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

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...

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Veröffentlicht in:Nature communications 2024-09, Vol.15 (1), p.8081-19, Article 8081
Hauptverfasser: Zhang, Shiyu, Wang, Zheng, Wang, Yijing, Zhu, Yixiao, Zhou, Qiao, Jian, Xingxing, Zhao, Guihu, Qiu, Jian, Xia, Kun, Tang, Beisha, Mutz, Julian, Li, Jinchen, Li, Bin
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Sprache:eng
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Zusammenfassung: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. The metabolomic changes over the course of aging are complex. Here, the authors present a comprehensive metabolomic profile of aging and construct a metabolomic aging score, which has potential for personalized aging monitoring and early disease-risk identification.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-024-52310-9