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Information derived from ˵omics″ data in life science research are frequently limited by specific spatial or temporal scales these data describe. As a case study of integrating physiological and molecular data in human, here we study associations between the heart magnetic resonance images and serum lipidomic profiles. In the best case, such associations could help infer the physiologic state of the heart from a blood serum sample without need to use expensive imaging techniques. Strong marginal and partial correlations are found between the lipid profiles and parameters derived from the heart images. Regression analyses are applied to study these dependencies in more detail. This study demonstrates the feasibility of mapping lipid profiles to heart images, and thus combining information from two very different scales, small molecules and macroscopic physiologic features. Such mappings could be generalized to other ˵omics″ data as well to complete our picture of the holistic function of a living organism. [ABSTRACT FROM AUTHOR]