Evidence map›Paper›PMID 39829316›Full record

ArticleAging cell2025

Assessing Metabolic Ageing via DNA Methylation Surrogate Markers: A Multicohort Study in Britain, Ireland and the USA.

Kexin Xu, Belinda Hernández, Thalida Em Arpawong, Stephane Camuzeaux, Elena Chekmeneva, Eileen M Crimmins, Paul Elliott, Giovani Fiorito, Beatriz Jiménez, Rose Anne Kenny and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Aging cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

17 authors.

Kexin XuMRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.ORCID 0009-0001-7373-7367
Belinda HernándezThe Irish Longitudinal Study on Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Thalida Em ArpawongLeonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA.
Stephane CamuzeauxNational Phenome Centre and Imperial Clinical Phenotyping Centre, Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, London, UK.
Elena ChekmenevaNational Phenome Centre and Imperial Clinical Phenotyping Centre, Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, London, UK.
Eileen M CrimminsLeonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA.
Paul ElliottMRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Giovani FioritoThe Irish Longitudinal Study on Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Beatriz JiménezNational Phenome Centre and Imperial Clinical Phenotyping Centre, Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, London, UK.
Rose Anne KennyThe Irish Longitudinal Study on Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Cathal McCroryThe Irish Longitudinal Study on Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.ORCID 0000-0001-6575-2367
Sinead McLoughlinThe Irish Longitudinal Study on Ageing (TILDA), Department of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.
Rui PintoMRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Caroline SandsNational Phenome Centre and Imperial Clinical Phenotyping Centre, Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, London, UK.
Paolo VineisMRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Chung-Ho E LauMRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.ORCID 0000-0002-3602-8326
Oliver RobinsonMRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.ORCID 0000-0002-4735-0468

Funding

USC/UCLA Center on Biodemography &Population HealthP30AG017265 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JENNIFER A AILSHIRE, HIRAM BELTRAN-SANCHEZ · 1999 to 2026
$17.9M
Social Circumstances and Epigenomics Promoting Health in Three CountriesR01AG068937 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRIMMINS, EILEEN M, FAUL, JESSICA · 2020 to 2025
$2.9M
Biological Underpinnings of Socioeconomic Differentials in Health and MortalityR01AG060110 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRIMMINS, EILEEN M · 2018 to 2022
$2.6M
Health Research BoardHome Office 780-TETRA; 2003-18Irish Research Council Advanced Laureate Award IRCLA/2023/2029Medical Research Council MC_PC_12025National Institute for Health Research Health Protection Research Unit NIHR-200922NIA NIH HHS P30 AG017265NIA NIH HHS R01 AG060110NIA NIH HHS R01AG060110NIA NIH HHS R01 AG068937Science Foundation Ireland SFI-19/US/3615UK Research and Innovation Future Leaders Fellowship MR/S03532X/1UK Research and Innovation Future Leaders Fellowship MR/Y02012X/1
6 · The paper itself

Abstract

Metabolomics and epigenomics have been used to develop 'ageing clocks' that assess biological age and identify 'accelerated ageing'. While metabolites are subject to short-term variation, DNA methylation (DNAm) may capture longer-term metabolic changes. We aimed to develop a hybrid DNAm-metabolic clock using DNAm as metabolite surrogates ('DNAm-metabolites') for age prediction. Within the UK Airwave cohort (n = 820), we developed DNAm metabolites by regressing 594 metabolites on DNAm and selected 177 DNAm metabolites and 193 metabolites to construct 'DNAm-metabolic' and 'metabolic' clocks. We evaluated clocks in their age prediction and association with noncommunicable disease risk factors. We additionally validated the DNAm-metabolic clock for the prediction of age and health outcomes in The Irish Longitudinal Study of Ageing (TILDA, n = 488) and the Health and Retirement Study (HRS, n = 4018). Around 70% of DNAm metabolites showed significant metabolite correlations (Pearson's r: > 0.30, p < 10

Indexed as

AgingBiomarkersDNA MethylationAgedCohort StudiesFemaleHumansIrelandLongitudinal StudiesMaleMiddle AgedUnited KingdomUnited StatesBiomarkersageingbiological agecohort studiesDNA methylationepigeneticsmetabolismmetabolomicsrisk factors

Identifiers

PMID39829316
PMCPMC12073893

What OpenQuestion holds

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Registered trials

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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.