Nature Communications (Sep 2024)

A metabolomic profile of biological aging in 250,341 individuals from the UK Biobank

  • Shiyu Zhang,
  • Zheng Wang,
  • Yijing Wang,
  • Yixiao Zhu,
  • Qiao Zhou,
  • Xingxing Jian,
  • Guihu Zhao,
  • Jian Qiu,
  • Kun Xia,
  • Beisha Tang,
  • Julian Mutz,
  • Jinchen Li,
  • Bin Li

DOI
https://doi.org/10.1038/s41467-024-52310-9
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 19

Abstract

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Abstract The metabolomic profile of aging is complex. Here, we analyse 325 nuclear magnetic resonance (NMR) biomarkers from 250,341 UK Biobank participants, identifying 54 representative aging-related biomarkers associated with all-cause mortality. We conduct genome-wide association studies (GWAS) for these 325 biomarkers using whole-genome sequencing (WGS) data from 95,372 individuals and perform multivariable Mendelian randomization (MVMR) analyses, discovering 439 candidate “biomarker - disease” causal pairs at the nominal significance level. We develop a metabolomic aging score that outperforms other aging metrics in predicting short-term mortality risk and exhibits strong potential for discriminating aging-accelerated populations and improving disease risk prediction. A longitudinal analysis of 13,263 individuals enables us to calculate a metabolomic aging rate which provides more refined aging assessments and to identify candidate anti-aging and pro-aging NMR biomarkers. Taken together, our study has presented a comprehensive aging-related metabolomic profile and highlighted its potential for personalized aging monitoring and early disease intervention.