Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction

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Abstract

Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental trait with complex and far-reaching social and health correlates.

Original languageEnglish
Pages (from-to)1367-1376
Number of pages27
JournalNature Neuroscience
Volume24
Issue number10
Early online date26 Aug 2021
DOIs
Publication statusPublished - Oct 2021

Bibliographical note

Funding Information:
This research was carried out under the auspices of the Externalizing Consortium. The study was classified as secondary research of de-identified participants, and the study was awarded ethical approval by the internal review board of Virginia Commonwealth University (VCU), with reference number HM20019386. These analyses were made possible by the generous public sharing of summary statistics from published GWAS from the PGC, the Million Veterans Program, the International Cannabis Consortium, the GWAS & Sequencing Consortium of Alcohol and Nicotine use, the Social Science Genetics Association Consortium, the Genetics of Personality Consortium and the Broad Antisocial Behavior Consortium. We thank the many studies that made these consortia possible, the researchers involved and the participants in those studies, without whom this effort would not be possible. We also thank the research participants and employees of 23andMe for making this work possible. This research was conducted in part using the UKB resource under applications 40830 and 11425. We thank all UKB cohort participants for making this study possible. We thank L. K. Davis for providing access to BioVU. Finally, we thank COGA; principal investigators B. Porjesz, V. Hesselbrock, H. Edenberg, L. Bierut; and collaborators at eleven different centers: University of Connecticut (V. Hesselbrock); Indiana University (H. J. Edenberg, J. Nurnberger Jr., T. Foroud and Y. Liu); University of Iowa (S. Kuperman and J. Kramer); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, J. Rice, K. Bucholz and A. Agrawal); University of California, San Diego (M. Schuckit); Rutgers University (J. Tischfield and A. Brooks); Department of Biomedical and Health Informatics, The Children’s Hospital of Philadelphia; Department of Genetics, Perelman School of Medicine, University of Pennsylvania (L. Almasy); Virginia Commonwealth University (D.M.D); Icahn School of Medicine at Mount Sinai (A. Goate); and Howard University (R. Taylor). Other COGA collaborators include: L. Bauer (University of Connecticut); J. McClintick, L. Wetherill, X. Xuei, D. Lai, S. O’Connor, M. Plawecki and S. Lourens (Indiana University); G. Chan (University of Iowa and University of Connecticut); J. Meyers, D. Chorlian, C. Kamarajan, A. Pandey and J. Zhang (SUNY Downstate); J. C. Wang, M. Kapoor and S. Bertelsen (Icahn School of Medicine at Mount Sinai); A. Anokhin, V. McCutcheon and S. Saccone (Washington University); J. Salvatore, F. Aliev and B. Cho (Virginia Commonwealth University); and M. Kos (University of Texas Rio Grande Valley). A. Parsian and H. Chen are the National Institute on Alcohol Abuse and Alcoholism (NIAAA) staff collaborators. All studies included in the externalizing GWAS are listed in the Supplementary Information. Funding: The Externalizing Consortium has been supported by the NIAAA through an administrative supplement (R01AA015416) and by the National Institute of Drug Abuse (R01DA050721). D.M.D. was supported through funding from the NIAAA (K02AA018755, U10AA008401 and P50AA022527). P.D.K. was supported through a European Research Council Consolidator Grant (647648 EdGe). K.P.H. was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; R01HD092548 and R01HD083613) and the Jacobs Foundation. A.A.P. was supported by the NIAAA (R01AA026281) and the National Institute of Drug Abuse (P50DA037844). S.S.-R. was supported through a NARSAD Young Investigator Award from the Brain and Behavior Foundation (grant no. 27676). Both A.A.P. and S.S.-R. were supported by funds from the California Tobacco-Related Disease Research Program (grant nos. 28IR-0070 and T29KT0526). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the above funding bodies. This research used data from Add Health, a program project directed by K.M.H. (principal investigator) and designed by J. R. Udry, P. S. Bearman and K.M.H. at the University of North Carolina at Chapel Hill, and funded by grant P01HD031921 from the Eunice Kennedy Shriver NICHD, with cooperative funding from 23 other federal agencies and foundations. Information on how to obtain the Add Health data files is available on the Add Health website (https://addhealth.cpc.unc. edu/). This research used Add Health GWAS data funded by Eunice Kennedy Shriver NICHD grants R01HD073342 to K.M.H. (principal investigator) and R01HD060726 to K.M.H., J. D. Boardman, and M. B. McQueen (multiple principal investigators). COGA is a national collaborative study supported by the National Institutes of Health (NIH) grant U10AA008401 from the NIAAA and the National Institute on Drug Abuse. Data were obtained from Vanderbilt University Medical Center’s BioVU, which is supported by numerous sources, including institutional funding, private agencies and federal grants. These include the NIH-funded shared instrumentation grant S10RR025141, and CTSA grants UL1TR002243, UL1TR000445 and UL1RR024975. Genomic data are also supported by investigator-led projects, including U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962 and R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/. Support for data collection for the PNC, acquired through dbGaP (accession no. phs000607, v3.p2), was provided by grant RC2MH089983 awarded to R. Gur and RC2MH089924 was awarded to H. Hakonarson. Participants were recruited and genotyped through the Center for Applied Genomics (CAG) at The Children’s Hospital in Philadelphia (CHOP). Phenotypic data collection occurred at the CAG/CHOP and at the Brain Behavior Laboratory, University of Pennsylvania. A full list of funding for investigator effort is available in the Supplementary Information.

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

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

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