Prediction of the molecular mechanisms and potential therapeutic targets for diabetic nephropathy by bioinformatics methods.

Abstract

In this study, we aimed to explore the molecular mechanisms of and genetic factors influencing diabetic nephropathy (DN). Gene expression profiles associated with DN were obtained from the GEO database (Accession no. GSE20844). The differentially expressed genes (DEGs) between diabetic mice and non-diabetic mice were screened. Subsequently, the DEGs were subjected to functional and pathway analysis. The protein-protein interaction (PPI) network was constructed and the transcription factors (TFs) were screened among the DEGs. A total of 92 upregulated and 118 downregulated genes were screened. Pathway analysis revealed that the p53 signaling pathway, the transforming growth factor (TGF)-β signaling pathway and the mitogen-activated protein kinase (MAPK) signaling pathway were significantly enriched by upregulated genes. Serpine1 (also known as plasminogen activator inhibitor-1), early growth response 1 (Egr1) and Mdk were found to be significant nodes in the PPI network by three methods. A total of 12 TFs were found to be differentially expressed, of which nuclear receptor subfamily 4, group A, member 1 (Nr4a1) and peroxisome proliferator-activated receptor gamma (Pparg) were found to have multiple interactions with other DEGs. We demonstrated that the p53 signaling pathway, the TGF-β signaling pathway and the MAPK signaling pathway were dysregulated in the diabetic mice. The significant nodes (Serpine1, Egr1 and Mdk) and differentially expressed TFs (Nr4a1 and Pparg) may provide a novel avenue for the targeted therapy of DN.