4.6 Article

Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden

Journal

CLINICAL EPIGENETICS
Volume 12, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s13148-020-00905-6

Keywords

DNA methylation; Biological ageing; Epigenetic age acceleration; Epidemiology

Funding

  1. Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6]
  2. Scottish Funding Council [HR03006]
  3. Medical Research Council UK
  4. Brain AMP
  5. Behavior Research Foundation [27404]
  6. Wellcome Trust [108890/Z/15/Z, 203771/Z/16/Z, 104036/Z/14/Z, 216767/Z/19/Z]
  7. Alzheimer's Research UK [ARUK-PG2017B-10]
  8. Sir Henry Wellcome Postdoctoral Fellowship [213674/Z/18/Z]
  9. 2018 NARSAD Young Investigator Grant from the Brain AMP
  10. Behavior Research Foundation [27404]
  11. UKRI MRC [MC_PC_17209, MR/S035818/1]
  12. European Union [SEP210574971]
  13. [1U01AG060908 01]
  14. Wellcome Trust [216767/Z/19/Z] Funding Source: researchfish
  15. MRC [MC_UU_00007/10, MR/S035818/1, MC_PC_17209] Funding Source: UKRI

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Background Individuals of the same chronological age display different rates of biological ageing. A number of measures of biological age have been proposed which harness age-related changes in DNA methylation profiles. These measures include five 'epigenetic clocks' which provide an index of how much an individual's biological age differs from their chronological age at the time of measurement. The five clocks encompass methylation-based predictors of chronological age (HorvathAge, HannumAge), all-cause mortality (DNAm PhenoAge, DNAm GrimAge) and telomere length (DNAm Telomere Length). A sixth epigenetic measure of ageing differs from these clocks in that it acts as a speedometer providing a single time-point measurement of the pace of an individual's biological ageing. This measure of ageing is termed DunedinPoAm. In this study, we test the association between these six epigenetic measures of ageing and the prevalence and incidence of the leading causes of disease burden and mortality in high-income countries (n <= 9537, Generation Scotland: Scottish Family Health Study). Results DNAm GrimAge predicted incidence of clinically diagnosed chronic obstructive pulmonary disease (COPD), type 2 diabetes and ischemic heart disease after 13 years of follow-up (hazard ratios = 2.22, 1.52 and 1.41, respectively). DunedinPoAm predicted the incidence of COPD and lung cancer (hazard ratios = 2.02 and 1.45, respectively). DNAm PhenoAge predicted incidence of type 2 diabetes (hazard ratio = 1.54). DNAm Telomere Length associated with the incidence of ischemic heart disease (hazard ratio = 0.80). DNAm GrimAge associated with all-cause mortality, the prevalence of COPD and spirometry measures at the study baseline. These associations were present after adjusting for possible confounding risk factors including alcohol consumption, body mass index, deprivation, education and tobacco smoking and surpassed stringent Bonferroni-corrected significance thresholds. Conclusions Our data suggest that epigenetic measures of ageing may have utility in clinical settings to complement gold-standard methods for disease assessment and management.

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