RUNX1 and CCL3 in Diabetes Mellitus-Related Coronary Artery Disease: A Bioinformatics Analysis

作者：Yi Zhong, Guoyong Du, Jie Liu, Shaohua Li, Junhua Lin, Guo‐Xiong Deng, Jinru Wei, Jun Huang · 发表于：DOAJ (DOAJ: Directory of Open Access Journals) · 年份：2022 · 被引用次数：15 · 研究领域：Bioinformatics and Genomic Networks、Peroxisome Proliferator-Activated Receptors、Atherosclerosis and Cardiovascular Diseases

Yi Zhong,1,2,* Guoyong Du,1,2,* Jie Liu,1,2,* Shaohua Li,1 Junhua Lin,1 Guoxiong Deng,1,2 Jinru Wei,1,2 Jun Huang1,2 1Department of Cardiology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China; 2Department of Cardiology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jinru Wei; Jun Huang, Tel +867712636193, Email weijinru@stu.gxmu.edu.cn; huangjijun1981@163.comBackground: Cardiovascular complications are a major cause of death and disability in patients with diabetes mellitus, but how such complications arise is unclear.Methods: Weighted gene correlation network analysis (WGCNA) was performed on gene expression profiles from healthy controls, individuals with diabetes mellitus, and individuals with diabetes mellitus-associated coronary artery disease (DMCAD). Phenotypically related module genes were analyzed for enrichment in Gene Ontology (GO) terms and Kyoto Gene and Genome Encyclopedia (KEGG) pathways. Predicted biological functions were validated using gene set enrichment analysis (GSEA) and ClueGo analysis. Based on the TRRUST v2 database and hypergeometric tests, a global network was built to identify transcription factors (TFs) and downstream target genes potentially involved in DMCAD.Results: WGCNA identified three modules associated with progression from d...