| Title: | A metabolomic profile of biological aging in 250,341 individuals from the UK Biobank |
| Journal: | Nature Communications |
| Published: | 15 Sep 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39278973/ |
| DOI: | https://doi.org/10.1038/s41467-024-52310-9 |
Publication 13485
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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.</p>
19 Keywords
- Adult
- Aged
- Aged, 80 and over
- Aging
- Biological Specimen Banks
- Biomarkers
- Female
- Genome-Wide Association Study
- Humans
- Longitudinal Studies
- Magnetic Resonance Spectroscopy
- Male
- Mendelian Randomization Analysis
- Metabolome
- Metabolomics
- Middle Aged
- UK Biobank
- United Kingdom
- Whole Genome Sequencing
13 Authors
- 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
1 Application
| Application ID | Title |
|---|---|
| 103082 | The association between age-related diseases and multi-omics, aging and environmental factors |
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