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Understanding biological aging through metabolic profiles
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Abstract
Chronological age is a crucial risk factor for diseases and disabilities among older adults.
- Individuals of the same chronological age can show different biological aging states, leading to varied health risk profiles.
- Aging clocks, which utilize omics data and machine learning, can help interpret biological aging at the molecular level.
- Metabolomics, which profiles small molecules in the body, offers insights into genome-environment interactions related to aging.
- Metabolomic aging clocks may provide a valuable framework for understanding biological aging.
- The review discusses the strengths, limitations, and applications of metabolomic approaches in the context of aging.
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