Novel genes identified in a high-density genome wide association study for nicotine dependence
Open accessAbstract
Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10(-4) (minimum P-value 1.53 x 10(-6)). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the beta3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.
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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.
“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 [90]
SNP rs578776 is strongly associated with nicotine dependence and has a low correlation with rs16969968 (r2 = 0.18), indicating that it represents a statistically independent signal.
“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 [90]
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- Authors
- Bierut, L. J., Madden, P. A. F., Breslau, N., Johnson, E. O., Hatsukami, D., Pomerleau, O. F., Swan, G. E., Rutter, J., Bertelsen, S., Fox, L., Fugman, D., Goate, A. M., Hinrichs, A. L., Konvicka, K., Martin, N. G., Montgomery, G. W., Saccone, N. L., Saccone, S. F., Wang, J. C., Chase, G. A., Rice, J. P., & Ballinger, D. G.
- Affiliations
- Washington University in St. Louis (US)
- Michigan State University (US)
- RTI International (US)
- University of Minnesota (US)
- University of Michigan (US)
- SRI International (US)
- National Institutes of Health (US)
- Rutgers, The State University of New Jersey (US)
- Perlegen (United States) (US)
- QIMR Berghofer Medical Research Institute (AU)
- Pennsylvania State University (US)
- Corresponding author
- Bierut, Laura Jean
- ORCID
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-12-07
- Volume
- 16
- Issue
- 1
- Pages
- 24-35
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- PMC
- PMC2278047
- OpenAlex
- W2112271873
- Cited by
- 622
- References
- 44
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 4 · 2023: 11 · 2022: 19 · 2021: 19 · 2020: 40 · 2019: 19 · 2018: 25 · 2017: 25 · 2016: 30 · 2015: 37 · 2014: 37 · 2013: 38 · 2012: 41
- FWCI
- 27.71
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Physiology › Smoking Behavior and Cessation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- nicotine dependence, tobacco use, genetic susceptibility, single nucleotide polymorphisms, genome-wide association study, NRXN1, CHRNA3, candidate genes, smoking
- MeSH terms
- Female, Gene Frequency, Genotype, Humans, Male, Smoking, Tobacco Use Disorder, Genome, Human, Case-Control Studies, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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