Genetic Vulnerability for Sustained Multi-Substance Use in MVP

MVP 中持续使用多种物质的遗传脆弱性

• 批准号: 10421257
• 负责人: Amy Caroline Justice
• 金额: --
• 依托单位: VA CONNECTICUT HEALTHCARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10421257
• 关键词: Address; Admixture; Affect; African American population; Aging; Alcohol Phenotype; Alcohol consumption; Alcohols; American; Behavior; Cessation of life; Clinical; Clinical Data; Clinical assessments; Cohort Studies; Complex; Computer Analysis; Data; Data Reporting; Development; Diagnosis; Disease; Dose; Electronic Health Record; Enrollment; Environmental Risk Factor; European; Frequencies; Gene Frequency; General Population; Genes; Genetic; Genetic Predisposition to Disease; Genetic Risk; Genetic Variation; Genetic study; Health; Healthcare; Heritability; Individual; International Classification of Disease Codes; Joints; Latino Population; Light; Link; Measurement; Measures; Mediation; Meta-Analysis; Modeling; Opioid; Pain; Participant; Pathway interactions; Patient Self-Report; Patients; Pharmacy facility; Phenotype; Population; Population Group; Preparation; Principal Component Analysis; Records; Risk; Risk Behaviors; Risk Factors; Role; Sample Size; Sampling; Sensitivity and Specificity; Series; Sex Differences; Single Nucleotide Polymorphism; Smoking Status; Substance Use Disorder; Surveys; Techniques; Time; Tobacco; Tobacco Phenotype; Tobacco use; Twin Studies; United States; Validation; Variant; Veterans; Work; base; chronic pain; chronic pain management; clinically relevant; disability; functional disability; genetic risk factor; genetic variant; genome wide association study; high risk; indexing; individual variation; innovation; interest; morphine equivalent; never smoking; novel; opioid use; pain score; pleiotropism; polysubstance use; prescription opioid; programs; psychiatric genomics; routine care; screening; sex; substance use; trait; wiki

Harmful substance use (alcohol, tobacco, and/or prescription opioids) is common and twin studies suggest a substantial genetic role. Further, combined use of alcohol with tobacco and tobacco with opioids, commonly occurs suggesting that environmental and genetic risks for these behaviors overlap. However, identified genetic variation explains only a small proportion of the phenotypic variation for individual or combined substance use. Studies aiming to identify shared genetic pathways across substances (pleiotropy) have yielded inconsistent results. Among the major challenges to gene finding for these traits are phenotypic ambiguity, measurement bias, and inadequate statistical power to detect the small genetic effects associated with complex disorders. Individual clinical assessments often do not capture all substances of interest or relevant clinical factors (e.g., chronic pain) and are subject to substantial variation and bias depending upon the patient's health state, the clinical setting in which the assessment occurs, and the clinician making the assessment. Administrative International Classification of Diseases (ICD) codes derived from these assessments are frequently used because they are readily available for large numbers of subjects, but they can add another layer of inaccuracy and bias. The unique, rich, longitudinal clinical data available within the Veterans Healthcare Administration (VA) combined with data available from the Million Veteran Program (MVP) is enabling us to overcome these limitations. We began with widely available and repeated electronic health record (EHR)-based metrics: AUDIT-C for hazardous alcohol; current/past/never smoking status for tobacco; and morphine equivalent daily dose (MEDD) from pharmacy fill/refill records for prescription opioids. Longitudinal summary metrics derived from these measures were initially validated in the Veterans Aging Cohort Study (VACS) and then extended to MVP, validating them against additional criterion standards and in a much larger, more generalizable, sample. Importantly, MVP also allowed us to validate against genetic criterion standards, previously identified single nucleotide polymorphisms (SNPs). This yielded Electronic Health Record (EHR)-based, CritErion-validated Longitudinal (ExCEL) phenotypes that were substantially more strongly associated with criterion and content standards for alcohol (1, 2), tobacco (3), and prescription opioids [Becker, in preparation] than alternative phenotypes. Genome-wide association studies (GWASs) of alcohol, tobacco, and opioids using ExCEL phenotypes are underway and have both reproduced prior findings and yielded many novel associations of SNPs and genes with these conditions. We have shared ExCEL phenotypes with Alpha and Beta project groups via the MVP wiki and the MVP Phenotype Workgroup. We are currently conducting joint GWASs of ExCEL phenotypes for tobacco and alcohol (Zhao and Dao) and will soon initiate joint GWASs of ExCEL phenotypes for tobacco and opioids. Because chronic pain is strongly associated with substance use, we propose to develop, validate, and apply an ExCEL phenotype of chronic pain using repeated measures of the Numeric Pain Rating Scale (NRS) and validating it against functional impairment due to pain from the MVP survey and a genetic risk score based on previously identified SNPs. In the next four years, we will use ExCEL phenotypes to conduct GWASs of substance use (alcohol, tobacco, and prescription opioids) and chronic pain, treating chronic pain as a confounder, as a necessary exposure, and as a unifying genetic link. We expect that our analyses will reveal the extent to which genetic factors are shared between chronic pain and substance use and shed light on how pain may influence the expression of genetic risk factors for substance-related traits.

有害物质使用（酒精，烟草和/或处方阿片类药物）很常见，双胞胎研究表明 实质性遗传作用。此外，酒精与烟草和烟草的联合使用与阿片类药物相结合，通常 发生的情况表明，这些行为的环境和遗传风险重叠。但是，确定 遗传变异仅解释了个体或组合的表型变异的一小部分 使用物质。旨在鉴定跨物质（多效性）共享遗传途径的研究具有 产生不一致的结果。这些特征的基因发现的主要挑战之一是表型 模棱两可，测量偏差和统计能力不足，无法检测相关的小遗传效应 患有复杂的疾病。个人临床评估通常不会捕获所有感兴趣的物质或 相关的临床因素（例如，慢性疼痛），并根据 患者的健康状况，进行评估的临床环境以及临床医生使 评估。从这些疾病的行政国际疾病分类（ICD）代码 经常使用评估，因为它们很容易适用于大量主题，但它们 可以添加另一层的不准确和偏见。独特的，丰富的纵向临床数据可用 退伍军人医疗保健管理局（VA）结合了百万退伍军人计划的数据 （MVP）使我们能够克服这些局限性。我们从广泛可用并重复电子开始 基于健康记录（EHR）的指标：危险酒精的审计-C；当前/过去/永不吸烟状态 烟草;处方阿片类药物的药学填充/补充记录中的吗啡等效的每日剂量（MEDD）。 从这些措施中得出的纵向摘要指标最初是在退伍军人衰老中验证的 队列研究（VACS），然后扩展到MVP，根据其他标准验证它们 一个更大，更具普遍的样本。重要的是，MVP还允许我们验证遗传 标准标准，以前鉴定出单核苷酸多态性（SNP）。这产生了电子 健康记录（EHR），基于标准验证的纵向（Excel）表型 与酒精（1、2），烟草（3）和处方的标准和内容标准更加密切相关 阿片类药物[Becker，在制备中]而不是替代表型。全基因组关联研究（GWASS） 使用Excel表型的酒精，烟草和阿片类药物正在进行中，并且都重现了先前的发现 并产生了许多新型SNP和基因与这些条件的关联。我们共享了Excel 通过MVP Wiki和MVP表型工作组与Alpha和Beta项目组的表型。我们是 目前正在为烟草和酒精（Zhao and dao）进行Excel表型的关节gwass，并将很快 启动烟草和阿片类药物的Excel表型的联合GWASS。因为慢性疼痛强烈 与药物使用相关，我们建议开发，验证和应用慢性的Excel表型 使用重复测量数字疼痛评分量表（NRS）的疼痛，并针对功能进行验证 MVP调查疼痛和基于先前确定的SNP的遗传风险评分引起的损害。在 接下来的四年，我们将使用Excel表型进行药物使用的GWASS（酒精，烟草，， 和处方阿片类药物）和慢性疼痛，将慢性疼痛视为混杂因素，是必要的暴露 并作为统一的遗传联系。我们预计我们的分析将揭示遗传因素在多大程度上 在慢性疼痛和使用物质使用之间共享，并阐明疼痛如何影响表达 与物质相关性状的遗传危险因素。