Browsing by Author "Rice, John"

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    A meta-analysis of two genome-wide association studies to identify novel loci for maximum number of alcoholic drinks
    (Springer, 2013) Kapoor, Manav; Wang, Jen-Chyong; Wetherill, Leah; Le, Nhung; Bertelsen, Sarah; Hinrichs, Anthony L.; Budde, John; Agrawal, Arpana; Bucholz, Kathleen; Dick, Danielle; Harari, Oscar; Hesselbrock, Victor; Kramer, John; Nurnberger, John I., Jr.; Rice, John; Saccone, Nancy; Schuckit, Marc; Tischfield, Jay; Porjesz, Bernice; Edenberg, Howard J.; Bierut, Laura; Foroud, Tatiana; Goate, Alison; Medical and Molecular Genetics, School of Medicine
    Maximum number of alcoholic drinks consumed in a 24-h period (maxdrinks) is a heritable (>50 %) trait and is strongly correlated with vulnerability to excessive alcohol consumption and subsequent alcohol dependence (AD). Several genome-wide association studies (GWAS) have studied alcohol dependence, but few have concentrated on excessive alcohol consumption. We performed two GWAS using maxdrinks as an excessive alcohol consumption phenotype: one in 118 extended families (N = 2,322) selected from the Collaborative Study on the Genetics of Alcoholism (COGA), and the other in a case-control sample (N = 2,593) derived from the Study of Addiction: Genes and Environment (SAGE). The strongest association in the COGA families was detected with rs9523562 (p = 2.1 × 10(-6)) located in an intergenic region on chromosome 13q31.1; the strongest association in the SAGE dataset was with rs67666182 (p = 7.1 × 10(-7)), located in an intergenic region on chromosome 8. We also performed a meta-analysis with these two GWAS and demonstrated evidence of association in both datasets for the LMO1 (p = 7.2 × 10(-7)) and PLCL1 genes (p = 4.1 × 10(-6)) with maxdrinks. A variant in AUTS2 and variants in INADL, C15orf32 and HIP1 that were associated with measures of alcohol consumption in a meta-analysis of GWAS studies and a GWAS of alcohol consumption factor score also showed nominal association in the current meta-analysis. The present study has identified several loci that warrant further examination in independent samples. Among the top SNPs in each of the dataset (p ≤ 10(-4)) far more showed the same direction of effect in the other dataset than would be expected by chance (p = 2 × 10(-3), 3 × 10(-6)), suggesting that there are true signals among these top SNPs, even though no SNP reached genome-wide levels of significance.
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    An ADH1B variant and peer drinking in progression to adolescent drinking milestones: Evidence of a gene-by-environment interaction
    (Wiley Online Library, 2014-10) Olfson, Emily; Edenberg, Howard J.; Nurnberger Jr., John; Agrawal, Arpana; Bucholz, Kathleen K.; Almasy, Laura A.; Chorlian, David; Dick, Danielle M.; Hesselbrock, Victor M.; Kramer, John R.; Kuperman, Samuel; Porjesz, Bernice; Schuckit, Marc A.; Tischfield, Jay A.; Wang, Jen-Chyong; Wetherill, Leah; Foroud, Tatiana M.; Rice, John; Goate, Alison; Bierut, Laura J.; Department of Biochemistry & Molecular Biology, IU School of Medicine
    BACKGROUND: Adolescent drinking is an important public health concern, one that is influenced by both genetic and environmental factors. The functional variant rs1229984 in alcohol dehydrogenase 1B (ADH1B) has been associated at a genome-wide level with alcohol use disorders in diverse adult populations. However, few data are available regarding whether this variant influences early drinking behaviors and whether social context moderates this effect. This study examines the interplay between rs1229984 and peer drinking in the development of adolescent drinking milestones. METHODS: One thousand five hundred and fifty European and African American individuals who had a full drink of alcohol before age 18 were selected from a longitudinal study of youth as part of the Collaborative Study on the Genetics of Alcoholism (COGA). Cox proportional hazards regression, with G × E product terms in the final models, was used to study 2 primary outcomes during adolescence: age of first intoxication and age of first DSM-5 alcohol use disorder symptom. RESULTS: The minor A allele of rs1229984 was associated with a protective effect for first intoxication (HR = 0.56, 95% CI 0.41 to 0.76) and first DSM-5 symptom (HR = 0.45, 95% CI 0.26 to 0.77) in the final models. Reporting that most or all best friends drink was associated with a hazardous effect for first intoxication (HR = 1.81, 95% CI 1.62 to 2.01) and first DSM-5 symptom (HR = 2.17, 95% 1.88 to 2.50) in the final models. Furthermore, there was a significant G × E interaction for first intoxication (p = 0.002) and first DSM-5 symptom (p = 0.01). Among individuals reporting none or few best friends drinking, the ADH1B variant had a protective effect for adolescent drinking milestones, but for those reporting most or all best friends drinking, this effect was greatly reduced. CONCLUSIONS: Our results suggest that the risk factor of best friends drinking attenuates the protective effect of a well-established ADH1B variant for 2 adolescent drinking behaviors. These findings illustrate the interplay between genetic and environmental factors in the development of drinking milestones during adolescence.
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    Alcohol Use Disorder Polygenic Score Compared With Family History and ADH1B
    (American Medical Association, 2024-12-02) Lai, Dongbing; Zhang, Michael; Abreu, Marco; Schwantes-An, Tae-Hwi; Chan, Grace; Dick, Danielle M.; Kamarajan, Chella; Kuang, Weipeng; Nurnberger, John I.; Plawecki, Martin H.; Rice, John; Schuckit, Marc; Porjesz, Bernice; Liu, Yunlong; Foroud, Tatiana; Medical and Molecular Genetics, School of Medicine
    Importance: Identification of individuals at high risk of alcohol use disorder (AUD) and subsequent application of prevention and intervention programs has been reported to decrease the incidence of AUD. The polygenic score (PGS), which measures an individual's genetic liability to a disease, can potentially be used to evaluate AUD risk. Objective: To assess the estimability and generalizability of the PGS, compared with family history and ADH1B, in evaluating the risk of AUD among populations of European ancestry. Design, setting, and participants: This genetic association study was conducted between October 1, 2023, and May 21, 2024. A 2-stage design was used. First, the pruning and thresholding method was used to calculate PGSs in the screening stage. Second, the estimability and generalizability of the best PGS was determined using 2 independent samples in the testing stage. Three cohorts ascertained to study AUD were used in the screening stage: the Collaborative Study on the Genetics of Alcoholism (COGA), the Study of Addiction: Genetics and Environment (SAGE), and the Australian Twin-Family Study of Alcohol Use Disorder (OZALC). The All of Us Research Program (AOU), which comprises participants with diverse backgrounds and conditions, and the Indiana Biobank (IB), consisting of Indiana University Health system patients, were used to test the best PGS. For the COGA, SAGE, and OZALC cohorts, cases with AUD were determined using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) or Fifth Edition (DSM-5) criteria; controls did not meet any criteria or did not have any other substance use disorders. For the AOU and IB cohorts, cases with AUD were identified using International Classification of Diseases, Ninth Revision (ICD-9) or International Classification of Diseases, Tenth Revision (ICD-10) codes; controls were aged 21 years or older and did not have AUD. Exposure: The PGS was calculated using single-nucleotide variants with concordant effects in 3 large-scale genome-wide association studies of AUD-related phenotypes. Main outcomes and measures: The main outcome was AUD determined with DSM-IV or DSM-5 criteria and ICD-9 or ICD-10 codes. Generalized linear mixed models and logistic regression models were used to analyze related and unrelated samples, respectively. Results: The COGA, SAGE, and OZALC cohorts included a total of 8799 samples (6323 cases and 2476 controls; 50.6% were men). The AOU cohort had a total of 116 064 samples (5660 cases and 110 404 controls; 60.4% were women). The IB cohort had 6373 samples (936 cases and 5437 controls; 54.9% were women). The 5% of samples with the highest PGS in the AOU and IB cohorts were approximately 2 times more likely to develop AUD (odds ratio [OR], 1.96 [95% CI, 1.78-2.16]; P = 4.10 × 10-43; and OR, 2.07 [95% CI, 1.59-2.71]; P = 9.15 × 10-8, respectively) compared with the remaining 95% of samples; these ORs were comparable to family history of AUD. For the 5% of samples with the lowest PGS in the AOU and IB cohorts, the risk of AUD development was approximately half (OR, 0.53 [95% CI, 0.45-0.62]; P = 6.98 × 10-15; and OR, 0.57 [95% CI, 0.39-0.84]; P = 4.88 × 10-3) compared with the remaining 95% of samples; these ORs were comparable to the protective effect of ADH1B. PGS had similar estimabilities in male and female individuals. Conclusions and relevance: In this study of AUD risk among populations of European ancestry, PGSs were calculated using concordant single-nucleotide variants and the best PGS was tested in targeted datasets. The findings suggest that the PGS may potentially be used to evaluate AUD risk. More datasets with similar AUD prevalence as in general populations are needed to further test the generalizability of PGS.
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    Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics
    (SpringerOpen, 2018-11-11) Breuer, René; Mattheisen, Manuel; Frank, Josef; Krumm, Bertram; Treutlein, Jens; Kassem, Layla; Strohmaier, Jana; Herms, Stefan; Mühleisen, Thomas W.; Degenhardt, Franziska; Cichon, Sven; Nöthen, Markus M.; Karypis, George; Kelsoe, John; Greenwood, Tiffany; Nievergelt, Caroline; Shilling, Paul; Shekhtman, Tatyana; Edenberg, Howard; Craig, David; Szelinger, Szabolcs; Nurnberger, John; Gershon, Elliot; Alliey‑Rodriguez, Ney; Zandi, Peter; Goes, Fernando; Schork, Nicholas; Smith, Erin; Koller, Daniel; Zhang, Peng; Badner, Judith; Berrettini, Wade; Bloss, Cinnamon; Byerley, William; Coryell, William; Foroud, Tatiana; Guo, Yirin; Hipolito, Maria; Keating, Brendan; Lawson, William; Liu, Chunyu; Mahon, Pamela; McInnis, Melvin; Murray, Sarah; Nwulia, Evaristus; Potash, James; Rice, John; Scheftner, William; Zöllner, Sebastian; McMahon, Francis J.; Rietschel, Marcella; Schulze, Thomas G.; Biochemistry and Molecular Biology, School of Medicine
    BACKGROUND: Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype-phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted. RESULTS: Two of these rules-one associated with eating disorder and the other with anxiety-remained significant in an independent dataset after robust correction for multiple testing. Both showed considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively) and support previously reported molecular biological findings. CONCLUSION: Our approach detected novel specific genotype-phenotype relationships in BD that were missed by standard analyses like GWAS. While we developed and applied our method within the context of BD gene discovery, it may facilitate identifying highly specific genotype-phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts.
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    Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder
    (Elsevier, 2019-01-01) Budde, Monika; Friedrichs, Stefanie; Alliey-Rodriguez, Ney; Ament, Seth; Badner, Judith A.; Berrettini, Wade H.; Bloss, Cinnamon S.; Byerley, William; Cichon, Sven; Comes, Ashley L.; Coryell, William; Craig, David W.; Degenhardt, Franziska; Edenberg, Howard J.; Foroud, Tatiana; Forstner, Andreas J.; Frank, Josef; Gershon, Elliot S.; Goes, Fernando S.; Greenwood, Tiffany A.; Guo, Yiran; Hipolito, Maria; Hood, Leroy; Keating, Brendan J.; Koller, Daniel L.; Lawson, William B.; Liu, Chunyu; Mahon, Pamela B.; McInnis, Melvin G.; McMahon, Francis J.; Meier, Sandra M.; Mühleisen, Thomas W.; Murray, Sarah S.; Nievergelt, Caroline M.; Nurnberger, John I.; Nwulia, Evaristus A.; Potash, James B.; Quarless, Danjuma; Rice, John; Roach, Jared C.; Scheftner, William A.; Schork, Nicholas J.; Shekhtman, Tatyana; Shilling, Paul D.; Smith, Erin N.; Streit, Fabian; Strohmaier, Jana; Szelinger, Szabolcs; Treutlein, Jens; Witt, Stephanie H.; Zandi, Peter P.; Zhang, Peng; Zöllner, Sebastian; Bickeböller, Heike; Falkai, Peter G.; Kelsoe, John R.; Nöthen, Markus M.; Rietschel, Marcella; Schulze, Thomas G.; Malzahn, Dörthe; Biochemistry and Molecular Biology, School of Medicine
    Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 – 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 – rs2086256 – rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.
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    Exome chip meta-analysis fine maps causal variants and elucidates the genetic architecture of rare coding variants in smoking and alcohol use
    (Elsevier, 2018) Brazel, David M.; Jiang, Yu; Hughey, Jordan M.; Turcot, Valérie; Zhan, Xiaowei; Gong, Jian; Batini, Chiara; Weissenkampen, J. Dylan; Liu, MengZhen; Barnes, Daniel R.; Bertelsen, Sarah; Chou, Yi-Ling; Erzurumluoglu, A. Mesut; Faul, Jessica D.; Haessler, Jeff; Hammerschlag, Anke R.; Hsu, Chris; Kapoor, Manav; Lai, Dongbing; Le, Nhung; de Leeuw, Christiaan A.; Loukola, Anu; Mangino, Massimo; Melbourne, Carl A.; Pistis, Giorgio; Qaiser, Beenish; Rohde, Rebecca; Shao, Yaming; Stringham, Heather; Wetherill, Leah; Zhao, Wei; Agrawal, Arpana; Bierut, Laura; Chen, Chu; Eaton, Charles B.; Goate, Alison; Haiman, Christopher; Heath, Andrew; Iacono, William G.; Martin, Nicholas G.; Polderman, Tinca J.; Reiner, Alex; Rice, John; Schlessinger, David; Scholte, H. Steven; Smith, Jennifer A.; Tardif, Jean-Claude; Tindle, Hilary A.; van der Leij, Andries R.; Boehnke, Michael; Chang-Claude, Jenny; Cucca, Francesco; David, Sean P.; Foroud, Tatiana; Howson, Joanna M. M.; Kardia, Sharon L. R.; Kooperberg, Charles; Laakso, Markku; Lettre, Guillaume; Madden, Pamela; McGue, Matt; North, Kari; Posthuma, Danielle; Spector, Timothy; Stram, Daniel; Tobin, Martin D.; Weir, David R.; Kaprio, Jaakko; Abecasis, Gonçalo R.; Liu, Dajiang J.; Vrieze, Scott; Medical and Molecular Genetics, School of Medicine
    Background Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences, and contribute to disease risk. Methods We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss of function coding variants. We performed a novel fine mapping analysis to winnow the number of putative causal variants within associated loci. Results Meta-analytic sample sizes ranged from 152,348-433,216, depending on the phenotype. Rare coding variation explained 1.1-2.2% of phenotypic variance, reflecting 11%-18% of the total SNP heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between 3 and 10 variants for 65 loci. 20 loci contained rare coding variants in the 95% credible intervals. Conclusions Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine mapping GWAS loci identifies specific variants contributing to the biological etiology of substance use behavior.
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    Genetic and neurophysiological correlates of the age of onset of alcohol use disorders in adolescents and young adults
    (Springer, 2013) Chorlian, David B.; Rangaswamy, Madhavi; Manz, Niklas; Wang, Jen-Chyong; Dick, Danielle; Almasy, Laura; Bauer, Lance; Bucholz, Kathleen; Foroud, Tatiana; Hesselbrock, Victor; Kang, Sun J.; Kramer, John; Kuperman, Sam; Nurnberger, John, Jr.; Rice, John; Schuckit, Marc; Tischfield, Jay; Edenberg, Howard J.; Goate, Alison; Bierut, Laura; Porjesz, Bernice; Medical and Molecular Genetics, School of Medicine
    Discrete time survival analysis was used to assess the age-specific association of event-related oscillations (EROs) and CHRM2 gene variants on the onset of regular alcohol use and alcohol dependence. The subjects were 2,938 adolescents and young adults ages 12-25. Results showed that the CHRM2 gene variants and ERO risk factors had hazards which varied considerably with age. The bulk of the significant age-specific associations occurred in those whose age of onset was under 16. These associations were concentrated in those subjects who at some time took an illicit drug. These results are consistent with studies which associate greater rates of alcohol dependence among those who begin drinking at an early age. The age specificity of the genetic and neurophysiological factors is consistent with recent studies of adolescent brain development, which locate an interval of heightened vulnerability to substance use disorders in the early to mid teens.
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    Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci
    (Springer Nature, 2019-01-07) Erzurumluoglu, A. Mesut; Liu, Mengzhen; Jackson, Victoria E.; Barnes, Daniel R.; Datta, Gargi; Melbourne, Carl A.; Young, Robin; Batini, Chiara; Surendran, Praveen; Jiang, Tao; Adnan, Sheikh Daud; Afaq, Saima; Agrawal, Arpana; Altmaier, Elisabeth; Antoniou, Antonis C.; Asselbergs, Folkert W.; Baumbach, Clemens; Bierut, Laura; Bertelsen, Sarah; Boehnke, Michael; Bots, Michiel L.; Brazel, David M.; Chambers, John C.; Chang-Claude, Jenny; Chen, Chu; Corley, Janie; Chou, Yi-Ling; David, Sean P.; Boer, Rudolf A. de; Leeuw, Christiaan A. de; Dennis, Joe G.; Dominiczak, Anna F.; Dunning, Alison M.; Easton, Douglas F.; Eaton, Charles; Elliott, Paul; Evangelou, Evangelos; Faul, Jessica D.; Foroud, Tatiana; Goate, Alison; Gong, Jian; Grabe, Hans J.; Haessler, Jeff; Haiman, Christopher; Hallmans, Göran; Hammerschlag, Anke R.; Harris, Sarah E.; Hattersley, Andrew; Heath, Andrew; Hsu, Chris; Iacono, William G.; Kanoni, Stavroula; Kapoor, Manav; Kaprio, Jaakko; Kardia, Sharon L.; Karpe, Fredrik; Kontto, Jukka; Kooner, Jaspal S.; Kooperberg, Charles; Kuulasmaa, Kari; Laakso, Markku; Lai, Dongbing; Langenberg, Claudia; Le, Nhung; Lettre, Guillaume; Loukola, Anu; Luan, Jian’an; Madden, Pamela A. F.; Mangino, Massimo; Marioni, Riccardo E.; Marouli, Eirini; Marten, Jonathan; Martin, Nicholas G.; McGue, Matt; Michailidou, Kyriaki; Mihailov, Evelin; Moayyeri, Alireza; Moitry, Marie; Müller-Nurasyid, Martina; Naheed, Aliya; Nauck, Matthias; Neville, Matthew J.; Nielsen, Sune Fallgaard; North, Kari; Perola, Markus; Pharoah, Paul D. P.; Pistis, Giorgio; Polderman, Tinca J.; Posthuma, Danielle; Poulter, Neil; Qaiser, Beenish; Rasheed, Asif; Reiner, Alex; Renström, Frida; Rice, John; Rohde, Rebecca; Rolandsson, Olov; Samani, Nilesh J.; Samuel, Maria; Schlessinger, David; Scholte, Steven H.; Scott, Robert A.; Sever, Peter; Shao, Yaming; Shrine, Nick; Smith, Jennifer A.; Starr, John M.; Stirrups, Kathleen; Stram, Danielle; Stringham, Heather M.; Tachmazidou, Ioanna; Tardif, Jean-Claude; Thompson, Deborah J.; Tindle, Hilary A.; Tragante, Vinicius; Trompet, Stella; Turcot, Valerie; Tyrrell, Jessica; Vaartjes, Ilonca; Leij, Andries R. van der; Meer, Peter van der; Varga, Tibor V.; Verweij, Niek; Völzke, Henry; Wareham, Nicholas J.; Warren, Helen R.; Weir, David R.; Weiss, Stefan; Wetherill, Leah; Yaghootkar, Hanieh; Yavas, Ersin; Jiang, Yu; Chen, Fang; Zhan, Xiaowei; Zhang, Weihua; Zhao, Wei; Zhao, Wei; Zhou, Kaixin; Amouyel, Philippe; Blankenberg, Stefan; Caulfield, Mark J.; Chowdhury, Rajiv; Cucca, Francesco; Deary, Ian J.; Deloukas, Panos; Angelantonio, Emanuele Di; Ferrario, Marco; Ferrières, Jean; Franks, Paul W.; Frayling, Tim M.; Frossard, Philippe; Hall, Ian P.; Hayward, Caroline; Jansson, Jan-Håkan; Jukema, J. Wouter; Kee, Frank; Männistö, Satu; Metspalu, Andres; Munroe, Patricia B.; Nordestgaard, Børge Grønne; Palmer, Colin N. A.; Salomaa, Veikko; Sattar, Naveed; Spector, Timothy; Strachan, David Peter; Harst, Pim van der; Zeggini, Eleftheria; Saleheen, Danish; Butterworth, Adam S.; Wain, Louise V.; Abecasis, Goncalo R.; Danesh, John; Tobin, Martin D.; Vrieze, Scott; Liu, Dajiang J.; Howson, Joanna M. M.; Medical and Molecular Genetics, School of Medicine
    Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10−8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10−8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10−3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
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    Rare missense variants in CHRNB3 and CHRNA3 are associated with risk of alcohol and cocaine dependence
    (Oxford University Press, 2014-02-01) Haller, Gabe; Kapoor, Manav; Budde, John; Xuei, Xiaoling; Edenberg, Howard; Nurnberger, John; Kramer, John; Brooks, Andy; Tischfield, Jay; Almasy, Laura; Agrawal, Arpana; Bucholz, Kathleen; Rice, John; Saccone, Nancy; Bierut, Laura; Goate, Alison; Department of Biochemistry & Molecular Biology, IU School of Medicine
    Previous findings have demonstrated that variants in nicotinic receptor genes are associated with nicotine, alcohol and cocaine dependence. Because of the substantial comorbidity, it has often been unclear whether a variant is associated with multiple substances or whether the association is actually with a single substance. To investigate the possible contribution of rare variants to the development of substance dependencies other than nicotine dependence, specifically alcohol and cocaine dependence, we undertook pooled sequencing of the coding regions and flanking sequence of CHRNA5, CHRNA3, CHRNB4, CHRNA6 and CHRNB3 in 287 African American and 1028 European American individuals from the Collaborative Study of the Genetics of Alcoholism (COGA). All members of families for whom any individual was sequenced (2504 African Americans and 7318 European Americans) were then genotyped for all variants identified by sequencing. For each gene, we then tested for association using FamSKAT. For European Americans, we find increased DSM-IV cocaine dependence symptoms (FamSKAT P = 2 × 10−4) and increased DSM-IV alcohol dependence symptoms (FamSKAT P = 5 × 10−4) among carriers of missense variants in CHRNB3. Additionally, one variant (rs149775276