The emerging landscape of dynamic DNA methylation in early childhood

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Xu , C-J , Bonder , M J , Soderhall , C , Bustamante , M , Baiz , N , Gehring , U , Jankipersadsing , S A , van der Vlies , P , van Diemen , C C , van Rijkom , B , Just , J , Kull , I , Kere , J , Anto , J M , Bousquet , J , Zhernakova , A , Wijmenga , C , Annesi-Maesano , I , Sunyer , J , Melen , E , Li , Y , Postma , D S & Koppelman , G H 2017 , ' The emerging landscape of dynamic DNA methylation in early childhood ' , BMC Genomics , vol. 18 , 25 . https://doi.org/10.1186/s12864-016-3452-1

Title: The emerging landscape of dynamic DNA methylation in early childhood
Author: Xu, Cheng-Jian; Bonder, Marc Jan; Soderhall, Cilla; Bustamante, Mariona; Baiz, Nour; Gehring, Ulrike; Jankipersadsing, Soesma A.; van der Vlies, Pieter; van Diemen, Cleo C.; van Rijkom, Bianca; Just, Jocelyne; Kull, Inger; Kere, Juha; Anto, Josep Maria; Bousquet, Jean; Zhernakova, Alexandra; Wijmenga, Cisca; Annesi-Maesano, Isabella; Sunyer, Jordi; Melen, Erik; Li, Yang; Postma, Dirkje S.; Koppelman, Gerard H.
Contributor: University of Helsinki, Research Programs Unit
Date: 2017-01-05
Language: eng
Number of pages: 11
Belongs to series: BMC Genomics
ISSN: 1471-2164
URI: http://hdl.handle.net/10138/174562
Abstract: Background: DNA methylation has been found to associate with disease, aging and environmental exposure, but it is unknown how genome, environment and disease influence DNA methylation dynamics in childhood. Results: By analysing 538 paired DNA blood samples from children at birth and at 4-5 years old and 726 paired samples from children at 4 and 8 years old from four European birth cohorts using the Illumina Infinium Human Methylation 450 k chip, we have identified 14,150 consistent age-differential methylation sites (a-DMSs) at epigenome-wide significance of rho <1.14x10(-7). Genes with an increase in age-differential methylation were enriched in pathways related to 'development', and were more often located in bivalent transcription start site (TSS) regions, which can silence or activate expression of developmental genes. Genes with a decrease in age-differential methylation were involved in cell signalling, and enriched on H3K27ac, which can predict developmental state. Maternal smoking tended to decrease methylation levels at the identified da-DMSs. We also found 101 a-DMSs (0.71%) that were regulated by genetic variants using cis-differential Methylation Quantitative Trait Locus (cis-dMeQTL) mapping. Moreover, a-DMS-associated genes during early development were significantly more likely to be linked with disease. Conclusion: Our study provides new insights into the dynamic epigenetic landscape of the first 8 years of life.
Subject: DNA methylation
Aging
Methylation quantitative trait loci
Maternal smoking
D-ASPARTATE
AGE
DISEASE
ASTHMA
COHORT
METAANALYSIS
POPULATION
MICROARRAY
NEWBORNS
PROJECT
1184 Genetics, developmental biology, physiology
3111 Biomedicine
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