Miao Yan, Yan Lei, Cao Huixia, Jiao Xiaojing, Shao Fengmin
Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, 450053, People's Republic of China.
Diabetes Metab Syndr Obes. 2025 Apr 10;18:1087-1098. doi: 10.2147/DMSO.S494644. eCollection 2025.
Diabetic nephropathy (DN) is a major cause of kidney failure, and its incidence is increasing worldwide. Existing studies have shown that mitochondrial dysfunction is potentially related to the pathogenesis of DN. This study aims to explore novel biomarkers related to mitochondrial metabolism that may affect the diagnosis and treatment of DN.
The Gene Expression Omnibus (GEO) database and MitoCarta3.0 database were used to download the DN datasets and mitochondrial metabolism-related genes (MRGs), respectively. Differentially expressed genes (DEGs) were identified using the "limma" R package, and their functional analysis was performed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Important gene modules were identified by weighted gene Coexpression network analysis (WGCNA) clustering. Next, we obtained key genes by intersecting DEGs, important gene modules and MRGs. The ROC curve was employed to assess the sensitivity and specificity of the diagnostic indicators for DN. Finally, the expression of key genes was assessed in the in vitro DN model and the mechanisms of key gene were investigated.
A total of 343 DEGs were identified, with functional analysis revealing a primary focus on metabolic biological processes. A sum of 752 important module genes was ascertained. PDK4, ECH1, and ETFB were selected as key genes. Then, the expression level and specificity of key genes were verified by the GSE104954 dataset, which confirmed the high diagnostic value of PDK4 and ECH1 (AUC>0.9). Finally, the q-PCR, flow cytometry, and Western blot results indicated that key genes were significantly decreased in high glucose induced HK-2 cells. ECH1 could promote fatty acid oxidation and inhibit cell apoptosis, oxidative stress, and inflammation.
This study identified biomarkers related to mitochondrial metabolism in DN, providing new insights and directions for the diagnosis and treatment of DN.
糖尿病肾病（DN）是肾衰竭的主要原因，其发病率在全球范围内呈上升趋势。现有研究表明，线粒体功能障碍可能与DN的发病机制有关。本研究旨在探索与线粒体代谢相关的新型生物标志物，这些标志物可能会影响DN的诊断和治疗。
分别使用基因表达综合数据库（GEO）和线粒体基因图谱3.0数据库（MitoCarta3.0）下载DN数据集和线粒体代谢相关基因（MRGs）。使用“limma”R包识别差异表达基因（DEGs），并通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）对其进行功能分析。通过加权基因共表达网络分析（WGCNA）聚类确定重要的基因模块。接下来，通过将DEGs、重要基因模块和MRGs进行交叉分析获得关键基因。采用受试者工作特征曲线（ROC曲线）评估DN诊断指标的敏感性和特异性。最后，在体外DN模型中评估关键基因的表达，并研究关键基因的作用机制。
共鉴定出343个DEGs，功能分析显示主要集中在代谢生物学过程。确定了752个重要的模块基因。选择丙酮酸脱氢酶激酶4（PDK4）、烯酰辅酶A水合酶1（ECH1）和电子转移黄素蛋白β亚基（ETFB）作为关键基因。然后，通过GSE104954数据集验证了关键基因的表达水平和特异性，证实了PDK4和ECH1具有较高的诊断价值（曲线下面积>0.9）。最后，定量聚合酶链反应（q-PCR）、流式细胞术和蛋白质免疫印迹法（Western blot）结果表明，在高糖诱导的人肾近端小管上皮细胞（HK-2细胞）中关键基因显著降低。ECH1可促进脂肪酸氧化，并抑制细胞凋亡、氧化应激和炎症。
本研究确定了DN中与线粒体代谢相关的生物标志物，为DN的诊断和治疗提供了新的见解和方向。
