Comprehensive analysis to identify age-associated genes in atherosclerosis and explore specific mechanisms

Abstract

Abstract Age is an independent risk factor for atherosclerosis. However, the precise mechanisms between them remain unclear, and this study combined aging and atherosclerosis genes in a comprehensive analysis. Gene expression profiles were obtained from the GEO database, and limma difference analysis and weighted correlation network analysis (WGCNA) were carried out on them respectively. Functional enrichment analysis and genomic enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) databases. The CIBERSORT algorithm was used to analyze the immune cell infiltration between the disease and control groups. The LASSO algorithm was used to obtain the hub gene and a diagnostic model was developed and finally validated in an external dataset. We identified that CCL3 expression is increased in senescent macrophages and regulates macrophage polarization by binding to CCR5. In this study, we analyzed the biological significance of aging-related genes in atherosclerosis and their correlation with immune infiltration, which may provide a new perspective for clinical treatment.