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Original Investigation |

Genome-wide Association Study of Cannabis Dependence Severity, Novel Risk Variants, and Shared Genetic Risks

Richard Sherva, PhD1; Qian Wang, MS2; Henry Kranzler, MD3,4; Hongyu Zhao, PhD2,5,6,7; Ryan Koesterer, MS1; Aryeh Herman, PsyD8; Lindsay A. Farrer, PhD1,9,10,11,12; Joel Gelernter, MD7,8,13,14
[+] Author Affiliations
1Section of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
2Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut
3Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia
4Mental Illness Research Education and Clinical Center, Veterans Affairs (VA) Stars and Stripes Healthcare Network, Philadelphia VA Medical Center, Philadelphia, Pennsylvania
5Department of Genetics, Yale School of Medicine, West Haven, Connecticut
6Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
7VA Cooperative Studies Program Coordinating Center, West Haven, Connecticut
8Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
9Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
10Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts
11Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
12Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
13Department of Psychiatry, VA Connecticut Healthcare Center, Yale University School of Medicine, West Haven, Connecticut
14Department of Neurobiology, Yale School of Medicine, New Haven, Connecticut
JAMA Psychiatry. 2016;73(5):472-480. doi:10.1001/jamapsychiatry.2016.0036.
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Importance  Cannabis dependence (CAD) is a serious problem worldwide and is of growing importance in the United States because cannabis is increasingly available legally. Although genetic factors contribute substantially to CAD risk, at present no well-established specific genetic risk factors for CAD have been elucidated.

Objective  To report findings for DSM-IV CAD criteria from association analyses performed in large cohorts of African American and European American participants from 3 studies of substance use disorder genetics.

Design, Setting, and Participants  This genome-wide association study for DSM-IV CAD criterion count was performed in 3 independent substance dependence cohorts (the Yale-Penn Study, Study of Addiction: Genetics and Environment [SAGE], and International Consortium on the Genetics of Heroin Dependence [ICGHD]). A referral sample and volunteers recruited in the community and from substance abuse treatment centers included 6000 African American and 8754 European American participants, including some from small families. Participants from the Yale-Penn Study were recruited from 2000 to 2013. Data were collected for the SAGE trial from 1990 to 2007 and for the ICGHD from 2004 to 2009. Data were analyzed from January 2, 2013, to November 9, 2015.

Main Outcomes and Measures  Criterion count for DSM-IV CAD.

Results  Among the 14 754 participants, 7879 were male, 6875 were female, and the mean (SD) age was 39.2 (10.2) years. Three independent regions with genome-wide significant single-nucleotide polymorphism associations were identified, considering the largest possible sample. These included rs143244591 (β = 0.54, P = 4.32 × 10−10 for the meta-analysis) in novel antisense transcript RP11-206M11.7;rs146091982 (β = 0.54, P = 1.33 × 10−9 for the meta-analysis) in the solute carrier family 35 member G1 gene (SLC35G1); and rs77378271 (β = 0.29, P = 2.13 × 10−8 for the meta-analysis) in the CUB and Sushi multiple domains 1 gene (CSMD1). Also noted was evidence of genome-level pleiotropy between CAD and major depressive disorder and for an association with single-nucleotide polymorphisms in genes associated with schizophrenia risk. Several of the genes identified have functions related to neuronal calcium homeostasis or central nervous system development.

Conclusions and Relevance  These results are the first, to our knowledge, to identify specific CAD risk alleles and potential genetic factors contributing to the comorbidity of CAD with major depression and schizophrenia.

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Figure.
Regional Manhattan Plots of Association Results for DSM-IV Cannabis Dependence Criterion Count in 4 Genomic Regions

Association results from single-nucleotide polymorphisms (SNPs) in 4 regions. A, The 148.8- to 149.2-MB region encompassing RP11-206M11.7 on chromosome 3 in the Yale-Penn and Study of Addiction: Genetics and Environment (SAGE) African American participants. B, The 95.3- to 96-MB region encompassing SLC35G1 on chromosome 10 in the Yale-Penn and SAGE African American participants. C, The 2.8- to 4.8-MB region on chromosome 8 encompassing CSMD1 in the Yale-Penn, SAGE, and International Consortium on the Genetics of Heroin Dependence (ICGHD) African American and European American participants. D, The 25.07- to 25.43-MB region encompassing PI4K2B on chromosome 4 in the Yale-Penn, SAGE, and ICGHD African American and European American participants. In A and B, the SNPs are color coded according to the correlation coefficient (r2) in the 1000 Genomes African samples with the most significant SNP. In C and D, results from the African American and European American participants were combined, and no linkage disequilibrium information was displayed. The light purple circle represents the −log10P value for the most significant regional SNP in the meta-analysis of the discovery samples; the purple diamond, the result for that SNP after meta-analysis with the replication sample(s). The light blue line and right y-axis show the observed recombination rate.

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