DataSheet_2_Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis.zip

ObjectiveThe study aimed to screen key genes in early diabetic kidney disease (DKD) and predict their biological functions and signaling pathways using bioinformatics analysis of gene chips interrelated to early DKD in the Gene Expression Omnibus database.
MethodsGene chip data for early DKD was obtained from the Gene Expression Omnibus expression profile database. We analyzed differentially expressed genes (DEGs) between patients with early DKD and healthy controls using the R language. For the screened DEGs, we predicted the biological functions and relevant signaling pathways by enrichment analysis of Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. Using the STRING database and Cytoscape software, we constructed a protein interaction network to screen hub pathogenic genes. Finally, we performed immunohistochemistry on kidney specimens from the Beijing Hospital to verify the above findings.
ResultsA total of 267 differential genes were obtained using GSE142025, namely, 176 upregulated and 91 downregulated genes. GO functional annotation enrichment analysis indicated that the DEGs were mainly involved in immune inflammatory response and cytokine effects. KEGG pathway analysis indicated that C-C receptor interactions and the IL-17 signaling pathway are essential for early DKD. We identified FOS, EGR1, ATF3, and JUN as hub sites of protein interactions using a protein–protein interaction network and module analysis. We performed immunohistochemistry (IHC) on five samples of early DKD and three normal samples from the Beijing Hospital to label the proteins. This demonstrated that FOS, EGR1, ATF3, and JUN in the early DKD group were significantly downregulated.
ConclusionThe four hub genes FOS, EGR1, ATF3, and JUN were strongly associated with the infiltration of monocytes, M2 macrophages, and T regulatory cells in early DKD samples. We revealed that the expression of immune response or inflammatory genes was suppressed in early DKD. Meanwhile, the FOS group of low-expression genes showed that the activated biological functions included mRNA methylation, insulin receptor binding, and protein kinase A binding. These genes and pathways may serve as potential targets for treating early DKD.

研究目的：本研究旨在通过对基因表达综合数据库（Gene Expression Omnibus, GEO）中与早期糖尿病肾病（diabetic kidney disease, DKD）相关的基因芯片进行生物信息学分析，筛选早期糖尿病肾病的关键基因，并预测其生物学功能与信号通路。
研究方法：本研究从基因表达综合数据库（Gene Expression Omnibus, GEO）的表达谱数据库中获取早期糖尿病肾病的基因芯片数据。采用R语言分析早期糖尿病肾病患者与健康对照者之间的差异表达基因（differentially expressed genes, DEGs）。针对筛选得到的差异表达基因，通过基因本体（Gene Ontology, GO）生物学功能富集分析与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）信号通路富集分析，预测其生物学功能与相关信号通路。借助STRING数据库与Cytoscape软件构建蛋白质相互作用网络，筛选核心致病基因。最后，采集北京医院的肾脏标本进行免疫组化实验，以验证上述分析结果。
研究结果：通过GSE142025数据集共筛选得到267个差异基因，其中上调基因176个，下调基因91个。基因本体功能注释富集分析显示，差异表达基因主要参与免疫炎症反应与细胞因子效应过程。京都基因与基因组百科全书信号通路分析表明，C-C受体相互作用及IL-17信号通路在早期糖尿病肾病中发挥关键作用。通过蛋白质相互作用网络与模块分析，筛选得到FOS、EGR1、ATF3及JUN作为蛋白质相互作用的核心基因。本研究对北京医院的5例早期糖尿病肾病标本与3例正常对照标本进行免疫组化（immunohistochemistry, IHC）染色以标记目标蛋白，结果显示早期糖尿病肾病组中FOS、EGR1、ATF3及JUN的表达水平显著下调。
研究结论：本研究筛选得到的4个核心基因FOS、EGR1、ATF3及JUN与早期糖尿病肾病样本中单核细胞、M2巨噬细胞及调节性T细胞的浸润程度显著相关。研究发现，早期糖尿病肾病中免疫应答或炎症相关基因的表达受到抑制。同时，低表达的FOS相关基因所富集的激活生物学功能包括mRNA甲基化、胰岛素受体结合及蛋白激酶A结合。上述基因与信号通路有望成为早期糖尿病肾病治疗的潜在靶点。