Yan Miao, Lei Yan, Huixia Cao, Xiaojing Jiao, Fengmin Shao

Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan Province, 450053, People’s Republic of China

Correspondence: Fengmin Shao, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, 7 Weiwu Road, Jinshui District, Zhengzhou, Henan, 450003, People’s Republic of China, Email shaofengmin123@163.com

Background: 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.
Methods: 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.
Results: 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.
Conclusion: This study identified biomarkers related to mitochondrial metabolism in DN, providing new insights and directions for the diagnosis and treatment of DN.

Keywords: ECH1, diabetic nephropathy, DN, mitochondrial metabolism