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

表征与酒精使用障碍遗传倾向相关的表型谱

• 批准号: 10559500
• 负责人: Rachel Lorraine Kember
• 金额: $ 12.35万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-10 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10559500
• 关键词: Adverse effects; Affect; African ancestry; Age; Alcohol consumption; Alcoholism; Alcohols; Anxiety Disorders; Biological; Biological Process; Cardiovascular Diseases; Categories; Clinical; Complex; Consumption; Data; Data Set; Development; Diabetes Mellitus; Diagnosis; Diagnostic; Disease; Drug Addiction; Early identification; Effectiveness; Environment; Environmental Exposure; Environmental Risk Factor; Epidemiologic Methods; Etiology; European ancestry; Exhibits; Exposure to; Foundations; Funding; Future; Gastrointestinal Diseases; Genetic; Genetic Heterogeneity; Genetic Models; Genetic Risk; Genomics; Goals; Gout; Height; Heterogeneity; Individual; Intervention; Interview; K-Series Research Career Programs; Knowledge; Lipids; Lung diseases; Measures; Medical; Medical Genetics; Mental disorders; Methods; Mood Disorders; Pathway interactions; Phenotype; Population; Prevention strategy; Records; Reporting; Research; Research Activity; Research Personnel; Resources; Risk; Risk Marker; Role; Sampling; Schedule; Schizophrenia; Severities; Social Behavior; Stratification; Structure; Subgroup; Substance Use Disorder; Testing; Tissues; Training; Training Activity; Training Programs; Translations; United States; accurate diagnosis; addiction; alcohol abuse therapy; alcohol exposure; alcohol use disorder; career; childhood adversity; comorbidity; design; disorder risk; drinking; ethnic diversity; gene environment interaction; genetic analysis; genetic epidemiology; genetic variant; genome wide association study; genome-wide; innovation; insight; personalized medicine; phenome; phenomenological models; phenotypic data; pleiotropism; polygenic risk score; prevent; psychiatric comorbidity; risk prediction; risk prediction model; risk variant; skill acquisition; skills; social; trait; trauma exposure; treatment program

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.

项目摘要 酒精使用障碍（AUD）患者的精神和医学共病风险增加 紊乱该病的合并症对AUD的诊断和治疗都提出了挑战， 合并症的病因还不清楚。最近的大规模全基因组关联 研究（GWAS）已经确定了AUD和其他几种特征的常见风险标志物。遗传相关 AUD和精神疾病之间的遗传学研究已经确定了多个基因座的遗传重叠。这些发现 表明存在增加多种疾病风险的共同位点或生物途径。识别 这些基因座将为共病疾病的病因学途径提供深入的了解， 准确诊断、分类、预防和治疗AUD以及同时发生的医学和精神疾病。 迄今为止的研究一直受到缺乏具有良好表征的表型信息的资源的限制 以及大量个体的基因数据。本K奖申请中提出的项目使用 在> 15，000人的样本中通过全面的精神病学访谈时间表收集的信息 富集物质使用障碍，以创建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评分将用于表征遗传易感性 疾病。我们将：1）确定与AUD遗传易感性相关的表型; 2）确定是否遗传 对其他性状的易感性与AUD相关; 3）结合生物信息以识别 基础共病风险;和4）包括环境因素，以测试基因-环境相互作用。我们 种族多样的样本（非洲和欧洲血统的数量几乎相等）将使我们能够建立 两个祖先群体中合并症的遗传易感性。在进行这项研究的背景下， 该职业发展奖将使申请人获得现象学的基础培训， 和精神病表型的评估，以便将表型记录准确地翻译成 用于高通量遗传分析的数据集。此外，申请人将获得必要的技能， 遗传流行病学，以开发遗传易感性和共病模型。拟议项目将 为未来的研究提供基础，使个体分层进入个性化治疗 基于他们的疾病病因学的计划，沿着早期识别风险个体的承诺， 以干预战略为目标。