Decoding personal and population variability in the human multiome

Background: With recent advances in technology, multiomic data have proliferated rapidly. Biobanks are now developing genomic, proteomic, lipidomic, and metabolomic data sets on the order of hundreds of thousands of people. However, bridging the gap between population-level data and the individual--a major challenge in precision medicine--remains a novel and challenging task. Methods: We analyzed the landscape of contemporary multiomics data and the drivers of population and personal molecular variability using a longitudinal cohort uniquely suited to precision health applications. Using healt

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