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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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02 /Specification & Classification

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