生命银行
代谢组学
计算生物学
医学
生物
数据科学
生物信息学
计算机科学
作者
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
标识
DOI:10.1038/s41467-024-52310-9
摘要
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.
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