Title:Screening and Identification of Differentially Expressed Genes Between Diabetic Nephropathy Glomerular and Normal Glomerular via Bioinformatics Technology
VOLUME: 24 ISSUE: 5
Author(s):Junjie Du, Jihong Yang* and Lingbing Meng
Affiliation:Nephrology Department, Beijing Hospital, National Center of Gerontology, No.1 Dahua Road, Dong Dan, Beijing100730, Nephrology Department, Beijing Hospital, National Center of Gerontology, No.1 Dahua Road, Dong Dan, Beijing100730, Departments of Cardiology, Beijing Hospital, National Center of Gerontology, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 DaHua Road, Dong Dan, Beijing100730
Keywords:Diabetic nephropathy, bioinformatics technology, differentially expressed genes, hub genes, glomeruli, public
data.
Abstract: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 that might serve as genetic markers to
enhance the diagnosis, treatment, and prognosis of DN.
Methods: 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, the 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. It was speculated that hub genes might be important inhibitory
genes in the pathogenesis of diabetic nephropathy, therefore, they are expected to become the new
gene targets for the treatment of DN.
