Characterizing the phenotypic spectrum associated with genetic liability for alcohol use disorder

项目总结 酒精使用障碍(AUD)患者患精神疾病和内科疾病的风险增加 精神错乱。疾病的共病对AUD的诊断和治疗都提出了挑战，但 共病的病因还不是很清楚。最近的大规模全基因组关联 研究(GWAS)已经确定了AUD和其他几个特征的共同风险标记。遗传相关 AUD和精神疾病之间的关系已经确定了多个基因座上的基因重叠。这些发现 提示有共同的基因或生物途径会增加患多种疾病的风险。识别 这些基因座将提供对共病障碍的病因途径的洞察，并可能推动努力 准确诊断、分类、预防和治疗AUD及其共生的医疗和精神疾病。 到目前为止，研究一直受到缺乏具有良好表型信息的资源的限制 以及大量个体的基因数据。此K奖项申请中提出的项目使用 通过全面的精神病学面谈计划收集的信息，样本为15,000人 丰富物质使用障碍以创建用于表型范围关联的多表型数据集 分析。同一组个体的多基因风险分数将被用来表征遗传风险 治疗疾病。我们将：1)确定与AUD遗传易感性相关的表型；2)确定 其他特征的易感性与AUD有关；3)结合生物信息以确定 潜在的共病风险；4)包括环境因素，以测试基因与环境的相互作用。我们的 种族多样化的样本(非洲和欧洲血统几乎相等)将使我们能够确定 在两个祖先群体中共病的遗传易感性。在进行这项研究的背景下， 这一职业发展奖将使申请者能够获得现象学方面的基础培训。 和精神病学表型的评估，以允许将表型记录准确地转换为 用于高通量遗传分析的数据集。此外，申请者还将获得必要的技能 遗传流行病学，以开发遗传责任和共病疾病的模型。拟议的项目将 为未来的研究奠定了基础，这些研究将允许对个体进行分层并进行个性化治疗 基于他们的疾病病因的计划，以及承诺及早识别高危个人 以干预策略为目标。

PROJECT SUMMARY Individuals with alcohol use disorder (AUD) are at increased risk of comorbid psychiatric and medical disorders. Comorbidity of disease poses a challenge to both the diagnosis and treatment of AUD, but the etiologic factors underlying comorbidity are not well understood. Recent large-scale genome-wide association studies (GWAS) have identified common risk markers for AUD and several other traits. Genetic correlations between AUD and psychiatric disorders have identified genetic overlap across multiple loci. These findings suggest that there are common loci or biological pathways that increase risk for multiple disorders. Identifying these loci will provide insight into the etiologic pathways for comorbid disorders, and could advance efforts to accurately diagnose, categorize, prevent, and treat AUD and co-occurring medical and psychiatric conditions. Research to date has been limited by the lack of resources with well characterized phenotypic information alongside genetic data for large numbers of individuals. The project proposed in this K-award application uses information collected with a comprehensive psychiatric interview schedule in a sample of >15,000 individuals enriched for substance use disorders to create a multi-phenotype dataset for phenome-wide association analysis. Polygenic risk scores for the same set of individuals will be used to characterize the genetic liability for disease. We will: 1) identify phenotypes associated with genetic liability for AUD; 2) identify whether genetic liability for other traits is associated with AUD; 3) incorporate biological information to identify pathways that underlie comorbid risk; and 4) include environmental factors to test for gene-environment interactions. Our ethnically diverse sample (nearly equal numbers of African and European ancestry) will allow us to establish the genetic liability for comorbidities in both ancestral populations. In the context of conducting this research, this career development award will enable the applicant to obtain fundamental training in the phenomenology and assessment of psychiatric phenotypes to allow the accurate translation of the phenotypic records into a dataset for high-throughput genetic analysis. Additionally, the applicant will acquire the necessary skills in genetic epidemiology to develop models for genetic liability and comorbid disease. The proposed project will provide a foundation for future studies that would allow stratification of individuals into personalized treatment programs based on their disease etiology, along with the promise of early identification of at-risk individuals to target with intervention strategies.