Identification of Differentially Expressed Genes and Prediction of Expression Regulation Networks in Dysfunctional Endothelium

Abstract

The detection of early coronary atherosclerosis (ECA) is still a challenge and the mechanism of endothelial dysfunction remains unclear. In the present study, we aimed to identify differentially expressed genes (DEGs) and the regulatory network of miRNAs as well as TFs in dysfunctional endothelium to elucidate the possible pathogenesis of ECA and find new potential markers. The GSE132651 data set of the GEO database was used for the bioinformatic analysis. Principal component analysis (PCA), the identification of DEGs, correlation analysis between significant DEGs, the prediction of regulatory networks of miRNA and transcription factors (TFs), the validation of the selected significant DEGs, and the receiver operating characteristic (ROC) curve analysis as well as area under the curve (AUC) values were performed. We identified ten genes with significantly upregulated signatures and thirteen genes with significantly downregulated signals. Following this, we found twenty-two miRNAs regulating two or more DEGs based on the miRNA–target gene regulatory network. TFs with targets ≥ 10 were E2F1, RBPJ, SSX3, MMS19, POU3F3, HOXB5, and KLF4. Finally, three significant DEGs (TOX, RasGRP3, TSPAN13) were selected to perform validation experiments. Our study identified TOX, RasGRP3, and TSPAN13 in dysfunctional endothelium and provided potential biomarkers as well as new insights into the possible molecular mechanisms of ECA.