Description
Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
Overall Design
Single Cell RNA-Seq performed on kidney tissues from 15 Chronic Kidney Disease (CKD), 12 Acute Kidney Disease (AKI) and 20 healthy reference (Ref) individuals. This research was performed as part of the Kidney Precision Medicine Project (KPMP) and the Chan Zuckerberg Initiative (CZI) and Human Cell Atlas (HCA).; »> Submitter declares that the raw data are deposited in KPMP due to patient privacy concerns. «<
Curator
xm_li