Identification of Underlying Hub Genes Associated with Hypertrophic Cardiomyopathy by Integrated Bioinformatics Analysis

作者：Zetao Ma, Xizhi Wang, Qingbo Lv, Yingchao Gong, Minghong Xia, Lenan Zhuang, Xue Lü, Ying Yang, Wenbin Zhang, Guosheng Fu, Yang Ye, Dongwu Lai · 发表于：Pharmacogenomics and Personalized Medicine · 年份：2021 · DOI：10.2147/pgpm.s314880 · 被引用次数：12 · 研究领域：Cardiac Fibrosis and Remodeling、Cardiomyopathy and Myosin Studies、Congenital heart defects research

BACKGROUND: Considered as one of the major reasons of sudden cardiac death, hypertrophic cardiomyopathy (HCM) is a common inherited cardiovascular disease. However, effective treatment for HCM is still lacking. Identification of hub gene may be a powerful tool for discovering potential therapeutic targets and candidate biomarkers. METHODS: We analysed three gene expression datasets for HCM from the Gene Expression Omnibus. Two of them were merged by "sva" package. The merged dataset was used for analysis while the other dataset was used for validation. Following this, a weighted gene coexpression network analysis (WGCNA) was performed, and the key module most related to HCM was identified. Based on the intramodular connectivity, we identified the potential hub genes. Then, a receiver operating characteristic curve analysis was performed to verify the diagnostic values of hub genes. Finally, we validated changes of hub genes, for genetic transcription and protein expression levels, in datasets of HCM patients and myocardium of transverse aortic constriction (TAC) mice. RESULTS: In the merged dataset, a total of 455 differentially expressed genes (DEGs) were identified from normal and hypertrophic myocardium. In WGCNA, the blue module was identified as the key module and the genes in this module showed a high positive correlation with HCM. Functional enrichment analysis of DEGs and key module revealed that the extracellular matrix, fibrosis, and neurohormone pathways played imp...