DunedinPACE, a DNA methylation biomarker of the pace of aging

  1. Daniel W Belsky  Is a corresponding author
  2. Avshalom Caspi
  3. David L Corcoran
  4. Karen Sugden
  5. Richie Poulton
  6. Louise Arseneault
  7. Andrea Baccarelli
  8. Kartik Chamarti
  9. Xu Gao
  10. Eilis Hannon
  11. Hona Lee Harrington
  12. Renate Houts
  13. Meeraj Kothari
  14. Dayoon Kwon
  15. Jonathan Mill
  16. Joel Schwartz
  17. Pantel Vokonas
  18. Cuicui Wang
  19. Benjamin S Williams
  20. Terrie E Moffitt
  1. Columbia University, United States
  2. Duke University, United States
  3. University of Otago, New Zealand
  4. King's College London, United Kingdom
  5. Peking University, China
  6. University of Exeter, United Kingdom
  7. Harvard TH Chan School of Public Health, United States
  8. VA Boston Healthcare System, United States

Abstract

Background: Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al. 2020). Here we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome).

Methods: We used data from the Dunedin Study 1972-3 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets.

Results: DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge.

Conclusions: DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience.

Funding: This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.

Data availability

DunedinPACE Data Availability StatementDatasets 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-template.Data 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.Data from the Framingham Heart Study were obtained from dbGaP, accession phs000007.v32.p13.GSE55763 is a publicly available dataset available from the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55763).

The following previously published data sets were used
    1. NHLBI
    (2021) The Framingham Heart Study
    dbGaP, accession phs000007.v32.p13.

Article and author information

Author details

  1. Daniel W Belsky

    Department of Epidemiology, Columbia University, New York, United States
    For correspondence
    db3275@cumc.columbia.edu
    Competing interests
    Daniel W Belsky, is listed as an inventor on a Duke University and University of Otago invention that was licensed to a commercial entity..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5463-2212
  2. Avshalom Caspi

    Center for Genomic and Computational Biology, Duke University, Durham, United States
    Competing interests
    Avshalom Caspi, is listed as an inventor on a Duke University and University of Otago invention that was licensed to a commercial entity..
  3. David L Corcoran

    Center for Genomic and Computational Biology, Duke University, Durham, United States
    Competing interests
    David L Corcoran, is listed as an inventor on a Duke University and University of Otago invention that was licensed to a commercial entity..
  4. Karen Sugden

    Department of Psychology and Neuroscience, Duke University, Durham, United States
    Competing interests
    Karen Sugden, is listed as an inventor on a Duke University and University of Otago invention that was licensed to a commercial entity..
  5. Richie Poulton

    Department of Psychology, University of Otago, Otago, New Zealand
    Competing interests
    Richie Poulton, is listed as an inventor on a Duke University and University of Otago invention that was licensed to a commercial entity..
  6. Louise Arseneault

    Social, Genetic, and Developmental Psychiatry Centre, King's College London, London, United Kingdom
    Competing interests
    No competing interests declared.
  7. Andrea Baccarelli

    Department of Environmental Health Sciences, Columbia University, New York, United States
    Competing interests
    No competing interests declared.
  8. Kartik Chamarti

    Department of Psychology and Neuroscience, Duke University, Durham, United States
    Competing interests
    No competing interests declared.
  9. Xu Gao

    Department of Occupational and Environmental Health, Peking University, Bejing, China
    Competing interests
    No competing interests declared.
  10. Eilis Hannon

    Complex Disease Epigenetics Group, University of Exeter, Exeter, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6840-072X
  11. Hona Lee Harrington

    Department of Psychology and Neuroscience, Duke University, Durham, United States
    Competing interests
    No competing interests declared.
  12. Renate Houts

    Department of Psychology and Neuroscience, Duke University, Durham, United States
    Competing interests
    No competing interests declared.
  13. Meeraj Kothari

    Robert N Butler Columbia Aging Center, Columbia University, Brooklyn, United States
    Competing interests
    No competing interests declared.
  14. Dayoon Kwon

    Robert N Butler Columbia Aging Center, Columbia University, New York, United States
    Competing interests
    No competing interests declared.
  15. Jonathan Mill

    Complex Disease Epigenetics Group, University of Exeter, Exeter, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1115-3224
  16. Joel Schwartz

    Department of Environmental Health Sciences, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    No competing interests declared.
  17. Pantel Vokonas

    Department of Medicine, VA Boston Healthcare System, Boston, United States
    Competing interests
    No competing interests declared.
  18. Cuicui Wang

    Department of Environmental Health Sciences, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    No competing interests declared.
  19. Benjamin S Williams

    Psychology, Duke University, Durham, United States
    Competing interests
    No competing interests declared.
  20. Terrie E Moffitt

    Department of Psychology and Neuroscience, Duke University, Durham, United States
    Competing interests
    Terrie E Moffitt, is listed as an inventors on a Duke University and University of Otago invention that was licensed to a commercial entity..

Funding

National Institute on Aging (AG032282,AG061378,AG066887)

  • Daniel W Belsky
  • Avshalom Caspi
  • Terrie E Moffitt

Medical Research Council (MR/P005918/1)

  • Terrie E Moffitt

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

Reviewing Editor

  1. Joris Deelen, Max Planck Institute for Biology of Ageing, Germany

Publication history

  1. Received: August 27, 2021
  2. Preprint posted: September 2, 2021 (view preprint)
  3. Accepted: December 13, 2021
  4. Accepted Manuscript published: January 14, 2022 (version 1)
  5. Version of Record published: February 17, 2022 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Daniel W Belsky
  2. Avshalom Caspi
  3. David L Corcoran
  4. Karen Sugden
  5. Richie Poulton
  6. Louise Arseneault
  7. Andrea Baccarelli
  8. Kartik Chamarti
  9. Xu Gao
  10. Eilis Hannon
  11. Hona Lee Harrington
  12. Renate Houts
  13. Meeraj Kothari
  14. Dayoon Kwon
  15. Jonathan Mill
  16. Joel Schwartz
  17. Pantel Vokonas
  18. Cuicui Wang
  19. Benjamin S Williams
  20. Terrie E Moffitt
(2022)
DunedinPACE, a DNA methylation biomarker of the pace of aging
eLife 11:e73420.
https://doi.org/10.7554/eLife.73420

Further reading

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    The retrospective cohort included 482,914 Danish patients (60.4% females). The incidence rate ratios (IRRs) of 101 phecodes were found statistically significant between the ABO blood groups, while the IRRs of 28 phecodes were found statistically significant for the RhD blood group. The associations included cancers and musculoskeletal-, genitourinary-, endocrinal-, infectious-, cardiovascular-, and gastrointestinal diseases.

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    We found associations of disease-wide susceptibility differences between the blood groups of the ABO and RhD systems, including cancer of the tongue, monocytic leukemia, cervical cancer, osteoarthrosis, asthma, and HIV- and hepatitis B infection. We found marginal evidence of associations between the blood groups and the age at first diagnosis.

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    1. Epidemiology and Global Health
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    Methods: We constructed PRS using weights curated in the online PGS Catalog. PRS performance was evaluated by distribution, discrimination, predictive ability, and calibration. Hazard ratios (HR) and corresponding confidence intervals [CI] of the common cancers after 20 years of follow-up were estimated using Cox proportional hazard models for different levels of PRS.

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    Funding This work is supported by the National Research Foundation Singapore (NRF-NRFF2017-02), PRECISION Health Research, Singapore (PRECISE) and the Agency for Science, Technology and Research (A*STAR). WP Koh was supported by National Medical Research Council, Singapore (NMRC/CSA/0055/2013). CC Khor was supported by National Research Foundation Singapore (NRF-NRFI2018-01). Rajkumar Dorajoo received a grant from the Agency for Science, Technology and Research Career Development Award (A*STAR CDA - 202D8090), and from Ministry of Health Healthy Longevity Catalyst Award (HLCA20Jan-0022). The Singapore Chinese Health Study was supported by grants from the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016) and the U.S. National Institutes of Health [NIH] (R01 CA144034 and UM1 CA182876).