Evidence map›Paper›PMID 33450751›Full record

ArticleHuman molecular genetics2021

Epigenome-wide change and variation in DNA methylation in childhood: trajectories from birth to late adolescence.

Rosa H Mulder, Alexander Neumann, Charlotte A M Cecil, Esther Walton, Lotte C Houtepen, Andrew J Simpkin, Jolien Rijlaarsdam, Bastiaan T Heijmans, Tom R Gaunt, Janine F Felix and 6 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Human molecular genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 17 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
104citing papers in PubMed, 17 pooled it
13.0field-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

104 citing papers in PubMed, 17 syntheses or guidelines pooled it, 176 citations in OpenAlex.

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44 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

16 authors at 10 institutions in 5 countries.

Rosa H MulderDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Alexander NeumannDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Charlotte A M CecilDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Esther WaltonMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Lotte C HoutepenMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Andrew J SimpkinMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Jolien RijlaarsdamDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Bastiaan T HeijmansMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Tom R GauntMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Janine F FelixGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Vincent W V JaddoeGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Marian J Bakermans-KranenburgClinical Child and Family Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Henning TiemeierDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Caroline L ReltonMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Marinus H van IJzendoornDepartment of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Matthew SudermanMRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
University of Bristol · GBErasmus MC · NLHarvard University · USJewish General Hospital · CAKing's College London · GBLeiden University · NLLeiden University Medical Center · NLOllscoil na Gaillimhe – University of Galway · IEUniversity of Cambridge · GBVrije Universiteit Amsterdam · NL

Funding

Epigenetic Pathways to Conduct Problem Trajectories: Early Environmental RisksR01HD068437 · NICHD · KING'S COLLEGE LONDON · PI BARKER, EDWARD D., MILL, JONATHAN · 2012 to 2014
$1.1M
Biotechnology and Biological Sciences Research Council BB/I025263/1Biotechnology and Biological Sciences Research Council BBI025751/1Medical Research Council MC_UU_00011/4Medical Research Council MC_UU_00011/5Medical Research Council MC_UU_12013/8Medical Research Council MR/S03658X/1NICHD NIH HHS R01 HD068437Wellcome TrustWellcome Trust 102215/2/13/2
6 · The paper itself

Abstract

DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5019 blood samples collected at multiple time-points from birth to late adolescence from 2348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases, DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs). Evidence for non-linear change and inter-individual variation in non-linear trajectories was somewhat less common (11 and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. In contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions. These findings depict a methylome undergoing widespread and often non-linear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.

Indexed as

Epigenesis, GeneticAdolescentAge FactorsChildChild, PreschoolCpG IslandsDNA MethylationEpigenomeFemaleHumansInfantInfant, NewbornMaleSex Characteristics

Identifiers

PMID33450751
PMCPMC8033147
OpenAlexW3124817069

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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.