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

Area of Science:

• Metabolomics
• Aging Research
• Biomarkers

Background:

• Existing metabolomic clocks fail to capture individual aging rate heterogeneity.
• Systematic study of modifiable and non-modifiable factors in metabolomic aging is lacking.

Purpose of the Study:

• Develop a novel aging measure, MetaboAgeMort, for 10-year all-cause mortality prediction.
• Investigate factors influencing metabolomic aging and their association with health outcomes.

Main Methods:

• Utilized metabolomic profiles from 239,291 UK Biobank participants.
• Developed MetaboAgeMort for mortality prediction and analyzed associations with mortality, diseases, and risk factors.
• Performed genetic and tissue-enrichment analyses.

Main Results:

• MetaboAgeMort significantly predicted all-cause and cause-specific mortality, and incident diseases.
• Incorporating MetaboAgeMort improved 10-year mortality prediction.
• Identified 99 modifiable factors, with pulmonary function, body composition, diet, smoking, alcohol, and disease status showing strong associations.
• Discovered 99 genomic risk loci and 271 associated genes, with significant liver enrichment.

Conclusions:

• MetaboAgeMort effectively captures heterogeneous metabolomic aging.
• Identified key modifiable factors for potential interventions to promote healthy aging.
• Highlights the potential for personalized interventions and anti-aging therapies.