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

Josine L. Min; Jenny van Dongen; Jouke Jan Hottenga; Gonneke Willemsen; Eco J.C. de Geus; Dorret I. Boomsma; Caroline L. Relton; BIOS Consortium

doi:10.1038/s41588-021-00923-x

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

Josine L. Min^*
, Jenny van Dongen
, Jouke Jan Hottenga
, Gonneke Willemsen
, Eco J.C. de Geus
, Dorret I. Boomsma
, Caroline L. Relton
, BIOS Consortium

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

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Abstract

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.

Original language	English
Pages (from-to)	1311-1321
Number of pages	11
Journal	Nature genetics
Volume	53
Issue number	9
Early online date	6 Sept 2021
DOIs	https://doi.org/10.1038/s41588-021-00923-x
Publication status	Published - Sept 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.

Funding

C.L.R., G.D.S., G.S., J.L.M., K.B., M. Suderman, T.G.R. and T.R.G. are supported by the UK Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol (MC_UU_00011/1, MC_UU_00011/4, MC_UU_00011/5). C.L.R. receives support from a Cancer Research UK Programme grant (no. C18281/A191169). G.H. is funded by the Wellcome Trust and the Royal Society (208806/Z/17/Z). E.H. and J.M. were supported by MRC project grants (nos. MR/K013807/1 and MR/R005176/1 to J.M.) and an MRC Clinical Infrastructure award (no. MR/M008924/1 to J.M.). B.T.H. is supported by the Netherlands CardioVascular Research Initiative (the Dutch Heart Foundation, Dutch Federation of University Medical Centres, the Netherlands Organisation for Health Research and Development, and the Royal Netherlands Academy of Sciences) for the GENIUS project ‘Generating the best evidence-based pharmaceutical targets for atherosclerosis’ (CVON2011-19, CVON2017-20). J.T.B. was supported by the Economic and Social Research Council (grant no. ES/N000404/1). The present study was also supported by JPI HDHL-funded DIMENSION project (administered by the BBSRC UK, grant no. BB/S020845/1 to J.T.B., and by ZonMW the Netherlands, grant no. 529051021 to B.T.H). A.D.B. has been supported by a Wellcome Trust PhD Training Fellowship for Clinicians and the Edinburgh Clinical Academic Track programme (204979/Z/16/Z). J. Klughammer was supported by a DOC fellowship of the Austrian Academy of Sciences. Cohort-specific acknowledgements and funding are presented in the Supplementary Note. T.R.G. receives funding from GlaxoSmithKline and Biogen for unrelated research. The other authors declare no competing interests.

Funders	Funder number
Programme grant
Dutch Heart Foundation
Biogen
Nederlandse Federatie van Universitair Medische Centra
Clinical Infrastructure award
GlaxoSmithKline
BBSRC UK
Netherlands CardioVascular Research Initiative
Royal Society	208806/Z/17/Z
UK Research and Innovation	MC_UU_00011/4
Economic and Social Research Council	ES/P010113/1, ES/N000404/1
Medical Research Council	MR/K013807/1, MR/M008924/1, MR/L501529/1, MR/R005176/1
Österreichischen Akademie der Wissenschaften	doc fellowship
Biotechnology and Biological Sciences Research Council	BB/S020845/1
Wellcome Trust	208806, 204979
ZonMw	529051021, 204979/Z/16/Z
University of Bristol	MC_UU_00011/1, MC_UU_00011/5
Horizon 2020 Framework Programme	733206
Royal Netherlands Academy of Sciences	CVON2017-20, CVON2011-19
Cancer Research UK	C18281/A191169

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10.1038/s41588-021-00923-x

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylationFinal published version, 10.5 MBLicence: Article 25fa Dutch Copyright Act

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title = "Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation",

abstract = "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.",

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note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.",

year = "2021",

month = sep,

doi = "10.1038/s41588-021-00923-x",

language = "English",

volume = "53",

pages = "1311--1321",

journal = "Nature genetics",

issn = "1061-4036",

publisher = "Nature Research",

number = "9",

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AU - Min, Josine L.

AU - Hemani, Gibran

AU - Hannon, Eilis

AU - Dekkers, Koen F.

AU - Castillo-Fernandez, Juan

AU - Luijk, René

AU - Carnero-Montoro, Elena

AU - Lawson, Daniel J.

AU - Burrows, Kimberley

AU - Suderman, Matthew

AU - Bretherick, Andrew D.

AU - Richardson, Tom G.

AU - Klughammer, Johanna

AU - Iotchkova, Valentina

AU - Sharp, Gemma

AU - Al Khleifat, Ahmad

AU - Shatunov, Aleksey

AU - Iacoangeli, Alfredo

AU - McArdle, Wendy L.

AU - Ho, Karen M.

AU - Kumar, Ashish

AU - Söderhäll, Cilla

AU - Soriano-Tárraga, Carolina

AU - Giralt-Steinhauer, Eva

AU - Kazmi, Nabila

AU - Mason, Dan

AU - McRae, Allan F.

AU - Corcoran, David L.

AU - Sugden, Karen

AU - Kasela, Silva

AU - Cardona, Alexia

AU - Day, Felix R.

AU - Cugliari, Giovanni

AU - Viberti, Clara

AU - Guarrera, Simonetta

AU - Lerro, Michael

AU - Gupta, Richa

AU - Bollepalli, Sailalitha

AU - Mandaviya, Pooja

AU - Zeng, Yanni

AU - Clarke, Toni Kim

AU - Walker, Rosie M.

AU - Schmoll, Vanessa

AU - Czamara, Darina

AU - Ruiz-Arenas, Carlos

AU - Rezwan, Faisal I.

AU - Marioni, Riccardo E.

AU - Lin, Tian

AU - Awaloff, Yvonne

AU - Germain, Marine

AU - Aïssi, Dylan

AU - Zwamborn, Ramona

AU - van Eijk, Kristel

AU - Dekker, Annelot

AU - van Dongen, Jenny

AU - Hottenga, Jouke Jan

AU - Willemsen, Gonneke

AU - Xu, Cheng Jian

AU - Barturen, Guillermo

AU - Català-Moll, Francesc

AU - Kerick, Martin

AU - Wang, Carol

AU - Melton, Phillip

AU - Elliott, Hannah R.

AU - Shin, Jean

AU - Bernard, Manon

AU - Yet, Idil

AU - Smart, Melissa

AU - Gorrie-Stone, Tyler

AU - Shaw, Chris

AU - Al Chalabi, Ammar

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AU - Wray, Naomi R.

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AU - Davies, Gareth E.

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AU - Boomsma, Dorret I.

AU - Vonk, Judith M.

AU - Brunekreef, Bert

AU - Koppelman, Gerard H.

AU - Alarcón-Riquelme, Marta E.

AU - Huang, Rae Chi

AU - Pennell, Craig E.

AU - van Meurs, Joyce

AU - Ikram, M. Arfan

AU - Hughes, Alun D.

AU - Tillin, Therese

AU - Chaturvedi, Nish

AU - Pausova, Zdenka

AU - Paus, Tomas

AU - Spector, Timothy D.

AU - Kumari, Meena

AU - Schalkwyk, Leonard C.

AU - Visscher, Peter M.

AU - Davey Smith, George

AU - Bock, Christoph

AU - Gaunt, Tom R.

AU - Bell, Jordana T.

AU - Heijmans, Bastiaan T.

AU - Mill, Jonathan

AU - Relton, Caroline L.

AU - BIOS Consortium

PY - 2021/9

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AB - 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.

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U2 - 10.1038/s41588-021-00923-x

DO - 10.1038/s41588-021-00923-x

M3 - Article

C2 - 34493871

SN - 1061-4036

VL - 53

SP - 1311

EP - 1321

JO - Nature genetics

JF - Nature genetics

IS - 9

ER -

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

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