Assessment of ageing using global mass-spectrometry based metabolomics: A cross-cohort longitudinal study in the UK and Ireland
The study developed a metabolomic clock that predicts chronological age and is associated with increased risks of mortality, cognitive impairment, and frailty.
Where it sits
this study against the rest of the pe 22-28 corpusSummary and findings
This study assessed biological age using LC-MS metabolomics in 2,295 participants aged 20-89 from the UK and Ireland. The research identified several metabolites associated with chronological age, frailty, and mortality. A metabolomic clock was developed, showing a strong correlation with chronological age.
Abstract
<h4>Introduction</h4> Understanding the links between metabolism, ageing and age-related phenotypes may clarify the role of ageing in disease onset and improve risk prediction. <h4>Methods</h4> We conducted a cross-cohort assessment of biological age using broad-spectrum LC-MS metabolomics in 2,295 participants, aged 20-89, from the UK Airwave study (N=960) and The Irish Longitudinal Study of Ageing (N=1,335). <h4>Results</h4> N 2 ,N 2 -dimethylguanosine, C-glycosyltryptophan, bile acid glucuronides, and zeta-carotene were associated with chronological age, frailty, and mortality. We developed a metabolomic clock that was highly predictive of chronological age (r = 0.92) in test samples. Metabolomic age acceleration was strongly correlated between study visits ( r > 0.6). Each standard deviation higher metabolomic age acceleration (∼5 years) was associated with 43% higher mortality risk, 27% higher risk of mild cognitive impairment, and 10% increased risk of a higher frailty score in fully adjusted models. <h4>Discussion</h4> Our metabolomic clock provides a reproducible marker of generalised age-related disease risk.