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Exploring the genetic architecture of alcohol dependence in African-Americans via analysis of a genomewide set of common variants

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Abstract

Alcohol dependence (AD) is a complex psychiatric disorder that affects about 12.5 % of US adults. Genetic factors play a major role in the development of AD. We conducted a genomewide association study in 2,875 African-Americans including 1,719 AD cases and 1,156 controls. We used the Illumina Omni 1-Quad microarray, which yielded 769,498 single-nucleotide polymorphisms (SNPs) after quality control. To explore the genetic architecture of AD, we estimated the variance that could be explained by all SNPs and subsets of SNPs using two different approaches to genome partitioning. We found that 23.9 % (s.e. 9.3 %) of the phenotypic variance could be explained by using all of the common SNPs on the array. We also found a significant linear relationship between the proportion of the top SNPs used and the phenotypic variance explained by them. Based on genome partitioning of common variants, we also observed a significant linear relationship between the variance explained by a chromosome and its length. Chromosome 4, known to contain several AD risk genes, accounted for excess risk in proportion to its length. By functional partitioning, we found that the genetic variants within 20 kb of genes explained 17.5 % (s.e. 11.4 %) of the phenotypic variance. Our findings are consistent with the generally accepted view that AD is a highly polygenic trait, i.e., the genetic risk in AD appears to be conferred by multiple variants, each of which may have a small or moderate effect.

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Acknowledgments

Genotyping services for a part of our GWAS study were provided by the Center for Inherited Disease Research (CIDR) and Yale University (Center for Genome Analysis). CIDR is fully funded through a federal contract from the National Institutes of Health to the Johns Hopkins University (contract number N01-HG-65403). This study was supported by National Institutes of Health grants RC2 DA028909, R01 DA12690, R01 DA12849, R01 DA18432, R01 AA11330, R01 AA017535, P50 AA12870, R01 GM59507, and R01 DA030976.

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Authors and Affiliations

  1. Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, 06520, USA

    Can Yang & Hongyu Zhao

  2. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA

    Can Yang & Joel Gelernter

  3. VACT Healthcare Center, West Haven, USA

    Can Yang & Joel Gelernter

  4. Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA

    Cong Li

  5. Department of Psychiatry, VISN 4 MIRECC, VAMC, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

    Henry R. Kranzler

  6. Departments of Medicine, Neurology, Ophthalmology, Genetics and Genomics, Epidemiology, and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA

    Lindsay A. Farrer

  7. Departments of Genetics and Neurobiology, Yale University School of Medicine, 950 Campbell Avenue, West Haven, CT, 06516, USA

    Joel Gelernter

Authors
  1. Can Yang
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  2. Cong Li
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  3. Henry R. Kranzler
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  4. Lindsay A. Farrer
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  5. Hongyu Zhao
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  6. Joel Gelernter
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Correspondence to Can Yang or Joel Gelernter.

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Yang, C., Li, C., Kranzler, H.R. et al. Exploring the genetic architecture of alcohol dependence in African-Americans via analysis of a genomewide set of common variants. Hum Genet 133, 617–624 (2014). https://doi.org/10.1007/s00439-013-1399-8

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  • DOI: https://doi.org/10.1007/s00439-013-1399-8

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