Analysis of shared heritability in common disorders of the brain

doi:10.1126/science.aap8757

Analysis of shared heritability in common disorders of the brain

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Abstract

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Original language	English
Article number	8757
Journal	Science
Volume	360
Issue number	6395
DOIs	https://doi.org/10.1126/science.aap8757
State	Published - Jun 22 2018

Bibliographical note

Funding Information:
We thank the members of the Neale and Daly laboratories for helpful discussions; R. Hoskins, J. Wessman, and J. Martin for comments on the manuscript; M. Whittall for inspiration; S. Knemeye for help with the summary figure; C. Hammond for organizational assistance; and the patients and participants of the respective consortia for their participation. Data on coronary artery disease have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from www.cardiogramplusc4d.org. matSpD (Matrix Spectral Decomposition method) is available at neurogenetics.qimrberghofer.edu.au/matSpD/. This research was conducted using the UK Biobank resource (application 18597). This work was supported by grants 1R01MH10764901 and 5U01MH09443203 from the National Institute of Mental Health, as well as the Orion Farmos Research Foundation (V.A.) and the Fannie and John Hertz Foundation (H.K.F.). Consortium specific funding is detailed in the supplementary materials (“Study-specific acknowledgments”).

Publisher Copyright:
© 2018 American Association for the Advancement of Science. All rights reserved.

ASJC Scopus subject areas

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@article{3b15ced1ef9942fd892330a10b8e5208,

title = "Analysis of shared heritability in common disorders of the brain",

abstract = "Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.",

author = "Verneri Anttila and Brendan Bulik-Sullivan and Finucane, {Hilary K.} and Walters, {Raymond K.} and Jose Bras and Laramie Duncan and Valentina Escott-Price and Falcone, {Guido J.} and Padhraig Gormley and Rainer Malik and Patsopoulos, {Nikolaos A.} and Stephan Ripke and Zhi Wei and Dongmei Yu and Lee, {Phil H.} and Patrick Turley and Benjamin Grenier-Boley and Vincent Chouraki and Yoichiro Kamatani and Claudine Berr and Luc Letenneur and Didier Hannequin and Philippe Amouyel and Anne Boland and Deleuze, {Jean Fran{\c c}ois} and Emmanuelle Duron and Vardarajan, {Badri N.} and Christiane Reitz and Goate, {Alison M.} and Huentelman, {Matthew J.} and {Ilyas Kamboh}, M. and Larson, {Eric B.} and Ekaterina Rogaeva and George-Hyslop, {Peter St} and Hakon Hakonarson and Kukull, {Walter A.} and Farrer, {Lindsay A.} and Barnes, {Lisa L.} and Beach, {Thomas G.} and {Yesim Demirci}, F. and Elizabeth Head and Hulette, {Christine M.} and Jicha, {Gregory A.} and Kauwe, {John S.K.} and Kaye, {Jeffrey A.} and Leverenz, {James B.} and Levey, {Allan I.} and Lieberman, {Andrew P.} and Pankratz, {Vernon S.} and {Van Eldik}, {Linda J.}",

note = "Funding Information: We thank the members of the Neale and Daly laboratories for helpful discussions; R. Hoskins, J. Wessman, and J. Martin for comments on the manuscript; M. Whittall for inspiration; S. Knemeye for help with the summary figure; C. Hammond for organizational assistance; and the patients and participants of the respective consortia for their participation. Data on coronary artery disease have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from www.cardiogramplusc4d.org. matSpD (Matrix Spectral Decomposition method) is available at neurogenetics.qimrberghofer.edu.au/matSpD/. This research was conducted using the UK Biobank resource (application 18597). This work was supported by grants 1R01MH10764901 and 5U01MH09443203 from the National Institute of Mental Health, as well as the Orion Farmos Research Foundation (V.A.) and the Fannie and John Hertz Foundation (H.K.F.). Consortium specific funding is detailed in the supplementary materials (“Study-specific acknowledgments”). Publisher Copyright: {\textcopyright} 2018 American Association for the Advancement of Science. All rights reserved.",

year = "2018",

month = jun,

day = "22",

doi = "10.1126/science.aap8757",

language = "English",

volume = "360",

number = "6395",

}

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T1 - Analysis of shared heritability in common disorders of the brain

AU - Anttila, Verneri

AU - Bulik-Sullivan, Brendan

AU - Finucane, Hilary K.

AU - Walters, Raymond K.

AU - Bras, Jose

AU - Duncan, Laramie

AU - Escott-Price, Valentina

AU - Falcone, Guido J.

AU - Gormley, Padhraig

AU - Malik, Rainer

AU - Patsopoulos, Nikolaos A.

AU - Ripke, Stephan

AU - Wei, Zhi

AU - Yu, Dongmei

AU - Lee, Phil H.

AU - Turley, Patrick

AU - Grenier-Boley, Benjamin

AU - Chouraki, Vincent

AU - Kamatani, Yoichiro

AU - Berr, Claudine

AU - Letenneur, Luc

AU - Hannequin, Didier

AU - Amouyel, Philippe

AU - Boland, Anne

AU - Deleuze, Jean François

AU - Duron, Emmanuelle

AU - Vardarajan, Badri N.

AU - Reitz, Christiane

AU - Goate, Alison M.

AU - Huentelman, Matthew J.

AU - Ilyas Kamboh, M.

AU - Larson, Eric B.

AU - Rogaeva, Ekaterina

AU - George-Hyslop, Peter St

AU - Hakonarson, Hakon

AU - Kukull, Walter A.

AU - Farrer, Lindsay A.

AU - Barnes, Lisa L.

AU - Beach, Thomas G.

AU - Yesim Demirci, F.

AU - Head, Elizabeth

AU - Hulette, Christine M.

AU - Jicha, Gregory A.

AU - Kauwe, John S.K.

AU - Kaye, Jeffrey A.

AU - Leverenz, James B.

AU - Levey, Allan I.

AU - Lieberman, Andrew P.

AU - Pankratz, Vernon S.

AU - Van Eldik, Linda J.

N1 - Funding Information: We thank the members of the Neale and Daly laboratories for helpful discussions; R. Hoskins, J. Wessman, and J. Martin for comments on the manuscript; M. Whittall for inspiration; S. Knemeye for help with the summary figure; C. Hammond for organizational assistance; and the patients and participants of the respective consortia for their participation. Data on coronary artery disease have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from www.cardiogramplusc4d.org. matSpD (Matrix Spectral Decomposition method) is available at neurogenetics.qimrberghofer.edu.au/matSpD/. This research was conducted using the UK Biobank resource (application 18597). This work was supported by grants 1R01MH10764901 and 5U01MH09443203 from the National Institute of Mental Health, as well as the Orion Farmos Research Foundation (V.A.) and the Fannie and John Hertz Foundation (H.K.F.). Consortium specific funding is detailed in the supplementary materials (“Study-specific acknowledgments”). Publisher Copyright: © 2018 American Association for the Advancement of Science. All rights reserved.

PY - 2018/6/22

Y1 - 2018/6/22

N2 - Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

AB - Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

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DO - 10.1126/science.aap8757

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AN - SCOPUS:85049284114

VL - 360

IS - 6395

M1 - 8757

ER -

Analysis of shared heritability in common disorders of the brain

Abstract

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