4.6 Article

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

Journal

HUMAN GENETICS
Volume 132, Issue 10, Pages 1141-1151

Publisher

SPRINGER
DOI: 10.1007/s00439-013-1318-z

Keywords

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Funding

  1. NIH from National Institute on Alcohol Abuse and Alcoholism (NIAAA) [U10AA008401]
  2. National Institute on Drug Abuse (NIDA)
  3. NIH Genes, Environment and Health Initiative (GEI) [U01 HG004422]
  4. Gene Environment Association Studies (GENEVA) under GEI
  5. NIH GEI [U01HG004438]
  6. NIAAA
  7. NIDA
  8. NIH

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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 x 10(-6)) located in an intergenic region on chromosome 13q31.1; the strongest association in the SAGE dataset was with rs67666182 (p = 7.1 x 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 x 10(-7)) and PLCL1 genes (p = 4.1 x 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 a parts per thousand currency sign 10(-4)) far more showed the same direction of effect in the other dataset than would be expected by chance (p = 2 x 10(-3), 3 x 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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