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Objective: Through the bioinformatic analysis of gene chips related to advanced diabetic nephropathy in the GEO database, the key genes of advanced diabetic nephropathy are screened, whose biological functions and signal pathways are predicted as well. Methods: The gene chips related to advanced diabetic nephropathy from the GEO expression profile database was downloaded, and the differentially expressed genes in patients with advanced diabetic nephropathy and normal people were analyzed through R. For the screened differentially expressed genes, the biological function of GO and the enrichment analysis of KEGG signal pathway were used to predict their biological functions and related signal pathways. In addition, a protein-protein interaction network was constructed, so as to screen core pathogenic genes utilizing STRING database and Cytoscape. Results: By analyzing the chip GSE142025, 301 differential genes were obtained, including 197 up-regulated genes and 104 down-regulated genes. Both GO annotation and enrichment analysis suggested that differential genes were mainly involved in immune-inflammatory response and cytokine action. Furthermore, KEGG pathway analysis suggested that the most important pathway related to advanced diabetic nephropathy was MAPK signaling pathway. Through protein-protein interaction network and module analysis, C3, CCR2, CCL19, and SAA1 were selected as the core sites of the interaction. Conclusions: Differential genes participate in the pathogenesis of advanced diabetic nephropathy through the KEGG pathway, the immune inflammatory response and cytokine action, which provides new ways for the diagnosis and treatment of advanced diabetic nephropathy.

Research on Potential Pathogenesis of Advanced Diabetic Nephropathy based on Bioinformatic Analysis