ArticleThe Journal of clinical endocrinology and metabolism2023
Cross-sectionally Calculated Metabolic Aging Does Not Relate to Longitudinal Metabolic Changes-Support for Stratified Aging Models.
Article in The Journal of clinical endocrinology and metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 15 citations in OpenAlex.
- Proteomic aging clocks in epidemiological studies: advances, applications and prospects.Nature aging · 2026Review
- Review
- Metabolomic-based aging clocks.npj metabolic health and disease · 2025Review
- Longitudinal analysis of genetic and environmental interplay in human metabolic profiles and the implication for metabolic health.Genome medicine · 2025Article
- Relationship Between Metabolic Age Determined by Bioimpedance and Insulin Resistance Risk Scales in Spanish Workers.Nutrients · 2025Article
- A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Article
- Influence of age and sex on longitudinal metabolic profiles and body weight trajectories in the UK Biobank.International journal of epidemiology · 2024Article
- Technical Report: A Comprehensive Comparison between Different Quantification Versions of Nightingale Health'sMetabolites · 2023Article
- NMR metabolomic modelling of age and lifespan: a multi-cohort analysis.medRxiv : the preprint server for health sciences · 2023Article
- Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic.International journal of obesity (2005) · 2023Observational
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextAging varies between individuals, with profound consequences for chronic diseases and longevity. One hypothesis to explain the diversity is a genetically regulated molecular clock that runs differently between individuals. Large human studies with long enough follow-up to test the hypothesis are rare due to practical challenges, but statistical models of aging are built as proxies for the molecular clock by comparing young and old individuals cross-sectionally. These models remain untested against longitudinal data.
objectiveWe applied novel methodology to test if cross-sectional modeling can distinguish slow vs accelerated aging in a human population.
methodsWe trained a machine learning model to predict age from 153 clinical and cardiometabolic traits. The model was tested against longitudinal data from another cohort. The training data came from cross-sectional surveys of the Finnish population (n = 9708; ages 25-74 years). The validation data included 3 time points across 10 years in the Young Finns Study (YFS; n = 1009; ages 24-49 years). Predicted metabolic age in 2007 was compared against observed aging rate from the 2001 visit to the 2011 visit in the YFS dataset and correlation between predicted vs observed metabolic aging was determined.
resultsThe cross-sectional proxy failed to predict longitudinal observations (R2 = 0.018%, P = 0.67).
conclusionThe finding is unexpected under the clock hypothesis that would produce a positive correlation between predicted and observed aging. Our results are better explained by a stratified model where aging rates per se are similar in adulthood but differences in starting points explain diverging metabolic fates.
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