Background: Alcohol dependence (AD) is a cluster of clinical phenomena that develop after repeated alcohol use. At least 50% of factors predisposing to AD are genetic and women affected with this disorder present with more psychiatric comorbidities, probably indicating different genetic factors involved. We aimed to run a genome-wide association study (GWAS) followed by a bioinformatic functional annotation of associated genomic regions in a cohort of patients with AD and eight additional clinical measures.

Methods: Chi-square tests and the signal localization approach were used for the genome-wide screening of associations with AD. Likelihood ratio tests were used to evaluate associations with the additional clinical measures. Regulatory sequences in the associated linkage disequilibrium blocks were retrieved from bioinformatic databases. The resulting list of regulated genes was analyzed for possible interactions.

Results: A genome-wide significant association of rs220677 with AD (p-value = 1.33×10-8) was discovered in female patients. Associations with six other single nucleotide polymorphisms listed in previous GWAS of psychiatric and addiction traits were differently replicated in female and male patients. The bioinformatic analysis showed that regulatory elements in the seven associated linkage disequilibrium blocks define the expression of 78 protein-coding genes. Nearly 68% of these and of 120 other previously published coding genes associated with alcohol phenotypes directly interact in a single network (i.e. without additional interactors added by the software).

Conclusions: Results of this study suggest that molecular pathways implicated in the pathogenesis of AD are the same in both sexes, but different genes play more prominent roles in men and women. The discovered gene network may contain clues to the understanding of the pathogenesis and to the discovery of new treatment options of AD.

Note: Funding: This work was supported by Saint Petersburg State University (Program of development, #M15-D3- N1). In addition, this work was in part supported by the Russian Foundation for Basic Research (Alexander O. Kibitov, Evgeny M. Krupitsky, Natalya A. Chuprova, Kseniya V. Rybakova, Anton E. Nikolishin, grant #18-015-00473А) and Saint Petersburg State University (Raul R. Gainetdinov, project #73022475). Furthermore, this work was carried out as part of the Russian National Consortium for Psychiatric Genetics (RNCPG) (Fedorenko et al., 2019).