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Screening and identification of differentially expressed genes between diabetic nephropathy glomerular and normal glomerular via bioinformatics technology.

BACKGROUND
Diabetes is a chronic metabolic disease characterized by disorders of glucose and lipid metabolism. Its most serious microvascular complication is diabetic nephropathy (DN), which is characterized by varying degrees of proteinuria and progressive glomerulosclerosis, eventually progressing to end-stage renal failure.


OBJECTIVE
The aim of this research is to identify hub genes which might serve as genetic markers to enhance the diagnosis, treatment, and prognosis of DN.


METHOD
The procedures of the study include access to public data, identification of differentially expressed genes (DEGs) by GEO2R, and functional annotation of DEGs using enrichment analysis. Subsequently, construction of the protein-protein interaction (PPI) network and identification of significant modules were performed. Finally, the hub genes were identified and analyzed, including clustering analysis, Pearson's correlation coefficient analysis, and multivariable linear regression analysis.


RESULTS
Between the GSE30122 and GSE1009 datasets a total of 142 DEGs were identified, which were mainly enriched in cell migration, platelet activation, glomerulus development, glomerular basement membrane development, focal adhesion, regulation of actin cytoskeleton, and the PI3K-AKT signaling pathway. The PPI network was composed of 205 edges and 142 nodes. A total of 10 hub genes (VEGFA, NPHS1, WT1, PODXL, TJP1, FYN, SULF1, ITGA3, COL4A3, and FGF1) were identified from the PPI network.


CONCLUSION
The DEGs between DN and control glomeruli samples may be involved in the occurrence and development of DN. We speculated that hub genes may be important inhibitory genes in the pathogenesis of diabetic nephropathy, so they are expected to become the new gene targets for the treatment of DN.