High-dimensional Data Analytics for Genome-Wide Association Studies: An Application to Alcoholism

Faculty Development Competitive Research Grant Program 2018-2020

Alcohol drinking places a significant burden upon the individuals and the society. Alcohol consumption is the world’s third largest risk factor for disease and disability [1] and the third cause of preventable death in United
States [2, 3]. According to the World Health Organization, Juvenile alcoholism in Kazakhstan is growing at a high rate despite the state’s struggle to curb the alcohol drinking habit [4]. Dr. Zhamilya Battakova, Director of Kazakhstan National Center for Healthy Lifestyle, states that “[in terms of alcohol abuse] we are indeed in the first place in Central Asia” [5].
Epidemiological studies have suggested the genetic component of alcohol dependence (AD). Adoption and twin studies have demonstrated the heritability of a large proportion of phenotypic variance ranging from 50% to 70% [6, 7]. Nevertheless, some studies comparing the monozygotic twins with dizygotic twins, where one twin is alcohol dependent and the other is drug dependent, suggest shared genetic factors account for both alcohol and other drugs dependence (AODD) [8-10]. This can explain in part the high rate of AD comorbidity with other drugs. It is estimated that the odds ratio of comorbidity of AD with other drug dependence in United States, adjusted for demographic characteristics, is as high as 18.7 [11].