Genetic Vulnerability for Sustained Multi-Substance Use in MVP

使用有害物质(酒精、烟草和/或处方阿片类药物)很常见，双胞胎研究表明 有很大的遗传作用。此外，酒精与烟草和烟草与阿片类药物的联合使用，通常 这表明这些行为的环境和遗传风险是重叠的。然而，确定了 遗传变异只解释了个体或组合的一小部分表型变异 物质使用。旨在确定跨物质(多效性)共享遗传路径的研究已经 结果不一致。寻找这些性状的基因面临的主要挑战之一是表型 不明确、测量偏差和不足以检测与之相关的微小遗传效应的统计能力 患有复杂的疾病。个别临床评估往往不能涵盖所有感兴趣的物质或 相关的临床因素(例如慢性疼痛)，并容易受到重大差异和偏见的影响，具体取决于 患者的健康状态，进行评估的临床环境，以及临床医生进行 评估。行政国际疾病分类(ICD)代码派生自这些 评估经常被使用，因为它们可以很容易地用于大量科目，但它们 可能会增加另一层不准确和偏见。独特的、丰富的、纵向的临床数据 退伍军人医疗保健管理局(VA)与百万退伍军人计划提供的数据相结合 (MVP)使我们能够克服这些限制。我们从广泛使用和重复使用的电子产品开始 基于健康记录(EHR)的指标：有害酒精的审核-C；当前/过去/从不吸烟状态 烟草；以及处方类阿片类药物的药房灌装/再灌装记录中的吗啡等效日剂量(Medd)。 从这些测量中得出的纵向总结指标在退伍军人老龄化中得到了初步验证 队列研究(VAS)，然后扩展到MVP，对照其他标准标准和 一个更大、更具普遍性的样本。重要的是，MVP还允许我们验证基因 标准标准，以前已确定的单核苷酸多态(SNPs)。这就产生了电子产品 基于健康记录(EHR)、经标准验证的纵向(EXCEL)表型 与酒精(1、2)、烟草(3)和处方的标准和含量标准更密切相关 阿片类药物[Becker，正在制备中]比其他表型更多。全基因组关联研究(GWAS) 使用EXCEL表型的酒精、烟草和阿片类药物正在进行中，两者都复制了先前的发现 并产生了许多与这些条件有关的SNPs和基因的新关联。我们共享了EXCEL 通过MVP维基和MVP表型工作组与Alpha和Beta项目组进行表型分析。我们是 目前正在进行烟草和酒精的EXCEL表型联合GWAS(赵和道)，并将很快 启动烟草和阿片类药物EXCEL表型的联合GWAS。因为慢性疼痛是强烈的 与物质使用相关，我们建议开发、验证并应用EXCEL表型的慢性 重复使用数字疼痛评定量表(NRS)测量疼痛并对照功能性疼痛进行验证 来自MVP调查的疼痛损害和基于先前识别的SNPs的遗传风险评分。在……里面 在接下来的四年里，我们将使用EXCEL表型来进行物质使用的GWAS(酒精、烟草、 和处方阿片类药物)和慢性疼痛，将慢性疼痛视为一种混淆，作为一种必要的暴露， 作为统一的基因纽带。我们预计，我们的分析将揭示遗传因素在多大程度上 慢性疼痛和物质使用之间的共同之处，并阐明了疼痛可能如何影响 物质相关性状的遗传风险因素。

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.