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An Integrated Atlas of the Human Kidney Spanning Health and Diseases

Stasinos, K.; Wang, H.; Predeus, A. V.; Richoz, N.; Menon, R.; Thokadiwala, M.; Zhu, Y.; Tian, R.; Zhou, W.; Chatzigeorgiou, A.; Yordanova, G.; Zucchi, I.; Laszik, Z.; Mueller, M. F.; The Human Cell Atlas Kidney Bionetwork, ; Subramanian, A.; Greka, A.; Regev, A.; Kretzler, M.; Marioni, J.; Luecken, M. D.; Clatworthy, M.; Teichmann, S. A.; He, P.

2026-08-21 genomics
10.64898/2026.08.12.744548 bioRxiv
Show abstract

The human kidney contains highly specialized cell populations. Despite numerous single-cell and single-nucleus transcriptomics studies, differences in cohorts, technologies, analytical pipelines, and annotation frameworks have limited the ability to define consensus kidney cell states, identify disease-associated populations and interpret kidney disease genetic susceptibility. Here, we assembled 18 human kidney single-cell and single-nucleus RNA-sequencing datasets spanning 232 donors and five major disease contexts into a uniformly processed and computationally integrated Human Kidney Cell Atlas (HKCA), comprising over one million high-quality cells (816,895) and nuclei (215,308). The HKCA resolves 63 cell types and 120 harmonized cell states, including rare epithelial and stromal populations associated with kidney diseases. Integration with spatial transcriptomics, intercellular communication networks, and human genetic association data further defined the anatomical context and disease relevance of these populations. The HKCA also provides a framework for automated annotation of independent kidney human and mouse datasets. Together, the HKCA establishes a comprehensive reference for human kidney biology, enabling disease interpretation and genetic risk localization at cellular resolution.

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