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

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Original languageEnglish
Pages (from-to)1311-1321
Number of pages11
JournalNature Genetics
Volume53
Issue number9
DOIs
PublishedSep 2021

Bibliographical note

Funding Information: 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. Funding Information: T.R.G. receives funding from GlaxoSmithKline and Biogen for unrelated research. The other authors declare no competing interests. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors

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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