Distinct DNA methylation profiles in subtypes of orofacial cleft

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Abstract

Background

Epigenetic data could help identify risk factors for orofacial clefts, either by revealing a causal role for epigenetic mechanisms in causing clefts or by capturing information about causal genetic or environmental factors. Given the evidence that different subtypes of orofacial cleft have distinct aetiologies, we explored whether children with different cleft subtypes showed distinct epigenetic profiles.

Methods

In whole-blood samples from 150 children from the Cleft Collective cohort study, we measured DNA methylation at over 450,000 sites on the genome. We then carried out epigenome-wide association studies (EWAS) to test the association between methylation at each site and cleft subtype (cleft lip only (CLO) n = 50; cleft palate only (CPO) n = 50; cleft lip and palate (CLP) n = 50). We also compared methylation in the blood to methylation in the lip or palate tissue using genome-wide data from the same 150 children and conducted an EWAS of CLO compared to CLP in lip tissue.

Results

We found four genomic regions in blood differentially methylated in CLO compared to CLP, 17 in CPO compared to CLP and 294 in CPO compared to CLO. Several regions mapped to genes that have previously been implicated in the development of orofacial clefts (for example, TBX1, COL11A2, HOXA2, PDGFRA), and over 250 associations were novel. Methylation in blood correlated with that in lip/palate at some regions. There were 14 regions differentially methylated in the lip tissue from children with CLO and CLP, with one region (near KIAA0415) showing up in both the blood and lip EWAS.

Conclusions

Our finding of distinct methylation profiles in different orofacial cleft (OFC) subtypes represents a promising first step in exploring the potential role of epigenetic modifications in the aetiology of OFCs and/or as clinically useful biomarkers of OFC subtypes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-017-0362-2) contains supplementary material, which is available to authorized users.

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DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

Janet Piñero, Àlex Bravo, Núria Queralt-Rosinach … (2016)

The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.

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'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

George Davey Smith, Shah Ebrahim (2003)

Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization-the random assortment of genes from parents to offspring that occurs during gamete formation and conception-provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization-the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.

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missMethyl: an R package for analyzing data from Illumina's HumanMethylation450 platform.

Belinda Phipson, Jovana Maksimovic, Alicia Oshlack (2016)

DNA methylation is one of the most commonly studied epigenetic modifications due to its role in both disease and development. The Illumina HumanMethylation450 BeadChip is a cost-effective way to profile >450 000 CpGs across the human genome, making it a popular platform for profiling DNA methylation. Here we introduce missMethyl, an R package with a suite of tools for performing normalization, removal of unwanted variation in differential methylation analysis, differential variability testing and gene set analysis for the 450K array.

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Author and article information

Contributors

Gemma C. Sharp: gemma.sharp@bristol.ac.uk

Karen Ho: Karen.ho@bristol.ac.uk

Amy Davies: a.davies@bristol.ac.uk

Evie Stergiakouli: E.Stergiakouli@bristol.ac.uk

Kerry Humphries: k.humphries@bristol.ac.uk

Wendy McArdle: wendy.mcardle@bristol.ac.uk

Jonathan Sandy: jonathan.sandy@bristol.ac.uk

George Davey Smith: k.z.davey-smith@bristol.ac.uk

Sarah J. Lewis: s.j.lewis@bristol.ac.uk

Caroline L. Relton: caroline.relton@bristol.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): 8 June 2017

Publication date PMC-release: 8 June 2017

Publication date Collection: 2017

Volume: 9

Electronic Location Identifier: 63

Affiliations

[1 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, MRC Integrative Epidemiology Unit, School of Oral and Dental Sciences, , University of Bristol, ; Bristol, England

[2 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, MRC Integrative Epidemiology Unit, School of Social and Community Medicine, , University of Bristol, ; Bristol, England

[3 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, School of Oral and Dental Sciences, , University of Bristol, ; Bristol, England

[4 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, School of Social and Community Medicine, , University of Bristol, ; Bristol, England

Article

Publisher ID: 362

DOI: 10.1186/s13148-017-0362-2

PMC ID: 5465456

PubMed ID: 28603561

SO-VID: b687df68-55e1-4073-99f4-b3ae544da751

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 : 13 March 2017

Date accepted : 26 May 2017

Funding

Funded by: Scar Free Foundation

Award ID: 13/SW/0064

Award Recipient : Jonathan Sandy

Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;

Award ID: MC_UU_12013

Award Recipient : Caroline L. Relton

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: cleft collective,dna methylation,epigenome-wide association study,ewas,cleft lip,cleft palate,orofacial clefts

Data availability:

ScienceOpen disciplines: Genetics

Keywords: cleft collective, dna methylation, epigenome-wide association study, ewas, cleft lip, cleft palate, orofacial clefts

Distinct DNA methylation profiles in subtypes of orofacial cleft

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Electronic supplementary material

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Genomic Prediction

Most cited references 59

DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

missMethyl: an R package for analyzing data from Illumina's HumanMethylation450 platform.

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