Abstract: FR-PO989
Characterising Human Kidney Disease Using Single-Cell Resolution Spatial Transcriptomics
Session Information
- CKD Mechanisms: From Mendel to Mars
November 03, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2303 CKD (Non-Dialysis): Mechanisms
Authors
- Ferenbach, David A., The University of Edinburgh Centre for Inflammation Research, Edinburgh, Edinburgh, United Kingdom
- Reck, Maximilian, The University of Edinburgh Centre for Cardiovascular Science, Edinburgh, Edinburgh, United Kingdom
- Baird, David Paul, The University of Edinburgh Centre for Inflammation Research, Edinburgh, Edinburgh, United Kingdom
- Docherty, Marie, The University of Edinburgh Centre for Inflammation Research, Edinburgh, Edinburgh, United Kingdom
- Denby, Laura, The University of Edinburgh Centre for Cardiovascular Science, Edinburgh, Edinburgh, United Kingdom
- Conway, Bryan, The University of Edinburgh Centre for Cardiovascular Science, Edinburgh, Edinburgh, United Kingdom
Background
There is accumulating evidence of the role played by subsets of transcriptionally altered epithelia in the progression of experimental chronic kidney disease (CKD) (Muto et al 2021, Mylonas et al 2021). Whilst bulk and single cell RNA-seq analysis has increased our understanding of kidney biology – the lack of spatial context has limited efforts to identify pathways by which inflammatory Vcam1+ epithelia, leukocytes and fibroblasts interact within the human kidney.
Advances in spatial sequencing now provide single cell resolution analysis in formalin fixed, paraffin embedded renal biopsies. We hypothesized that spatial analysis of cell-cell signalling in human kidneys would uncover signalling pathways relevant to progressive chronic kidney disease.
Methods
We used the NanoString CosMx spatial molecular imager to analyse ~1000 RNA transcripts in 13 human renal biopsies spanning benign (minimal change disease, MCD) non progressive IgAN and progressive IgAN CKD (defined as >30% eGFR loss over study period).
Results
Interrogating our spatial dataset, we identified 19 transcriptionally distinct cell types – including previously published and novel Vcam1+ epithelia from proximal tubules and loop of Henle. Analysis was undertaken on Vcam1+ epithelia in patient biopsies of MCD and IgAN. Assessment of ligand receptor signalling pathways between Vcam1+ epithelia, leukocytes and fibroblasts within 50microns revealed multiple spatially linked ligand/receptor pathways (see Figure below). One example was the spatial link between reduced Vcam1+ epithelia<>fibroblast distance and increased fibroblast Col1a1 and Col3a1 production (n=10,935 total fibroblasts, all p<0.0001 vs spatially distant SC/fibroblast pairings, with reduced mean distance in progressive IgAN vs MCD).
Conclusion
Our data demonstrates the ability of spatial transcriptomic analysis to identify and map multiple transcipts and ligand/receptor pairings. The addition of spatial information adds additional information about putative signalling pathways in disease progression.
Funding
- Commercial Support – Research Grant awarded by NanoString