AI Article Synopsis

  • Biological age is a measure of a person's risk for negative health outcomes based on biological data, using various methods to gauge this risk.
  • A study comparing multiple biological age measures, including epigenetic and metabolomic markers, analyzed data from over 3,200 participants to assess their effectiveness in predicting frailty and mortality.
  • Results indicated that biomarkers influenced by mortality data, particularly DNAm GrimAge and MetaboHealth, had the strongest associations with frailty and mortality, suggesting that these markers could enhance understanding and evaluation of biological age in clinical settings.

Article Abstract

Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562890PMC
http://dx.doi.org/10.1093/gerona/glad137DOI Listing

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