Identification of and as potential biomarkers of atherosclerosis via Gene Set Enrichment Analysis

Abstract

Objective Atherosclerosis (AS) is a life-threatening disease in aging populations worldwide. However, the molecular and gene regulation mechanisms of AS are still unclear. This study aimed to identify gene expression differences between atheroma plaques and normal tissues in humans. Methods The expression profiling dataset GSE43292 was obtained from the Gene Expression Omnibus (GEO) dataset. The differentially expressed genes (DEGs) were identified between the atheroma plaques and normal tissues via GEO2R, and functional annotation of the DEGs was performed by GSEA. STRING and MCODE plug-in of Cytoscape were used to construct a protein–protein interaction (PPI) network and analyze hub genes. Finally, quantitative polymerase chain reaction (qPCR) was performed to verify the hub genes. Results Overall, 134 DEGs were screened. Functional annotation demonstrated that these DEGs were mainly enriched in sphingolipid metabolism, apoptosis, lysosome, and more. Six hub genes were identified from the PPI network: ITGAX , CCR1 , IL1RN , CXCL10 , CD163 , and MMP9 . qPCR analysis suggested that the relative expression levels of the six hub genes were significantly higher in AS samples. Conclusions We used bioinformatics to identify six hub genes: ITGAX, CCR1, IL1RN, CXCL10, CD163 , and MMP9 . These hub genes are potential promising diagnostic and therapeutic targets for AS.