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Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits
Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. We undertook a comprehensive analysis of common genetic variation on DNA methylation (DNAm) b...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6217758/ https://www.ncbi.nlm.nih.gov/pubmed/30401456 http://dx.doi.org/10.1016/j.ajhg.2018.09.007 |
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author | Hannon, Eilis Gorrie-Stone, Tyler J. Smart, Melissa C. Burrage, Joe Hughes, Amanda Bao, Yanchun Kumari, Meena Schalkwyk, Leonard C. Mill, Jonathan |
author_facet | Hannon, Eilis Gorrie-Stone, Tyler J. Smart, Melissa C. Burrage, Joe Hughes, Amanda Bao, Yanchun Kumari, Meena Schalkwyk, Leonard C. Mill, Jonathan |
author_sort | Hannon, Eilis |
collection | PubMed |
description | Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. We undertook a comprehensive analysis of common genetic variation on DNA methylation (DNAm) by using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (p < 6.52 × 10(−14)) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified by previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits by using summary-data-based Mendelian randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression and thereby identify 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database as a resource to the research community. |
format | Online Article Text |
id | pubmed-6217758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-62177582018-12-18 Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits Hannon, Eilis Gorrie-Stone, Tyler J. Smart, Melissa C. Burrage, Joe Hughes, Amanda Bao, Yanchun Kumari, Meena Schalkwyk, Leonard C. Mill, Jonathan Am J Hum Genet Article Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. We undertook a comprehensive analysis of common genetic variation on DNA methylation (DNAm) by using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (p < 6.52 × 10(−14)) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified by previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits by using summary-data-based Mendelian randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression and thereby identify 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database as a resource to the research community. Elsevier 2018-11-01 2018-10-25 /pmc/articles/PMC6217758/ /pubmed/30401456 http://dx.doi.org/10.1016/j.ajhg.2018.09.007 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hannon, Eilis Gorrie-Stone, Tyler J. Smart, Melissa C. Burrage, Joe Hughes, Amanda Bao, Yanchun Kumari, Meena Schalkwyk, Leonard C. Mill, Jonathan Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits |
title | Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits |
title_full | Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits |
title_fullStr | Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits |
title_full_unstemmed | Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits |
title_short | Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits |
title_sort | leveraging dna-methylation quantitative-trait loci to characterize the relationship between methylomic variation, gene expression, and complex traits |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6217758/ https://www.ncbi.nlm.nih.gov/pubmed/30401456 http://dx.doi.org/10.1016/j.ajhg.2018.09.007 |
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