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Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns


Title: Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns
Author: Czamara, Darina
Sigurdsson, Engilbert   orcid.org/0000-0001-9404-7982
Stefansson, Kari   orcid.org/0000-0003-1676-864X
Date: 2019-06-11
Language: English
Scope: 2548
University/Institute: Háskóli Íslands
University of Iceland
School: Heilbrigðisvísindasvið (HÍ)
School of Health Sciences (UI)
Department: Læknadeild (HÍ)
Faculty of Medicine (UI)
Series: Nature Communications;10(1)
ISSN: 2041-1723
DOI: 10.1038/s41467-019-10461-0
Subject: Biomarkers; DNA methylation; Epigenomics; Erfðagreining; Genamengi; DNA-rannsóknir; Nýburar
URI: https://hdl.handle.net/20.500.11815/1633

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Citation:

Czamara, D., Eraslan, G., Page, C.M. et al. Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns. Nature Communications 10, 2548 (2019). https://doi.org/10.1038/s41467-019-10461-0

Abstract:

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.

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Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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