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

作者：Heath Andrew C^*; Whitfield John B; Martin Nicholas G; Pergadia Michele L; Goate Alison M; Lind Penelope A; McEvoy Brian P; Schrage Andrew J; Grant Julia D; Chou Yi Ling; Zhu Rachel; Henders Anjali K; Medland Sarah E; Gordon Scott D; Nelson Elliot C; Agrawal Arpana; Nyholt Dale R; Bucholz Kathleen K; Madden Pamela A F; Montgomery Grant W

来源：Biological Psychiatry, 2011, 70(6): 513-518.

DOI：10.1016/j.biopsych.2011.02.028

• Alcoholism
• genome-wide association
• nonreplication
• quantitative trait

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).

• 出版日期2011-9-15
• 单位河北医科大学