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.

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