datasets of NAFLD and AS, leading to the identification of genes that are commonly dysregulated in both conditions. Gene set enrichment analysis (GSEA) was performed on 2 datasets, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to investigate the potential biological functions and signaling pathways associated with the common DEGs. A protein-protein interaction network was constructed using the STRING database to identify hub genes. The diagnostic efficacy of these hub genes was evaluated through receiver operating characteristic curve analysis of the GSE63067 and GSE57691 datasets. A total of 45 common DEGs were identified. GSEA indicated that there were common pathways in the GSE89632 and GSE100927 datasets. The GO and KEGG pathway enrichment analyses revealed that the co-expressed genes were mainly enriched in regulating cytokine production, increasing responsiveness to external stimuli, and macrophage activation. The identified signaling pathways primarily included cytokine-cytokine receptor interaction, the toll-like receptor signaling pathway, and the interleukin-17 signaling pathway. Ten hub genes were OSM, IL1B, CCL3, CSF3, IL1RN, TAGLN, CNN1, RGCC, MYH11, and ACTG2. Common DEGs were identified between AS and NAFLD, indicating that these diseases may mutually influence and exacerbate each other during their progression. Exploring their shared pathogenic mechanisms may provide insights into potential therapeutic targets and contribute to the prevention of AS development in patients with NAFLD.

Keywords: atherosclerosis; bioinformatics; comorbidity; diagnostic markers; differentially expressed genes; nonalcoholic fatty liver disease; pathogenesis.