Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease - Dang, Ruoyu; Qu, Bojian; Guo, Kaimin; Zhou, Shuiping; Sun, He; Wang, Wenjia; Han, Jihong; Feng, Ke; Lin, Jianping; Hu, Yunhui (Frontiers in Genetics, 2022)
Background: Coronary artery disease exerts as a global challenge to the public health. Genetic heritability is one of the most vital contributing factors in CAD pathophysiology. Co-expression network analysis is an applicable and robust method to interpret biological interaction from microarray data. Previous CAD studies focus on peripheral blood samples, since the processes of CAD may vary from tissue to blood, it is necessary to find biomarkers for CAD in heart tissue, and the association requires to be further illustrated. Materials and Methods: To filter for causal genes, an analysis of microarray expression profile GSE12504 and GSE22253 were performed with WGCNA. Co-expression modules were constructed after batch effect removal and data normalization. The result showed 7 co-expression modules with 8,525 genes and 1,210 DEGs were identified. Further, GO and KEGG enrichment analysis was conducted and 4 major pathways in CAD tissue and hub genes were addressed in HMDP/HPA, ISO/DOX induced heart toxicity models were used to validate hub genes. Lastly, the hub gene and risk variants were verified in CAD cohort and GWAS studies. Results: The results showed RNF181 along with other 8 hub genes are perturbed during CAD in heart tissues. Additionally, the expression of RNF181 were validated using RT-PCR as well as immunohistochemical (IHC) staining in two cardiotoxicity mouse model, the association is further verified in CAD patient cohort and GWAS studies. Conclusion: Our findings illustrate for the first time that the E3 ubiquitination ligase protein, RNF181, may serve as a potential biomarker in CAD and further in vivo validation are warranted.