Richard Sherva1, Qian Wang2, Henry Kranzler3, Hongyu Zhao4, Ryan Koesterer1, Aryeh Herman5, Lindsay A Farrer6, Joel Gelernter7. 1. Section of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts. 2. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut. 3. Department 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, Philadelphi. 4. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut5Department of Genetics, Yale School of Medicine, West Haven, Connecticut6Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut7VA Coop. 5. Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut. 6. Section of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts9Department of Neurology, Boston University School of Medicine, Boston, Massachusetts10Department of Ophthalmology, Boston University School. 7. VA Cooperative Studies Program Coordinating Center, West Haven, Connecticut8Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut13Department of Psychiatry, VA Connecticut Healthcare Center, Yale University School of Medicine, West Hav.
Abstract
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.
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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