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Abstract: FR-OR096

Integrative Analysis of Single Cell and Bulk Transcriptomic Data Identifies FSGS Subgroup with Endothelial Cell Activation

Session Information

Category: Glomerular Diseases

  • 1202 Glomerular Diseases: Immunology and Inflammation

Authors

  • Menon, Rajasree, University of Michigan, Ann Arbor, Michigan, United States
  • Otto, Edgar A., University of Michigan, Ann Arbor, Michigan, United States
  • Hoover, Paul J., Broad Institute, Cambridge, Massachusetts, United States
  • Eddy, Sean, University of Michigan, Ann Arbor, Michigan, United States
  • Mariani, Laura H., University of Michigan, Ann Arbor, Michigan, United States
  • Berthier, Celine C., University of Michigan, Ann Arbor, Michigan, United States
  • Naik, Abhijit S., University of Michigan, Ann Arbor, Michigan, United States
  • Eichinger, Felix H., University of Michigan, Ann Arbor, Michigan, United States
  • Ju, Wenjun, University of Michigan, Ann Arbor, Michigan, United States
  • Harder, Jennifer L., University of Michigan, Ann Arbor, Michigan, United States
  • Godfrey, Brad A., The University of Michigan, Ann Arbor, Michigan, United States
  • Nair, Viji, University of Michigan, Ann Arbor, Michigan, United States
  • Barisoni, Laura, Duke University, Durham, North Carolina, United States
  • Zee, Jarcy, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Luo, Jinghui, University of Michigan, Ann Arbor, Michigan, United States
  • Royal, Virginie, Hopital Maisonneuve-Rosemont, Montreal, Quebec, Canada
  • Hodgin, Jeffrey B., University of Michigan, Ann Arbor, Michigan, United States
  • Kretzler, Matthias, University of Michigan, Ann Arbor, Michigan, United States
Background

Single cell RNA sequencing (scRNA-seq) generates transcriptomic data at cellular resolution allowing the identification of both known and novel cell-type specific markers. These markers enable to investigate the role of distinct cell types in kidney disease. In this study, we used glomerular endothelial cell type markers identified by scRNA-seq to analyze micro-dissected glomerular mRNA data from FSGS patients in NEPTUNE Consortium.

Methods

As part of the Kidney Precision Medicine Project (KPMP), single cell analysis (10x Chromium) was performed on unaffected kidney tissue from 16 tumor-nephrectomy and 10 surveillance transplant biopsy samples. Integrated analysis was performed on the single cell data from these 26 reference datasets including normalization, batch correction, unsupervised clustering and cell-specific marker identifications. Cell specific markers were used to cluster glomerular RNA transcriptomic data from 74 NEPTUNE FSGS patients followed by functional analysis.

Results

37 kidney cell-type clusters were identified including glomerular, tubular and immune cell types as well as 3 distinct endothelial cell types (arteriolar, peritubular and glomerular). The glomerular endothelium-specific markers were then used to sort bulk tissue gene expression from FSGS patients resulting in two main groups, 1 (n=44) and 2 (n=30). Group 2 demonstrated significant enrichment of glomerular endothelial activation markers. Higher hazards of a composite progression endpoint (>40% reduction eGFR reduction or ESRD) indicated poor prognosis for Group 2. Differentially expressed genes (DEGs) up-regulated in group 2 were involved in type-1 interferon response, ras-protein signaling, and response to endothelin receptor antagonists in model systems.

Conclusion

Glomerular endothelial marker genes identify a subgroup of patients with poor prognosis and establish a molecular correlate for the endothelin treatment response observed in clinical trials in FSGS.

Funding

  • NIDDK Support