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1.  Distinct Loci in the CHRNA5/CHRNA3/CHRNB4 Gene Cluster Are Associated With Onset of Regular Smoking 
Stephens, Sarah H. | Hartz, Sarah M. | Hoft, Nicole R. | Saccone, Nancy L. | Corley, Robin C. | Hewitt, John K. | Hopfer, Christian J. | Breslau, Naomi | Coon, Hilary | Chen, Xiangning | Ducci, Francesca | Dueker, Nicole | Franceschini, Nora | Frank, Josef | Han, Younghun | Hansel, Nadia N. | Jiang, Chenhui | Korhonen, Tellervo | Lind, Penelope A. | Liu, Jason | Lyytikäinen, Leo-Pekka | Michel, Martha | Shaffer, John R. | Short, Susan E. | Sun, Juzhong | Teumer, Alexander | Thompson, John R. | Vogelzangs, Nicole | Vink, Jacqueline M. | Wenzlaff, Angela | Wheeler, William | Yang, Bao-Zhu | Aggen, Steven H. | Balmforth, Anthony J. | Baumeister, Sebastian E. | Beaty, Terri H. | Benjamin, Daniel J. | Bergen, Andrew W. | Broms, Ulla | Cesarini, David | Chatterjee, Nilanjan | Chen, Jingchun | Cheng, Yu-Ching | Cichon, Sven | Couper, David | Cucca, Francesco | Dick, Danielle | Foroud, Tatiana | Furberg, Helena | Giegling, Ina | Gillespie, Nathan A. | Gu, Fangyi | Hall, Alistair S. | Hällfors, Jenni | Han, Shizhong | Hartmann, Annette M. | Heikkilä, Kauko | Hickie, Ian B. | Hottenga, Jouke Jan | Jousilahti, Pekka | Kaakinen, Marika | Kähönen, Mika | Koellinger, Philipp D. | Kittner, Stephen | Konte, Bettina | Landi, Maria-Teresa | Laatikainen, Tiina | Leppert, Mark | Levy, Steven M. | Mathias, Rasika A. | McNeil, Daniel W. | Medland, Sarah E. | Montgomery, Grant W. | Murray, Tanda | Nauck, Matthias | North, Kari E. | Paré, Peter D. | Pergadia, Michele | Ruczinski, Ingo | Salomaa, Veikko | Viikari, Jorma | Willemsen, Gonneke | Barnes, Kathleen C. | Boerwinkle, Eric | Boomsma, Dorret I. | Caporaso, Neil | Edenberg, Howard J. | Francks, Clyde | Gelernter, Joel | Grabe, Hans Jörgen | Hops, Hyman | Jarvelin, Marjo-Riitta | Johannesson, Magnus | Kendler, Kenneth S. | Lehtimäki, Terho | Magnusson, Patrik K.E. | Marazita, Mary L. | Marchini, Jonathan | Mitchell, Braxton D. | Nöthen, Markus M. | Penninx, Brenda W. | Raitakari, Olli | Rietschel, Marcella | Rujescu, Dan | Samani, Nilesh J. | Schwartz, Ann G. | Shete, Sanjay | Spitz, Margaret | Swan, Gary E. | Völzke, Henry | Veijola, Juha | Wei, Qingyi | Amos, Chris | Cannon, Dale S. | Grucza, Richard | Hatsukami, Dorothy | Heath, Andrew | Johnson, Eric O. | Kaprio, Jaakko | Madden, Pamela | Martin, Nicholas G. | Stevens, Victoria L. | Weiss, Robert B. | Kraft, Peter | Bierut, Laura J. | Ehringer, Marissa A.
Genetic epidemiology  2013;37(8):846-859.
Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.
doi:10.1002/gepi.21760
PMCID: PMC3947535  PMID: 24186853
CHRNA5; CHRNA3; CHRNB4; meta-analysis; nicotine; smoke
2.  A Partially Linear Tree-based Regression Model for Multivariate Outcomes 
Biometrics  2009;66(1):89-96.
Summary
In the genetic study of complex traits, especially behavior related ones, such as smoking and alcoholism, usually several phenotypic measurements are obtained for the description of the complex trait, but no single measurement can quantify fully the complicated characteristics of the symptom because of our lack of understanding of the underlying etiology. If those phenotypes share a common genetic mechanism, rather than studying each individual phenotype separately, it is more advantageous to analyze them jointly as a multivariate trait in order to enhance the power to identify associated genes. We propose a multilocus association test for the study of multivariate traits. The test is derived from a partially linear tree-based regression model for multiple outcomes. This novel tree-based model provides a formal statistical testing framework for the evaluation of the association between a multivariate outcome and a set of candidate predictors, such as markers within a gene or pathway, while accommodating adjustment for other covariates. Through simulation studies we show that the proposed method has an acceptable type I error rate and improved power over the univariate outcome analysis, which studies each component of the complex trait separately with multiple-comparison adjustment. A candidate gene association study of multiple smoking-related phenotypes is used to demonstrate the application and advantages of this new method. The proposed method is general enough to be used for the assessment of the joint effect of a set of multiple risk factors on a multivariate outcome in other biomedical research settings.
doi:10.1111/j.1541-0420.2009.01235.x
PMCID: PMC2875329  PMID: 19432770
Generalized estimating equation; Genetic association study; Model selection; Multiple-comparison adjustment; Tree-based model
3.  Pathway analysis by adaptive combination of P-values 
Genetic epidemiology  2009;33(8):700-709.
It is increasingly recognized that pathway analyses—a joint test of association between the outcome and a group of single nucleotide polymorphisms (SNPs) within a biological pathway—could potentially complement single-SNP analysis and provide additional insights for the genetic architecture of complex diseases. Building upon existing P-value combining methods, we propose a class of highly flexible pathway analysis approaches based on an adaptive rank truncated product (ARTP) statistic that can effectively combine evidence of associations over different SNPs and genes within a pathway. The statistical significance of the pathway-level test-statistics is evaluated using a highly efficient permutation algorithm that remains computationally feasible irrespective of the size of the pathway and complexity of the underlying test-statistics for summarizing SNP- and gene-level associations. We demonstrate through simulation studies that a gene-based analysis, that treats the underlying genes, as opposed to the underlying SNPs, as the basic units for hypothesis testing, is a very robust and powerful approach to pathway-based association testing. We also illustrate the advantage of the proposed methods using a study of the association between the nicotinic receptor pathway and cigarette smoking behaviors.
doi:10.1002/gepi.20422
PMCID: PMC2790032  PMID: 19333968
Pathway analysis; genetic association study; permutation procedure
4.  Increased Genetic Vulnerability to Smoking at CHRNA5 in Early-Onset Smokers 
Hartz, Sarah M. | Short, Susan E. | Saccone, Nancy L. | Culverhouse, Robert | Chen, LiShiun | Schwantes-An, Tae-Hwi | Coon, Hilary | Han, Younghun | Stephens, Sarah H. | Sun, Juzhong | Chen, Xiangning | Ducci, Francesca | Dueker, Nicole | Franceschini, Nora | Frank, Josef | Geller, Frank | Guđbjartsson, Daniel | Hansel, Nadia N. | Jiang, Chenhui | Keskitalo-Vuokko, Kaisu | Liu, Zhen | Lyytikäinen, Leo-Pekka | Michel, Martha | Rawal, Rajesh | Hum, Sc | Rosenberger, Albert | Scheet, Paul | Shaffer, John R. | Teumer, Alexander | Thompson, John R. | Vink, Jacqueline M. | Vogelzangs, Nicole | Wenzlaff, Angela S. | Wheeler, William | Xiao, Xiangjun | Yang, Bao-Zhu | Aggen, Steven H. | Balmforth, Anthony J. | Baumeister, Sebastian E. | Beaty, Terri | Bennett, Siiri | Bergen, Andrew W. | Boyd, Heather A. | Broms, Ulla | Campbell, Harry | Chatterjee, Nilanjan | Chen, Jingchun | Cheng, Yu-Ching | Cichon, Sven | Couper, David | Cucca, Francesco | Dick, Danielle M. | Foroud, Tatiana | Furberg, Helena | Giegling, Ina | Gu, Fangyi | Hall, Alistair S. | Hällfors, Jenni | Han, Shizhong | Hartmann, Annette M. | Hayward, Caroline | Heikkilä, Kauko | Lic, Phil | Hewitt, John K. | Hottenga, Jouke Jan | Jensen, Majken K. | Jousilahti, Pekka | Kaakinen, Marika | Kittner, Steven J. | Konte, Bettina | Korhonen, Tellervo | Landi, Maria-Teresa | Laatikainen, Tiina | Leppert, Mark | Levy, Steven M. | Mathias, Rasika A. | McNeil, Daniel W. | Medland, Sarah E. | Montgomery, Grant W. | Muley, Thomas | Murray, Tanda | Nauck, Matthias | North, Kari | Pergadia, Michele | Polasek, Ozren | Ramos, Erin M. | Ripatti, Samuli | Risch, Angela | Ruczinski, Ingo | Rudan, Igor | Salomaa, Veikko | Schlessinger, David | Styrkársdóttir, Unnur | Terracciano, Antonio | Uda, Manuela | Willemsen, Gonneke | Wu, Xifeng | Abecasis, Goncalo | Barnes, Kathleen | Bickeböller, Heike | Boerwinkle, Eric | Boomsma, Dorret I. | Caporaso, Neil | Duan, Jubao | Edenberg, Howard J. | Francks, Clyde | Gejman, Pablo V. | Gelernter, Joel | Grabe, Hans Jörgen | Hops, Hyman | Jarvelin, Marjo-Riitta | Viikari, Jorma | Kähönen, Mika | Kendler, Kenneth S. | Lehtimäki, Terho | Levinson, Douglas F. | Marazita, Mary L. | Marchini, Jonathan | Melbye, Mads | Mitchell, Braxton D. | Murray, Jeffrey C. | Nöthen, Markus M. | Penninx, Brenda W. | Raitakari, Olli | Rietschel, Marcella | Rujescu, Dan | Samani, Nilesh J. | Sanders, Alan R. | Schwartz, Ann G. | Shete, Sanjay | Shi, Jianxin | Spitz, Margaret | Stefansson, Kari | Swan, Gary E. | Thorgeirsson, Thorgeir | Völzke, Henry | Wei, Qingyi | Wichmann, H.-Erich | Amos, Christopher I. | Breslau, Naomi | Cannon, Dale S. | Ehringer, Marissa | Grucza, Richard | Hatsukami, Dorothy | Heath, Andrew | Johnson, Eric O. | Kaprio, Jaakko | Madden, Pamela | Martin, Nicholas G. | Stevens, Victoria L. | Stitzel, Jerry A. | Weiss, Robert B. | Kraft, Peter | Bierut, Laura J.
Archives of general psychiatry  2012;69(8):854-860.
Context
Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968.
Objective
To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking.
Data Sources
Primary data.
Study Selection
Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy.
Data Extraction
Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum.
Data Synthesis
Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR]=1.45; 95% CI, 1.36–1.55; n=13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21–1.33, n = 19 505) (P = .01).
Conclusion
These results highlight an increased genetic vulnerability to smoking in early-onset smokers.
doi:10.1001/archgenpsychiatry.2012.124
PMCID: PMC3482121  PMID: 22868939
5.  Genome-Wide and Candidate Gene Association Study of Cigarette Smoking Behaviors 
PLoS ONE  2009;4(2):e4653.
The contribution of common genetic variation to one or more established smoking behaviors was investigated in a joint analysis of two genome wide association studies (GWAS) performed as part of the Cancer Genetic Markers of Susceptibility (CGEMS) project in 2,329 men from the Prostate, Lung, Colon and Ovarian (PLCO) Trial, and 2,282 women from the Nurses' Health Study (NHS). We analyzed seven measures of smoking behavior, four continuous (cigarettes per day [CPD], age at initiation of smoking, duration of smoking, and pack years), and three binary (ever versus never smoking, ≤10 versus >10 cigarettes per day [CPDBI], and current versus former smoking). Association testing for each single nucleotide polymorphism (SNP) was conducted by study and adjusted for age, cohabitation/marital status, education, site, and principal components of population substructure. None of the SNPs achieved genome-wide significance (p<10−7) in any combined analysis pooling evidence for association across the two studies; we observed between two and seven SNPs with p<10−5 for each of the seven measures. In the chr15q25.1 region spanning the nicotinic receptors CHRNA3 and CHRNA5, we identified multiple SNPs associated with CPD (p<10−3), including rs1051730, which has been associated with nicotine dependence, smoking intensity and lung cancer risk. In parallel, we selected 11,199 SNPs drawn from 359 a priori candidate genes and performed individual-gene and gene-group analyses. After adjusting for multiple tests conducted within each gene, we identified between two and five genes associated with each measure of smoking behavior. Besides CHRNA3 and CHRNA5, MAOA was associated with CPDBI (gene-level p<5.4×10−5), our analysis provides independent replication of the association between the chr15q25.1 region and smoking intensity and data for multiple other loci associated with smoking behavior that merit further follow-up.
doi:10.1371/journal.pone.0004653
PMCID: PMC2644817  PMID: 19247474

Results 1-5 (5)