Abstract: SA-PO0337
Rewriting Tissue Analysis in Diabetic Kidney Disease with Single-Cell Spatial Transcriptomics
Session Information
- Diabetic Kidney Disease: Basic and Translational Science Advances - 2
November 08, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 701 Diabetic Kidney Disease: Basic
Authors
- Dumoulin, Bernhard, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- Levinsohn, Jonathan, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
- Bergeson, Andi M., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
- Susztak, Katalin, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
Group or Team Name
- Susztak Lab.
Background
Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide, affecting millions of individuals. While currently, diagnosis relies on visual assessment of tissue architecture using standard stains, single-cell spatial transcriptomics (scSTx) provides an unbiased, high-resolution approach to identifying disease-associated patterns based on molecularly defined cell types and their spatial relationships.
Methods
We generated scSTx profiles from healthy individuals and patients with diabetes or diabetic kidney disease (eGFR 12–114), using CosMx (1,000 genes, 48 patients) and Xenium (5,100 genes, 16 patients), and integrated them with single-cell RNA-seq data from 146 patients using deep learning.
Results
Our atlas spans over 5 million kidney cells and identified 32 distinct cell types. To capture disease-associated cellular patterns, we define niches as a spatially organized neighborhood of interacting cell types that together form a distinct molecular and functional unit. Using this framework, we uncovered 11 reproducible kidney niches. The proximal tubule niche was positively correlated with eGFR, while injured proximal tubule niches were negatively correlated, highlighting their association with disease severity and progression. To investigate tubular injury, we defined microenvironments (MEs) as spatially confined cell neighborhoods centered around injured tubular epithelial cells and identified five distinct injured MEs. Tubular cells within these MEs exhibited marked transcriptional changes, highlighting how the local ME explains injured epithelial cell states. One ME was enriched for fibroblasts and displayed a distinct profibrotic program. Spatial co-localization with Sirius Red staining confirmed its association with fibrosis. We further deciphered the paracrine axis between injured tubules and fibroblasts by prioritizing ligand–receptor interactions correlated with increased COL1A1 expression, revealing key signals driving matrix deposition.
Conclusion
This study highlights scSTx as a transformative approach that surpasses traditional histopathology and resolves kidney architecture, spatially defined cellular interactions and disease-associated signaling networks. Our findings lay the foundation for spatially informed diagnostics and therapeutic discovery.
Funding
- NIDDK Support