4.7 Article

A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications

期刊

BIOLOGICAL PSYCHIATRY
卷 70, 期 6, 页码 513-518

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.biopsych.2011.02.028

关键词

Alcoholism; genome-wide association; nonreplication; quantitative trait

资金

  1. National Institutes of Health [AA07535, AA07728, AA13320, AA13321, AA14041, AA11998, AA17688, DA012854, DA019951]
  2. Australian National Health and Medical Research Council [241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 552485, 552498]
  3. Australian Research Council [A7960034, A79906588, A79801419, DP0770096, DP0212016, DP0343921]
  4. 5th Framework Programme (FP-5) GenomEUtwin Project [QLG2-CT-2002-01254]
  5. Center for Inherited Disease Research [AA13320]
  6. National Health and Medical Research Council

向作者/读者索取更多资源

Background: Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. Methods: Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. Results: No findings reached genome-wide significance (p = 8.4 x 10(-8) for this study), with lowest p value for primary phenotypes of 1.2 x 10(-7). Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene (TMEM108) and for ANKS1A. The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. Conclusions: We conclude that 1) meta-analyses of consumption data may contribute usefully to gene discovery; 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging; and 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e. g., prospective high-risk or resilience studies).

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