---
_id: '12719'
abstract:
- lang: eng
  text: "Background\r\nEpigenetic clocks can track both chronological age (cAge) and
    biological age (bAge). The latter is typically defined by physiological biomarkers
    and risk of adverse health outcomes, including all-cause mortality. As cohort
    sample sizes increase, estimates of cAge and bAge become more precise. Here, we
    aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving
    our understanding of their epigenomic architecture.\r\n\r\nMethods\r\nFirst, we
    perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of
    chronological age and all-cause mortality. Next, to create a cAge predictor, we
    use methylation data from 24,674 participants from the Generation Scotland study,
    the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly
    available data. In addition, we train a predictor of time to all-cause mortality
    as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths).
    For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins
    and the 8 component parts of GrimAge, one of the current best epigenetic predictors
    of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936,
    the Framingham Heart Study and the Women’s Health Initiative study).\r\n\r\nResults\r\nThrough
    the inclusion of linear and non-linear age-CpG associations from the EWAS, feature
    pre-selection in advance of elastic net regression, and a leave-one-cohort-out
    (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute
    error equal to 2.3 years. Our bAge predictor was found to slightly outperform
    GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47
    [1.40, 1.54] with p = 1.08 × 10−52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10−60).
    Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide
    CpG-age associations.\r\n\r\nConclusions\r\nThe integration of multiple large
    datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection
    has facilitated improvements to the blood-based epigenetic prediction of biological
    and chronological age."
acknowledgement: We are grateful to all the families who took part, the general practitioners,
  and the Scottish School of Primary Care for their help in recruiting them and the
  whole GS team that includes interviewers, computer and laboratory technicians, clerical
  workers, research scientists, volunteers, managers, receptionists, healthcare assistants,
  and nurses.
article_number: '12'
article_processing_charge: No
article_type: original
author:
- first_name: Elena
  full_name: Bernabeu, Elena
  last_name: Bernabeu
- first_name: Daniel L.
  full_name: Mccartney, Daniel L.
  last_name: Mccartney
- first_name: Danni A.
  full_name: Gadd, Danni A.
  last_name: Gadd
- first_name: Robert F.
  full_name: Hillary, Robert F.
  last_name: Hillary
- first_name: Ake T.
  full_name: Lu, Ake T.
  last_name: Lu
- first_name: Lee
  full_name: Murphy, Lee
  last_name: Murphy
- first_name: Nicola
  full_name: Wrobel, Nicola
  last_name: Wrobel
- first_name: Archie
  full_name: Campbell, Archie
  last_name: Campbell
- first_name: Sarah E.
  full_name: Harris, Sarah E.
  last_name: Harris
- first_name: David
  full_name: Liewald, David
  last_name: Liewald
- first_name: Caroline
  full_name: Hayward, Caroline
  last_name: Hayward
- first_name: Cathie
  full_name: Sudlow, Cathie
  last_name: Sudlow
- first_name: Simon R.
  full_name: Cox, Simon R.
  last_name: Cox
- first_name: Kathryn L.
  full_name: Evans, Kathryn L.
  last_name: Evans
- first_name: Steve
  full_name: Horvath, Steve
  last_name: Horvath
- first_name: Andrew M.
  full_name: Mcintosh, Andrew M.
  last_name: Mcintosh
- first_name: Matthew Richard
  full_name: Robinson, Matthew Richard
  id: E5D42276-F5DA-11E9-8E24-6303E6697425
  last_name: Robinson
  orcid: 0000-0001-8982-8813
- first_name: Catalina A.
  full_name: Vallejos, Catalina A.
  last_name: Vallejos
- first_name: Riccardo E.
  full_name: Marioni, Riccardo E.
  last_name: Marioni
citation:
  ama: Bernabeu E, Mccartney DL, Gadd DA, et al. Refining epigenetic prediction of
    chronological and biological age. <i>Genome Medicine</i>. 2023;15. doi:<a href="https://doi.org/10.1186/s13073-023-01161-y">10.1186/s13073-023-01161-y</a>
  apa: Bernabeu, E., Mccartney, D. L., Gadd, D. A., Hillary, R. F., Lu, A. T., Murphy,
    L., … Marioni, R. E. (2023). Refining epigenetic prediction of chronological and
    biological age. <i>Genome Medicine</i>. Springer Nature. <a href="https://doi.org/10.1186/s13073-023-01161-y">https://doi.org/10.1186/s13073-023-01161-y</a>
  chicago: Bernabeu, Elena, Daniel L. Mccartney, Danni A. Gadd, Robert F. Hillary,
    Ake T. Lu, Lee Murphy, Nicola Wrobel, et al. “Refining Epigenetic Prediction of
    Chronological and Biological Age.” <i>Genome Medicine</i>. Springer Nature, 2023.
    <a href="https://doi.org/10.1186/s13073-023-01161-y">https://doi.org/10.1186/s13073-023-01161-y</a>.
  ieee: E. Bernabeu <i>et al.</i>, “Refining epigenetic prediction of chronological
    and biological age,” <i>Genome Medicine</i>, vol. 15. Springer Nature, 2023.
  ista: Bernabeu E, Mccartney DL, Gadd DA, Hillary RF, Lu AT, Murphy L, Wrobel N,
    Campbell A, Harris SE, Liewald D, Hayward C, Sudlow C, Cox SR, Evans KL, Horvath
    S, Mcintosh AM, Robinson MR, Vallejos CA, Marioni RE. 2023. Refining epigenetic
    prediction of chronological and biological age. Genome Medicine. 15, 12.
  mla: Bernabeu, Elena, et al. “Refining Epigenetic Prediction of Chronological and
    Biological Age.” <i>Genome Medicine</i>, vol. 15, 12, Springer Nature, 2023, doi:<a
    href="https://doi.org/10.1186/s13073-023-01161-y">10.1186/s13073-023-01161-y</a>.
  short: E. Bernabeu, D.L. Mccartney, D.A. Gadd, R.F. Hillary, A.T. Lu, L. Murphy,
    N. Wrobel, A. Campbell, S.E. Harris, D. Liewald, C. Hayward, C. Sudlow, S.R. Cox,
    K.L. Evans, S. Horvath, A.M. Mcintosh, M.R. Robinson, C.A. Vallejos, R.E. Marioni,
    Genome Medicine 15 (2023).
date_created: 2023-03-12T23:01:02Z
date_published: 2023-02-28T00:00:00Z
date_updated: 2023-08-01T13:38:12Z
day: '28'
ddc:
- '570'
department:
- _id: MaRo
doi: 10.1186/s13073-023-01161-y
external_id:
  isi:
  - '000940286600001'
file:
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  date_created: 2023-03-14T10:29:47Z
  date_updated: 2023-03-14T10:29:47Z
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file_date_updated: 2023-03-14T10:29:47Z
has_accepted_license: '1'
intvolume: '        15'
isi: 1
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
publication: Genome Medicine
publication_identifier:
  eissn:
  - 1756-994X
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Refining epigenetic prediction of chronological and biological age
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 15
year: '2023'
...