A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications
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 d...
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Veröffentlicht in: | Biological psychiatry (1969) 2011-09, Vol.70 (6), p.513-518 |
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Zusammenfassung: | 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 × 10−8 for this study), with lowest p value for primary phenotypes of 1.2 × 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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ISSN: | 0006-3223 1873-2402 |
DOI: | 10.1016/j.biopsych.2011.02.028 |