Evidence mapPaperPMID 39618079Full record

ArticleAging cell2025

Tissue-specific methylomic responses to a lifestyle intervention in older adults associate with metabolic and physiological health improvements.

Lucy Sinke, Marian Beekman, Yotam Raz, Thies Gehrmann, Ioannis Moustakas, Alexis Boulinguiez, Nico Lakenberg, Eka Suchiman, Fatih A Bogaards, Daniele Bizzarri and 7 more

Abstract read
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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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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.

Lucy SinkeMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.ORCID 0000-0002-9209-1266
Marian BeekmanMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Yotam RazMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Thies GehrmannMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Ioannis MoustakasMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Alexis BoulinguiezMyology Center for Research, U974, Sorbonne Université, INSERM, AIM, GH Pitié Salpêtrière Bat Babinski, Paris, France.
Nico LakenbergMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Eka SuchimanMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Fatih A BogaardsMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Daniele BizzarriMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Erik B van den AkkerMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
Melanie WaldenbergerResearch Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Neuherberg, Germany.
Gillian Butler-BrowneMyology Center for Research, U974, Sorbonne Université, INSERM, AIM, GH Pitié Salpêtrière Bat Babinski, Paris, France.
Capucine TrolletMyology Center for Research, U974, Sorbonne Université, INSERM, AIM, GH Pitié Salpêtrière Bat Babinski, Paris, France.
C P G M de GrootDivision of Human Nutrition, Wageningen University and Research, Wageningen, The Netherlands.
Bastiaan T HeijmansMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.ORCID 0000-0001-5918-0534
P Eline SlagboomMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek 050-060-810Nederlandse Organisatie voor Wetenschappelijk Onderzoek 184.021.007ZonMw 457001001ZonMw 529051021
6 · The paper itself

Abstract

Across the lifespan, diet and physical activity profiles substantially influence immunometabolic health. DNA methylation, as a tissue-specific marker sensitive to behavioral change, may mediate these effects through modulation of transcription factor binding and subsequent gene expression. Despite this, few human studies have profiled DNA methylation and gene expression simultaneously in multiple tissues or examined how molecular levels react and interact in response to lifestyle changes. The Growing Old Together (GOTO) study is a 13-week lifestyle intervention in older adults, which imparted health benefits to participants. Here, we characterize the DNA methylation response to this intervention at over 750 thousand CpGs in muscle, adipose, and blood. Differentially methylated sites are enriched for active chromatin states, located close to relevant transcription factor binding sites, and associated with changing expression of insulin sensitivity genes and health parameters. In addition, measures of biological age are consistently reduced, with decreases in grimAge associated with observed health improvements. Taken together, our results identify responsive molecular markers and demonstrate their potential to measure progression and finetune treatment of age-related risks and diseases.

Indexed as

DNA MethylationLife StyleAgedAgingFemaleHumansMaleMiddle AgedOrgan SpecificityDNA methylationepigenomicsfunctional genomicshealthy aginglifestylemetabolismmuscle

Identifiers

PMID39618079
PMCPMC11984676

What Socratic holds

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Registered trials

None linked

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 Socratic graph.