A quantitative-trait genome-wide association study of alcoholism risk in the community: findings and implications.
paper
Cited
Public
- Authors
- 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
- Year
- 2011
- Journal
- Biological psychiatry
- PMID
- 21529783
- DOI
- 10.1016/j.biopsych.2011.02.028
- PMCID
- PMC3210694
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 Γ 10(-8) for this study), with lowest p value for primary phenotypes of 1.2 Γ 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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