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Whole genome sequence study of cannabis dependence in two independent cohorts.

ABSTRACT: Recent advances in genome wide sequencing techniques and analytical methods allow for more comprehensive examinations of the genome than microarray-based genome-wide association studies (GWAS). The present report provides the first application of whole genome sequencing (WGS) to identify low frequency variants involved in cannabis dependence across two independent cohorts. The present study used low-coverage whole genome sequence data to conduct set-based association and enrichment analyses of low frequency variation in protein-coding regions as well as regulatory regions in relation to cannabis dependence. Two cohorts were studied: a population-based Native American tribal community consisting of 697 participants nested within large multi-generational pedigrees and a family-based sample of 1832 predominantly European ancestry participants largely nested within nuclear families. Participants in both samples were assessed for Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) lifetime cannabis dependence, with 168 and 241 participants receiving a positive diagnosis in each sample, respectively. Sequence kernel association tests identified one protein-coding region, C1orf110 and one regulatory region in the MEF2B gene that achieved significance in a meta-analysis of both samples. A regulatory region within the PCCB gene, a gene previously associated with schizophrenia, exhibited a suggestive association. Finally, a significant enrichment of regions within or near genes with multiple splice variants or involved in cell adhesion or potassium channel activity were associated with cannabis dependence. This initial study demonstrates the potential utility of low pass whole genome sequencing for identifying genetic variants involved in the etiology of cannabis use disorders.

SUBMITTER: Gizer IR

PROVIDER: S-EPMC5522771 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Whole genome sequence study of cannabis dependence in two independent cohorts.

Gizer Ian R IR Bizon Chris C Gilder David A DA Ehlers Cindy L CL Wilhelmsen Kirk C KC

Addiction biology 20170123 1

Recent advances in genome wide sequencing techniques and analytical methods allow for more comprehensive examinations of the genome than microarray-based genome-wide association studies (GWAS). The present report provides the first application of whole genome sequencing (WGS) to identify low frequency variants involved in cannabis dependence across two independent cohorts. The present study used low-coverage whole genome sequence data to conduct set-based association and enrichment analyses of l ...[more]

PMID: 28111843

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Project description:ImportanceCannabis 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.ObjectiveTo 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 participantsThis 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 measuresCriterion count for DSM-IV CAD.ResultsAmong 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 relevanceThese 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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Whole genome sequence study of cannabis dependence in two independent cohorts.

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Whole genome sequence study of cannabis dependence in two independent cohorts.

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