Genomics of Alcohol Withdrawal and Treatment Response to Benzodiazepines

摘要 酒精戒断是酒精成瘾发展和持续的关键组成部分， 酒精使用障碍（AUD）患者的显著发病率和死亡率。引入 苯二氮卓类药物可降低酒精戒断综合征（AWS）的严重程度， 并发症的频率。虽然研究表明某些神经递质系统参与了 AWS的神经生物学，与AWS易感性相关的遗传标记及其治疗反应 仍然未知。因此，我们建议进行全面的遗传分析，包括全基因组分析。 关联研究（GWAS），以确定AWS风险的遗传标记和对苯二氮卓类药物的反应 AWS的处理。拟议的分析将构成AWS迄今为止最大的GWAS， AUD主题的规模比之前发布的唯一AWS GWAS大10倍， 苯二氮反应我们还将研究遗传对AWS的影响的性别差异， 对治疗的反应。我们的研究将涉及高级分析，包括基于SNP的评估。 AWS的遗传性沿着基因和途径水平分析（包括药物靶向富集），以及 精细定位以检测相关的遗传效应。我们还将使用多基因风险评分来确定 AUD相关性状的遗传负荷与AWS相关。拟议的研究与NIAAA政策保持一致， GWAS是“鉴定和确认基因的首选方法， 携带导致AUD和相关表型的变异，因为这些研究的结果可能会 为转化研究和新的治疗靶点提供潜在的见解”。拟议的研究还 支持NIH努力提高对研究中性和性别的认识和关注。我们的初步数据 和功效计算表明，对现有数据的分析有望确定共同的遗传学特征， 与AWS相关的变体。发现影响AWS风险的遗传变异将产生 了解其神经生物学知识，并最终有助于开发用于 识别有风险的患者，并根据对患者之间的了解选择治疗方案， 对AUD的这一核心成分的敏感性存在个体差异。这一系列的研究也可能 有助于开发新的AUD治疗方法，旨在恢复生理 与这些遗传变异相关的功能障碍。

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.