Abstract
Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health–related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.
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Change history
05 June 2019
Several occurrences of the word ‘schizophrenia’ have been re-worded as ‘liability to schizophrenia’ or ‘schizophrenia risk’, including in the title, which should have been “GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability,” as well as in Supplementary Figures 1–10 and Supplementary Tables 7–10, to more accurately reflect the findings of the work.
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Acknowledgements
We would like to thank the research participants and employees of 23andMe for making this work possible. We gratefully acknowledge the Psychiatric Genomics Consortium contributing studies and the participants in those studies without whom this effort would not have been possible. J.A.P. and J.M.V. are supported by the European Research Council (Beyond the Genetics of Addiction ERC-284167, PI J.M.V.). K.J.H.V. is supported by the Foundation Volksbond Rotterdam. N.A.G. is supported by US National Institutes of Health, National Institute on Drug Abuse R00DA023549. J.L.T. is supported by the Netherlands Organization for Scientific Research (NWO; Rubicon grant 446-16-009). S.M. is supported by an Australian Research Council Fellowship. Statistical analyses were partly carried out on the Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and financially supported by the Netherlands Organization for Scientific Research (NWO 480-05-003 PI: Posthuma) along with a supplement from the Dutch Brain Foundation and the VU University Amsterdam. M.G.N. is supported by Royal Netherlands Academy of Science Professor Award to D.I.B. (PAH/6635). Part of the computation of this project was funded by NWO Exact Sciences for the application: “Population scale Genetic Analysis” awarded to M.G.N. The genome-wide association analysis on the UK Biobank dataset has been conducted using the UK Biobank resource under application numbers 9905, 16406 and 25331.
The Substance Use Disorders Working Group of the Psychiatric Genomics Consortium (PGC-SUD) is supported by funds from NIDA and NIMH to MH109532 and, previously, with analyst support from NIAAA to U01AA008401 (COGA). J.M.’s contributions were partially supported by the Peter Boris Chair in Addictions Research. S.S.-R. was supported by the Frontiers of Innovation Scholars Program (FISP; #3-P3029), the Interdisciplinary Research Fellowship in NeuroAIDS (IRFN; MH081482) and a pilot award from DA037844. R.M. was supported by the European Union through the European Regional Development Fund (Project No. 2014-2020.4.01.15-0012) and the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements No 692065 and 692145. J.K. was supported by Academy Professorship grants by the Academy of Finland (263278, 292782). M.R. is a recipient of a Miguel de Servet contract from the Instituto de Salud Carlos III, Spain (CP09/00119 and CPII15/00023).
Contributors to the 23andMe Research Team
M. Agee, B. Alipanahi, A. Auton, R. K. Bell, K. Bryc, S. L. Elson, P. Fontanillas, N. A. Furlotte, D. A. Hinds, K. E. Huber, A. Kleinman, N. K. Litterman, J. C. McCreight, M. H. McIntyre, J. L. Mountain, E. S. Noblin, C. A. M. Northover, S. J. Pitts, J. Fah Sathirapongsasuti, O. V. Sazonova, J. F. Shelton, S. Shringarpure, C. Tian, J. Y. Tung, V. Vacic and C.H. Wilson.
Contributors to the International Cannabis Consortium
S. Stringer, C. C. Minica, K. J. H. Verweij, H. Mbarek, M. Bernard, J. Derringer, K. R. van Eijk, J. D. Isen, A. Loukola, D. F. Maciejewski, E. Mihailov, P. J. van der Most, C. Sánchez-Mora, L. Roos, R. Sherva, R. Walters, J.J. Ware, A. Abdellaoui, T. B. Bigdeli, S. J. T. Branje, S. A. Brown, M. Bruinenberg, M. Casas, T. Esko, I. Garcia-Martinez, S. D. Gordon, J. M. Harris, C. A. Hartman, A. K. Henders, A. C. Heath, I. B. Hickie, M. Hickman, C. J. Hopfer, J. J. Hottenga, A. C. Huizink, D. E. Irons, R. S. Kahn, T. Korhonen, H. R. Kranzler, K. Krauter, P. A. C. van Lier, G. H. Lubke, P. A. F. Madden, R. Mägi, M. K. McGue, S. E. Medland, W. H. J. Meeus, M. B. Miller, G. W. Montgomery, M. G. Nivard, I. M. Nolte, A. J. Oldehinkel, Z. Pausova, B. Qaiser, L. Quaye, J. A. Ramos-Quiroga, V. Richarte, R. J. Rose, J. Shin, M. C. Stallings, A. I. Stiby, T. L. Wall, M. J. Wright, H. M. Koot, T. Paus, J. K. Hewitt, M. Ribasés, J. Kaprio, M. P. M. Boks, H. Snieder, T. Spector, M. R. Munafò, A. Metspalu, J. Gelernter, D. I. Boomsma, W. G. Iacono, N. G. Martin, N. A. Gillespie, E. M. Derks and J. M. Vink.
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K.J.H.V., E.M.D. and J.M.V. were responsible for the study concept and the design of the study. I.C.C. contributed existing genome-wide summary data from the International Cannabis Consortium. The PGC-SUD group provided summary statistics of the cannabis dependence GWAS. S.S., S.S.-R., M.G.N., B.M.L.B., J.-S.O., H.F.I., M.D.v.d.Z., M.B., F.R.D., P.F., S.M., J.R.B.P., A.A.P. and D.P. performed or supervised genome-wide association analyses. J.A.P. performed the quality control and meta-analysis of genome-wide association studies, under supervision of K.J.H.V., B.M.L.B. and J.M.V. J.A.P., K.J.H.V., Z.G., J.L.T., A.A., M.R.M. and E.M.D. contributed to secondary analyses of the data. J.A.P., K.J.H.V., Z.G., N.A.G., E.M.D. and J.M.V. wrote the manuscript. J.L.D., S.J.T.B., C.A.H., A.C.H., P.A.C.v.L., P.A.F.M., R.M., W.M., G.W.M., A.J.O., Z.P., J.A.R.-Q., T.P., M.R., J.K., M.P.M.B., J.T.B., T.D.S., J.G., D.I.B. and N.G.M. contributed to data acquisition of the samples in the International Cannabis Consortium. S.L.E., H.d.W., L.K.D. and J.M.K. contributed to data acquisition and analysis for the 23andMe dataset. All authors provided critical revision of the manuscript for important intellectual content.
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P.F., S.L.E. and members of the 23andMe Research Team are employees of 23andMe Inc. J.A.R.-Q. was on the speakers’ bureau and/or acted as consultant for Eli Lilly, Janssen-Cilag, Novartis, Shire, Lundbeck, Almirall, BRAINGAZE, Sincrolab and Rubió in the last 5 years. He also received travel awards (air tickets and hotel) for taking part in psychiatric meetings from Janssen-Cilag, Rubió, Shire and Eli Lilly. The Department of Psychiatry chaired by him received unrestricted educational and research support from the following pharmaceutical companies in the last 5 years: Eli Lilly, Lundbeck, Janssen- Cilag, Actelion, Shire, Ferrer and Rubió.
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Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–10
Supplementary Table 1
All genome-wide significant SNP associations in the meta-analysis
Supplementary Table 2
Independent genome-wide significant associations with lifetime cannabis use in the UK Biobank sample
Supplementary Table 3
Description of the genome-wide significant associations in the gene-based test of association and the S-PrediXcan analysis, with a short (non-comprehensive) overview of relevant literature findings on gene–phenotype associations
Supplementary Table 4
Significant S-PrediXcan associations after correction for multiple testing
Supplementary Table 5
Summary of S-PrediXcan associations by target gene
Supplementary Table 6
Results from LD score regression analysis: genetic correlations between lifetime cannabis use and various traits of interest
Supplementary Table 7
SNPs included in the genetic instruments used for bidirectional two-sample Mendelian randomization analyses between lifetime cannabis use and schizophrenia diagnosis
Supplementary Table 8
Cochran’s heterogeneity statistic (Q) for inverse-variance-weighted (IVW) bidirectional two-sample Mendelian randomization analyses between lifetime cannabis use and schizophrenia diagnosis
Supplementary Table 9
I2 statistic for the heterogeneity between genetic variants in an instrument for the MR-Egger SIMEX analysis
Supplementary Table 10
MR-Egger SIMEX intercept, indicating degree of horizontal pleiotropy, for bidirectional two-sample Mendelian randomization analyses between lifetime cannabis use and schizophrenia diagnosis
Supplementary Table 11
Methodological details of the individual GWASs
Supplementary Table 12
quality control steps in the individual GWASs
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Pasman, J.A., Verweij, K.J.H., Gerring, Z. et al. GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability. Nat Neurosci 21, 1161–1170 (2018). https://doi.org/10.1038/s41593-018-0206-1
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DOI: https://doi.org/10.1038/s41593-018-0206-1
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