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Longitudinal dynamics of gene expression and metabolomics in an aging population cohort.

Created on 04 Sep 2026

Authors

Julia S El-Sayed Moustafa, Anna Ramisch, Yasrab N Raza, Gwenael G R Leday, Yunlong Jiao, Dongmeng Wang, Michael Stevens, Amy L Roberts, Max Tomlinson, Xinyu Yan, Elizabeth Ing-Simmons, Samuel Wadge, Moustafa Abdalla, Mario Falchi, Christopher C Holmes, Cristina Menni, George Nicholson, Mark I McCarthy, Emmanouil T Dermitzakis, Sylvia Richardson, Tim D Spector, Kerrin S Small

Published in

Science (New York, N.Y.). Volume 393. Issue 6815. Pages eaed6452. Sep 03, 2026. Epub Sep 03, 2026.

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.

PMID:
42691178
Bibliographic data and abstract were imported from PubMed on 04 Sep 2026.

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