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Abstract: PO0675

Integrative Transcriptome Analysis Reveals Involvement of Spermatogenesis-Related Genes in Diabetic Nephropathy

Session Information

Category: Diabetic Kidney Disease

  • 601 Diabetic Kidney Disease: Basic

Authors

  • Ma, Xinxin, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Lin, Hongchun, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Li, Yuanqing, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Lai, Weiyan, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Shu, Shuangshuang, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Sun, Yuxiang, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Li, Yongjie, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Song, Jun, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Ye, Zengchun, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
  • Peng, Hui, The Third Affiliated Hospital of Sun Yet-sun University Department of Nephrology, Guangzhou, Guangdong, China
Background

Cell heterogeneity has impeded the accurate interpretation of the bulk transcriptome data from patients with diabetic nephropathy (DN). We performed an analysis by integrating bulk and single-cell transcriptome datasets to uncover novel mechanism leading to DN, especially in the podocytes.

Methods

Microdissected glomeruli and tubules transcriptome datasets were selected from Gene Expression Omnibus (GEO). Then the consistency between datasets was evaluated. The analysis of bulk dataset and single-nucleus RNA dataset was integrated to reveal the cell type-specific responses to DN. The candidate genes were validated in kidney tissues from DN patients and diabetic mice.

Results

We compared 4 glomerular and 4 tubular datasets and found considerable discrepancies among datasets regarding the differentially expressed genes (DEGs), involved signaling pathways and the hallmark enrichment profiles. Deconvolution of the bulk data revealed that the variations in cell-type proportion contributed greatly to this discrepancy. Integrative analysis uncovered that the dysregulation of spermatogenesis-related genes, including TEKT2 and PIAS2 was involved in development of DN. Importantly, the mRNA level of TEKT2 was negatively correlated with the mRNA levels of nephrin (r= -0.66, p<0.0001) and podocin (r= -0.85, p<0.0001) in human diabetic glomeruli. Immunostaining confirmed that the expression of TEKT2 and PIAS2 were up-regulated in podocytes of DN patients and diabetic mice.

Conclusion

The integrative strategy can help us to efficiently use the publicly available transcriptomics resources. Using this approach, we identified TEKT2 and PIAS2, two spermatogenesis-related genes involved in the pathogenesis of DN.