基于加权基因共表达网络分析高血压的关键基因

Identification of key genes in hypertension through weighted gene co-expression network analysis

目的挖掘分析高血压的关键基因,为阐明高血压的发病机制提供生物信息学支持。方法从GEO数据库下载GSE 74144数据进行差异表达基因(DEG)分析,并使用WGCNA包筛选高血压临床特征相关的模块和基因,而后用ClusterProfiler进行基因功能的注释富集分析。将DEG与WGCNA中的性状模块基因取交集,获取关键基因,并对其进行相关性分析。结果共筛选出79个DEGs,主要与氧化磷酸化、线粒体内膜蛋白复合物形成和呼吸小体形成等有关。获得1个与高血压高度相关的模块,主要参与血小板活化、局部粘附、RAP1信号通路等,并获取12个关键基因FAM69B、FLJ44511、EPB49、CDKN2A、ND2、OST4、HIST1H2BI、ODF3L2、SPARC、MMD、TMEM140和DDX11L2。结论通过WGCNA获得与高血压高度相关的模块和12个关键基因,为更深入地探索高血压发生发展机制提供理论依据。

Objective To excavate the key genes in hypertension,and provide bioinformatics support for elucidating the pathogenesis of hypertension.Methods GSE74144 data was downloaded from the GEO database for differentially expressed genes(DEG)analysis,and the weighted gene coexpression network analysis(WGCNA)package was used to screen the modules and genes related to clinical features of hypertension,and then ClusterProfiler was applied to perform annotation enrichment analysis of gene function.Besides,the intersection of the trait module genes in DEG and WGCNA was taken to obtain the key genes and performed the correlation analysis on them.Results A total of 79 DEGs were identified,which were mainly related to the oxidative phosphorylation,the formation of mitochondrial inner membrane protein complexes and respiratory corpuscles.A module related to hypertension was obtained,which was mainly involved in the platelet activation,local adhesion,RAP1 signaling pathway,etc.12 key gene swere identified,including FAM69 B,FLJ44511,EPB49,CDKN2 A,ND2,OST4,HIST1 H2 BI,ODF3 L2,SPARC,MMD,TMEM140,and DDX11 L2.Conclusion The highly related modules and 12 key genes are obtained by WGCNA,which provides a theoretical basis for further exploration of the pathogenesis of hypertension.