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Kidney Week

Abstract: TH-PO875

Bioinformatic Analysis of Kidney Transcriptome Sequencing from Patients with Diabetic Nephropathy Based on Different Sequencing Platforms

Session Information

Category: Diabetic Kidney Disease

  • 601 Diabetic Kidney Disease: Basic

Authors

  • Lin, Hongchun, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
  • Luo, Dan, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
  • Li, Yongjie, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
  • Song, Jun, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
  • Peng, Hui, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
Background

Diabetic Nephropathy (DN) is one of serious complications of diabetes mellitus. The changes in kidney gene expression profile in patients with DN remain unclear. The field has seen studies of kidney transcriptome sequencing data from patients with DN using different sequencing platforms with varied results. Our aim is to combine those sequencing data and find the differentially expressed genes(DEGs) profile in the kidneys of DN patients by means of bioinformatic analysis.

Methods

The microarray data of human diabetic glomeruli and tubules were screened in GEO database. The selection criteria were as follows: 1. The samples include both DN kidney tissue and normal ones; 2. The samples must be detected after the glomeruli or tubules were separated. 3. DN tissue is not subject to other experimental biological factors. In total, 82 cases of glomeruli and 77 cases of kidney tubule tissues, coming from GPL11670,GPL14663,GPL30122 platforms, were included to identify the DEGs.The contrast model is constructed on the DN and CTL data from the three platforms respectively, using limma function package in R software. We performed Bayesian Test according to contrast Model (Log FC > 1 and P < 0.05 were defined as DEGs). The results of gene intersection between different sequencing platforms were analyzed with STRING and DAVID on-line tools. Cytoscape was used to screen proteins with stable differential expression trend.

Results

There were 134 common DEGs with multiple sequencing platforms in the glomerular of DN patients which were enriched in the exosome process and Rap1 signaling pathway. Among them, 7 genes (WT1,FGF9,IGF1,ALB,TJP1,EGF,BMP7) exhibited the most stable protein interaction. 20 genes show a consistent trend of differential expression in kidney tubule. Exosome process is the most enriched biological process in functional analysis. Moreover, 3 genes (LUM,THBS2,VCAN) exhibited the most stable interaction. We confirmed the expression of these genes in the human protein library(HPA) and verified the different expressions in the kidneys of DN patients by RT-qPCR.

Conclusion

DEGs of microarray data in glomeruli and tubules of DN patients are not the same. DEGs from different sequencing platforms are inconsistent. The function of common DEGs in different platforms may be more closely related to the pathogenesis of DN.

Funding

  • Other U.S. Government Support