Similar Datasets
Project description:Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are 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 a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
| S-EPMC10356613 | biostudies-literature
Project 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.
2022-10-10 | GSE183277 | GEO
Project 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.
2022-10-10 | GSE183276 | GEO
Project 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.
2022-10-10 | GSE183274 | GEO
Project 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.
2022-10-10 | GSE183273 | GEO
Project 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.
2022-10-10 | GSE199711 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-01-24 | E-GEOD-54288 | biostudies-arrayexpress
Project description:To spatially localize cell types within the tissue, snCv3 subclasses were used to predict the corresponding identities in Visium transcriptomic data. This allowed for recapitulated renal corpuscle, tubular, vascular, and interstitial cell types having proportions, marker profiles, and spatial organizations consistent observed histopathology.
2022-10-12 | GSE183456 | GEO
Project description:An atlas of healthy and injured cell states and niches in the human kidney
| PRJNA759877 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-09-08 | E-GEOD-54500 | biostudies-arrayexpress