Gene-methylation interactions: discovering region-wise DNA methylation levels that modify SNP-associated disease risk.
Clin Epigenetics
; 12(1): 109, 2020 07 16.
Article
em En
| MEDLINE
| ID: mdl-32678018
ABSTRACT
BACKGROUND:
Current technology allows rapid assessment of DNA sequences and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals simultaneously. This has led to an increase in epigenome-wide association studies (EWAS) of complex traits, particularly those that are poorly explained by previous genome-wide association studies (GWAS). However, the genome and epigenome are intertwined, e.g., DNA methylation is known to affect gene expression through, for example, genomic imprinting. There is thus a need to go beyond single-omics data analyses and develop interaction models that allow a meaningful combination of information from EWAS and GWAS.RESULTS:
We present two new methods for genetic association analyses that treat offspring DNA methylation levels as environmental exposure. Our approach searches for statistical interactions between SNP alleles and DNA methylation (G ×Me) and between parent-of-origin effects and DNA methylation (PoO ×Me), using case-parent triads or dyads. We use summarized methylation levels over nearby genomic region to ease biological interpretation. The methods were tested on a dataset of parent-offspring dyads, with EWAS data on the offspring. Our results showed that methylation levels around a SNP can significantly alter the estimated relative risk. Moreover, we show how a control dataset can identify false positives.CONCLUSIONS:
The new methods, G ×Me and PoO ×Me, integrate DNA methylation in the assessment of genetic relative risks and thus enable a more comprehensive biological interpretation of genome-wide scans. Moreover, our strategy of condensing DNA methylation levels within regions helps overcome specific disadvantages of using sparse chip-based measurements. The methods are implemented in the freely available R package Haplin ( https//cran.r-project.org/package=Haplin ), enabling fast scans of multi-omics datasets.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Metilação de DNA
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Polimorfismo de Nucleotídeo Único
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Exposição Ambiental
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Estudo de Associação Genômica Ampla
Tipo de estudo:
Etiology_studies
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Observational_studies
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Risk_factors_studies
Limite:
Female
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Humans
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Male
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article