An atlas of healthy and injured cell states and niches in the human kidney.

Autor: Lake BB; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.; San Diego Institute of Science, Altos Labs, San Diego, CA, USA., Menon R; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA., Winfree S; Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA., Hu Q; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA., Melo Ferreira R; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA., Kalhor K; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA., Barwinska D; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA., Otto EA; Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA., Ferkowicz M; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA., Diep D; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.; San Diego Institute of Science, Altos Labs, San Diego, CA, USA., Plongthongkum N; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA., Knoten A; Department of Medicine, Washington University School of Medicine, St Louis, MO, USA., Urata S; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA., Mariani LH; Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA., Naik AS; Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA., Eddy S; Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA., Zhang B; Department of Medicine, Washington University School of Medicine, St Louis, MO, USA., Wu Y; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.; San Diego Institute of Science, Altos Labs, San Diego, CA, USA., Salamon D; Department of Medicine, Washington University School of Medicine, St Louis, MO, USA., Williams JC; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA., Wang X; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA., Balderrama KS; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Hoover PJ; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Murray E; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Marshall JL; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Noel T; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Vijayan A; Department of Medicine, Washington University School of Medicine, St Louis, MO, USA., Hartman A; New York Genome Center, New York, NY, USA., Chen F; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Waikar SS; Section of Nephrology, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA., Rosas SE; Kidney and Hypertension Unit, Joslin Diabetes Center, Boston, MA, USA.; Harvard Medical School, Boston, MA, USA., Wilson FP; Department of Medicine, Yale University School of Medicine, New Haven, CT, USA., Palevsky PM; Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA., Kiryluk K; Department of Medicine, Columbia University, New York, NY, USA., Sedor JR; Lerner Research and Glickman Urology and Kidney Institutes, Cleveland Clinic, Cleveland, OH, USA., Toto RD; Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA., Parikh CR; Division of Nephrology, Johns Hopkins School of Medicine, Baltimore, MD, USA., Kim EH; Department of Surgery, Washington University School of Medicine, St Louis, MO, USA., Satija R; New York Genome Center, New York, NY, USA., Greka A; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Macosko EZ; Broad Institute of Harvard and MIT, Cambridge, MA, USA., Kharchenko PV; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.; San Diego Institute of Science, Altos Labs, San Diego, CA, USA., Gaut JP; Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA., Hodgin JB; Department of Pathology, University of Michigan, Ann Arbor, MI, USA., Eadon MT; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. meadon@iupui.edu., Dagher PC; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. pdaghe2@iu.edu., El-Achkar TM; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. telachka@iu.edu., Zhang K; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA. kzhang@bioeng.ucsd.edu.; San Diego Institute of Science, Altos Labs, San Diego, CA, USA. kzhang@bioeng.ucsd.edu., Kretzler M; Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA. kretzler@med.umich.edu., Jain S; Department of Medicine, Washington University School of Medicine, St Louis, MO, USA. sanjayjain@wustl.edu.; Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA. sanjayjain@wustl.edu.
Jazyk: angličtina
Zdroj: Nature [Nature] 2023 Jul; Vol. 619 (7970), pp. 585-594. Date of Electronic Publication: 2023 Jul 19.
DOI: 10.1038/s41586-023-05769-3
Abstrakt: Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods 1 . 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.
(© 2023. The Author(s).)
Databáze: MEDLINE