Longevitomics as the Science of the Longevitome: Towards a Unified Systems Science of Healthy Longevity.

Abstract

The twenty-first century has transformed longevity research through genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome science, digital phenotyping and artificial intelligence. Yet healthy longevity remains difficult to explain because its determinants are commonly studied as separate molecular layers, mechanisms or biomarkers. Here, we introduce Longevitomics as an integrative systems framework for understanding, modeling and predicting healthy longevity and define the Longevitome inspired by the Latin expression vita longa (long life) as the dynamic architecture of biological, environmental and behavioral determinants that collectively shape psychosomatic resilience across the life course. We position this proposal in relation to the Hallmarks of Aging, geroscience, biological-age biomarkers, multi-omics and systems medicine. Longevitomics is not intended to replace these established frameworks or to constitute another molecular "ome." Rather, it provides a systems-level framework in which mechanistic hallmarks, multi-omic layers, physiological phenotypes, exposures and adaptive responses can be integrated longitudinally. We further consider how network analysis, causal inference, machine learning and digital-twin approaches may enable reconstruction of individual Longevitome trajectories and support a transition toward predictive and personalized longevity medicine.

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