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

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• 作者：Andrew C.  ; Heath^a ;   ; ^{aheath@wustl.edu} ; John B.  ; Whitfield^b ; Nicholas G.  ; Martin^b ; Michele L.  ; Pergadia^a ; Alison M.  ; Goate^a ; Penelope A.  ; Lind^b ; Brian P.  ; McEvoy^b ; Andrew J.  ; Schrage^a ; Julia D.  ; Grant^a ; Yi-Ling  ; Chou^a ; Rachel  ; Zhu^a ; Anjali K.  ; Henders^b ; Sarah E.  ; Medland^b ; Scott D.  ; Gordon^b ; Elliot C.  ; Nelson^a ; Arpana  ; Agrawal^a ; Dale R.  ; Nyholt^b ; Kathleen K.  ; Bucholz^a ; Pamela A.F.  ; Madden^a ; Grant W.  ; Montgomery^b
• 关键词：Alcoholism ; genome-wide association ; nonreplication ; quantitative trait
• 刊名：Biological Psychiatry
• 出版年：2011
• 出版时间：15 September 2011
• 年：2011
• 卷：70
• 期：6
• 页码：513-518
• 全文大小：181 K

文摘

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 ¡Á 10^? for this study), with lowest p value for primary phenotypes of 1.2 ¡Á 10^?. 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).