Preuss; U.W.a, Ridinger; M.c, Fehr; C.d, Koller; G.b, Bondy; B.b, Wodarz; N.c, Soyka; M.e, Zill; P.b
a Department of Psychiatry, Psychotherapy, Psychosomatics, Martin-Luther-University, Halle; Vitos Hospital Herborn, Germany
b Department of Psychiatry and Psychotherapy, Ludwig-Maximilians University, Munich, Germany
c Department of Psychiatry, Psychosomatics and Psychotherapy, University Medical Center, Regensburg, Germany
d Department of Psychiatry, Johannes-Gutenberg-University, Mainz, Germany
e Privatklinik Meiringen, Meiringen, Switzerland
Criteria of alcohol use disorders are heterogeneous and include dimensions of behavioural (“loss of control”), psychological (craving) and physiological (withdrawal, tolerance) as well as criteria of social consequences (negligence of activities). Each of these criteria may have a separate genetic background. The aim of this analyses of a large sample of inpatient alcohol-dependent individuals (vs. control subjects) is to conduct association analyses of candidate gene variants with ICD10 and DSM V criteria.
More than 1800 inpatient subjects with DSM-IV AD from three addiction treatment centres were included. Characteristics of AD and suicidal behavior were obtained using standardized structured interviews (CIDI, DIA-X, SSAGA). All subjects were genotyped for a number of candidate genes (GABRA1, GABRA6, GABRB2, GABRG3, TPH1, 5HT2A, MAO-A, COMT, BDNF, 5-HTT, ADH4, DRD2, NR2A, OPRM) variants. Single Nucleotide Polymorphism (SNP) and haplotypic associations and a logistic regression analyses were conducted when initial SNP associations reached statistical significance.
Different sets of gene variants influence phenotypes but, in logistic regression analyses, explain only a small fraction of variance.
This study confirms the small but significant and independent role of several candidate gene variants in the heterogeneous alcohol use disorder criteria phenotypes. Further research is needed to identify additional gene variants, epigenetic changes and other gene-environment interactions to explain a larger fraction of phenotype variance.