加权基因共表达网络分析鉴定与冠状动脉疾病相关的特定模块和枢纽基因。
Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease.
机构信息
Department of Cardiology, The Central Hospital of Shao Yang, 36 QianYuan lane, Shaoyang, 422000, Hunan, People's Republic of China.
Graduate School of Guangxi Medical University, 22 Shuangyong Road, Nanning, 530021, Guangxi, People's Republic of China.
出版信息
Sci Rep. 2021 Mar 23;11(1):6711. doi: 10.1038/s41598-021-86207-0.
This investigation seeks to dissect coronary artery disease molecular target candidates along with its underlying molecular mechanisms. Data on patients with CAD across three separate array data sets, GSE66360, GSE19339 and GSE97320 were extracted. The gene expression profiles were obtained by normalizing and removing the differences between the three data sets, and important modules linked to coronary heart disease were identified using weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and genomes (KEGG) pathway enrichment analyses were applied in order to identify statistically significant genetic modules with the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool (version 6.8; http://david.abcc.ncifcrf.gov ). The online STRING tool was used to construct a protein-protein interaction (PPI) network, followed by the use of Molecular Complex Detection (MCODE) plug-ins in Cytoscape software to identify hub genes. Two significant modules (green-yellow and magenta) were identified in the CAD samples. Genes in the magenta module were noted to be involved in inflammatory and immune-related pathways, based on GO and KEGG enrichment analyses. After the MCODE analysis, two different MCODE complexes were identified in the magenta module, and four hub genes (ITGAM, degree = 39; CAMP, degree = 37; TYROBP, degree = 28; ICAM1, degree = 18) were uncovered to be critical players in mediating CAD. Independent verification data as well as our RT-qPCR results were highly consistent with the above finding. ITGAM, CAMP, TYROBP and ICAM1 are potential targets in CAD. The underlying mechanism may be related to the transendothelial migration of leukocytes and the immune response.
本研究旨在剖析冠心病的分子靶标及其潜在的分子机制。从三个独立的基因芯片数据集 GSE66360、GSE19339 和 GSE97320 中提取了 CAD 患者的数据。通过标准化和去除三个数据集之间的差异,获得基因表达谱,并使用加权基因共表达网络分析(WGCNA)识别与冠心病相关的重要模块。为了识别具有统计学意义的遗传模块,我们使用了京都基因与基因组百科全书(KEGG)通路富集分析和基因本体论(GO)功能注释分析,并利用在线数据库 for Annotation, Visualization and Integrated Discovery (DAVID) 工具(版本 6.8;http://david.abcc.ncifcrf.gov)。使用在线 STRING 工具构建蛋白质-蛋白质相互作用(PPI)网络,然后在 Cytoscape 软件中使用 Molecular Complex Detection (MCODE) 插件识别枢纽基因。在 CAD 样本中鉴定出两个显著的模块(绿色-黄色和品红色)。基于 GO 和 KEGG 富集分析,品红色模块中的基因被认为与炎症和免疫相关途径有关。在 MCODE 分析后,在品红色模块中鉴定出两个不同的 MCODE 复合物,发现四个枢纽基因(ITGAM,度=39;CAMP,度=37;TYROBP,度=28;ICAM1,度=18)在介导 CAD 中起着关键作用。独立验证数据和我们的 RT-qPCR 结果与上述发现高度一致。ITGAM、CAMP、TYROBP 和 ICAM1 是 CAD 的潜在靶点。其潜在机制可能与白细胞跨内皮迁移和免疫反应有关。