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A meta-analysis of two genome-wide association studies to identify novel loci for maximum number of alcoholic drinks

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Abstract

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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Acknowledgments

The Collaborative Study on the Genetics of Alcoholism (COGA): COGA, Principal Investigators B Porjesz, V Hesselbrock, H Edenberg, L Bierut includes ten different centers: University of Connecticut (V Hesselbrock); Indiana University (HJ Edenberg, J Nurnberger Jr, T Foroud); University of Iowa (S Kuperman, J Kramer); SUNY Downstate (B Porjesz); Washington University in Saint Louis (L Bierut, A Goate, J Rice, K Bucholz); University of California at San Diego (M Schuckit); Rutgers University (J Tischfield); Southwest Foundation (L Almasy), Howard University (R Taylor) and Virginia Commonwealth University (D Dick). A Parsian and M Reilly are the NIAAA Staff Collaborators. We continue to be inspired by our memories of Henri Begleiter and Theodore Reich, founding PI and Co-PI of COGA, and also owe a debt of gratitude to other past organizers of COGA, including Ting-Kai Li, currently a consultant with COGA, P Michael Conneally, Raymond Crowe and Wendy Reich, for their critical contributions. This national collaborative study is supported by NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA).

The Study of Addiction: Genetics and Environment (SAGE): Funding support for SAGE was provided through the NIH Genes, Environment and Health Initiative (GEI) (U01 HG004422). SAGE is one of the GWAS funded as part of the Gene Environment Association Studies (GENEVA) under GEI. Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01 HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Support for collection of data sets and samples was provided by COGA (U10 AA008401), the Collaborative Genetic Study of Nicotine Dependence (COGEND; P01 CA089392) and the Family Study of Cocaine Dependence (FSCD; R01 DA013423, R01 DA019963). Genotyping at the Johns Hopkins University Center for Inherited Disease Research was supported by the NIH GEI (U01HG004438) Grant, NIAAA, NIDA and the NIH contract ‘High throughput genotyping for studying the genetic contributions to human disease’.

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Authors and Affiliations

  1. Department of Psychiatry, B8134, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA

    Manav Kapoor, Jen-Chyong Wang, Nhung Le, Sarah Bertelsen, Anthony L. Hinrichs, John Budde, Arpana Agrawal, Kathleen Bucholz, Oscar Harari, John Rice, Laura Bierut & Alison Goate

  2. Indiana University School of Medicine, Indianapolis, USA

    Leah Wetherill, John I. Nurnberger Jr, Howard J. Edenberg & Tatiana Foroud

  3. Virginia Commonwealth University, Richmond, USA

    Danielle Dick

  4. University of Connecticut Health Center, Farmington, USA

    Victor Hesselbrock

  5. University of Iowa Carver College of Medicine, Iowa, USA

    John Kramer

  6. University of California, San Diego, USA

    Marc Schuckit

  7. Rutgers University, Piscataway, USA

    Jay Tischfield

  8. SUNY Health Sciences Center, Brooklyn, USA

    Bernice Porjesz

  9. Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, USA

    Nancy Saccone

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  1. Manav Kapoor
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  2. Jen-Chyong Wang
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  3. Leah Wetherill
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  4. Nhung Le
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  19. Bernice Porjesz
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  20. Howard J. Edenberg
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  21. Laura Bierut
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  22. Tatiana Foroud
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  23. Alison Goate
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Correspondence to Alison Goate.

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Kapoor, M., Wang, JC., Wetherill, L. et al. A meta-analysis of two genome-wide association studies to identify novel loci for maximum number of alcoholic drinks. Hum Genet 132, 1141–1151 (2013). https://doi.org/10.1007/s00439-013-1318-z

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