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      Multiple Independent Loci at Chromosome 15q25.1 Affect Smoking Quantity: a Meta-Analysis and Comparison with Lung Cancer and COPD

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      1 , * , 2 , 3 , 1 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 5 , 23 , 21 , 14 , 5 , 20 , 24 , 18 , 25 , 26 , 26 , 27 , 27 , 28 , 29 , 24 , 30 , 31 , 32 , 33 , 20 , 1 , 3 , 20 , 34 , 11 , 19 , 20 , 35 , 36 , 37 , 10 , 14 , 18 , 38 , 39 , 19 , 10 , 21 , 12 , 24 , 30 , 5 , 6 , 25 , 40 , 35 , 28 , 20 , 7 , 41 , 42 , 37 , 43 , 9 , 22 , 11 , 20
      PLoS Genetics
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          Abstract

          Recently, genetic association findings for nicotine dependence, smoking behavior, and smoking-related diseases converged to implicate the chromosome 15q25.1 region, which includes the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit genes. In particular, association with the nonsynonymous CHRNA5 SNP rs16969968 and correlates has been replicated in several independent studies. Extensive genotyping of this region has suggested additional statistically distinct signals for nicotine dependence, tagged by rs578776 and rs588765. One goal of the Consortium for the Genetic Analysis of Smoking Phenotypes (CGASP) is to elucidate the associations among these markers and dichotomous smoking quantity (heavy versus light smoking), lung cancer, and chronic obstructive pulmonary disease (COPD). We performed a meta-analysis across 34 datasets of European-ancestry subjects, including 38,617 smokers who were assessed for cigarettes-per-day, 7,700 lung cancer cases and 5,914 lung-cancer-free controls (all smokers), and 2,614 COPD cases and 3,568 COPD-free controls (all smokers). We demonstrate statistically independent associations of rs16969968 and rs588765 with smoking (mutually adjusted p-values<10 −35 and <10 −8 respectively). Because the risk alleles at these loci are negatively correlated, their association with smoking is stronger in the joint model than when each SNP is analyzed alone. Rs578776 also demonstrates association with smoking after adjustment for rs16969968 (p<10 −6). In models adjusting for cigarettes-per-day, we confirm the association between rs16969968 and lung cancer (p<10 −20) and observe a nominally significant association with COPD (p = 0.01); the other loci are not significantly associated with either lung cancer or COPD after adjusting for rs16969968. This study provides strong evidence that multiple statistically distinct loci in this region affect smoking behavior. This study is also the first report of association between rs588765 (and correlates) and smoking that achieves genome-wide significance; these SNPs have previously been associated with mRNA levels of CHRNA5 in brain and lung tissue.

          Author Summary

          Nicotine binds to cholinergic nicotinic receptors, which are composed of a variety of subunits. Genetic studies for smoking behavior and smoking-related diseases have implicated a genomic region that encodes the alpha5, alpha3, and beta4 subunits. We examined genetic data across this region for over 38,000 smokers, a subset of which had been assessed for lung cancer or chronic obstructive pulmonary disease. We demonstrate strong evidence that there are at least two statistically independent loci in this region that affect risk for heavy smoking. One of these loci represents a change in the protein structure of the alpha5 subunit. This work is also the first to report strong evidence of association between smoking and a group of genetic variants that are of biological interest because of their links to expression of the alpha5 cholinergic nicotinic receptor subunit gene. These advances in understanding the genetic influences on smoking behavior are important because of the profound public health burdens caused by smoking and nicotine addiction.

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          Most cited references47

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          Equivalence of the mediation, confounding and suppression effect.

          This paper describes the statistical similarities among mediation, confounding, and suppression. Each is quantified by measuring the change in the relationship between an independent and a dependent variable after adding a third variable to the analysis. Mediation and confounding are identical statistically and can be distinguished only on conceptual grounds. Methods to determine the confidence intervals for confounding and suppression effects are proposed based on methods developed for mediated effects. Although the statistical estimation of effects and standard errors is the same, there are important conceptual differences among the three types of effects.
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            A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer.

            We conducted a genome-wide association study (GWAS) of breast cancer by genotyping 528,173 SNPs in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls. We identified four SNPs in intron 2 of FGFR2 (which encodes a receptor tyrosine kinase and is amplified or overexpressed in some breast cancers) that were highly associated with breast cancer and confirmed this association in 1,776 affected individuals and 2,072 controls from three additional studies. Across the four studies, the association with all four SNPs was highly statistically significant (P(trend) for the most strongly associated SNP (rs1219648) = 1.1 x 10(-10); population attributable risk = 16%). Four SNPs at other loci most strongly associated with breast cancer in the initial GWAS were not associated in the replication studies. Our summary results from the GWAS are available online in a form that should speed the identification of additional risk loci.
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              Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1.

              To identify risk variants for lung cancer, we conducted a multistage genome-wide association study. In the discovery phase, we analyzed 315,450 tagging SNPs in 1,154 current and former (ever) smoking cases of European ancestry and 1,137 frequency-matched, ever-smoking controls from Houston, Texas. For replication, we evaluated the ten SNPs most significantly associated with lung cancer in an additional 711 cases and 632 controls from Texas and 2,013 cases and 3,062 controls from the UK. Two SNPs, rs1051730 and rs8034191, mapping to a region of strong linkage disequilibrium within 15q25.1 containing PSMA4 and the nicotinic acetylcholine receptor subunit genes CHRNA3 and CHRNA5, were significantly associated with risk in both replication sets. Combined analysis yielded odds ratios of 1.32 (P < 1 x 10(-17)) for both SNPs. Haplotype analysis was consistent with there being a single risk variant in this region. We conclude that variation in a region of 15q25.1 containing nicotinic acetylcholine receptors genes contributes to lung cancer risk.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                August 2010
                August 2010
                5 August 2010
                : 6
                : 8
                : e1001053
                Affiliations
                [1 ]Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [2 ]Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [3 ]Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [4 ]Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
                [5 ]Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
                [6 ]Department of Human Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
                [7 ]Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
                [8 ]Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
                [9 ]Department of Psychiatry, University of Munich (LMU), Munich, Germany
                [10 ]Departments of Psychiatry, Genetics, and Neurobiology, Yale University School of Medicine, New Haven, Connecticut, United States of America
                [11 ]Department of Epidemiology, University of Texas M. D. Anderson Cancer Center, Houston, Texas, United States of America
                [12 ]Department of Public Health, University of Helsinki, Helsinki, Finland
                [13 ]Department of Quantitative Sciences, GlaxoSmithKline, King of Prussia, Pennsylvania, United States of America
                [14 ]Division of Cancer Epidemiology and Genetics, National Institutes of Health, Bethesda, Maryland, United States of America
                [15 ]Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
                [16 ]Department of Sociology, Brown University, Providence, Rhode Island, United States of America
                [17 ]Environmental and Occupational Medicine and Epidemiology Program, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [18 ]Institute for Behavioral Genetics, University of Colorado, Boulder, Colorado, United States of America
                [19 ]Epidemiology Research, American Cancer Society, Atlanta, Georgia, United States of America
                [20 ]Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [21 ]Section of Cancer Genetics, Institute of Cancer Research, Sutton Surrey, United Kingdom
                [22 ]Karmanos Cancer Institute, Wayne State University, Detroit, Michigan, United States of America
                [23 ]Department of Epidemiology, Michigan State University, East Lansing, Michigan, United States of America
                [24 ]National Institute for Health and Welfare, Helsinki, Finland
                [25 ]Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [26 ]Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [27 ]Queensland Institute of Medical Research, Brisbane, Queensland, Australia
                [28 ]Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia, United States of America
                [29 ]Department of Otolaryngology and Communicative Sciences, The University of Mississippi Medical Center, Jackson, Mississippi, United States of America
                [30 ]Institute for Molecular Medicine Finland FIMM, Helsinki, Finland
                [31 ]Department of Medical Genetics, University of Helsinki, Helsinki, Finland
                [32 ]Wellcome Trust Sanger Institute, Cambridge, United Kingdom
                [33 ]Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
                [34 ]Department of Medicine (Genetics Program), Boston University School of Medicine, Boston, Massachusetts, United States of America
                [35 ]Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
                [36 ]Information Management Services, Rockville, Maryland, United States of America
                [37 ]Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health Mannheim, Mannheim, Germany
                [38 ]Department of Integrative Physiology, University of Colorado, Boulder, Colorado, United States of America
                [39 ]Cambridge Biomedical Research Centre, Cambridge, United Kingdom
                [40 ]Department of Biostatistics, Harvard University, Boston, Massachusetts, United States of America
                [41 ]Institute of Human Genetics, University of Bonn, Bonn, Germany
                [42 ]Glaxo SmithKline, Research Triangle Park, North Carolina, United States of America
                [43 ]Department of Psychiatry, University of Bonn, Bonn, Germany
                Georgia Institute of Technology, United States of America
                Author notes
                [¤]

                Current address: Pharmaceutical Research and Development, Roche Pharmaceuticals, Nutley, New Jersey, United States of America

                Conceived and designed the experiments: NLS RCC THSA DSC XC SC IG SH YH KKV XK MTL JZM SES SHS VLS YW NB PB ACH MH NRH DJH MKJ NGM GWM TJP LP MLP JPR MRS JCW RBW NEC MAE TE SMG JG RSH JK KSK PK MFL MDL PAFM MMN MR DR AS CIA LJB. Performed the experiments: NLS RCC THSA XK SES SHS VLS YW PB JC NRH JCW SHW MAE TE RSH JK PK SP CIA LJB. Analyzed the data: NLS RCC THSA DSC XC SC SH YH KKV XK JZM SES SHS LS YW ASW SHA PB NC NRH TN RS MRS JS WW BZY MAE TE RSH SP CIA LJB. Wrote the paper: NLS RCC THSA DSC IG SH KKV JZM SES SHS VLS LS NB MH NRH NGM GWM TN TJP LP MLP JPR RS MRS JCW RBW BZY MAE JG JK PK MDL PAFM DR AS CIA LJB. Contributed analysis tools: NLS RCC THSA YH CIA. Performed meta-analysis: NLS RCC THSA LS. Wrote first draft of paper: NLS RCC THSA LS LJB.

                Article
                10-PLGE-RA-NV-2658R2
                10.1371/journal.pgen.1001053
                2916847
                20700436
                d75e1d18-74c6-4529-87af-1c0fc46fa4c9
                This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                History
                : 23 February 2010
                : 7 July 2010
                Page count
                Pages: 16
                Categories
                Research Article
                Genetics and Genomics/Complex Traits
                Genetics and Genomics/Genetics of Disease

                Genetics
                Genetics

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