Identification of Hub Genes in Diabetic Nephropathy by an Integrated Bioinformatic Analysis

Abstract BackgroundDiabetic nephropathy (DN) is a progressive kidney disease caused by damage to the capillaries in the kidneys' glomeruli. The dysregulation of genes plays a significant role in the progression of DN. MethodsIn the present study, gene expression profiles were analyzed to identify the key genes and pathways involved in DN. Gene expression profiles of 9 patients with DN and 11 normal subjects were downloaded from the Gene Expression Omnibus (GEO) database. Subsequently, differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. In addition, protein-protein interaction (PPI) networks were established and hub genes were identified. ResultsAs a result, a total of 424 DEGs were identified (113 were upregulated and 311 were downregulated). In the protein-protein interaction network, four hub modules and 30 hub genes were identified. To explore potential associations between gene and DN clinical features and to identify hub genes, the top 25% of genes with the greatest variance in the gene expression profiles were extracted for weighted correlation network analysis (WGCNA). There were ten genes (RNASE6, CD1C, SASH3, COL1A2, MS4A6A, CD163, CLEC10A, MOXD1, IQGAP2, GHR) identified as significant DN‐associated genes. Furthermore, the expression level of these hub genes was confirmed in the GSE96804 dataset. ConclusionsThese findings provide new insight into DN pathogenesis, which may enhance our fundamental knowledge of the molecular mechanisms underlying this disease.