Pharmacogenetic Study of Opioid Agonist Treatments in MVP

阿片类激动剂治疗 MVP 的药物遗传学研究

• 批准号: 9890783
• 负责人: KYLE Matthew KAMPMAN
• 金额: --
• 依托单位: PHILADELPHIA VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9890783
• 关键词: Absence of pain sensation; Acute; Acute Pain; Acute pain management; Adverse effects; Affect; Age; Alleles; Analgesics; Biological Markers; Body Weight; Buprenorphine; Cessation of life; Chronic; Clinical; Data; Data Set; Death Rate; Dose; Drug Prescriptions; Drug Screening; Drug usage; Effectiveness; Epidemic; General Population; Genotype; Guidelines; Health system; Inpatients; Maintenance; Maintenance Therapy; Meta-Analysis; Methadone; Methodology; Minor; Modeling; Morphine; Naltrexone; Operative Surgical Procedures; Opioid; Opioid Analgesics; Opioid Antagonist; Opioid agonist; Opioid replacement therapy; Outpatients; Overdose; Pain; Pain management; Patient Recruitments; Patients; Perioperative; Pharmaceutical Preparations; Pharmacogenetics; Pharmacy facility; Phenotype; Population; Population Group; Postoperative Pain; Postoperative Period; Prevalence; Procedures; Prospective Studies; Publishing; Receptor Gene; Records; Regression Analysis; Research Design; Running; Sampling; Series; Suicide; System; Testing; Treatment Protocols; United States; United States Food and Drug Administration; Urine; Validation; Variant; Veterans; Veterans Health Administration; addiction; chronic pain; chronic pain management; clinical predictors; dosage; genetic predictors; genetic variant; genome wide association study; genome-wide; hip replacement arthroplasty; improved; indexing; knee replacement arthroplasty; methadone patient; methadone treatment; morphine equivalent; mu opioid receptors; non-cancer pain; novel; opioid abuse; opioid agonist therapy; opioid epidemic; opioid misuse; opioid mortality; opioid overdose; opioid use; opioid use disorder; overdose death; overdose risk; pain patient; pediatric patients; personalized medicine; polygenic risk score; prescription opioid; programs; prospective; relapse risk; sex; suicide rate; trend

1. Objectives: In the US, opioids are widely used for maintenance treatment of opioid use disorder (OUD) and to manage acute and chronic pain. Over the past three decades, efforts to treat pain aggressively in the absence of objective markers to guide opioid prescribing have led to a quadrupling of opioid prescriptions, an epidemic of opioid misuse and abuse, and a tripling of the overdose death rate in the general population and among Veterans. The overarching objective of this proposal is to identify valid biomarkers of opioid sensitivity, which can be used to guide the safe and effective use of opioid agonists to treat both OUD and pain. Following the identification of pharmacogenetic predictors, we will validate the findings in an independent MVP sample. The findings will inform the treatment of OUD using buprenorphine and the management of acute and chronic pain with prescription opioids. 2. Research Design: We will conduct a series of genome-wide association studies (GWASs) using data from the Million Veteran Program (MVP). The initial GWAS will be conducted in the ~300,000 Veterans for whom GWAS data are currently available; genotypes from ~100,000 newly recruited participants will be used to replicate the initial findings. 3. Methodology: We will conduct separate GWASs of: 1) the effectiveness and dosing of buprenorphine maintenance, using urine drug screen data and VA pharmacy dosing records; 2) mean maximal morphine equivalent dose (MEDD) in treating acute pain in the perioperative period, separately for different classes of opioids, using inpatient pharmacy records for Veterans who have undergone hip or knee arthroplasty; and 3) opioid analgesic dosing for the treatment of chronic pain, using outpatient pharmacy records to estimate mean MEDD for the month of heaviest opioid use. Analyses will also be run both separately by opioid class (followed by meta-analysis) and with longitudinal trajectories of opioid use. Regression analyses will examine the proportion of urine tests positive for opioids and usual daily dosage of buprenorphine for maintenance, mean maximal MEDD in inpatient analyses, and MEDD and opioid use trajectories in outpatient analyses. Imputed minor allele dosage, age, body weight, sex, and the top ancestry principal components will serve as covariates, along with covariates relevant to each of the specific aims. We will conduct all GWAS analyses separately by population group and combine the results by meta-analysis. Polygenic risk score (PRS) analysis will serve to increase the utility of the GWAS findings. 4. Impact/Significance: The identification and validation of genetic variants and PRS scores will be used to generate indices that can be evaluated prospectively as guides to prescribers in their selection of the optimal opioid agonist and dosage for buprenorphine maintenance and opioid analgesia. Personalizing the treatment of OUD can increase its effectiveness and reduce relapse risk and adverse effects of maintenance therapy. Genetic predictors of opioid analgesic dosing could help to reduce both excessive dosing of these widely used medications and their diversion, abuse, and overdose risk, and under dosing, which provides inadequate pain control.

1.目的：在美国，阿片类药物广泛用于阿片类药物使用的维持治疗 疾病（OUD）和管理急性和慢性疼痛。在过去的三十年里， 在缺乏指导阿片类药物的客观标志物的情况下积极治疗疼痛的努力 处方导致阿片类药物处方的四倍，阿片类药物的流行 误用和滥用，以及普通人群中过量死亡率的三倍 在退伍军人中，本提案的总体目标是确定有效的 阿片类药物敏感性的生物标志物，可用于指导安全有效的 使用阿片激动剂治疗OUD和疼痛。在确定了 药物遗传学预测因子，我们将在独立的MVP中验证结果 sample.这些发现将为使用丁丙诺啡治疗OUD提供信息， 用处方阿片类药物管理急性和慢性疼痛。 2.研究设计：我们将进行一系列全基因组关联研究 （GWAS）使用百万退伍军人计划（MVP）的数据。最初的GWAS将 在GWAS数据目前被 可用;来自约100，000名新招募参与者的基因型将用于 重现最初的发现 3.方法：我们将进行单独的GWAS：1）有效性和剂量 丁丙诺啡维持，使用尿液药物筛选数据和VA药房给药 记录; 2）治疗急性疼痛的平均最大吗啡等效剂量（MEDD） 围手术期，分别为不同类别的阿片类药物，使用住院 接受髋关节或膝关节置换术的退伍军人的药房记录;以及3） 使用门诊药房治疗慢性疼痛的阿片类镇痛剂剂量 记录，以估计阿片类药物使用最严重月份的平均MEDD。分析将 也可以分别按阿片类药物类别（随后进行荟萃分析）和 阿片类药物使用的纵向轨迹。回归分析将检查 阿片类药物尿检阳性的比例和 维持、住院分析中的平均最大MEDD以及MEDD和阿片类药物使用 门诊病人分析的轨迹。插补次要等位基因剂量、年龄、体重、性别， 和最高祖先主成分将作为协变量，沿着 与每个特定目标相关的协变量。我们将进行所有GWAS分析 分别按人群分组，并通过荟萃分析将结果联合收割机合并。多基因 风险评分（PRS）分析将有助于提高GWAS结果的实用性。 4.影响/意义：遗传变异和PRS的识别和验证 分数将用于生成可前瞻性评估的指数， 指导处方医生选择最佳阿片类激动剂和剂量， 丁丙诺啡维持和阿片类镇痛。个性化治疗OUD 可以增加其有效性，减少复发风险和不良影响， 维持治疗阿片类镇痛药剂量的遗传预测因素可能有助于 减少这些广泛使用的药物的过量剂量及其转移， 滥用和过量风险，以及剂量不足，这提供了不充分的疼痛控制。