Further evidence for association of polymorphisms in theCNR1gene with cocaine addiction: confirmation in an independent sample and meta-analysis

Abstract

Genetic research on cocaine dependence may help clarify our understanding of the disorder as well as provide insights for effective treatment. Since endocannabinoid signaling and dopamine neurotransmission have been shown to be involved with drug reward, genes related to these systems are plausible candidates for susceptibility to cocaine dependence. The cannabinoid receptor 1 (CB1) protein regulates both the endocannabinoid and dopaminergic neurobiological systems, and polymorphisms in the cannabinoid receptor gene, CNR1, have been previously been associated with substance dependence. In this study, we attempt to replicate a finding associating CNR1 with cocaine dependence in African Americans. Cocaine dependent individuals (n=883) and unaffected controls (n=334) of African descent were genotyped for two single nucleotide polymorphisms (SNPs) in the CB1 gene (rs6454674, rs806368). We observed a significant difference in genotype frequencies between cases and controls for both SNPs (p≤0.05). This study confirms the association between variants in the CNR1 and cocaine dependence. However, considering the substantial co-morbidity of cocaine dependence with other drugs of abuse, additional studies are necessary to determine whether polymorphisms in CNR1 induce a general susceptibility to substance dependence or are specific to cocaine addiction.

Common single nucleotide variants underlying drug addiction: more than a decade of research

“…; Clarke et al . ): Zuo et al . () found a clear association between cocaine dependence and the rs806368 SNP in European‐American family and case–control samples, but for African‐Americans, the association was only significant in the family sample.…”

CB1 receptor antagonism blocks stress-potentiated reinstatement of cocaine seeking in rats

“…Notably, polymorphisms of the gene for the CB1 receptor, CNR1 , are associated with cocaine dependence (Clarke et al 2013; Lopez-Moreno et al 2012; Zuo et al 2007; Zuo et al 2009) and it has been suggested that circulating endocannabinoids may be a viable biomarker for cocaine use disorder in humans (Pavon et al 2013). Demonstration of a contribution of endocannabinoid signaling to cocaine use in the context of stress may shed additional light on the complex relationship between endocannabinoids and cocaine addiction.…”

Genome‐wide scans of genetic variants for psychophysiological endophenotypes: A methodological overview

“…The first set comprised 1,180 SNPs related to disorders or traits that are likely a priori to be associated with the different endophenotypes. These were identified through MEDLINE and included meta‐ and mega‐analyses of alcohol (Wang et al., ) and drug (C. Y. Li et al., ) dependence, cocaine abuse (Clarke et al., ), smoking and nicotine dependence (Belsky et al., ; Bierut et al., ; Furberg et al., ; Liu, Tozzi et al., ; Thorgeirsson et al., ), ADHD (B. M. Neale et al., ), schizophrenia, bipolar disorder, and major depression (Greenwood et al., ; Hek et al., ; Ripke et al., ; Smoller et al., ; Sullivan, Daly, & O'Donovan, ), or related phenotypes, such as heavy drinking (Heath et al., ) and the maximum number of drinks consumed at one time (Kapoor et al., ; Pan et al., ), and the personality characteristic of excitement seeking (Terracciano et al., ).The second candidate SNP set was different for each investigation, consisting of SNPs that have been reported in previous research to be associated with the specific endophenotypes investigated. SNPs in either of these two sets that were not on the Illumina array were imputed, using the program Minimac (Howie, Fuchsberger, Stephens, Marchini, & Abecasis, ), after genotypes had first been phased using Beagle (Browning & Browning, ), which uses known familial structure to improve phasing accuracy.…”

“…The first set comprised 1,180 SNPs related to disorders or traits that are likely a priori to be associated with the different endophenotypes. These were identified through MEDLINE and included meta-and mega-analyses of alcohol (Wang et al, 2011) and drug (C. Y. dependence, cocaine abuse (Clarke et al, 2013), smoking and nicotine dependence (Belsky et al, 2013;Bierut et al, 2008;Furberg et al, 2010;Liu, Tozzi et al, 2010;Thorgeirsson et al, 2010), ADHD (B. M. Neale et al, 2010), schizophrenia, bipolar disorder, and major depression (Greenwood et al, 2011;Hek et al, 2013;Ripke et al, 2012;Smoller et al, 2013;Sullivan, Daly, & O'Donovan, 2012), or related phenotypes, such as heavy drinking (Heath et al, 2011) and the maximum number of drinks consumed at one time (Kapoor et al, 2013;Pan et al, 2013), and the personality characteristic of excitement seeking (Terracciano et al, 2011).…”