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Journal Article

Leveraging DNA-methylation quantitative-trait loci to characterize the relationship between methylomic variation, gene expression, and complex traits

Authors

Publication date

01 Nov 2018

Summary

Characterizing the complex relationship between genetic, epigenetic and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. In this study, we describe the most comprehensive analysis of common genetic variation on DNA methylation (DNAm) to date, 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 < 6.52x10-14) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified using 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, 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, identifying 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 (www.epigenomicslab.com) as a resource to the research community.

Published in

American Journal of Human Genetics

Volume and page numbers

103 , 654 -665

DOI

https://doi.org/10.1016/j.ajhg.2018.09.007

ISSN

16

Subjects

Science And Technology, Research, Health, Biology, and Genetics

Notes

Open Access; Under a Creative Commons license


Related publications

  1. Leveraging DNA methylation quantitative trait loci to characterize the relationship between methylomic variation, gene expression and complex traits

    Eilis Hannon, Tyler J. Gorrie-Stone, Melissa Smart, et al.

    1. Science And Technology
    2. Research
    3. Health
    4. Biology
    5. Genetics

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