Abstract: SA-PO0010
Glomeruli Spatial Transcriptomics Reveal Immune Axis Along Renal Lesion Progression in ANCA-Associated Vasculitis
Session Information
- Intelligent Imaging and Omics: Phenotyping and Risk Stratification
November 08, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Artificial Intelligence, Digital Health, and Data Science
- 300 Artificial Intelligence, Digital Health, and Data Science
Authors
- Barkhuizen, Melinda, Evotec International GmbH, Göttingen, NDS, Germany
- Schreiter, Kay, Evotec International GmbH, Göttingen, NDS, Germany
- Tampe, Bjoern, Universitatsmedizin Gottingen, Göttingen, NDS, Germany
- Zeisberg, Michael, Universitatsmedizin Gottingen, Göttingen, NDS, Germany
- Oliveira Vidal, Ramon, Evotec International GmbH, Göttingen, NDS, Germany
- Severo Witte, Maiara, Evotec International GmbH, Göttingen, NDS, Germany
- Zheng, Menglin, Evotec International GmbH, Göttingen, NDS, Germany
- Komarov, Ilya, Evotec International GmbH, Göttingen, NDS, Germany
- Poondi Krishnan, Varsha, Evotec International GmbH, Göttingen, NDS, Germany
- Seip, Britta, Evotec International GmbH, Göttingen, NDS, Germany
- Schoening, Janne M, Evotec International GmbH, Göttingen, NDS, Germany
- Skroblin, Philipp, Evotec International GmbH, Göttingen, NDS, Germany
- Wunderlich, Winfried, Evotec International GmbH, Göttingen, NDS, Germany
- Radresa, Olivier, Evotec International GmbH, Göttingen, NDS, Germany
- Andag, Uwe, Evotec International GmbH, Göttingen, NDS, Germany
Background
Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a rare and severe, heterogeneous autoimmune disorder with frequent renal involvement. Currently, biopsy-based classifications relying on the percentage of normal, crescentic and sclerotic glomeruli form the gold standard for diagnosis. A detailed understanding of the cellular- and biological changes occurring at the molecular level is urgently needed to develop less-invasive diagnostics and identify candidate targets directly derived from patient data.
Methods
37 kidney biopsy slices along with matching blood samples from 30 patients with newly diagnosed ANCA vasculitis were analyzed as part of a larger multi-omics AAV cohort. Biopsy slices were processed for spatial transcriptomics with the Visium v2 platform (10x Genomics) following annotation of the different glomerular lesions by a pathologist. Using a combination of gene expression, microenvironment prediction and histological feature locations, we identified molecular niches associated with histopathology annotations. Blood single-cell RNA expression from this same cohort along with kidney cell-type signatures were used to deconvolute the niches into their cell-type compositions.
Results
424 glomeruli with 6 distinct histological annotations were characterized across the slices. The most common phenotypes were histologically normal glomeruli (n= 203), followed by sclerotic (n = 115) and crescentic (n =36) ones. Molecular analysis of the glomeruli revealed a reduction in homeostasis-associated gene expression, along with an increase in immune-associated and fibrosis gene expression. Deconvolution of the transcriptomic data identified immune cell signatures within the glomeruli, consistent with the autoimmune (inflammatory) nature of AAV.
Conclusion
We combined histopathological annotations with spatial transcriptomics and with single cell RNA sequencing data from blood samples to identify distinct molecular niches of renal lesions in AAV patients. The combined multi-omics approach supports the discovery of much needed disease biomarkers and candidate targets.