Background: Diabetic Nephropathy (DN) is the leading cause of end-stage renal disease worldwide. Extensive studies have been performed to elucidate the underlying mechanisms of DN, which still need to be clarified. The identification of key biomarkers using integrated bioinformatics could provide a certain theoretical foundation for future research and provide experimental direction for subsequent experimental verification.Methods: GSE1009, GSE30528, and GSE96804 were downloaded from the Gene Expression Omnibus (GEO) database to screen Differentially Expressed Genes (DEGs) between normal renal tissue and DN renal tissue by using the limma package. Then, the Robust Rank Aggreg (RRA) method was used to integrate and analyze the three datasets to obtain integrated DEGs. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to determine the molecular mechanisms of integrated DEGs involved in the progression of DN. A Protein-Protein Interaction (PPI) network of integrated DEGs was constructed via the STRING database, PPI network visualization and module analyses were performed by using Cytoscape software, and the hub genes in the PPI network were selected by topological analysis. Finally, the Nephroseq v5 online platform was utilized to explore the correlation between hub genes and clinical features of DN Results: In total, 249 integrated DEGs, including 191 upregulated genes and 58 downregulated genes, were identified and enriched in pathways involved in several functions and expression pathways, such as extracellular matrix,complement and coagulation cascades, focal adhesion, ECM-receptor interactions, cytokine-cytokine receptor interaction, the renin-angiotensin system, and chemokine signaling pathways. The top 10 hub genes identified from the PPI network were ALB, FN1, VEGFA, IGF1, JUN, FOS, CTGF, C3, COL1A2, and CLU. In addition, a KEGG pathway analysis of the top 2 modules identified from the PPI network revealed that Module 1 was mainly involved in focal adhesion and ECM-receptor interactions, while Module 2 was mainly involved in cytokine-cytokine receptor interactions, the chemokine signaling pathway, the Toll-like receptor signaling pathway, and the TGF-beta signaling pathway.Correlation and subgroup analyses of 10 hub genes and the clinical characteristics of DN indicated that ALB, FN1, VEGFA, IGF1, JUN, FOS, CTGF, C3, COL1A2, and CLU may participate in the development of DN.
Conclusions:The identification of hub genes may be a key biomarker for early DN diagnosis and targeted treatment.