Evidence map›Paper›PMID 34372922›Full record

ArticleClinical epigenetics2021

Childhood growth and development and DNA methylation age in mid-life.

Jane Maddock, Juan Castillo-Fernandez, Andrew Wong, George B Ploubidis, Diana Kuh, Jordana T Bell, Rebecca Hardy

Open access · goldAbstract readComparative Study
In one paragraph

Article in Clinical epigenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 27% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Using Epigenetic Clocks to Characterize Biological Aging in Studies of Children and Childhood Exposures: a Systematic Review.Prevention science : the official journal of the Society for Prevention Research · 2023
    Pooled it
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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

7 authors at 3 institutions in 1 country.

Jane MaddockMRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK. jane.maddock@ucl.ac.uk.ORCID 0000-0002-7975-4221
Juan Castillo-FernandezDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Andrew WongMRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
George B PloubidisCentre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK.
Diana KuhMRC Unit for Lifelong Health and Ageing at UCL, Faculty of Population Health, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
Jordana T BellDepartment of Twin Research and Genetic Epidemiology, King's College London, London, UK.
Rebecca HardyCLOSER, UCL Institute of Education, University College London, London, WC1H 0NU, UK.
MRC Unit for Lifelong Health and Ageing · GBKing's College London · GBUniversity College London · GB

Funding

Biotechnology and Biological Sciences Research Council ES/N000404/1Economic and Social Research Council ES/K000357/1Economic and Social Research Council ES/N000404/1Medical Research Council MC_UU_00019/1Medical Research Council MC_UU_00019/4Medical Research Council MC_UU_12019/2Medical Research Council MR/P023444/1
6 · The paper itself

Abstract

backgroundIn the first study of its kind, we examine the association between growth and development in early life and DNAm age biomarkers in mid-life.

methodsParticipants were from the Medical Research Council National Survey of Health and Development (n = 1376). Four DNAm age acceleration (AgeAccel) biomarkers were measured when participants were aged 53 years: AgeAccelHannum; AgeAccelHorvath; AgeAccelLevine; and AgeAccelGrim. Exposure variables included: relative weight gain (standardised residuals from models of current weight z-score on current height, and previous weight and height z-scores); and linear growth (standardised residuals from models of current height z-score on previous height and weight z-scores) during infancy (0-2 years, weight gain only), early childhood (2-4 years), middle childhood (4-7 years) and late childhood to adolescence (7-15 years); age at menarche; and pubertal stage for men at 14-15 years. The relationship between relative weight gain and linear growth and AgeAccel was investigated using conditional growth models. We replicated analyses from the late childhood to adolescence period and pubertal timing among 240 participants from The National Child and Development Study (NCDS).

resultsA 1SD increase in relative weight gain in late childhood to adolescence was associated with 0.50 years (95% CI 0.20, 0.79) higher AgeAccelGrim. Although the CI includes the null, the estimate was similar in NCDS [0.57 years (95% CI - 0.01, 1.16)] There was no strong evidence that relative weight gain and linear growth in childhood was associated with any other AgeAccel biomarker. There was no relationship between pubertal timing in men and AgeAccel biomarkers. Women who reached menarche ≥ 12 years had 1.20 years (95% CI 0.15, 2.24) higher AgeAccelGrim on average than women who reached menarche < 12 years; however, this was not replicated in NCDS and was not statistically significant after Bonferroni correction.

conclusionsOur findings generally do not support an association between growth and AgeAccel biomarkers in mid-life. However, we found rapid weight gain during pubertal development, previously related to higher cardiovascular disease risk, to be associated with older AgeAccelGrim. Given this is an exploratory study, this finding requires replication.

Indexed as

BiomarkersChild DevelopmentAdolescentAdultAge FactorsAgingBirth WeightBody HeightBody Mass IndexChildChild, PreschoolDNA MethylationFemaleHumansInfantInfant, NewbornBiomarkersBiological ageingBiomarkers of ageingCohortEpigenetic clockLongitudinal

Identifiers

PMID34372922
PMCPMC8351141
OpenAlexW3189960692

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.