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Family-based association analysis of alcohol dependence in the COGA sample and replication in the Australian twin-family study

  • Basic Neurosciences, Genetics and Immunology - Original Article
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Abstract

Family, twin, and adoption studies have indicated that genetic and environmental factors contribute to the development of alcohol dependence (AD). We conducted a low-density genome-wide association analysis to identify genetic variants influencing AD. We used 11,120 SNPs from the Affymetrix 10K Genechips genotyped in 116 Caucasian pedigrees (272 nuclear families) from Genetic Analysis Workshop 14, a subset from the Collaborative Study on the Genetics of Alcoholism (COGA). Family-based association analyses for AD were performed by the PBAT program for autosomal SNPs and by the FBAT program for X-chromosome SNPs. We identified 37 SNPs associated with AD (P < 10−3), thirteen of which were located in known genes. The most significant association with AD was observed with SNP rs1986644 (P = 8.51 × 10−6) at 13q22 near EDNRB gene. The next best signal was at 1q41 in USH2A (rs532342, P = 1.07 × 10−5) and the third region was at 3q25.31 in TIPARP (rs1367311, P = 2.31 × 10−5). Furthermore, we found support for association of MAOA gene (P = 4.14 × 10−4 for rs979606). Six of the 37 AD associated SNPs were confirmed to be associated with AD in Australian twin-family study sample (P < 0.05). Interestingly, four SNPs in DSCAML1 at 11q23 reached the genome-wide significance (the top SNP is rs10892169 with P = 5.31 × 10−9), while rs637547 in NKAIN2 at 6q21 showed strong association with AD (P = 5.11 × 10−7) in the replication sample. These findings offer the potential for new insights into the pathogenesis of AD and will serve as a resource for replication in other populations to elucidate the potential role of these genetic variants in AD.

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Acknowledgments

The Collaborative Study on the Genetics of Alcoholism (COGA) (H. Begleiter, SUNY HSCB, Principal Investigator: T. Reich, Washington University, Co-Principal Investigator) includes nine centers where data collection, analysis, and/or storage take place. This national collaborative study is supported by NIH grant U10AA08403 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA). The National Institute of General Medical Sciences has provided continuous funding for the Genetic Analysis Workshops (GAW) since 1982, through grant R01 GM31575 to Jean MacCluer (Southwest Foundation for Biomedical Research). The GAW14 data was kindly provided by Jean MacCluer (Southwest Foundation for Biomedical Research). We acknowledge the contributions of the COGA, supported by NIH Grants U10AA08401 and U10AA08403 (NIAAA) and the contributions of all scientists who have provided genotyping data to the Wave I and/or Wave II–Genetic Analysis Data. We were granted access to the COGA data by NIAAA. The dataset for replication study was obtained from the CIDA database found at http://www.ncbi.nlm.nih.gov/projects/gap/ through the dbGAP accession number Study Accession: phs000181.v1.p1. Funding support for the (CIDR-OZALC GWAS0 was provided through the Center for Inherited Disease Research (CIDR) and the National Institute on Alcohol Abuse and Alcoholism (NIAAA). CIDR-OZALC GWAS is a genome-wide association study funded as part of the NIAAA grant 5 R01 AA013320-04. Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the CIDR-OZALC GWAS. Assistance with data cleaning was provided by the National Center for Biotechnology Information. Support for collection of datasets and samples was provided by the MARC: Risk Mechanisms in Alcoholism and Comorbidity (MARC; P60 AA011998-11). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, and the NIH contract “High throughput genotyping for studying the genetic contributions to human disease” (HHSN268200782096C). This work was partially supported by RDC major research grant (to KSW and XFL), East Tennessee State University.

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The authors declared no conflict of interest.

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Authors and Affiliations

  1. Department of Biostatistics and Epidemiology, College of Public Health, East Tennessee State University, PO Box 70259, Lamb Hall, Johnson City, TN, 37614-1700, USA

    Ke-Sheng Wang, Xuefeng Liu, Nagesh Aragam & Xueqiu Jian

  2. Department of Pathology, James H. Quillen College of Medicine, East Tennessee State University, Johnson City, TN, USA

    Jerald E. Mullersman

  3. Department of Mathematics and Statistics, College of Arts and Sciences, East Tennessee State University, Johnson City, TN, USA

    Yali Liu & Yue Pan

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  1. Ke-Sheng Wang
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  2. Xuefeng Liu
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Correspondence to Ke-Sheng Wang.

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Wang, KS., Liu, X., Aragam, N. et al. Family-based association analysis of alcohol dependence in the COGA sample and replication in the Australian twin-family study. J Neural Transm 118, 1293–1299 (2011). https://doi.org/10.1007/s00702-011-0628-3

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