A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors

Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, a new aging measure-MetaboAgeMort-is developed using metabolomic profiles from 239,291 UK Biobank participants for 10-year all-cause mortality prediction. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to a conventional risk factors model improved the predictive ability of 10-year mortality. A total of 99 modifiable factors across seven categories are identified for MetaboAgeMort. Among these, 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. The tissue-enrichment analysis showed significant enrichment in liver. While the external validation of the MetaboAgeMort is required, this study illuminates heterogeneous metabolomic aging across the same age, providing avenues for identifying high-risk individuals, developing anti-aging therapies, and personalizing interventions, thus promoting healthy aging and longevity.

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Publication Details

Journal
Advanced Science
Published
2024-09-27
DOI
https://doi.org/10.1002/advs.202406670
Citations
21
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
4.91

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article

A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors

Xueqing Jia, Xingqi Cao, Lina Ma, Daniele Bizzarri et al.
21 citations
Advanced Science
Metabolomics and Mass Spectrometry Studies
4.91
article

A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors

Xueqing Jia, Xingqi Cao, Lina Ma, Daniele Bizzarri, Erik B. van den Akker, Joris Deelen, Zeinab Abdelrahman, Zuyun Liu, Haitao Zhu, P. Eline Slagboom, Dan Zhou, Fei Zhao, Jiayao Fan, Xucheng Wu
article en
21 citations

Abstract

Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, a new aging measure-MetaboAgeMort-is developed using metabolomic profiles from 239,291 UK Biobank participants for 10-year all-cause mortality prediction. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to a conventional risk factors model improved the predictive ability of 10-year mortality. A total of 99 modifiable factors across seven categories are identified for MetaboAgeMort. Among these, 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. The tissue-enrichment analysis showed significant enrichment in liver. While the external validation of the MetaboAgeMort is required, this study illuminates heterogeneous metabolomic aging across the same age, providing avenues for identifying high-risk individuals, developing anti-aging therapies, and personalizing interventions, thus promoting healthy aging and longevity.

Advanced ScienceVol. 11(43)
Queen's University Belfast (GB), University of Ulster (GB), University of Cologne (DE), Capital Medical University (CN), Leiden University Medical Center (NL), Sir Run Run Shaw Hospital (CN), Royal Victoria Hospital (GB), Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (DE), Max Planck Institute for Biology of Ageing (DE), Second Affiliated Hospital of Zhejiang University (CN), Zhejiang University (CN), Delft University of Technology (NL)
National Natural Science Foundation of China, Zhejiang University, Fundamental Research Funds for the Central Universities
Good health and well-being
Openalex Percentile: Top 4%
Metabolomics and Mass Spectrometry Studies
4.91
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