Identification of key genes in calcific aortic valve disease by integrated bioinformatics analysis

Calcific aortic valve disease (CAVD) is highly prevalent in our aging world and has no effective pharmaceutical treatment. Intense efforts have been made but the underlying molecular mechanisms of CAVD are still unclear. This study was designed to identify the critical genes and pathways in CAVD by bioinformatics analysis. Microarray datasets of GSE12644, GSE51472, and GSE83453 were obtained from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and functional and pathway enrichment analysis was performed. Subsequently, the protein–protein interaction network (PPI) was constructed with Search Tool for the Retrieval of Interacting Genes and was visualized with Cytoscape to identify the most significant module. Hub genes were identified by Cytoscape plugin cytoHubba. A total of 179 DEGs, including 101 upregulated genes and 78 downregulated genes, were identified. The enriched functions and pathways of the DEGs include inflammatory and immune response, chemotaxis, extracellular matrix (ECM) organization, complement and coagulation cascades, ECM receptor interaction, and focal adhesion. The most significant module in the PPI network was analyzed and genes among it were mainly enriched in chemotaxis, locomotory behavior, immune response, chemokine signaling pathway, and extracellular space. In addition, DEGs, with degrees ≥ 10 and the top 10 highest Maximal Chique Centrality (MCC) score, were identified as hub genes. CCR1, MMP9, VCAM1, and ITGAX, which were of the highest degree or MCC score, were manually reviewed. The DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the pathogenesis of CAVD and might serve as candidate therapeutic targets for CAVD.