ASN's Mission

To create a world without kidney diseases, the ASN Alliance for Kidney Health elevates care by educating and informing, driving breakthroughs and innovation, and advocating for policies that create transformative changes in kidney medicine throughout the world.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on X

Kidney Week

Please note that you are viewing an archived section from 2020 and some content may be unavailable. To unlock all content for 2020, please visit the archives.

Abstract: PO0947

Exploring New Targets of Diabetic Nephropathy by Bioinformatics Analysis

Session Information

Category: Diabetic Kidney Disease

  • 601 Diabetic Kidney Disease: Basic

Authors

  • Tang, Shumei, Xiangya Hospital Central South University, Changsha, Hunan, China
  • Xiao, Xiangcheng, Xiangya Hospital Central South University, Changsha, Hunan, China
Background

The pathogenesis of diabetic nephropathy has not been fully understood and the public platform contains mass data for bioinformatics analysis.

Methods

Difference analysis and weighted gene coexpression network analysis were carried out on GSE30529 to obtain target genes and perform functional enrichment analysis. Non-coding RNA analysis was studied to understand the potential mechanism of differential expression of target genes. Using STRING database to build protein-protein interaction network. Nephroseq v5 database can access gene expression characteristics and clinical characteristics.

Results

From the GSE30529, 345 genes were identified through bioinformatics analysis. GO annotations of them included neutrophil activation, regulation of immune effector process and positive regulation of cytokine production. KEGG pathways included phagosome, complement and coagulation cascades and cell adhesion molecules. From miRNA profile, miR-1237-3p/SH2B3, miR-1238-5p/ZNF652 and miR-766-3p/TGFBI axis may be involved in diabetic nephropathy. C3 is located at the center of PPI network. Correlation analysis with GFR showed SYK, CXCL1, LYN, VWF, ANXA1, C3, HLA-E, RHOA, SERPING1, EGF and KNG1 may be related to diabetic nephropathy.

Conclusion

C3 may serve as a therapeutic target for diabetic nephropathy