Bioinformatics analysis identifies potential ferroptosis-related key genes in the pathogenesis of diabetic nephropathy

Abstract

Objective: To identify potential ferroptosis-related key genes in the pathogenesis of diabetic nephropathy (DN) through bioinformatics analysis, thereby providing new targets for the treatment of DN.

Methods: We first downloaded the RNA expression dataset GSE30529 from the GEO database and intersected it with a ferroptosis dataset to obtain ferroptosis-related differentially expressed genes (DEGs). Venny 2.1 was used to generate Venn diagrams of the DEGs, and Heml software was used to draw heatmaps of the DEGs. DAVID 6.8, Metascape, and WebGestalt were employed for functional enrichment analysis of the DEGs. Protein-protein interactions (PPIs) were retrieved through the STRING database and visualized by Cytoscape v3.6.0 software. miRWalk 2.0 was used to predict target key miRNAs and construct related gene-miRNA interaction networks.

Results:Our study identified 31 ferroptosis-related DEGs. Gene Set Enrichment Analysis (GSEA) revealed that the biological processes of these genes were significantly enriched in response to stress signals, starvation signals, lipids and atherosclerosis, and regulation of endogenous apoptotic signaling pathways, among others. The regulatory network of the MAPK8 molecule is the most crucial potential molecule that may affect the occurrence of DN. The endogenous apoptotic signaling pathway is the main biological pathway involved. We screened out one key module through MCODE, which includes two downregulated genes (MAPK8 and DDIT3) and three upregulated genes (XBP1, HSPA5, and ASNS).

Conclusion:The ferroptosis-related key genes MAPK8, has-miR-4775, HSPA5, has-miR-4712-5p/has-miR-770-5p, and XBP1 form a regulatory network, participating in the occurrence and development of DN. This provides some important references for our future basic research verification and suggests a potential target for the development of DN treatment strategies.