Potential Regulatory Role of lncRNA-miRNA-mRNA in Coronary Artery Disease (CAD).

Coronary artery disease (CAD) is a high-incidence of heart disease. We aimed to identify potential biomarkers linked to the progression of CAD using multiple sets of data mining analysis methods. The long noncoding RNA (lncRNA) + messenger RNA (mRNA) data set GSE113079 and microRNA (miRNA) data set GSE28858 were downloaded from Gene Expression Omnibus. After data preprocessing, differentially expressed mRNA, lncRNA, and miRNA were identified using limma software. In addition, weighted gene co-expression network analysis (WGCNA) was used for the construction and screening of modules related to disease states. Besides, key mRNAs and lncRNAs were extracted for protein-protein interaction (PPI) network construction and lncRNA-mRNA co-expression analysis. Additionally, the final integration resulted in the lncRNA-miRNA-mRNA relationship pairs (competing endogenous RNA (ceRNA) network). Finally, CTD 2020 update database was used for the verification of the expression level of the candidate genes. A total of 1319 differentially expressed mRNAs and 1983 lncRNAs were screened. After WGCNA, a total of 234 mRNAs and 546 lncRNAs were identified. A PPI network including 127 mRNA corresponding proteins was constructed. The ceRNA network included 24 up-regulated lncRNAs, 16 down-regulated miRNAs, and 42 up-regulated mRNAs. Through the validation of CTD 2020 update database, 21 CAD related mRNAs, and four important ceRNAs those may be participated in the pathogenesis of CAD were obtained. In this study, through multiple sets of data mining methods, the regulatory relationship of lncRNA, miRNA, and mRNA was comprehensively analyzed, and the important role of lncRNA-miRNA-mRNA in the pathogenesis of CAD was emphasized.