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Kidney Week

Abstract: TH-OR037

Single-Cell Multiomics Analysis of Human Kidney Diseases

Session Information

Category: Glomerular Diseases

  • 1401 Glomerular Diseases: Mechanisms, including Podocyte Biology

Authors

  • Saritas, Turgay, University Hospital RWTH Aachen, Aachen, Germany
  • Boys, Charlotte May, Universitat Heidelberg, Heidelberg, BW, Germany
  • Kuppe, Christoph, University Hospital RWTH Aachen, Aachen, Germany
  • Frommer, Leon Merlin, University Hospital RWTH Aachen, Aachen, Germany
  • Maryam, Sidrah, University Hospital RWTH Aachen, Aachen, Germany
  • Bleckwehl, Tore, University Hospital RWTH Aachen, Aachen, Germany
  • Mohanta, Debashish, Erasmus Universiteit Rotterdam, Rotterdam, ZH, Netherlands
  • Goepp, Vivien, University Hospital RWTH Aachen, Aachen, Germany
  • Malik, Muhammad Shoaib, University Hospital RWTH Aachen, Aachen, Germany
  • Schreibing, Felix, University Hospital RWTH Aachen, Aachen, Germany
  • van den Bosch, Thierry P.p., Erasmus Universiteit Rotterdam, Rotterdam, ZH, Netherlands
  • Knoppert, Sebastiaan, Universitair Medisch Centrum Utrecht, Utrecht, UT, Netherlands
  • Clahsen - van Groningen, Marian, Erasmus Universiteit Rotterdam, Rotterdam, ZH, Netherlands
  • Goldschmeding, Roel, Universitair Medisch Centrum Utrecht, Utrecht, UT, Netherlands
  • Nguyen, Tri Q., Universitair Medisch Centrum Utrecht, Utrecht, UT, Netherlands
  • Hayat, Sikander, University Hospital RWTH Aachen, Aachen, Germany
  • Saez-Rodriguez, Julio, European Bioinformatics Institute, Cambridge, England, United Kingdom
  • Kramann, Rafael, University Hospital RWTH Aachen, Aachen, Germany
Background

To better understand the molecular mechanisms underlying human kidney diseases, we constructed a comprehensive, high-resolution molecular map using advanced multi-omics technologies.

Methods

Our study spans both healthy kidneys and a spectrum of common glomerular and tubulointerstitial diseases, including diabetic kidney disease, tubulointerstitial nephritis, IgA nephropathy, focal segmental glomerulosclerosis, and membranous glomerulopathy. Clinical metadata, including kidney function with longitudinal follow-up extending up to 20 years, were integrated into the analysis. We applied single-nucleus RNA sequencing (snRNA-seq), ATAC sequencing, and spatial transcriptomics (10x Genomics Chromium and Xenium platforms) to 95 kidney biopsies. Using Multi-Omics Factor Analysis (MOFA), we performed unsupervised integration of the transcriptomic and epigenomic datasets to identify biologically meaningful patterns of variation. Gene regulatory networks and transcription factor activity were inferred and perturbed in silico using CellOracle to explore mechanisms underlying maladaptive cellular states.

Results

MOFA uncovered latent factors including RUNX1, CDH6, MMP7 and SPP1 predictive of kidney function and interstitial fibrosis and tubular atrophy (IFTA), beyond what is captured by standard single-cell clustering. We identified both disease-specific and shared molecular alterations, including eGFR-independent signatures and a gene set associated with rapid progression of chronic kidney disease. Spatial transcriptomics confirmed disease-specific cellular crosstalk in situ. Integration of multi-omics data revealed distinct cellular states and their regulatory networks, highlighting a complex interplay among kidney cell types across disease conditions.

Conclusion

Our integrative molecular atlas of common kidney diseases offers critical insights into disease pathogenesis, highlights potential therapeutic targets, and supports the development of precision medicine approaches tailored to specific cell types, diseases and disease stages.

Digital Object Identifier (DOI)