Preprint identifies genetic drivers of protein-level changes over time in TOPMed and UK Biobank
Using longitudinal proteomics data from two major cohorts, researchers have begun mapping which genetic variants influence how protein abundances shift with age across diverse individuals.
A preprint deposited on bioRxiv on 7 August 2026 reports findings from a study of genetic drivers of longitudinal protein changes, drawing on Olink 3k proteomics data from participants in the Multi-Ethnic Study of Atherosclerosis (MESA) and other cohorts within the TOPMed programme, as well as the UK Biobank.
The work addresses a recognised gap in ageing biology: most genetic studies of proteins are cross-sectional, capturing a single time point. Because chronological age and biological age can diverge substantially between individuals, identifying which genetic variants are associated with the trajectory of protein levels — rather than their static abundance — could help characterise the mechanisms that distinguish healthy from accelerated biological ageing.
The authors apply longitudinal modelling frameworks to repeated proteomics measurements, identifying genetic loci associated with the rate of protein change over time. The multi-ethnic design of TOPMed cohorts is noted as relevant for assessing whether such associations generalise across ancestry groups.
This research connects to broader efforts in 'omics clock development and to genomics approaches that aim to distinguish drivers of individual ageing trajectories. As a preprint, the findings have not yet been peer-reviewed.
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Primary sourcePreprint bioRxiv (Cold Spring Harbor Laboratory) · 2026-08-07Genetic drivers of protein changes over time: Findings, considerations, and approaches in TOPMed cohorts and UK Biobank