title: 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.
authors.affiliation: Department of Psychological Sciences, University of Missouri, Columbia, MO, USA.
authors.forename: Ian R
authors.initials: IR
authors.lastname: Gizer
authors.affiliation: Departments of Neurology and Genetics, University of North Carolina, Chapel Hill, NC, USA.
authors.forename: Chris
authors.initials: C
authors.lastname: Bizon
authors.affiliation: Department of Molecular and Cellular Neurosciences, The Scripps Research Institute, La Jolla, CA, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Gilder
authors.affiliation: Department of Molecular and Cellular Neurosciences, The Scripps Research Institute, La Jolla, CA, USA.
authors.forename: Cindy L
authors.initials: CL
authors.lastname: Ehlers
authors.affiliation: Departments of Neurology and Genetics, University of North Carolina, Chapel Hill, NC, USA.
authors.forename: Kirk C
authors.initials: KC
authors.lastname: Wilhelmsen
mesh_terms: D000328:Adult; D015331:Cohort Studies; D005260:Female; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D007198:Indians, North American / Q000235:genetics*; D064326:MEF2 Transcription Factors / Q000235:genetics; D008297:Male; D002189:Marijuana Abuse / Q000235:genetics*; D043586:Methylmalonyl-CoA Decarboxylase / Q000235:genetics; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D015221:Potassium Channels / Q000235:genetics; D044465:White People / Q000235:genetics*; D000073336:Whole Genome Sequencing
chemical_list: D064326:MEF2 Transcription Factors; C578038:MEF2B protein, human; D015221:Potassium Channels; D043586:Methylmalonyl-CoA Decarboxylase
keywords: cannabis; genetic association; genetics; marijuana dependence; whole genome sequencing