Variants near CHRNB3-CHRNA6 are associated with DSM-5 cocaine use disorder: evidence for pleiotropy.
paper
Primary
Public
- Authors
- Sadler, Brooke; Haller, Gabe; Agrawal, Arpana; Culverhouse, Rob; Bucholz, Kathleen; Brooks, Andy; Tischfield, Jay; Johnson, Eric O; Edenberg, Howard; Schuckit, Marc; Saccone, Nancy; Bierut, Laura; Goate, Alison
- Year
- 2014
- Journal
- Scientific reports
- PMID
- 24675634
- DOI
- 10.1038/srep04497
- PMCID
- PMC4894386
In the U.S.A., cocaine is the second most abused illicit drug. Variants within the CHRNB3-A6 gene cluster have been associated with cigarette consumption in several GWAS. These receptors represent intriguing candidates for the study of cocaine dependence because nicotinic receptors are thought to be involved in generalized addiction pathways. Using genotypic data from a GWAS of the Study of Addiction: Genetics and Environment (SAGE) dataset, we tested for association of CHRNB3-A6 SNPs with DSM-5 cocaine use disorder. Multiple SNPs in the region were significantly associated with increased risk of cocaine use disorder. Inclusion of the most significant SNP as a covariate in a linear regression model provided evidence for an additional independent signal within this locus for cocaine use disorder. These results suggest that the CHRNB3-A6 locus contains multiple variants affecting risk for vulnerability to cocaine and nicotine dependence as well as bipolar disorder, suggesting that they have pleiotropic effects.
LD plot of the region.Values and gray-scale represent r-squared. Importantly, rs9298626, the top SNP associated with DSM-5 cocaine use disorder and the shared SNP that becomes significant when putting this SNP into the respective model as a covariate (rs892413) are circled in blue, and SNPs representing the previously discovered association with nicotine dependence (rs1451240, rs6474413, and rs4952) are circled in red.
| # | Section | Preview |
|---|---|---|
| 20 | Methods — COGA sample | Out of more than 11,000 subjects who participated in COGA, a case-control series of unrelated… |
| 21 | Methods — FSCD sample | Subjects in the FSCD were specifically recruited for cocaine use from chemical dependency treatment… |
| 22 | Methods — Genotyping and Q/C | All DNA samples were genotyped on the Illumina Human 1M-Duo beadchip by the Center for Inherited… |
| 23 | Methods — Phenotype | Cocaine use disorder for all members of the SAGE dataset was measured using the DSM-5 criteria37. As… |
| 24 | Methods — Statistical analyses | All analyses were performed on genotyped data. Association analyses were conducted in PLINK38 for… |
| 25 | Methods — Statistical analyses | In a case/control division of subjects based on presence or absence of cocaine use disorder,… |
| 26 | Methods — Statistical analyses | To improve our understanding of observed associations, the top SNPs identified in the whole SAGE… |
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| Citation | PMID | DOI | Status |
|---|---|---|---|
| BierutL. J. et al. A genome-wide association study of alcohol dependence. Proc Natl Acad Sci U S A 107, 5082–5087, 10.1073/pnas.0911109107 (2010).20202923PMC2841942 | — | — | — |
| BierutL. J. et al. ADH1B is associated with alcohol dependence and alcohol consumption in populations of European and African ancestry. Mol Psychiatry 17, 445–450, 10.1038/mp.2011.124 (2012).21968928PMC3252425 | — | — | — |
| FarrerL. A. et al. Association of variants in MANEA with cocaine-related behaviors. Arch Gen Psychiatry 66, 267–274, 10.1001/archgenpsychiatry.2008.538 (2009).19255376PMC2758158 | — | — | — |
| GelernterJ. et al. Genome-wide association study of cocaine dependence and related traits: FAM53B identified as a risk gene. Mol Psychiatry, 10.1038/mp.2013.99 (2013).PMC386515823958962 | — | — | — |
| GelernterJ. et al. Genomewide linkage scan for nicotine dependence: identification of a chromosome 5 risk locus. Biol Psychiatry 61, 119–126, 10.1016/j.biopsych.2006.08.023 (2007).17081504 | — | — | — |
| Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat Gen 42, 441–447, 10.1038/ng.571 (2010).PMC291460020418890 | — | — | — |
| GoldmanD., OrosziG. & DucciF. The genetics of addictions: uncovering the genes. Nat Rev Genet 6, 521–532, 10.1038/nrg1635 (2005).15995696 | — | — | — |
| GoodwinR. D., ZvolenskyM. J., KeyesK. M. & HasinD. S. Mental disorders and cigarette use among adults in the United States. Am J Addic 21, 416–423, 10.1111/j.1521-0391.2012.00263.x (2012).PMC370130422882392 | — | — | — |
| GossopM., StewartD., TreacyS. & MarsdenJ. A prospective study of mortality among drug misusers during a 4-year period after seeking treatment. Addiction 97, 39–47 (2002).1189526910.1046/j.1360-0443.2002.00079.x | — | — | — |
| GruczaR. A. et al. A risk allele for nicotine dependence in CHRNA5 is a protective allele for cocaine dependence. Biol Psychiatry 64, 922–929, 10.1016/j.biopsych.2008.04.018 (2008).18519132PMC2582594 | — | — | — |
| HallerG. et al. Rare missense variants in CHRNB3 and CHRNA3 are associated with risk of alcohol and cocaine dependence (accepted). Hum Mol Genet, 10.1093/hmg/ddt463 (2013).PMC388826324057674 | — | — | — |
| HansenS. T. & MarkG. P. The nicotinic acetylcholine receptor antagonist mecamylamine prevents escalation of cocaine self-administration in rats with extended daily access. Psychopharmacology (Berl) 194, 53–61, 10.1007/s00213-007-0822-z (2007).17530475 | — | — | — |
| HartzS. M. et al. Genetic association of bipolar disorder with the beta(3) nicotinic receptor subunit gene. Psychiatr Genet 21, 77–84, 10.1097/YPG.0b013e32834135eb (2011).21191315PMC3107398 | — | — | — |
| HasinD. S. et al. DSM-5 Criteria for Substance Use Disorders: Recommendations and Rationale. Am J Psychiatry 170, 834–851, 10.1176/appi.ajp.2013.12060782 (2013).23903334PMC3767415 | — | — | — |
| HoftN. R. et al. Genetic association of the CHRNA6 and CHRNB3 genes with tobacco dependence in a nationally representative sample. Neuropsychopharmacology 34, 698–706, 10.1038/npp.2008.122 (2009).18704094PMC2915837 | — | — | — |
| KendlerK. S., MyersJ. & PrescottC. A. Specificity of genetic and environmental risk factors for symptoms of cannabis, cocaine, alcohol, caffeine, and nicotine dependence. Arch Gen Psychiatry 64, 1313–1320, 10.1001/archpsyc.64.11.1313 (2007).17984400 | — | — | — |
| KennesonA., FunderburkJ. S. & MaistoS. A. Substance use disorders increase the odds of subsequent mood disorders. Drug Alcohol Depend, 10.1016/j.drugalcdep.2013.06.011 (2013).23906994 | — | — | — |
| KoobG. F. Drug addiction: the yin and yang of hedonic homeostasis. Neuron 16, 893–896 (1996).863024410.1016/s0896-6273(00)80109-9 | — | — | — |
| LaurieC. C. et al. Quality control and quality assurance in genotypic data for genome-wide association studies. Genet Epidemiol 34, 591–602, 10.1002/gepi.20516 (2010).20718045PMC3061487 | — | — | — |
| LinP. I. et al. Clinical correlates and familial aggregation of age at onset in bipolar disorder. Am J Psychiatry 163, 240–246, 10.1176/appi.ajp.163.2.240 (2006).16449477 | — | — | — |
| MwenifumboJ. C. & TyndaleR. F. Molecular genetics of nicotine metabolism. Handb Exp Pharmacol, 235–259, 10.1007/978-3-540-69248-5_9 (2009).19184652 | — | — | — |
| NuttD. J., KingL. A. & PhillipsL. D. Drug harms in the UK: a multicriteria decision analysis. Lancet 376, 1558–1565, 10.1016/S0140-6736(10)61462-6 (2010).21036393 | — | — | — |
| PostR. M. & KalivasP. Bipolar disorder and substance misuse: pathological and therapeutic implications of their comorbidity and cross-sensitisation. Br J Psychiatry 202, 172–176, 10.1192/bjp.bp.112.116855 (2013).23457180PMC4340700 | — | — | — |
| PurcellS. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81, 559–575, 10.1086/519795 (2007).17701901PMC1950838 | — | — | — |
| PurcellS. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 81, 559–75 (2007).1770190110.1086/519795PMC1950838 | — | — | — |
| RiceJ. P. et al. CHRNB3 is more strongly associated with Fagerstrom test for cigarette dependence-based nicotine dependence than cigarettes per day: phenotype definition changes genome-wide association studies results. Addiction 107, 2019–2028, 10.1111/j.1360-0443.2012.03922.x (2012).22524403PMC3427406 | — | — | — |
| SacconeN. L. et al. Multiple independent loci at chromosome 15q25.1 affect smoking quantity: a meta-analysis and comparison with lung cancer and COPD. PLoS Genet 6, 10.1371/journal.pgen.1001053 (2010).PMC291684720700436 | — | — | — |
| SacconeN. L. et al. The CHRNA5-CHRNA3-CHRNB4 nicotinic receptor subunit gene cluster affects risk for nicotine dependence in African-Americans and in European-Americans. Cancer Res 69, 6848–6856, 10.1158/0008-5472.CAN-09-0786 (2009).19706762PMC2874321 | — | — | — |
| SacconeS. F. et al. Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs. Hum Mol Genet 16, 36–49, 10.1093/hmg/ddl438 (2007).17135278PMC2270437 | — | — | — |
| ShervaR. et al. Variation in nicotinic acetylcholine receptor genes is associated with multiple substance dependence phenotypes. Neuropsychopharmacology 35, 1921–1931, 10.1038/npp.2010.64 (2010).20485328PMC3055642 | — | — | — |
| TandaG., PontieriF. E. & Di ChiaraG. Cannabinoid and heroin activation of mesolimbic dopamine transmission by a common mu1 opioid receptor mechanism. Science 276, 2048–2050 (1997).919726910.1126/science.276.5321.2048 | — | — | — |
| ThorgeirssonT. E. et al. Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nat Genet 42, 448–453, 10.1038/ng.573 (2010).20418888PMC3080600 | — | — | — |
| TsuangM. T., BarJ. L., HarleyR. M. & LyonsM. J. The Harvard Twin Study of Substance Abuse: what we have learned. Harv Rev Psychiatry 9, 267–279 (2001).11600486 | — | — | — |
| WangJ. C., KapoorM. & GoateA. M. The genetics of substance dependence. Annu Rev Genomics Hum Genet 13, 241–261, 10.1146/annurev-genom-090711-163844 (2012).22703173PMC3474605 | — | — | — |
| WiseR. A. Addictive drugs and brain stimulation reward. Annu Rev Neurosci 19, 319–340, 10.1146/annurev.ne.19.030196.001535 (1996).8833446 | — | — | — |
| YangB. Z., HanS., KranzlerH. R., FarrerL. A. & GelernterJ. A genomewide linkage scan of cocaine dependence and major depressive episode in two populations. Neuropsychopharmacology 36, 2422–2430, 10.1038/npp.2011.122 (2011).21849985PMC3194068 | — | — | — |
| ZeigerJ. S. et al. The neuronal nicotinic receptor subunit genes (CHRNA6 and CHRNB3) are associated with subjective responses to tobacco. Hum Mol Genet 17, 724–734, 10.1093/hmg/ddm344 (2008).18055561 | — | — | — |
| ZhangH. et al. Pro-opiomelanocortin gene variation related to alcohol or drug dependence: evidence and replications across family- and population-based studies. Biol Psychiatry 66, 128–136, 10.1016/j.biopsych.2008.12.021 (2009).19217079PMC2896237 | — | — | — |
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External
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|---|---|---|---|---|
| Investigating CHRNA5, CHRNA3, and CHRNB4 variants in the genetic landscape of substance use disorder in Jordan. | Al-Eitan L et al. | — | 2024 | → |
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| The phenomics and genetics of addictive and affective comorbidity in opioid use disorder. | Freda PJ et al. | — | 2021 | → |
| Tobacco Smoking: Risk to Develop Addiction, Chronic Obstructive Pulmonary Disease, and Lung Cancer. | Santoro A et al. | — | 2019 | → |
| Effects of repeated long-term psychosocial stress and acute cannabinoid exposure on mouse corticostriatal circuitries: Implications for neuropsychiatric disorders. | Tomas-Roig J et al. | — | 2018 | → |
| Environmental, genetic and epigenetic contributions to cocaine addiction. | Pierce RC et al. | — | 2018 | → |
| Symptoms of anhedonia, not depression, predict the outcome of treatment of cocaine dependence. | Crits-Christoph P et al. | — | 2018 | → |
| Drug-seeking motivation level in male rats determines offspring susceptibility or resistance to cocaine-seeking behaviour. | Le Q et al. | — | 2017 | → |
| Evidence for Association Between Low Frequency Variants in CHRNA6/CHRNB3 and Antisocial Drug Dependence. | Kamens HM et al. | — | 2016 | → |
| Nicotinic acetylcholine receptors: upregulation, age-related effects and associations with drug use. | Melroy-Greif WE et al. | — | 2016 | → |
| Positive Selection on Loci Associated with Drug and Alcohol Dependence. | Sadler B et al. | — | 2015 | → |