Evidence map›Paper›PMID 32736664›Full record

ArticleClinical epigenetics2020

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

Robert F Hillary, Anna J Stevenson, Daniel L McCartney, Archie Campbell, Rosie M Walker, David M Howard, Craig W Ritchie, Steve Horvath, Caroline Hayward, Andrew M McIntosh and 4 more

Abstract read
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In one paragraph

Article in Clinical epigenetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 139 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
139citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

139 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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  6. The Role of Epigenetic Clocks in Explaining Educational Inequalities in Mortality: A Multicohort Study and Meta-analysis.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022
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79 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Robert F HillaryCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Anna J StevensonCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Daniel L McCartneyCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Archie CampbellCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Rosie M WalkerCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
David M HowardInstitute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.
Craig W RitchieEdinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4UX, UK.
Steve HorvathDepartment of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90095-7088, USA.
Caroline HaywardMRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Andrew M McIntoshCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
David J PorteousCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Ian J DearyLothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
Kathryn L EvansCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
Riccardo E MarioniCentre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. riccardo.marioni@ed.ac.uk.ORCID 0000-0003-4430-4260

Funding

Validation and optimization of epigenetic clocksU01AG060908 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RITZ, BEATE R. · 2018 to 2022
$3.4M
Chief Scientist Office CZD/16/6Medical Research Council G0700704Medical Research Council MC_PC_17209Medical Research Council MC_UU_00007/10Medical Research Council MR/K026992/1Medical Research Council MR/S035818/1NIA NIH HHS U01 AG060908Wellcome Trust 104036/Z/14/ZWellcome Trust 108890/Z/15/ZWellcome Trust 203771/Z/16/ZWellcome Trust 213674/Z/18/ZWellcome Trust 216767/Z/19/Z
6 · The paper itself

Abstract

backgroundIndividuals 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).

resultsDNAm 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.

conclusionsOur data suggest that epigenetic measures of ageing may have utility in clinical settings to complement gold-standard methods for disease assessment and management.

Indexed as

Cost of IllnessAgingCause of DeathDiabetes Mellitus, Type 2Epigenesis, GeneticEpigenomicsFemaleHumansIncidenceMaleMiddle AgedMyocardial IschemiaPredictive Value of TestsPrevalencePulmonary Disease, Chronic ObstructiveScotlandBiological ageingDNA methylationEpidemiologyEpigenetic age acceleration

Identifiers

PMID32736664
PMCPMC7394682

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.