Quantification of the pace of biological aging in humans through a blood test, The DunedinPoAm DNA methylation algorithm

  1. Daniel W W Belsky  Is a corresponding author
  2. Avshalom Caspi
  3. Louise Arseneault
  4. Andrea Baccarelli
  5. David L Corcoran
  6. Xu Gao
  7. Eiliss Hannon
  8. Hona Lee Harrington
  9. Line J H Rasmussen
  10. Renate Houts
  11. Kim Huffman
  12. William E Kraus
  13. Dayoon Kwon
  14. Jonathan Mill
  15. Carl F Pieper
  16. Joseph A Prinz
  17. Richie Poulton
  18. Joel Schwartz
  19. Karen Sugden
  20. Pantel Vokonas
  21. Benjamin S Williams
  22. Terrie E Moffitt
  1. Columbia University Mailman School of Public Health, United States
  2. Duke University, United States
  3. Institute of Psychiatry, Kings College London, United Kingdom
  4. University of Exeter, United Kingdom
  5. Duke University, United Kingdom
  6. University of Otago, New Zealand
  7. Harvard TH Chan School of Public Health, United States
  8. Boston University School of Medicine, United States

Abstract

Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n=954 members of the Dunedin Study born in 1972-1973. Rates of change in each biomarker over ages 26-38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person's pace of biological aging.

Data availability

Datasets are available from the data owners. Data from the Dunedin and E-Risk Study can be accessed through agreement with the Study investigators. Instructions are available at https://sites.google.com/site/moffittcaspiprojects/. The data access application form can be downloaded here: https://sites.google.com/site/moffittcaspiprojects/forms-for-new-projects/concept-paper-templateData from the Understanding Society Study is available through METADAC at https://www.metadac.ac.uk/ukhls/. All details are on the Metadac website (https://www.metadac.ac.uk/data-access-through-metadac/). The data access application form can be found here https://www.metadac.ac.uk/files/2019/02/v2.41-UKHLS-METADAC-application-form-2019-2hak8bv.docx Data from the Normative Aging Study were obtained from the Study investigators. Data are accessible through dbGaP, accession phs000853.v1.p1. CALERIE Data are available for download from the CALERIE Biorepository at https://calerie.duke.edu/. Details are on the website here: https://calerie.duke.edu/samples-data-access-and-analysis

Article and author information

Author details

  1. Daniel W W Belsky

    Epidemiology, Columbia University Mailman School of Public Health, New York, United States
    For correspondence
    db3275@cumc.columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5463-2212
  2. Avshalom Caspi

    Psychology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Louise Arseneault

    SGDP, Institute of Psychiatry, Kings College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Andrea Baccarelli

    Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. David L Corcoran

    Center for Genomic and Computational Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Xu Gao

    Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Eiliss Hannon

    Complex Disease Epigenetics Group, University of Exeter, Exeter, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Hona Lee Harrington

    Psychology, Duke University, Durham, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  9. Line J H Rasmussen

    Psychology & Neuroscience, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6613-2469
  10. Renate Houts

    Psychology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Kim Huffman

    DMPI, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. William E Kraus

    Department of Medicine, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Dayoon Kwon

    Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Jonathan Mill

    University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  15. Carl F Pieper

    Biostatistics, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Joseph A Prinz

    Biostatistics, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  17. Richie Poulton

    University of Otago, Otago, New Zealand
    Competing interests
    The authors declare that no competing interests exist.
  18. Joel Schwartz

    Epidemiology, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  19. Karen Sugden

    Biostatistics, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  20. Pantel Vokonas

    Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  21. Benjamin S Williams

    Psychology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  22. Terrie E Moffitt

    Biostatistics, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

Medical Research Council (MR/P005918/1)

  • Terrie E Moffitt

Medical Research Council (G1002190)

  • Terrie E Moffitt

National Institute on Aging (AG032282)

  • Terrie E Moffitt

National Institute on Aging (U24AG047121)

  • William E Kraus

National Institute on Aging (R01AG061378)

  • Daniel W W Belsky

National Institute on Aging (R21AG054846)

  • Daniel W W Belsky

National Institute of Child Health and Development (HD077482)

  • Avshalom Caspi

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Sara Hagg, Karolinska Institutet, Sweden

Ethics

Human subjects: Research participants provided informed consent for participation in the included studies. Approval for this study was provided by the institutional review boards of the New Zealand Ministry of Health Health and Disability Ethics Committee (17/STH/25/AM05), Duke University (protocols 1604 and 0414B0360), Duke University Medical Center (00078391) and Columbia University Irving Medical Center (protocols AAAS2948 and AAAQ8739).

Version history

  1. Received: January 3, 2020
  2. Accepted: April 22, 2020
  3. Accepted Manuscript published: May 5, 2020 (version 1)
  4. Version of Record published: June 9, 2020 (version 2)
  5. Version of Record updated: June 11, 2020 (version 3)

Copyright

© 2020, Belsky et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Daniel W W Belsky
  2. Avshalom Caspi
  3. Louise Arseneault
  4. Andrea Baccarelli
  5. David L Corcoran
  6. Xu Gao
  7. Eiliss Hannon
  8. Hona Lee Harrington
  9. Line J H Rasmussen
  10. Renate Houts
  11. Kim Huffman
  12. William E Kraus
  13. Dayoon Kwon
  14. Jonathan Mill
  15. Carl F Pieper
  16. Joseph A Prinz
  17. Richie Poulton
  18. Joel Schwartz
  19. Karen Sugden
  20. Pantel Vokonas
  21. Benjamin S Williams
  22. Terrie E Moffitt
(2020)
Quantification of the pace of biological aging in humans through a blood test, The DunedinPoAm DNA methylation algorithm
eLife 9:e54870.
https://doi.org/10.7554/eLife.54870

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https://doi.org/10.7554/eLife.54870

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