{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T04:38:37Z","timestamp":1790829517877,"version":"4.1.0"},"reference-count":61,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:00:00Z","timestamp":1620691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:p><jats:bold>Background:<\/jats:bold> Valvular heart disease is obtaining growing attention in the cardiovascular field and it is believed that calcific aortic valve disease (CAVD) is the most common valvular heart disease (VHD) in the world. CAVD does not have a fully effective treatment to delay its progression and the specific molecular mechanism of aortic valve calcification remains unclear.<\/jats:p><jats:p><jats:bold>Materials and Methods:<\/jats:bold> We obtained the gene expression datasets GSE12644 and GSE51472 from the public comprehensive free database GEO. Then, a series of bioinformatics methods, such as GO and KEGG analysis, STING online tool, Cytoscape software, were used to identify differentially expressed genes in CAVD and healthy controls, construct a PPI network, and then identify key genes. In addition, immune infiltration analysis was used via CIBERSORT to observe the expression of various immune cells in CAVD.<\/jats:p><jats:p><jats:bold>Results:<\/jats:bold> A total of 144 differential expression genes were identified in the CAVD samples in comparison with the control samples, including 49 up-regulated genes and 95 down-regulated genes. GO analysis of DEGs were most observably enriched in the immune response, signal transduction, inflammatory response, proteolysis, innate immune response, and apoptotic process. The KEGG analysis revealed that the enrichment of DEGs in CAVD were remarkably observed in the chemokine signaling pathway, cytokine-cytokine receptor interaction, and PI3K-Akt signaling pathway. Chemokines CXCL13, CCL19, CCL8, CXCL8, CXCL16, MMP9, CCL18, CXCL5, VCAM1, and PPBP were identified as the hub genes of CAVD. It was macrophages that accounted for the maximal proportion among these immune cells. The expression of macrophages M0, B cells memory, and Plasma cells were higher in the CAVD valves than in healthy valves, however, the expression of B cells na\u00efve, NK cells activated, and macrophages M2 were lower.<\/jats:p><jats:p><jats:bold>Conclusion:<\/jats:bold> We detected that chemokines CXCL13, CXCL8, CXCL16, and CXCL5, and CCL19, CCL8, and CCL18 are the most important markers of aortic valve disease. The regulatory macrophages M0, plasma cells, B cells memory, B cells na\u00efve, NK cells activated, and macrophages M2 are probably related to the occurrence and the advancement of aortic valve stenosis. These identified chemokines and these immune cells may interact with a subtle adjustment relationship in the development of calcification in CAVD.<\/jats:p>","DOI":"10.3389\/fgene.2021.650213","type":"journal-article","created":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T08:00:55Z","timestamp":1620720055000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Predicting the Key Genes Involved in Aortic Valve Calcification Through Integrated Bioinformatics Analysis"],"prefix":"10.3389","volume":"12","author":[{"given":"Dinghui","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianhua","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenlong","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaihu","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"She","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2021,5,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1002194","article-title":"Patterns ofImmune infiltration in breast cancer and their clinical implications: a gene-expression-based retrospective study.","volume":"13","author":"Ali","year":"2016","journal-title":"PLoS Med."},{"key":"B2","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.pharmthera.2010.04.006","article-title":"Chemokine receptors intracellular trafficking.","volume":"127","author":"Borroni","year":"2010","journal-title":"Pharmacol. 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