BACKGROUND: A wealth of literature supports the role of gamma-aminobutyric acid (GABA) in neurobiological pathways contributing to alcohol dependence and related phenotypes. Animal studies have consistently tied rodent homologs of the GABAA receptor genes on human chromosome 5q to alcohol-related behaviors; however, human studies have produced mixed results. Family-based association analyses previously conducted in the Collaborative Study on the Genetics of Alcoholism (COGA) sample yielded no evidence of association with Diagnostic and Statistical Manual of Mental Disorder-fourth edition (DSM-IV) alcohol dependence and these genes. As a follow-up to that study, we examined several alcohol-related behaviors in the COGA sample as follows: (1) a broader definition of alcohol dependence, including DSM-III-R symptoms and Feighner criteria (referred to as COGA alcohol dependence); (2) withdrawal; (3) history of alcohol-induced blackouts; (4) level of response to alcohol; (5) age of onset of regular drinking; and (6) age at first drunkenness. METHODS: Family-based association tests were conducted, using multiple single-nucleotide polymorphisms (SNPs) in each of the 4 GABAA receptor genes on chromosome 5q. RESULTS: In GABRA1, we found evidence of association with several of the drinking behavior phenotypes, including COGA alcohol dependence, history of blackouts, age at first drunkenness, and level of response to alcohol. We did not find consistent evidence of association with the remaining genes and any of the phenotypes. CONCLUSIONS: We found evidence for association between GABRA1 and COGA alcohol dependence, history of blackouts, age at first drunkenness, and level of response to alcohol. These analyses suggest that efforts to characterize genetic contributions to alcohol dependence may benefit by examining alcohol-related behaviors in addition to clinical alcohol dependence diagnoses.
BACKGROUND: A wealth of literature supports the role of gamma-aminobutyric acid (GABA) in neurobiological pathways contributing to alcohol dependence and related phenotypes. Animal studies have consistently tied rodent homologs of the GABAA receptor genes on human chromosome 5q to alcohol-related behaviors; however, human studies have produced mixed results. Family-based association analyses previously conducted in the Collaborative Study on the Genetics of Alcoholism (COGA) sample yielded no evidence of association with Diagnostic and Statistical Manual of Mental Disorder-fourth edition (DSM-IV) alcohol dependence and these genes. As a follow-up to that study, we examined several alcohol-related behaviors in the COGA sample as follows: (1) a broader definition of alcohol dependence, including DSM-III-R symptoms and Feighner criteria (referred to as COGA alcohol dependence); (2) withdrawal; (3) history of alcohol-induced blackouts; (4) level of response to alcohol; (5) age of onset of regular drinking; and (6) age at first drunkenness. METHODS: Family-based association tests were conducted, using multiple single-nucleotide polymorphisms (SNPs) in each of the 4 GABAA receptor genes on chromosome 5q. RESULTS: In GABRA1, we found evidence of association with several of the drinking behavior phenotypes, including COGA alcohol dependence, history of blackouts, age at first drunkenness, and level of response to alcohol. We did not find consistent evidence of association with the remaining genes and any of the phenotypes. CONCLUSIONS: We found evidence for association between GABRA1 and COGA alcohol dependence, history of blackouts, age at first drunkenness, and level of response to alcohol. These analyses suggest that efforts to characterize genetic contributions to alcohol dependence may benefit by examining alcohol-related behaviors in addition to clinical alcohol dependence diagnoses.
Authors: Heidi M B Lesscher; Julia M Houthuijzen; Marian J Groot Koerkamp; Frank C P Holstege; Louk J M J Vanderschuren Journal: PLoS One Date: 2012-05-22 Impact factor: 3.240
Authors: George R Uhl; Tomas Drgon; Catherine Johnson; Oluwatosin O Fatusin; Qing-Rong Liu; Carlo Contoreggi; Chuan-Yun Li; Kari Buck; John Crabbe Journal: Biochem Pharmacol Date: 2007-07-25 Impact factor: 5.858
Authors: George R Uhl; Tomas Drgon; Catherine Johnson; Chuan-Yun Li; Carlo Contoreggi; Judith Hess; Daniel Naiman; Qing-Rong Liu Journal: Ann N Y Acad Sci Date: 2008-10 Impact factor: 5.691
Authors: Tiebing Liang; Mark W Kimpel; Jeanette N McClintick; Ashley R Skillman; Kevin McCall; Howard J Edenberg; Lucinda G Carr Journal: Genome Biol Date: 2010-02-03 Impact factor: 13.583