Identifying miRNA-TF-mRNA Regulatory Network for Aortic Valve Calcification Diseases Through Bioinformatics Analysis

Background: Calcareous aortic valve disease(CAVD) is widespread in society, and its incidence seems to increase with the age of the global population. However, the specific pathogenesis of calcareous aortic valve disease remains unclear. The purpose of the research is to construct miRNA-TF-mRNA regulatory networks and find the key genes, microRNAs (miRNAs) and transcription factors (TFs) to clarify the pathogenesis of CAVD and provide new treatment methods for CAVD. Methods: GSE51472, GSE87885 and GSE12644 datasets were downloaded from Gene Expression Omnibus (GEO) database. Differentailly expressed genes (DEGs) and differentially expressed miRNAs(DEMs) were identified through integrative analysis by R software. Moreover, KEGG pathway analysis and Gene Ontology (GO) analysis were performed using the clusterProfiler R package. Then, STRING database, Cytoscape and Cytohubba were applied to construct the protein-protein interaction (PPI) network and screen hub genes. Finally, a miRNA-TF-mRNA network was constructed based on bioinformatics data based on the TRRUST, miRWalk and miRtarbase database. And through the verification of dataset GSE12644, we have determined the key regulatory factors. Results: We have established a regulatory network of miRNA-TF-mRNA includes 17 genes,17 miRNAs and 12 TFs. In the miRNA-TF-mRNA network, genes VCAM1, ITGB2, CD86, transcription factors HIF1A, KLF2 are identified as key regulators. Conclusions: Our study has constructed a regulatory network of miRNA-TF-mRNA in CAVD, which may provide new insights about the interaction between genes, miRNAs and TFs in the pathogenesis of CAVD, and identify potential biomarkers or therapeutic targets for CAVD, which may reveal promising approaches for CAVD diagnosis and therapy.