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Kidney Week

Abstract: FR-OR31

Decoding the Spatial Transcriptomic Landscape of Diabetic Nephropathy

Session Information

Category: Diabetic Kidney Disease

  • 701 Diabetic Kidney Disease: Basic

Authors

  • Deng, Qiwen, Stanford University School of Medicine, Stanford, California, United States
  • Liu, Yu, Stanford University School of Medicine, Stanford, California, United States
  • Bracey, Nathan, Stanford University School of Medicine, Stanford, California, United States
  • Charu, Vivek, Stanford University School of Medicine, Stanford, California, United States
  • Wernig, Gerlinde, Stanford University School of Medicine, Stanford, California, United States
Background

Diabetic nephropathy (DN) is a major cause of chronic kidney disease globally. However, the lack of targeted treatments for renal fibrosis in DN is due to an incomplete understanding of disease progression. We generated a detailed map of human diabetic nephropathy by employing single-cell gene expression and spatial transcriptomic profiling of DN patients and controls.

Methods

We characterized the signature of diabetic nephropathy through spatial transcriptomics, analyzing eight patient biopsies using the 10x VISIUM-FFPE platform. Integrating spatially resolved transcriptomics with single-cell gene expression, we mapped cell types in space, revealing the spatial organization and structure of DN tissue. Our analysis included trajectory analysis for cell transition directions, spatial dependencies between signaling pathways and cell types, and gene-regulatory networks distinguishing DN from normal kidney tissue. Furthermore, subcellular characterization of 100 genes of interest was performed using Molecular Cartography on frozen tissues from the same patients.

Results

Deconvoluting spatial transcriptomic spots into cell-type abundances unveiled the spatial organization of kidney tissue, identifying major cell-type niches as structural building blocks. Within the glomerulus niche, we inferred a pseudotime trajectory from endothelial cells to pathogenic fibroblasts (IGKC+), supported by significant upregulation of POSTN in DN endothelial cells. We linked spatial cell composition information to cellular functions, detecting increased TGFß signaling activity in areas abundant in mesangial cells and fibroblasts. In the fibrotic niche, we observed strong dependencies between mesenchymal cells and leukocytes, highlighting the key role of macrophages in fibroblast activation. Subclustering fibroblasts and mesangial cells identified pathogenic fibroblasts (Fib 6) marked by IGKC and pathogenic mesangial cells (MES 2 & 3) marked by TMSB4X, MYL9, and ACTA2. Additionally, we discovered a novel innate immune checkpoint, CD63, highly expressed in DN samples and specifically overexpressed in Fib 6 and MES 2 & 3, supporting its crucial role in DN fibrogenesis.

Conclusion

Our study provides an integrative molecular map of diabetic nephropathy, serving as a vital reference for the field and facilitating advanced mechanistic and therapeutic investigations of diabetic kidney disease.