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Genome-wide association study identifies 5q21 and 9p24.1 (KDM4C) loci associated with alcohol withdrawal symptoms

  • Basic Neurosciences, Genetics and Immunology - Original Article
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Abstract

Several genome-wide association (GWA) studies of alcohol dependence (AD) and alcohol-related phenotypes have been conducted; however, little is known about genetic variants influencing alcohol withdrawal symptoms (AWS). We conducted the first GWA study of AWS using 461 cases of AD with AWS and 408 controls in Caucasian population in the Collaborative Study on the Genetics of Alcoholism (COGA) sample. Logistic regression analysis of AWS as a binary trait, adjusted for age and sex, was performed using PLINK. We identified 51 SNPs associated with AWS with p < 10−4. The first best signal was rs770182 (p = 3.65 × 10−6) at 5q21 near EFNA5 gene which was replicated in the Australian twin-family study of 273 families (p = 0.0172). Furthermore, three SNPs (rs10975990, rs10758821 and rs1407862) within KDM4C gene at 9p24.1 showed p < 10−4 (p = 7.15 × 10−6, 2.79 × 10−5 and 4.93 × 10−5, respectively) in the COGA sample while one SNP rs12001158 within KDM4C with p = 1.97 × 10−4 in the COGA sample was replicated in the family sample (p = 0.01). Haplotype analysis further supported the associations of single-marker analyses of KDM4C in the COGA sample. Moreover, two SNPs (rs2046593 and rs10497668) near FSIP2 at 2q32.1 with moderate associations with AWS in the COGA sample (p = 2.66 × 10−4 and 9.48 × 10−5, respectively) were replicated in the family sample (p = 0.0013 and 0.0162, respectively). In addition, several SNPs in GABRA1, GABRG1, and GABRG3 were associated with AWS (p < 10−2) in the COGA sample. In conclusion, we identified several loci associated with AWS. These findings offer the potential for new insights into the pathogenesis of AD and AWS.

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Acknowledgments

Funding support for the (CIDR–COGA Study) was provided through the [the Center for Inherited Disease Research (CIDR) and the Collaborative Study on the Genetics of Alcoholism (COGA)]. The CIDR–COGA Study is a genome-wide association studies funded as part of the Collaborative Study on the Genetics of Alcoholism (COGA). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the COGA. Assistance with data cleaning was provided by the National Center for Biotechnology Information. Support for collection of datasets and samples were provided by the Collaborative Study on the Genetics of Alcoholism (COGA; U10 AA008401). 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). The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/sites/entrez?Db=gap through dbGaP accession number: phs000125.v1.p1. 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 GWAS) 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 studies 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 study was approved by Internal Review Board (IRB), East Tennessee State University.

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  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 & Min Zeng

  2. Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, 63108, USA

    Qunyuan Zhang

  3. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON, Canada

    Long-Yang Wu

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  1. Ke-Sheng Wang
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Wang, KS., Liu, X., Zhang, Q. et al. Genome-wide association study identifies 5q21 and 9p24.1 (KDM4C) loci associated with alcohol withdrawal symptoms. J Neural Transm 119, 425–433 (2012). https://doi.org/10.1007/s00702-011-0729-z

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