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Updated: Sep 5, 2026

Measuring Single-Cell Aging with an Imaging-based Biomarker of Chromatin and Epigenetic Aging
Published on: January 30, 2026
Longitudinal dynamics of gene expression and metabolomics in an aging population cohort
Julia S El-Sayed Moustafa1, Anna Ramisch2,3,4, Yasrab N Raza1
1Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Abstract:
Multiomic profiling provides a comprehensive physiological overview at the molecular level, but understanding of its spatiotemporal dynamics remains limited in human populations. We profiled longitudinal whole-blood gene expression and metabolite levels in 335 females over 8 years. Levels of 5061 genes and 181 metabolites changed over time, with individual trajectories often diverging from population-level trends. Longitudinally variable genes showed cell type specificity and enrichment for aging-relevant pathways, including cardiometabolic and neurodegenerative disorders. Longitudinal trajectories were further shaped by genetics, circadian rhythm, seasonality, and environmental pollutant exposures. Integrative analyses revealed extensive static and time-variable cross-omic connectivity. Longitudinal profiling offers insight into the temporal evolution of age-related conditions at the molecular level, and understanding individual variation within these longitudinal patterns will be essential for future precision medicine approaches.
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