ABSTRACT Alcohol withdrawal is a critical component of development and persistence of addiction to alcohol and a cause for significant morbidity and mortality in patients with alcohol use disorders (AUD). Introduction of benzodiazepines resulted in reduced severity of alcohol withdrawal syndrome (AWS), and decreased mortality and frequency of complications. While research suggests involvement of certain neurotransmitter systems in the neurobiology of AWS, genetic markers associated with predisposition to AWS and its treatment response remain unknown. We therefore propose to perform comprehensive genetic analyses, including genome-wide association studies (GWASs), to identify genetic markers of AWS risk and response to benzodiazepine treatment of AWS. The proposed analyses will constitute the largest GWAS of AWS to date, with a sample size of AUD subjects 10 times larger than the only previously published AWS GWAS, and the first GWAS of benzodiazepine response. We will also investigate sex differences in genetic effects on AWS and response to its treatment. Our study will involve advanced analyses, including assessment of SNP-based heritability of AWS along with gene and pathway-level analyses (including drug-target enrichment) and fine-mapping to detect relevant genetic effects. We will also use polygenic risk scores to determine if genetic load for AUD-related traits is associated with AWS. The proposed study is aligned with NIAAA policy, which states that GWAS is “the preferred approach for the identification of and the confirmation of genes that harbor variants that contribute to AUD and related phenotypes, since results from these studies will likely provide potential insights into translational studies and new therapeutic targets”. The proposed research also supports NIH efforts to increase awareness and attention to sex and gender in research. Our preliminary data and power calculations demonstrate that analysis of available data is expected to identify common genetic variants associated with AWS. Discovery of genetic variants that impact the risk of AWS will generate knowledge on its neurobiology and ultimately contribute to the development of tools for the identification of patients at risk and selection of treatment options based on an understanding of inter- individual differences in sensitivity to this central component of AUD. This line of research may also contribute to development of new AUD treatment approaches aimed to restore physiological dysfunction associated with those genetic variants.