Integrated Weighted Gene Co-expression Network Analysis Identified That TLR2 and CD14 Are Related to Coronary Artery Disease

作者：Bin Qi, Jianhong Chen, Lin Tao, Chuan-Meng Zhu, Yong Wang, Guo‐Xiong Deng, Liu Miao · 发表于：Frontiers in Genetics · 年份：2021 · DOI：10.3389/fgene.2020.613744 · 被引用次数：14 · 研究领域：Atherosclerosis and Cardiovascular Diseases、Bioinformatics and Genomic Networks、Ferroptosis and cancer prognosis

The current research attempted to identify possible hub genes and pathways of coronary artery disease (CAD) and to detect the possible mechanisms. Array data from GSE90074 were downloaded from the Gene Expression Omnibus (GEO) database. Integrated weighted gene co-expression network analysis (WGCNA) was performed to analyze the gene module and clinical characteristics. Gene Ontology annotation (GO), Disease Ontology (DO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by clusterProfiler and the DOSE package in R. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using Molecular Complex Detection (MCODE) to identify hub genes. Then, further functional validation of hub genes in other microarrays and population samples was performed, and survival analysis was performed to investigate the prognosis. A total of 660 genes were located in three modules and associated with CAD. GO functions identified 484 biological processes, 39 cellular components, and 22 molecular functions with an adjusted P < 0.05. In total, 38 pathways were enriched in KEGG pathway analysis, and 147 DO items were identified with an adjusted P < 0.05 (false discovery rate, FDR set at < 0.05). There was a total of four modules with a score > 10 after PPI network analysis using the MCODE app, and two hub genes ( TLR2 and CD14 ) were identified. Then, we validated ...