DNA methylation links prenatal smoking exposure to later life health outcomes in offspring

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Abstract

Background

Maternal smoking during pregnancy is associated with adverse offspring health outcomes across their life course. We hypothesize that DNA methylation is a potential mediator of this relationship.

Methods

We examined the association of prenatal maternal smoking with offspring blood DNA methylation in 2821 individuals (age 16 to 48 years) from five prospective birth cohort studies and perform Mendelian randomization and mediation analyses to assess whether methylation markers have causal effects on disease outcomes in the offspring.

Results

We identify 69 differentially methylated CpGs in 36 genomic regions ( P value < 1 × 10 ⁻⁷) associated with exposure to maternal smoking in adolescents and adults. Mendelian randomization analyses provided evidence for a causal role of four maternal smoking-related CpG sites on an increased risk of inflammatory bowel disease or schizophrenia. Further mediation analyses showed some evidence of cg25189904 in GNG12 gene mediating the effect of exposure to maternal smoking on schizophrenia-related outcomes.

Conclusions

DNA methylation may represent a biological mechanism through which maternal smoking is associated with increased risk of psychiatric morbidity in the exposed offspring.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0683-4) contains supplementary material, which is available to authorized users.

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Most cited references 27

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Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation.

Nizar Touleimat, Jörg Tost (2012)

Huge progress has been made in the development of array- or sequencing-based technologies for DNA methylation analysis. The Illumina Infinium(®) Human Methylation 450K BeadChip (Illumina Inc., CA, USA) allows the simultaneous quantitative monitoring of more than 480,000 CpG positions, enabling large-scale epigenotyping studies. However, the assay combines two different assay chemistries, which may cause a bias in the analysis if all signals are merged as a unique source of methylation measurement. We confirm in three 450K data sets that Infinium I signals are more stable and cover a wider dynamic range of methylation values than Infinium II signals. We evaluated the methylation profile of Infinium I and II probes obtained with different normalization protocols and compared these results with the methylation values of a subset of CpGs analyzed by pyrosequencing. We developed a subset quantile normalization approach for the processing of 450K BeadChips. The Infinium I signals were used as 'anchors' to normalize Infinium II signals at the level of probe coverage categories. Our normalization approach outperformed alternative normalization or correction approaches in terms of bias correction and methylation signal estimation. We further implemented a complete preprocessing protocol that solves most of the issues currently raised by 450K array users. We developed a complete preprocessing pipeline for 450K BeadChip data using an original subset quantile normalization approach that performs both sample normalization and efficient Infinium I/II shift correction. The scripts, being freely available from the authors, will allow researchers to concentrate on the biological analysis of data, such as the identification of DNA methylation signatures.

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DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring

Leanne Küpers, Xiaojing Xu, Soesma Jankipersadsing … (2015)

Background: We examined whether the effect of maternal smoking during pregnancy on birthweight of the offspring was mediated by smoking-induced changes to DNA methylation in cord blood. Methods: First, we used cord blood of 129 Dutch children exposed to maternal smoking vs 126 unexposed to maternal and paternal smoking (53% male) participating in the GECKO Drenthe birth cohort. DNA methylation was measured using the Illumina HumanMethylation450 Beadchip. We performed an epigenome-wide association study for the association between maternal smoking and methylation followed by a mediation analysis of the top signals [false-discovery rate (FDR) < 0.05]. We adjusted both analyses for maternal age, education, pre-pregnancy BMI, offspring’s sex, gestational age and white blood cell composition. Secondly, in 175 exposed and 1248 unexposed newborns from two independent birth cohorts, we replicated and meta-analysed results of eight cytosine-phosphate-guanine (CpG) sites in the GFI1 gene, which showed the most robust mediation. Finally, we performed functional network and enrichment analysis. Results: We found 35 differentially methylated CpGs (FDR < 0.05) in newborns exposed vs unexposed to smoking, of which 23 survived Bonferroni correction (P < 1 × 10-7). These 23 CpGs mapped to eight genes: AHRR, GFI1, MYO1G, CYP1A1, NEUROG1, CNTNAP2, FRMD4A and LRP5. We observed partial confirmation as three of the eight CpGs in GFI1 replicated. These CpGs partly mediated the effect of maternal smoking on birthweight (Sobel P < 0.05) in meta-analysis of GECKO and the two replication cohorts. Differential methylation of these three GFI1 CpGs explained 12–19% of the 202 g lower birthweight in smoking mothers. Functional enrichment analysis pointed towards activation of cell-mediated immunity. Conclusions: Maternal smoking during pregnancy was associated with cord blood methylation differences. We observed a potentially mediating role of methylation in the association between maternal smoking during pregnancy and birthweight of the offspring. Functional network analysis suggested a role in activating the immune system.

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Adverse health effects of prenatal and postnatal tobacco smoke exposure on children.

Alex de Crespigny, W Hofhuis, P Merkus (2003)

Parents who choose to smoke are possibly not aware of, or deny, the negative effects of passive smoking on their offspring. This review summarises a wide range of effects of passive smoking on mortality and morbidity in children. It offers paediatricians, obstetricians, specialists in preventive child health care, general practitioners, and midwives an approach to promote smoking cessation in smoking parents before, during, and after pregnancy.

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Author and article information

Contributors

Petri Wiklund: p.wiklund@imperial.ac.uk

Ville Karhunen: v.karhunen@imperial.ac.uk

Rebecca C. Richmond: rebecca.richmond@bristol.ac.uk

Priyanka Parmar: priyanka.parmar@oulu.fi

Alina Rodriguez: a.rodriguez@imperial.ac.uk

Maneka De Silva: m.de-silva@imperial.ac.uk

Matthias Wielscher: m.wielscher@imperial.ac.uk

Faisal I. Rezwan: f.rezwan@soton.ac.uk

Tom G. Richardson: tom.g.richardson@bristol.ac.uk

Juha Veijola: juha.veijola@oulu.fi

Karl-Heinz Herzig: karl-heinz.herzig@oulu.fi

John W. Holloway: j.w.holloway@soton.ac.uk

Caroline L. Relton: caroline.relton@bristol.ac.uk

Sylvain Sebert: sylvain.sebert@oulu.fi

Marjo-Riitta Järvelin:

ORCID: http://orcid.org/0000-0002-2149-0630

m.jarvelin@imperial.ac.uk

Journal

Journal ID (nlm-ta): Clin Epigenetics

Journal ID (iso-abbrev): Clin Epigenetics

Title: Clinical Epigenetics

Publisher: BioMed Central (London )

ISSN (Print): 1868-7075

ISSN (Electronic): 1868-7083

Publication date (Electronic): 1 July 2019

Publication date PMC-release: 1 July 2019

Publication date Collection: 2019

Volume: 11

Electronic Location Identifier: 97

Affiliations

[1 ]ISNI 0000 0001 0941 4873, GRID grid.10858.34, Center for Life Course Health Research, , University of Oulu, ; Oulu, Finland

[2 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department of Epidemiology and Biostatistics, , Imperial College London, ; London, UK

[3 ]ISNI 0000 0001 1013 7965, GRID grid.9681.6, Department of Health Sciences, , University of Jyvaskyla, ; Jyvaskyla, Finland

[4 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, MRC Integrative Epidemiology Unit, , University of Bristol, ; Bristol, UK

[5 ]ISNI 0000 0004 0420 4262, GRID grid.36511.30, School of Psychology, , University of Lincoln, ; Lincoln, UK

[6 ]ISNI 0000 0004 1936 9297, GRID grid.5491.9, Human Development and Health, Faculty of Medicine, , University of Southampton, ; Southampton, UK

[7 ]Medical Research Center Oulu, Oulu, Finland

[8 ]ISNI 0000 0004 4685 4917, GRID grid.412326.0, Oulu University Hospital, ; Oulu, Finland

[9 ]ISNI 0000 0001 0941 4873, GRID grid.10858.34, Research Unit of Clinical Neuroscience, , University of Oulu, ; Oulu, Finland

[10 ]ISNI 0000 0001 0941 4873, GRID grid.10858.34, Institute of Biomedicine and Biocenter of Oulu, ; Oulu, Finland

[11 ]ISNI 0000 0001 2205 0971, GRID grid.22254.33, Department of Gastroenterology and Metabolism, , Poznan University of Medical Sciences, ; Poznan, Poland

[12 ]ISNI 0000 0004 1936 9297, GRID grid.5491.9, Clinical and Experimental Sciences, Faculty of Medicine, , University of Southampton, ; Southampton, UK

[13 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department for Genomics of Common Diseases, School of Medicine, , Imperial College London, ; London, UK

[14 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, MRC-PHE Centre for Environment and Health, , Imperial College London, ; London, W2 1PG UK

[15 ]ISNI 0000 0001 0724 6933, GRID grid.7728.a, Department of Life Sciences, College of Health and Life Sciences, , Brunel University London, ; London, UK

Author information

Marjo-Riitta Järvelin http://orcid.org/0000-0002-2149-0630

Article

Publisher ID: 683

DOI: 10.1186/s13148-019-0683-4

PMC ID: 6604191

PubMed ID: 31262328

SO-VID: 8dbfa63c-2140-4512-b95d-575d9303a333

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 22 February 2019

Date accepted : 13 May 2019

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100010686, H2020 European Institute of Innovation and Technology;

Award ID: 633595

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: maternal smoking,pregnancy,dna methylation,persistence,mediation,disease,causality,life course

Data availability:

ScienceOpen disciplines: Genetics

Keywords: maternal smoking, pregnancy, dna methylation, persistence, mediation, disease, causality, life course

DNA methylation links prenatal smoking exposure to later life health outcomes in offspring

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Abstract

Background

Methods

Results

Conclusions

Electronic supplementary material

Related collections

Decoding Infection and Transmission

Most cited references 27

Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation.

DNA methylation mediates the effect of maternal smoking during pregnancy on birthweight of the offspring

Adverse health effects of prenatal and postnatal tobacco smoke exposure on children.

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