Spatially resolved human kidney multi-omics single cell atlas highlights the key role of the fibrotic microenvironment in kidney disease progression
Kidneys have one of the most complex three-dimensional cellular organizations in the body, but the spatial molecular principles of kidney health and disease are poorly understood. Here we generate high-quality single cell (sc), single nuclear (sn), spatial (sp) RNA expression and sn open chromatin datasets for 73 samples, capturing half a million cells from healthy, diabetic, and hypertensive diseased human kidneys. Combining the sn/sc and sp RNA information, we identify > 100 cell types and states and successfully map them back to their spatial locations. Computational deconvolution of spRNA-seq identifies glomerular/vascular, tubular, immune, and fibrotic spatial microenvironments (FMEs). Although injured proximal tubule cells appear to be the nidus of fibrosis, we reveal the complex, heterogenous cellular and spatial organization of human FMEs, including the highly intricate and organized immune environment. We demonstrate the clinical utility of the FME spatial gene signature for the classification of a large number of human kidneys for disease severity and prognosis. We provide a comprehensive spatially-resolved molecular roadmap for the human kidney and the fibrotic process and demonstrate the clinical utility of spatial transcriptomics.
To reference this project, please use the following link:
Downloaded and exported data is governed by the HCA Data Release Policy and licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). For more information please see our Data Use Agreement.
Atlas
Analysis Portals
NoneProject Label
KidneyFibroticMicroenvironmentSpecies
Homo sapiens
Sample Type
specimens
Anatomical Entity
kidney
Organ Part
Unspecified
Selected Cell Types
Unspecified
Disease Status (Specimen)
Disease Status (Donor)
Development Stage
human adult stage
Library Construction Method
Nucleic Acid Source
Paired End
false, trueAnalysis Protocol
matrix_generation_ATAC-seq, matrix_generation_RNA-seq, matrix_generation_visiumFile Format
Cell Count Estimate
453.8kDonor Count
48