Department of Nephrology, XiangYa Hospital, Central South University, XiangYa Road NO 87, Changsha, 41008, Hunan, China.
Sci Rep. 2020 Aug 10;10(1):13468. doi: 10.1038/s41598-020-70540-x.
The pathogenesis of diabetic nephropathy is not completely understood, and the effects of existing treatments are not satisfactory. Various public platforms already contain extensive data for deeper bioinformatics analysis. From the GSE30529 dataset based on diabetic nephropathy tubular samples, we identified 345 genes through differential expression analysis and weighted gene coexpression correlation network analysis. GO annotations mainly included neutrophil activation, regulation of immune effector process, positive regulation of cytokine production and neutrophil-mediated immunity. KEGG pathways mostly included phagosome, complement and coagulation cascades, cell adhesion molecules and the AGE-RAGE signalling pathway in diabetic complications. Additional datasets were analysed to understand the mechanisms of differential gene expression from an epigenetic perspective. Differentially expressed miRNAs were obtained to construct a miRNA-mRNA network from the miRNA profiles in the GSE57674 dataset. The miR-1237-3p/SH2B3, miR-1238-5p/ZNF652 and miR-766-3p/TGFBI axes may be involved in diabetic nephropathy. The methylation levels of the 345 genes were also tested based on the gene methylation profiles of the GSE121820 dataset. The top 20 hub genes in the PPI network were discerned using the CytoHubba tool. Correlation analysis with GFR showed that SYK, CXCL1, LYN, VWF, ANXA1, C3, HLA-E, RHOA, SERPING1, EGF and KNG1 may be involved in diabetic nephropathy. Eight small molecule compounds were identified as potential therapeutic drugs using Connectivity Map.
糖尿病肾病的发病机制尚不完全清楚，现有治疗方法的效果也不尽人意。各种公共平台已经包含了广泛的数据，可供更深入的生物信息学分析。我们从基于糖尿病肾病管状样本的 GSE30529 数据集，通过差异表达分析和加权基因共表达网络分析，鉴定出 345 个基因。GO 注释主要包括中性粒细胞激活、免疫效应过程调节、细胞因子产生的正调控和中性粒细胞介导的免疫。KEGG 通路主要包括吞噬体、补体和凝血级联、细胞黏附分子以及糖尿病并发症中的 AGE-RAGE 信号通路。分析了额外的数据集，从表观遗传学角度了解差异基因表达的机制。从 miRNA Profiles in the GSE57674 数据集获得差异表达 miRNA，构建 miRNA-mRNA 网络。miR-1237-3p/SH2B3、miR-1238-5p/ZNF652 和 miR-766-3p/TGFBI 轴可能参与糖尿病肾病。还基于 GSE121820 数据集的基因甲基化图谱测试了 345 个基因的甲基化水平。使用 CytoHubba 工具识别 PPI 网络中的前 20 个枢纽基因。与 GFR 的相关性分析表明，SYK、CXCL1、LYN、VWF、ANXA1、C3、HLA-E、RHOA、SERPING1、EGF 和 KNG1 可能参与糖尿病肾病。使用 Connectivity Map 鉴定了 8 种小分子化合物作为潜在的治疗药物。
