Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation
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Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation. / Min, Josine L.; Hemani, Gibran; Hannon, Eilis; Dekkers, Koen F.; Castillo-Fernandez, Juan; Luijk, René; Carnero-Montoro, Elena; Lawson, Daniel J.; Burrows, Kimberley; Suderman, Matthew; Bretherick, Andrew D.; Richardson, Tom G.; Klughammer, Johanna; Iotchkova, Valentina; Sharp, Gemma; Al Khleifat, Ahmad; Shatunov, Aleksey; Iacoangeli, Alfredo; McArdle, Wendy L.; Ho, Karen M.; Kumar, Ashish; Söderhäll, Cilla; Soriano-Tárraga, Carolina; Giralt-Steinhauer, Eva; Kazmi, Nabila; Mason, Dan; McRae, Allan F.; Corcoran, David L.; Sugden, Karen; Kasela, Silva; Cardona, Alexia; Day, Felix R.; Cugliari, Giovanni; Viberti, Clara; Guarrera, Simonetta; Lerro, Michael; Gupta, Richa; Bollepalli, Sailalitha; Mandaviya, Pooja; Zeng, Yanni; Clarke, Toni Kim; Walker, Rosie M.; Schmoll, Vanessa; Czamara, Darina; Ruiz-Arenas, Carlos; Elliott, Hannah R.; Nohr, Ellen A.; Sørensen, Thorkild I.A.; Hansen, Torben; Morgen, Camilla S.; BIOS Consortium.
In: Nature Genetics, Vol. 53, No. 9, 2021, p. 1311-1321.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation
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 - Elliott, Hannah R.
AU - Nohr, Ellen A.
AU - Sørensen, Thorkild I.A.
AU - Hansen, Torben
AU - Morgen, Camilla S.
AU - BIOS Consortium
N1 - Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2021
Y1 - 2021
N2 - 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.
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.
U2 - 10.1038/s41588-021-00923-x
DO - 10.1038/s41588-021-00923-x
M3 - Journal article
C2 - 34493871
AN - SCOPUS:85103124472
VL - 53
SP - 1311
EP - 1321
JO - Nature Genetics
JF - Nature Genetics
SN - 1061-4036
IS - 9
ER -
ID: 280232365