Single-Cell Spatial Atlas of Immune and Kidney Cell States in Human Rapidly Progressive Glomerulonephritis

Background: Rapidly progressive glomerulonephritis (RPGN) represents the most aggressive form of autoimmune kidney disease and is characterized by the formation of glomerular crescents and the infiltration of immune cells. However, a detailed definition of leukocyte composition, cellular localization and the interactions of immune cells with renal tissue cells leading to the formation of glomerular crescents and loss of renal function is lacking. Methods: We employed high-dimensional in situ mRNA detection (10x Xenium) to investigate immune cell infiltration and kidney cell reactions in patients with RPGN (ANCA-GN: n= 32; lupus nephritis: n=19; anti-GBM: n=6) and controls (n=6). Based on single-cell RNA-seq and spatial transcriptomics data from kidney samples from the same cohort, we designed a panel consisting of 480 probes for mRNA detection to cover a broad range of immune cells, parenchymal kidney cells and potential drivers of tissue inflammation. We used manual annotation as well as a graph neural network (GNN)-based clustering algorithm to define kidney niches. Results: Our analysis resulted in a total of 2,899,179 cells from all disease categories and the panel enabled the definition and localization of all major immune and kidney cell types. Gene-expression-based pseudotime analysis from annotated glomeruli provided a trajectory from healthy glomeruli identified most frequently in control samples to severely damaged glomeruli mainly from anti-GBM patients. Patients with ANCA-GN showed glomeruli with all stages of the pseudotime. These analyses define the sequential recruitment of proinflammatory T cells and macrophages into inflammatory niches causing changes in cellular composition and crosstalk between different cell types and resulting in altered transcriptional profiles of epithelial kidney cells leading to crescent formation. Conclusion: This integrated high-dimensional spatial immune and kidney cell atlas of healthy and RPGN kidneys represents a comprehensive benchmark of the cellular players with their localization and interactions in glomerular pathology. This is the basis for a better understanding of the cellular and molecular mechanisms required to develop targeted therapies in glomerulonephritis. Funding: Government Support – Non-U.S.

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Journal
Journal of the American Society of Nephrology
Published
2024-10-01
DOI
https://doi.org/10.1681/asn.2024fnrwxc0m
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Single-Cell Spatial Atlas of Immune and Kidney Cell States in Human Rapidly Progressive Glomerulonephritis

Hans‐Joachim Paust, Thorsten Wiech, Stefan Bonn, Behnam Yousefi et al.
Journal of the American Society of Nephrology
Single-cell and spatial transcriptomics
article

Single-Cell Spatial Atlas of Immune and Kidney Cell States in Human Rapidly Progressive Glomerulonephritis

Hans‐Joachim Paust, Thorsten Wiech, Stefan Bonn, Behnam Yousefi, Saskia-Larissa Jauch-Speer, Christian F. Krebs, Ulf Panzer, Nikhat Shaikh, Tobias B. Huber, Varshi Sivayoganathan, Robin Khatri, Zeba Sultana
article en

Abstract

Background: Rapidly progressive glomerulonephritis (RPGN) represents the most aggressive form of autoimmune kidney disease and is characterized by the formation of glomerular crescents and the infiltration of immune cells. However, a detailed definition of leukocyte composition, cellular localization and the interactions of immune cells with renal tissue cells leading to the formation of glomerular crescents and loss of renal function is lacking. Methods: We employed high-dimensional in situ mRNA detection (10x Xenium) to investigate immune cell infiltration and kidney cell reactions in patients with RPGN (ANCA-GN: n= 32; lupus nephritis: n=19; anti-GBM: n=6) and controls (n=6). Based on single-cell RNA-seq and spatial transcriptomics data from kidney samples from the same cohort, we designed a panel consisting of 480 probes for mRNA detection to cover a broad range of immune cells, parenchymal kidney cells and potential drivers of tissue inflammation. We used manual annotation as well as a graph neural network (GNN)-based clustering algorithm to define kidney niches. Results: Our analysis resulted in a total of 2,899,179 cells from all disease categories and the panel enabled the definition and localization of all major immune and kidney cell types. Gene-expression-based pseudotime analysis from annotated glomeruli provided a trajectory from healthy glomeruli identified most frequently in control samples to severely damaged glomeruli mainly from anti-GBM patients. Patients with ANCA-GN showed glomeruli with all stages of the pseudotime. These analyses define the sequential recruitment of proinflammatory T cells and macrophages into inflammatory niches causing changes in cellular composition and crosstalk between different cell types and resulting in altered transcriptional profiles of epithelial kidney cells leading to crescent formation. Conclusion: This integrated high-dimensional spatial immune and kidney cell atlas of healthy and RPGN kidneys represents a comprehensive benchmark of the cellular players with their localization and interactions in glomerular pathology. This is the basis for a better understanding of the cellular and molecular mechanisms required to develop targeted therapies in glomerulonephritis. Funding: Government Support – Non-U.S.

Journal of the American Society of NephrologyVol. 35(10S)
Universität Hamburg (DE), University Medical Center Hamburg-Eppendorf (DE)
Good health and well-being
Openalex Percentile: Top 83%
Single-cell and spatial transcriptomics
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