Department of Endocrinology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P. R. China.
Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Cancer Institute, Zhejiang University School of Medicine, Hangzhou, P. R. China.
Biosci Rep. 2020 Jul 31;40(7). doi: 10.1042/BSR20200507.
This research was carried out to reveal specific hub genes involved in diabetic heart failure, as well as remarkable pathways that hub genes locate. The GSE26887 dataset from the GEO website was downloaded. The gene co-expression network was generated and central modules were analyzed to identify key genes using the WGCNA method. Functional analyses were conducted on genes of the clinical interest modules via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment, associated with protein-protein interaction (PPI) network construction in a sequence. Centrality parameters of the PPI network were determined using the CentiScape plugin in Cytoscape. Key genes, defined as genes in the ≥95% percentile of the degree distribution of significantly perturbed networks, were identified. Twenty gene co-expression modules were detected by WGCNA analysis. The module marked in light yellow exhibited the most significant association with diabetes (P=0.08). Genes involved in this module were primarily located in immune response, plasma membrane and receptor binding, as shown by the GO analysis. These genes were primarily assembled in endocytosis and phagosomes for KEGG pathway enrichment. Three key genes, STK39, HLA-DPB1 and RAB5C, which may be key genes for diabetic heart failure, were identified. To our knowledge, our study is the first to have constructed the co-expression network involved in diabetic heart failure using the WGCNA method. The results of the present study have provided better understanding the molecular mechanism of diabetic heart failure.
本研究旨在揭示糖尿病心力衰竭相关的特定枢纽基因，并鉴定枢纽基因所在的显著通路。从 GEO 网站下载 GSE26887 数据集。使用 WGCNA 方法生成基因共表达网络，并分析中心模块，以识别关键基因。通过京都基因与基因组百科全书（KEGG）通路和基因本体论（GO）富集对临床感兴趣模块中的基因进行功能分析，与蛋白质-蛋白质相互作用（PPI）网络的构建相关。使用 Cytoscape 中的 CentiScape 插件确定 PPI 网络的中心性参数。关键基因定义为显著扰动网络的度分布的≥95%分位数中的基因。通过 WGCNA 分析检测到 20 个基因共表达模块。标记为浅黄色的模块与糖尿病的关联最显著（P=0.08）。GO 分析显示，该模块中的基因主要位于免疫反应、质膜和受体结合中。KEGG 通路富集显示，这些基因主要组装在内吞作用和吞噬体中。鉴定出三个关键基因 STK39、HLA-DPB1 和 RAB5C，它们可能是糖尿病心力衰竭的关键基因。据我们所知，我们的研究首次使用 WGCNA 方法构建了与糖尿病心力衰竭相关的共表达网络。本研究的结果为更好地理解糖尿病心力衰竭的分子机制提供了依据。
