Evidence map›Paper›PMID 28399939›Full record

ArticleGenome biology2017

Multi-tissue DNA methylation age predictor in mouse.

Thomas M Stubbs, Marc Jan Bonder, Anne-Katrien Stark, Felix Krueger, BI Ageing Clock Team, Ferdinand von Meyenn, Oliver Stegle, Wolf Reik

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 240 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
240citing papers in PubMed, 1 pooled it
18.6field-weighted citation impact, top 1% of its field
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

240 citing papers in PubMed, 1 synthesis or guideline pooled it, 427 citations in OpenAlex.

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  20. Designing Epigenetic Clocks for Wildlife Research.Molecular ecology resources · 2025
    Review

180 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

8 authors at 2 institutions in 1 country.

Thomas M StubbsEpigenetics Programme, The Babraham Institute, Cambridge, CB22 3AT, UK.
Marc Jan BonderEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK.
Anne-Katrien StarkImmunology Programme, The Babraham Institute, Cambridge, CB22 3AT, UK.
Felix KruegerBioinformatics Group, The Babraham Institute, Cambridge, CB22 3AT, UK.
BI Ageing Clock Team
Ferdinand von MeyennEpigenetics Programme, The Babraham Institute, Cambridge, CB22 3AT, UK. vonmeyenn@babraham.ac.uk.
Oliver StegleEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK. oliver.stegle@ebi.ac.uk.
Wolf ReikEpigenetics Programme, The Babraham Institute, Cambridge, CB22 3AT, UK. wolf.reik@babraham.ac.uk.
Babraham Institute · GBEuropean Bioinformatics Institute · GB

Funding

Biotechnology and Biological Sciences Research Council BB/K010867/1Biotechnology and Biological Sciences Research Council BBS/E/B/000C0407Biotechnology and Biological Sciences Research Council BBS/E/B/000C0409Wellcome Trust 095645/Z/11/Z
6 · The paper itself

Abstract

backgroundDNA methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing process. It has also not been shown whether this epigenetic clock is unique to humans or conserved in the more experimentally tractable mouse.

resultsWe have generated a comprehensive set of genome-scale base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. Many CpG sites show significant tissue-independent correlations with age which allowed us to develop a multi-tissue predictor of age in the mouse. Our model, which estimates age based on DNA methylation at 329 unique CpG sites, has a median absolute error of 3.33 weeks and has similar properties to the recently described human epigenetic clock. Using publicly available datasets, we find that the mouse clock is accurate enough to measure effects on biological age, including in the context of interventions. While females and males show no significant differences in predicted DNA methylation age, ovariectomy results in significant age acceleration in females. Furthermore, we identify significant differences in age-acceleration dependent on the lipid content of the diet.

conclusionsHere we identify and characterise an epigenetic predictor of age in mice, the mouse epigenetic clock. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ticking rate and resetting the clock in vivo to study the impact on biological age.

Indexed as

DNA MethylationEpigenesis, GeneticAgingAnimalsCluster AnalysisCpG IslandsEpigenomicsFemaleGene Expression ProfilingHumansMaleMiceOrgan SpecificityAgeing/agingBiological ageChronological ageDNA methylationEpigenetic clockEpigeneticsHigh fat dietModelOvariectomyPrediction

Identifiers

PMID28399939
PMCPMC5389178
OpenAlexW2606865793

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.