Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction

Abstract

Acute myocardial infarction (AMI) is the most severe manifestation of coronary artery disease. Considerable efforts have been made to elucidate its etiology and pathology, but the genetic factors that play a decisive role in the occurrence of AMI are still unclear. To determine the molecular mechanism of the occurrence and development of AMI, four microarray datasets, namely, GSE29111, GSE48060, GSE66360, and GSE97320, were downloaded from the Gene Expression Omnibus (GEO) database. We analyzed the four GEO datasets to obtain the differential expression genes (DEGs) of patients with AMI and patients with non-AMI and then performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Protein-protein interaction (PPI) network analysis. A total of 41 DEGs were identified, including 39 upregulated genes and 2 downregulated genes. The enriched functions and pathways of the DEGs included the inflammatory response, neutrophil chemotaxis, immune response, extracellular space, positive regulation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcription factor activity, response to lipopolysaccharide, receptor for advanced glycation end products (RAGE) receptor binding, innate immune response, defense response to bacterium, and receptor activity. The cytoHubba plug-in in Cytoscape was used to select the most significant hub gene from the PPI network. Ten hub genes were identified, and GO enrichment analysis revealed that these genes were mainly enriched in inflammatory response, neutrophil chemotaxis, immune response, RAGE receptor binding, and extracellular region. In conclusion, this study integrated four datasets and used bioinformatics methods to analyze the gene chips of AMI samples and control samples and identified DEGs that may be involved in the occurrence and development of AMI. The study provides reliable molecular biomarkers for AMI screening, diagnosis, and prognosis.

Keywords

• acute myocardial infarction
• bioinformatics
• geo database