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Journal Article

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

MPS-Authors
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Schmoll,  Vanessa
Dept. Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society;

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Czamara,  Darina
Dept. Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society;

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Awaloff,  Yvonne
Dept. Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society;

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Binder,  Elisabeth B.
Dept. Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society;

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Lucae,  Susanne
Max Planck Institute of Psychiatry, Max Planck Society;

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Citation

Min, J. L., Hemani, G., Hannon, E., Dekkers, K. F., Castillo-Fernandez, J., Luijk, R., et al. (2021). Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation. NATURE GENETICS, 53(9), 1311-+. doi:10.1038/s41588-021-00923-x.


Cite as: https://hdl.handle.net/21.11116/0000-0009-5366-7
Abstract
DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs.
Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.