Identification of Potential Hub Genes of Atherosclerosis Through Bioinformatic Analysis

J Comput Biol. 2021 Jan;28(1):60-78. doi: 10.1089/cmb.2019.0334. Epub 2020 Apr 15.

Abstract

Cardiovascular and cerebrovascular diseases, which mainly consist of atherosclerosis (AS), are major causes of death. A great deal of research has been carried out to clarify the molecular mechanisms of AS. However, the etiology of AS remains poorly understood. To screen the potential genes of AS occurrence and development, GSE43292 and GSE57691 were obtained from the Gene Expression Omnibus (GEO) database in this study for bioinformatic analysis. First, GEO2R was used to identify differentially expressed genes (DEGs) and the functional annotation of DEGs was performed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The Search Tool for the Retrieval of Interacting Genes (STRING) tool was used to construct the protein-protein interaction network and the most important modules and core genes were mined. The results show that a total of 211 DEGs are identified. The functional changes of DEGs are mainly associated with the cellular process, catalytic activity, and protein binding. Eighteen genes were identified as core genes. Bioinformatic analysis showed that the core genes are mainly enriched in numerous processes related to actin. In conclusion, the DEGs and hub genes identified in this study may help us understand the potential etiology of the occurrence and development of AS.

Keywords: atherosclerosis; bioinformatic analysis; cardiac-cerebral vascular diseases; differentially expressed genes; protein-protein interaction.

MeSH terms

  • Atherosclerosis / genetics*
  • Gene Regulatory Networks*
  • Genetic Predisposition to Disease
  • Genomics / methods*
  • Humans