Zhang Yumin, Li Wei, Zhou Yunting
Department of Endocrinology, Zhongda Hospital, Southeast University, Nanjing, China.
Institute of Diabetes, Medical School, Southeast University, Nanjing, China.
Ann Transl Med. 2020 Aug;8(16):997. doi: 10.21037/atm-20-5171.
Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease; however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics analysis has provided a comprehensive insight toward the molecular mechanisms of DKD. Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with DKD and contribute to a better understanding of DKD pathogenesis.
Three datasets including GSE131882, GSE30122, and GSE30529 were utilized to find differentially expressed genes (DEGs). The potential functions of DEGs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein-protein interaction (PPI) network was constructed, and hub genes were selected with the top three molecular complex detection (MCODE) score. A correlation analysis between hub genes and clinical indicators was also performed.
In total, 84 upregulated DEGs and 49 downregulated DEGs were identified. Enriched pathways of the upregulated DEGs included extracellular matrix (ECM) receptor interaction, focal adhesion, human papillomavirus infection, malaria, and cell adhesion molecules. The downregulated DEGs were mainly enriched in ascorbate and aldarate metabolism, arginine and proline metabolism, endocrine- and other factor-regulated calcium reabsorption, mineral absorption and longevity regulating pathway, and multiple species signaling pathway. Seventeen hub genes were identified, and correlation analysis between unexplored hub genes and clinical features of DKD suggested that EGF, KNG1, GADD45B, and CDH2 might have reno-protective roles in DKD. Meanwhile, ATF3, B2M, VCAM1, CLDN4, SPP1, SOX9, JAG1, C3, and CD24 might promote the progression of DKD. Finally, most hub genes were found present in the immune cells of diabetic kidneys, which suggest the important role of inflammation infiltration in DKD pathogenesis.
In this study, we found seventeen hub genes using a scRNA-seq contained multiple-microarray analysis, which enriched the present understanding of molecular mechanisms underlying the pathogenesis of DKD in cells' level and provided candidate targets for diagnosis and treatment of DKD.
糖尿病肾病（DKD）是终末期肾病的主要病因；然而，其潜在的分子机制仍不清楚。最近，生物信息学分析为DKD的分子机制提供了全面的见解。在此，我们重新分析了三个mRNA微阵列数据集，包括一个单细胞RNA测序（scRNA-seq）数据集，旨在识别与DKD相关的关键基因，并有助于更好地理解DKD的发病机制。
利用包括GSE131882、GSE30122和GSE30529在内的三个数据集来寻找差异表达基因（DEG）。通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析来分析DEG的潜在功能。构建蛋白质-蛋白质相互作用（PPI）网络，并选择分子复合物检测（MCODE）得分最高的前三个基因作为枢纽基因。还进行了枢纽基因与临床指标之间的相关性分析。
总共鉴定出84个上调的DEG和49个下调的DEG。上调的DEG富集的通路包括细胞外基质（ECM）受体相互作用、粘着斑、人乳头瘤病毒感染、疟疾和细胞粘附分子。下调的DEG主要富集在抗坏血酸和醛糖代谢、精氨酸和脯氨酸代谢、内分泌和其他因子调节的钙重吸收、矿物质吸收和寿命调节通路以及多种物种信号通路。鉴定出17个枢纽基因，对未探索的枢纽基因与DKD临床特征之间的相关性分析表明，表皮生长因子（EGF）、激肽原1（KNG1）、生长停滞和DNA损伤诱导蛋白45β（GADD45B）和钙粘蛋白2（CDH2）可能在DKD中具有肾脏保护作用。同时，活化转录因子3（ATF3）、β2微球蛋白（B2M）、血管细胞粘附分子1（VCAM1）、紧密连接蛋白4（CLDN4）、分泌型磷蛋白1（SPP1）、性别决定区Y盒9（SOX9）、信号分子Jagged1（JAG1）、补体成分3（C3）和分化簇24（CD24）可能促进DKD的进展。最后，发现大多数枢纽基因存在于糖尿病肾病的免疫细胞中，这表明炎症浸润在DKD发病机制中起重要作用。
在本研究中，我们使用包含多微阵列分析的scRNA-seq发现了17个枢纽基因，这在细胞水平上丰富了目前对DKD发病机制分子机制的理解，并为DKD的诊断和治疗提供了候选靶点。
