Clinical and Genetic Study of Prescription Opioid Addiction

处方阿片类药物成瘾的临床和遗传学研究

• 批准号: 9405766
• 负责人: Wade H Berrettini
• 金额: $ 84.52万
• 依托单位: GEISINGER CLINIC
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9405766
• 关键词: Accounting; Acupuncture Therapy; Address; Adult; Agreement; Appointment; Back Pain; Behavior; Biological; Blood specimen; Brain; Characteristics; Chronic; Clinical; Clinical Research; Collaborations; Community Health; Consent; Contracts; Counseling; DNA; Data; Databases; Development; Disease; Dose; Electronic Health Record; Emergency department visit; Enrollment; Ensure; Epidemic; Exposure to; Foundations; Genes; Genetic Variation; Genetic study; Genomics; Genotype; Goals; Grant; Health system; Image; Individual; Ingestion; Institutes; Intervention; Knowledge; Laboratories; Link; Literature; Medical; Medical Genetics; Medicine; Monitor; Morphine; Musculoskeletal Pain; Mutation; Nerve Block; Non-Malignant; Opiate Addiction; Opioid; Oxycodone; Pain; Pain Clinics; Participant; Patient Self-Report; Patients; Pennsylvania; Persons; Pharmaceutical Preparations; Pharmacologic Substance; Pharmacotherapy; Phenotype; Physicians; Population; Preclinical Drug Evaluation; Preventive measure; Primary Health Care; Probability; Public Health; Questionnaires; Recording of previous events; Records; Recruitment Activity; Recurrence; Reporting; Research; Resources; Risk; Risk Factors; Sampling; Services; Source; Standardization; Structure; System; Terminology; Testing; United States; Urine; Variant; Vicodin; addiction; base; biobank; candidate marker; chronic pain; cohort; economic cost; exome; exome sequencing; genetic profiling; genetic variant; genome wide association study; genomic data; health care delivery; high risk; medical specialties; multidisciplinary; neuroimaging; opioid use; patient population; personalized medicine; phenotypic data; predictive modeling; prescription opioid; rare variant; relating to nervous system; risk minimization; skeletal; tool

Opioid addiction (OA) is a multifactorial disease characterized by aberrant behavior related to obtaining and using opioids. It often arises from treatment of chronic pain patients with prescription opioid (PO) medications and is recognized as a major public health problem. The magnitude of the risk for developing OA remains controversial, because calculated rates suffer from imprecise and poorly defined terminology. This is underscored by the wide range of estimates of PO addiction (POA) in the literature which vary widely from 1% to > 40% of individuals treated long-term with POs for chronic non-progressive musculo-skeletal pain. Notably, there are few data on clinical characteristics and genetic variants that confer risk of POA. This project is focused on identifying the clinical, genetic, and neural characteristics which convey risk for POA. Towards this end, we have assembled a multi-disciplinary team to study a large patient population with a similar history of chronic non-progressive musculoskeletal pain and exposure to PO drugs. We will leverage the central biorepository and electronic health record (EHR) database of the Geisinger Health System to conduct large- scale genomics research and phenotype development. Through a collaboration with Regeneron Pharmaceuticals, the Geisinger biobank currently contains DNA samples on about 110,000 participants and includes both Illumina OmniExpressExome (HOEE) genotyping and whole exome sequence (WES) data, including common and rare variants, from over 60,000 of these subjects. This discovery cohort contains thousands of chronic musculoskeletal pain patients who have been taking greater than 120 mg-equivalents of morphine for more than 3 months and who are considered at high risk for developing POA. Using EHR and self-report tools to develop a case definition and quantitative scoring for POA, we will conduct a robust genome wide association study (GWAS). From the top GWAS candidates, we will identify nearby genes and use the WES data to search for rare variants that could contribute to POA. Using this information, we will derive a clinical/genetic profile of POA. This profile will be enhanced via integration of neuroimaging data. The on-going effort with Regeneron will yield genotype and WES data in a total of 250,000 participants over the next three years, providing additional samples for replication analyses. In the context of long-term opioid therapy, these results will permit identification of chronic non-progressive pain patients at risk for development of POA and provide the basis for preventative measures (non-opioid pharmacotherapy, regular counseling, frequent urine drug screens) and/or alternative pain specialty treatments (acupuncture, stimulators, nerve blocks). This personalized medicine approach will have major clinical impact by minimizing the risk for POA in the chronic pain population.

阿片类药物成瘾（OA）是一种多因素疾病，其特征是与获得和使用阿片类药物有关的异常行为。 使用阿片类药物它通常是由治疗慢性疼痛患者的处方阿片类药物（PO）药物引起的 并被认为是一个主要的公共卫生问题。发展OA的风险程度仍然是 由于计算的比率不精确，术语定义不明确，因此存在争议。这是 在文献中PO成瘾（POA）的估计范围很广，从1% > 40%的患者长期接受PO治疗慢性非进行性肌肉骨骼疼痛。值得注意地是， 很少有关于临床特征和遗传变异的数据，赋予POA的风险。这个项目是 重点是识别临床、遗传和神经特征，这些特征传达了POA的风险。为实现这一 最后，我们组建了一个多学科团队来研究具有类似病史的大量患者人群， 慢性非进行性肌肉骨骼疼痛和暴露于PO药物。我们将利用中央 Geisinger卫生系统的生物储存库和电子健康记录（EHR）数据库， 规模基因组学研究和表型开发。通过与Regeneron的合作 Geisinger生物银行目前包含约11万名参与者的DNA样本， 包括Illumina Omniplasmid外显子组（HOEE）基因分型和全外显子组序列（WES）数据， 包括常见的和罕见的变异，来自超过60，000名受试者。此发现队列包含 成千上万的慢性肌肉骨骼疼痛患者一直服用超过120毫克当量的 吗啡超过3个月，被认为是发展POA的高风险。使用EHR和 自我报告工具，以制定一个案件的定义和定量评分的POA，我们将进行一个强大的基因组 广泛关联研究（GWAS）。从最佳GWAS候选者中，我们将识别附近的基因，并使用 WES数据来搜索可能导致POA的罕见变异。利用这些信息，我们将得到一个 POA的临床/遗传特征。通过整合神经影像学数据，将增强这一概况。正在进行的 与Regeneron的合作将在未来三年内产生总共250，000名参与者的基因型和WES数据 年，为重复分析提供额外的样本。在长期阿片类药物治疗的背景下，这些 结果将允许识别有发生POA风险的慢性非进行性疼痛患者， 提供预防措施的基础（非阿片类药物治疗，定期咨询，频繁排尿 药物筛选）和/或替代的疼痛专业治疗（针灸、刺激器、神经阻滞）。这 个性化用药方法将通过最大限度地降低慢性POA患者的风险， 疼痛人群