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Kidney Week

Abstract: PO0901

Single-Cell Immune Landscape of Mouse Diabetic Kidney Disease

Session Information

Category: Diabetic Kidney Disease

  • 601 Diabetic Kidney Disease: Basic

Authors

  • Fu, Jia, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Wang, Xuan, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Sun, Zeguo, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Zhang, Weijia, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Lee, Kyung, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • He, John Cijiang, Icahn School of Medicine at Mount Sinai, New York, New York, United States
Background

Diabetic kidney disease (DKD) is historically been considered as a non-inflammatory glomerular disease that is induced by metabolic and haemodynamic derangement. Increasing evidence suggests that renal inflammation contributes to the pathogenesis and progression of DKD. However, specific characteristics of dysregulated immune cells under diabetic conditions are poorly understood. We hypothesized that single cell RNA-seq could provide insight into the cellular mechanisms of diabetic nephropathy.

Methods

We collected kidney samples from control(n=9) and OVE26 (n=9) mice at 16 weeks. CD45+ innate immune cells were harvested by flow cytometry cell sorting and processed using 10x Genomics Chromium platform.

Results

18000 immune cells (avg=1400 unique genes detected/cel) from control and diabetic mice were included in the integrated analysis. 17 immune cell clusters were identified and included all major immune cell types, with differential expression of hundreds of genes across all clusters. Increased expression of inflammatory cytokines was detected in particular immune cell clusters. Resident macrophages which took the majority of macrophage subtypes in the kidney are decreased after injury. Trem2high, IFN signature high, Stmn1high macrophage, and Chemokinehigh dendritic cells, which exhibited inflammatory response activation and strong ability of proliferation was observed with higher infiltration in diabetes. By Macspectrum analysis, we found a spectrum of diabetic macrophage activation states with greater complexity than traditional M1/M2 definitions. We generated a detailed diabetic immune cell intercellular communication map between macrophage, NK cell, T cell and Neutrophil. We observed restricted expression for kidney risk inflammatory signature (KRIS) in specific cell types, with macrophage showing the highest enrichment suggesting multiple unique functionalities may contribute to dysfunctional kidney physiology in diabetes.

Conclusion

This is the first comprehensive immune single cell landscape of a mouse model of DN. We demonstrate that (1) activated macrophage subtype recruitment, (2) spectrum of macrophage activation; (3) detailed diabetic immune cell intercellular communication, (3) Macrophage-specific expression of KRIS that associated with progression of ESRD in T1DM and T2DM patients.

Funding

  • NIDDK Support