Identification of key genes in calcific aortic valve disease via weighted gene co-expression network analysis

BMC Medical Genomics

Yue-Yun Shen¹  Jun-Yan Kan²  Yang Hua²  Xiang-Qing Kong²  Jin-Yu Sun²  Qiang Qu²  Wei Sun²  Hui Shen² 

[1] Department of Cardiology, Liyang People’s Hospital, 213300, Liyang, China;Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210000, Nanjing, China;

关键词: Calcific aortic valve disease;    Weighted gene co-expression network analysis;    Differentially expressed genes;    Integrated bioinformatics analysis;   

DOI  :  10.1186/s12920-021-00989-w

来源: Springer

【 摘 要 】

BackgroundCalcific aortic valve disease (CAVD) is the most common subclass of valve heart disease in the elderly population and a primary cause of aortic valve stenosis. However, the underlying mechanisms remain unclear.MethodsThe gene expression profiles of GSE83453, GSE51472, and GSE12644 were analyzed by ‘limma’ and ‘weighted gene co-expression network analysis (WGCNA)’ package in R to identify differentially expressed genes (DEGs) and key modules associated with CAVD, respectively. Then, enrichment analysis was performed based on Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, DisGeNET, and TRRUST database. Protein–protein interaction network was constructed using the overlapped genes of DEGs and key modules, and we identified the top 5 hub genes by mixed character calculation.ResultsWe identified the blue and yellow modules as the key modules. Enrichment analysis showed that leukocyte migration, extracellular matrix, and extracellular matrix structural constituent were significantly enriched. SPP1, TNC, SCG2, FAM20A, and CD52 were identified as hub genes, and their expression levels in calcified or normal aortic valve samples were illustrated, respectively.ConclusionsThis study suggested that SPP1, TNC, SCG2, FAM20A, and CD52 might be hub genes associated with CAVD. Further studies are required to elucidate the underlying mechanisms and provide potential therapeutic targets.

【 授权许可】

CC BY