Abstract
Tissue atlases provide foundational knowledge on the cellular organization and molecular distributions across molecular classes and spatial scales. Here, we construct a comprehensive spatiomolecular lipid atlas of the human kidney from 29 donor tissues using integrated multimodal molecular imaging. Our approach leverages high-spatial-resolution matrix-assisted laser desorption/ionization imaging mass spectrometry for untargeted lipid mapping, stained microscopy for histopathological assessment, and tissue segmentation using autofluorescence microscopy. With a combination of unsupervised, supervised, and interpretable machine learning, the atlas provides multivariate lipid profiles of specific multicellular functional tissue units (FTUs) of the nephron, including the glomerulus, proximal tubules, thick ascending limb, distal tubules, and collecting ducts. In total, the atlas consists of tens of thousands of FTUs and millions of mass spectrometry measurements. Detailed patient, clinical, and histopathologic information allowed molecular data to be mined on the basis of these features. As examples, we highlight the discovery of how lipid profiles are altered with sex and differences in body mass index.