Literature DB >> 18519829

An autosomal linkage scan for cannabis use disorders in the nicotine addiction genetics project.

Arpana Agrawal1, Michele L Pergadia, Scott F Saccone, Michael T Lynskey, Jen C Wang, Nicholas G Martin, Dixie Statham, Anjali Henders, Megan Campbell, Robertino Garcia, Ulla Broms, Richard D Todd, Alison M Goate, John Rice, Jaakko Kaprio, Andrew C Heath, Grant W Montgomery, Pamela A F Madden.   

Abstract

CONTEXT: Despite accumulating evidence that there is a genetic basis for cannabis use disorders (ie, abuse and dependence), few studies have identified genomic regions that may harbor biological risk and protective factors.
OBJECTIVE: To conduct autosomal linkage analyses that identify genomic regions that may harbor genes conferring a vulnerability to cannabis use disorders.
DESIGN: In 289 Australian families who participated in the Nicotine Addiction Genetics Project, 423 autosomal markers were genotyped. Families were ascertained for heavy cigarette smoking. Linkage was conducted for DSM-IV cannabis dependence and for a novel factor score representing problems with cannabis use, including occurrence of 3 of 4 abuse criteria (excluding legal problems) and 6 DSM-IV dependence criteria.
RESULTS: A maximum logarithm of odds (LOD) of 3.36 was noted for the cannabis problems factor score on chromosome arm 1p. An LOD of 2.2 was noted on chromosome 4 in the region of the gamma-aminobutyric acid type A gene cluster, including GABRA2, which has been implicated in drug use disorders. For DSM-IV cannabis dependence, a modest LOD score on chromosome 6 (1.42) near cannabinoid receptor 1 (CNR1) was identified. In addition, support for an elevation on chromosome 3, identified in prior independent studies, was noted for the factor score and cannabis dependence (LOD, 1.4).
CONCLUSIONS: Genes such as ELTD1 on chromosome 1, in addition to genes on chromosomes 4 (eg, GABRA2) and 6 (eg, CNR1), may be associated with the genetic risk for cannabis use disorders. We introduce a novel quantitative phenotype, a cannabis problems factor score composed of DSM-IV abuse and dependence criteria, that may be useful for future linkage and association studies.

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Year:  2008        PMID: 18519829     DOI: 10.1001/archpsyc.65.6.713

Source DB:  PubMed          Journal:  Arch Gen Psychiatry        ISSN: 0003-990X


  29 in total

1.  Genetic variation in FAAH is associated with cannabis use disorders in a young adult sample of Mexican Americans.

Authors:  Whitney E Melroy-Greif; Kirk C Wilhelmsen; Cindy L Ehlers
Journal:  Drug Alcohol Depend       Date:  2016-06-25       Impact factor: 4.492

2.  Impulsivity, variation in the cannabinoid receptor (CNR1) and fatty acid amide hydrolase (FAAH) genes, and marijuana-related problems.

Authors:  L Cinnamon Bidwell; Jane Metrik; John McGeary; Rohan H C Palmer; S Francazio; Valerie S Knopik
Journal:  J Stud Alcohol Drugs       Date:  2013-11       Impact factor: 2.582

3.  CNR1 and FAAH variation and affective states induced by marijuana smoking.

Authors:  Rohan H C Palmer; John E McGeary; Valerie S Knopik; L Cinnamon Bidwell; Jane M Metrik
Journal:  Am J Drug Alcohol Abuse       Date:  2019-06-11       Impact factor: 3.829

4.  Common heritable contributions to low-risk trauma, high-risk trauma, posttraumatic stress disorder, and major depression.

Authors:  Carolyn E Sartor; Julia D Grant; Michael T Lynskey; Vivia V McCutcheon; Mary Waldron; Dixie J Statham; Kathleen K Bucholz; Pamela A F Madden; Andrew C Heath; Nicholas G Martin; Elliot C Nelson
Journal:  Arch Gen Psychiatry       Date:  2012-03

Review 5.  A comparison of selected quantitative trait loci associated with alcohol use phenotypes in humans and mouse models.

Authors:  Cindy L Ehlers; Nicole A R Walter; Danielle M Dick; Kari J Buck; John C Crabbe
Journal:  Addict Biol       Date:  2010-04       Impact factor: 4.280

Review 6.  New insights into the genetics of addiction.

Authors:  Ming D Li; Margit Burmeister
Journal:  Nat Rev Genet       Date:  2009-04       Impact factor: 53.242

7.  ELTD1, a potential new biomarker for gliomas.

Authors:  Rheal A Towner; Randy L Jensen; Howard Colman; Brian Vaillant; Nataliya Smith; Rebba Casteel; Debra Saunders; David L Gillespie; Robert Silasi-Mansat; Florea Lupu; Cory B Giles; Jonathan D Wren
Journal:  Neurosurgery       Date:  2013-01       Impact factor: 4.654

8.  Examining the association of NRXN3 SNPs with borderline personality disorder phenotypes in heroin dependent cases and socio-economically disadvantaged controls.

Authors:  Vassilis N Panagopoulos; Timothy J Trull; Anne L Glowinski; Michael T Lynskey; Andrew C Heath; Arpana Agrawal; Anjali K Henders; Leanne Wallace; Alexandre A Todorov; Pamela A F Madden; Elizabeth Moore; Louisa Degenhardt; Nicholas G Martin; Grant W Montgomery; Elliot C Nelson
Journal:  Drug Alcohol Depend       Date:  2012-12-12       Impact factor: 4.492

9.  Linkage analyses of cannabis dependence, craving, and withdrawal in the San Francisco family study.

Authors:  Cindy L Ehlers; Ian R Gizer; Cassandra Vieten; Kirk C Wilhelmsen
Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2010-04-05       Impact factor: 3.568

10.  Monoacylglycerol lipase (MGLL) polymorphism rs604300 interacts with childhood adversity to predict cannabis dependence symptoms and amygdala habituation: Evidence from an endocannabinoid system-level analysis.

Authors:  Caitlin E Carey; Arpana Agrawal; Bo Zhang; Emily D Conley; Louisa Degenhardt; Andrew C Heath; Daofeng Li; Michael T Lynskey; Nicholas G Martin; Grant W Montgomery; Ting Wang; Laura J Bierut; Ahmad R Hariri; Elliot C Nelson; Ryan Bogdan
Journal:  J Abnorm Psychol       Date:  2015-11
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