A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications
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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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For ALC, the published GWAS are small and no large-scale meta-analysis has been conducted.
“For ALC, the published GWAS are small and no large-scale meta-analysis has been conducted. 93–97”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [97]
Risk profile analysis suggested that larger samples would yield more associations for ALC.
“particularly given that risk profile analysis (Box 3) suggested that larger samples would yield more associations. 97”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [97]
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- Authors
- Heath, A. C., Whitfield, J. B., Martin, N. G., Pergadia, M. L., Goate, A. M., Lind, P. A., McEvoy, B. P., Schrage, A. J., Grant, J. D., Chou, Y.-L., Zhu, R., Henders, A. K., Medland, S. E., Gordon, S. D., Nelson, E. C., Agrawal, A., Nyholt, D. R., Bucholz, K. K., Madden, P. A. F., & Montgomery, G. W.
- Affiliations
- Washington University in St. Louis (US)
- QIMR Berghofer Medical Research Institute (AU)
- Corresponding author
- Heath, Andrew C.
- ORCID
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2011-09
- Volume
- 70
- Issue
- 6
- Pages
- 513-518
- ISSN
- 0006-3223 (ISSN-L)
- PMC
- PMC3210694
- OpenAlex
- W2011133239
- Cited by
- 193
- References
- 48
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 3 · 2023: 8 · 2022: 7 · 2021: 8 · 2020: 7 · 2019: 11 · 2018: 7 · 2017: 17 · 2016: 15 · 2015: 21 · 2014: 21 · 2013: 26 · 2012: 29
- FWCI
- 16.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- Funders
- National Institutes of Health (AA07535, AA07728, AA11998, AA13320, AA13321, AA14041, AA17688, DA012854, DA019951)
- Australian Research Council (A7960034, A79801419, A79906588, DP0212016, DP0343921, DP0770096)
- National Health and Medical Research Council (241944, 339462, 389875, 389891, 389892, 389927, 389938, 442915, 442981, 496739, 552485, 552498)
- Fifth Framework Programme (FP-5, QLG2-CT-2002-01254)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- alcoholism, alcoholism risk, genetic susceptibility, single nucleotide polymorphisms, family-based association, heritability, alcohol consumption, genetic risk prediction
- MeSH terms
- Alcohol Drinking, Alcoholism, Genotype, Humans, Phenotype, Residence Characteristics, Case-Control Studies, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study
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