Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Lieke M. Kuiper; Harmke A. Polinder-Bos; Daniele Bizzarri; Dina Vojinovic; Costanza L. Vallerga; Marian Beekman; E. T. Dollé; Mohsen Ghanbari; Trudy Voortman; Marcel J.T. Reinders; W. M.Monique Verschuren; P. Eline Slagboom; Erik B. van den Akker; Joyce B.J. van Meurs

doi:10.1093/gerona/glad137

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Lieke M. Kuiper
, Harmke A. Polinder-Bos
, Daniele Bizzarri
, Dina Vojinovic
, Costanza L. Vallerga
, Marian Beekman
, E. T. Dollé
, Mohsen Ghanbari
, Trudy Voortman
, Marcel J.T. Reinders
, W. M.Monique Verschuren
, P. Eline Slagboom
, Erik B. van den Akker
, Joyce B.J. van Meurs^*

^*Corresponding author for this work

Leiden University Medical Centre
Delft University of Technology
National Institute of Public Health and the Environment
Center for Nutrition
Utrecht University
Max Planck Institute for Biology of Ageing

Research output: Contribution to journal › Article › Academic › peer-review

67 Citations (Scopus)

146 Downloads (Pure)

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.

Original language	English
Pages (from-to)	1753-1762
Number of pages	10
Journal	The journals of gerontology. Series A, Biological sciences and medical sciences
Volume	78
Issue number	10
DOIs	https://doi.org/10.1093/gerona/glad137
Publication status	Published - 1 Oct 2023

Bibliographical note

Publisher Copyright:
© The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https:// creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited.

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Cite this

Kuiper, L. M., Polinder-Bos, H. A., Bizzarri, D., Vojinovic, D., Vallerga, C. L., Beekman, M., Dollé, E. T., Ghanbari, M., Voortman, T., Reinders, M. J. T., Verschuren, W. M. M., Slagboom, P. E., van den Akker, E. B., & van Meurs, J. B. J. (2023). Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk. The journals of gerontology. Series A, Biological sciences and medical sciences, 78(10), 1753-1762. https://doi.org/10.1093/gerona/glad137

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title = "Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk",

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.",

author = "Kuiper, \{Lieke M.\} and Polinder-Bos, \{Harmke A.\} and Daniele Bizzarri and Dina Vojinovic and Vallerga, \{Costanza L.\} and Marian Beekman and Doll{\'e}, \{E. T.\} and Mohsen Ghanbari and Trudy Voortman and Reinders, \{Marcel J.T.\} and Verschuren, \{W. M.Monique\} and Slagboom, \{P. Eline\} and \{van den Akker\}, \{Erik B.\} and \{van Meurs\}, \{Joyce B.J.\}",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https:// creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited.",

year = "2023",

month = oct,

day = "1",

doi = "10.1093/gerona/glad137",

language = "English",

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Kuiper, LM, Polinder-Bos, HA, Bizzarri, D, Vojinovic, D , Vallerga, CL, Beekman, M, Dollé, ET, Ghanbari, M , Voortman, T, Reinders, MJT, Verschuren, WMM, Slagboom, PE, van den Akker, EB & van Meurs, JBJ 2023, 'Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk', The journals of gerontology. Series A, Biological sciences and medical sciences, vol. 78, no. 10, pp. 1753-1762. https://doi.org/10.1093/gerona/glad137

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk. / Kuiper, Lieke M.; Polinder-Bos, Harmke A.; Bizzarri, Daniele et al.
In: The journals of gerontology. Series A, Biological sciences and medical sciences, Vol. 78, No. 10, 01.10.2023, p. 1753-1762.

Research output: Contribution to journal › Article › Academic › peer-review

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AU - Kuiper, Lieke M.

AU - Polinder-Bos, Harmke A.

AU - Bizzarri, Daniele

AU - Vojinovic, Dina

AU - Vallerga, Costanza L.

AU - Beekman, Marian

AU - Dollé, E. T.

AU - Ghanbari, Mohsen

AU - Voortman, Trudy

AU - Reinders, Marcel J.T.

AU - Verschuren, W. M.Monique

AU - Slagboom, P. Eline

AU - van den Akker, Erik B.

AU - van Meurs, Joyce B.J.

N1 - Publisher Copyright: © The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https:// creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited.

PY - 2023/10/1

Y1 - 2023/10/1

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.

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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 -

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

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