TY - JOUR
T1 - Epigenetic and Metabolomic Biomarkers for Biological Age
T2 - A Comparative Analysis of Mortality and Frailty Risk
AU - Kuiper, Lieke M.
AU - Polinder-Bos, Harmke A.
AU - Bizzarri, Daniele
AU - Vojinovic, Dina
AU - Vallerga, Costanza L.
AU - Reinders, Marcel J.T.
AU - Slagboom, P. Eline
AU - van den Akker, Erik B.
AU - More Authors, null
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - DNA methylation
KW - Frailty
KW - Mortality
UR - http://www.scopus.com/inward/record.url?scp=85173583279&partnerID=8YFLogxK
U2 - 10.1093/gerona/glad137
DO - 10.1093/gerona/glad137
M3 - Article
C2 - 37303208
AN - SCOPUS:85173583279
SN - 1079-5006
VL - 78
SP - 1753
EP - 1762
JO - The journals of gerontology. Series A, Biological sciences and medical sciences
JF - The journals of gerontology. Series A, Biological sciences and medical sciences
IS - 10
ER -