The Identification of Candidate Biomarkers and Pathways in Atherosclerosis by Integrated Bioinformatics Analysis

Abstract

Background. Atherosclerosis (AS) is a type of yellow substance containing cholesterol in the intima of large and middle arteries, which is mostly caused by fat metabolism disorders and neurovascular dysfunction. Materials and Methods. The GSE100927 data got analyzed to find out the differentially expressed genes (DEGs) using the limma package in R software. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the DEGs were assessed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) visualized the Protein-Protein Interaction (PPI) network of the aggregated DEGs. GSEA software was used to verify the biological process. Result. We screened 1574 DEGs from 69 groups of atherosclerotic carotid artery and 35 groups of control carotid artery, including 1033 upregulated DEGs and 541 downregulated DEGs. DEGs of AS were chiefly related to immune response, Epstein-Barr virus infection, vascular smooth muscle contraction, and cGMP-PKG signaling pathway. Through PPI networks, we found that the hub genes of AS were PTAFR, VAMP8, RNF19A, VPRBP, RNF217, KLHL42, NEDD4, SH3RF1, UBE2N, PJA2, RNF115, ITCH, SKP1, FBXW4, and UBE2H. GSEA analysis showed that GSE100927 was concentrated in RIPK1-mediated regulated necrosis, FC epsilon receptor fceri signaling, Fceri-mediated NF KB activation, TBC rabgaps, TRAF6-mediated induction of TAK1 complex within TLR4 complex, and RAB regulation of trafficking. Conclusion. Our analysis reveals that immune response, Epstein-Barr virus infection, and so on were major signatures of AS. PTAFR, VAMP8, VPRBP, RNF217, KLHL42, and NEDD4 might facilitate the AS tumorigenesis, which could be new biomarkers for diagnosis and therapy of AS.