The DOI matches its Crossref record; 46 of the 48 references it cites were found in a registry or an index.
Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs
Open accessAbstract
Nicotine dependence is one of the world's leading causes of preventable death. To discover genetic variants that influence risk for nicotine dependence, we targeted over 300 candidate genes and analyzed 3713 single nucleotide polymorphisms (SNPs) in 1050 cases and 879 controls. The Fagerström test for nicotine dependence (FTND) was used to assess dependence, in which cases were required to have an FTND of 4 or more. The control criterion was strict: control subjects must have smoked at least 100 cigarettes in their lifetimes and had an FTND of 0 during the heaviest period of smoking. After correcting for multiple testing by controlling the false discovery rate, several cholinergic nicotinic receptor genes dominated the top signals. The strongest association was from an SNP representing CHRNB3, the beta3 nicotinic receptor subunit gene (P = 9.4 x 10(-5)). Biologically, the most compelling evidence for a risk variant came from a non-synonymous SNP in the alpha5 nicotinic receptor subunit gene CHRNA5 (P = 6.4 x 10(-4)). This SNP exhibited evidence of a recessive mode of inheritance, resulting in individuals having a 2-fold increase in risk of developing nicotine dependence once exposed to cigarette smoking. Other genes among the top signals were KCNJ6 and GABRA4. This study represents one of the most powerful and extensive studies of nicotine dependence to date and has found novel risk loci that require confirmation by replication studies.
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“It has been shown that allelic variation in the α5/α3/β4 nAChR subunit gene cluster located in chromosome region 15q25 significantly increases risk of tobacco addiction (Saccone et al. 2007;Berrettini et al. 2008;Lips et al. 2010).”
From Mechanisms of Nicotine Addiction (2021) · cites this paper as Saccone et al. 2007
In the citing paper
“The most compelling evidence for risk variants contributing to smoking behavior was in the CHRNA5/A3/B4 gene cluster, which encodes the α5, α3, and β4 subunits.”
From Nicotine is a selective pharmacological chaperone of acetylcholine receptor number and stoichiometry. Implications for drug discovery (2009) · cites this paper as [91]
In the citing paper
“The most thoroughly investigated and replicated finding to date is the association with rs16969968, in CHRNA5 (91).”
From Nicotine is a selective pharmacological chaperone of acetylcholine receptor number and stoichiometry. Implications for drug discovery (2009) · cites this paper as [91]
In the citing paper
“A second signal in the CHRNA5/A3/B4 cluster is tagged by SNP rs578776; it is strongly associated with nicotine dependence and has a low correlation with rs16969968 (r2 = 0.18), indicating that it represents a statistically independent signal (90,91).”
From Nicotine is a selective pharmacological chaperone of acetylcholine receptor number and stoichiometry. Implications for drug discovery (2009) · cites this paper as [91]
In the citing paper
“With regard to the latter factors, initiation of smoking behavior and transition to dependence (i.e. persistent smoking) has been found to show strong heritability (60). The reported heritability coefficients range from 30% to greater than 80% (a mean of approximately 60% for initiation and 70% for progression to dependence).”
From Tobacco addiction (2008) · cites this paper as [60]
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Inference of Population Structure Using Multilocus Genotype Data
Pritchard, J. K., Stephens, M., & Donnelly, P. (2000) · Genetics · doi:10.1093/genetics/155.2.945 · Cited by 33,871
Haploview: analysis and visualization of LD and haplotype maps
Barrett, J. C., Fry, B., Maller, J., & Daly, M. J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth457 · Cited by 14,563
The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire
HEATHERTON, T. F., KOZLOWSKI, L. T., FRECKER, R. C., & FAGERSTROM, K. (1991) · British Journal of Addiction · doi:10.1111/j.1360-0443.1991.tb01879.x · Cited by 10,738
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
A Direct Approach to False Discovery Rates
Storey, J. D. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00346 · Cited by 5,603
More powerful procedures for multiple significance testing
Hochberg, Y., & Benjamini, Y. (1990) · Statistics in Medicine · doi:10.1002/sim.4780090710 · Cited by 2,715
Carlson, C. S., Eberle, M. A., Rieder, M. J., Qian, Y., Kruglyak, L., & Nickerson, D. A. (2004) · The American Journal of Human Genetics · doi:10.1086/381000 · Cited by 1,587
Tanoue, L. T. (2007) · Yearbook of Medicine · doi:10.1016/s0084-3873(08)70176-7 · Cited by 1,413
Mackay, J. M., & Eriksen, M. P. (2002) · Medical Entomology and Zoology · Cited by 1,322
Research works printed but not linked: 1
- Tapper, 2006, Neuronal nicotinic acetylcholine receptors and nicotine dependence
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McPherson, R., Pertsemlidis, A., Kavaslar, N., Stewart, A., Roberts, R., Cox, D. R., Hinds, D. A., Pennacchio, L. A., Tybjaerg-Hansen, A., Folsom, A. R., et al. (2007) · Science · doi:10.1126/science.1142447 · Cited by 1,587
A variant associated with nicotine dependence, lung cancer and peripheral arterial disease
Thorgeirsson, T. E., Geller, F., Sulem, P., Rafnar, T., Wiste, A., Magnusson, K. P., Manolescu, A., Thorleifsson, G., Stefansson, H., Ingason, A., et al. (2008) · Nature · doi:10.1038/nature06846 · Cited by 1,523
Benowitz, N. L. (2010) · New England Journal of Medicine · doi:10.1056/nejmra0809890 · Cited by 1,508
Amos, C. I., Wu, X., Broderick, P., Gorlov, I. P., Gu, J., Eisen, T., Dong, Q., Zhang, Q., Gu, X., Vijayakrishnan, J., et al. (2008) · Nature Genetics · doi:10.1038/ng.109 · Cited by 1,310
Hung, R. J., McKay, J. D., Gaborieau, V., Boffetta, P., Hashibe, M., Zaridze, D., Mukeria, A., Szeszenia-Dabrowska, N., Lissowska, J., Rudnai, P., et al. (2008) · Nature · doi:10.1038/nature06885 · Cited by 1,275
Metadata
- Authors
- Saccone, S. F., Hinrichs, A. L., Saccone, N. L., Chase, G. A., Konvicka, K., Madden, P. A. F., Breslau, N., Johnson, E. O., Hatsukami, D., Pomerleau, O., Swan, G. E., Goate, A. M., Rutter, J., Bertelsen, S., Fox, L., Fugman, D., Martin, N. G., Montgomery, G. W., Wang, J. C., Ballinger, D. G., Rice, J. P., & Bierut, L. J.
- Affiliations
- Washington University in St. Louis (US)
- Pennsylvania State University (US)
- Perlegen (United States) (US)
- Michigan State University (US)
- RTI International (US)
- University of Minnesota (US)
- University of Michigan (US)
- SRI International (US)
- National Institute on Drug Abuse (US)
- Rutgers, The State University of New Jersey (US)
- QIMR Berghofer Medical Research Institute (AU)
- Corresponding author
- Saccone, Scott F.
- ORCID
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-11-29
- Volume
- 16
- Issue
- 1
- Pages
- 36-49
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- PMC
- PMC2270437
- OpenAlex
- W2118320202
- Cited by
- 850
- References
- 48
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 12 · 2023: 20 · 2022: 16 · 2021: 24 · 2020: 65 · 2019: 37 · 2018: 35 · 2017: 35 · 2016: 54 · 2015: 51 · 2014: 48 · 2013: 58 · 2012: 86
- FWCI
- 31.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Human Molecular Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institute on Drug Abuse (R56DA012854, DA12854, DA015129, N01DA07079, K01DA015129, R01DA012854)
- National Cancer Institute (CA89392, P01CA089392)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Smoking Behavior and Cessation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Nicotinic Acetylcholine Receptors Study
- Keywords
- nicotine dependence, CHRNA5, single nucleotide polymorphisms, genetic association, genetic susceptibility loci, recessive inheritance, KCNJ6, GABRA4, smoking, Fagerström Test for Nicotine Dependence
- MeSH terms
- Adult, Aged, Aged, 80 and over, Chromosomes, Human, Pair 8, Female, Genetic Markers, Genotype, Humans, Male, Middle Aged, Receptors, Nicotinic, Tobacco Use Disorder, Genetic Variation, Cluster Analysis, Case-Control Studies, Polymorphism, Single Nucleotide
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