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

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Listed:
  • Shiyu Zhang

    (Central South University
    Central South University)

  • Zheng Wang

    (Central South University
    Central South University
    Central South University)

  • Yijing Wang

    (Central South University)

  • Yixiao Zhu

    (Central South University)

  • Qiao Zhou

    (Central South University)

  • Xingxing Jian

    (Central South University)

  • Guihu Zhao

    (Central South University)

  • Jian Qiu

    (Central South University
    Central South University
    Central South University)

  • Kun Xia

    (Central South University)

  • Beisha Tang

    (Central South University
    Central South University
    The First Affiliated Hospital University of South China)

  • Julian Mutz

    (King’s College London)

  • Jinchen Li

    (Central South University
    Central South University
    Xiangya Hospital & Furong Laboratory)

  • Bin Li

    (Central South University)

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.

Suggested Citation

  • 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, 2024. "A metabolomic profile of biological aging in 250,341 individuals from the UK Biobank," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-52310-9
    DOI: 10.1038/s41467-024-52310-9
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