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。它通常是由处方阿片类药物（PO）药物的慢性疼痛患者的治疗引起的 并被认为是一个主要的公共卫生问题。仍存在开发OA风险的大小 有争议的，因为计算出的速率遭受了不精确且定义较差的术语。这是 在文献中的广泛估计值（POA）的强调，与1％相比差异很大 至> 40％的人在长期治疗慢性肌肉骨骼疼痛的长期治疗。尤其， 赋予POA风险的临床特征和遗传变异的数据很少。这个项目是 专注于确定传达POA风险的临床，遗传和神经特征。走向这个 最后，我们组建了一个多学科团队，研究了一个大量的患者人群 慢性非促进性肌肉骨骼疼痛和暴露于PO药物。我们将利用中央 Geisinger Health System的生物验证和电子健康记录（EHR）数据库进行大规模进行 比例基因组学研究和表型开发。通过与Regeneron的合作 药品，Geisinger Biobank目前包含大约110,000名参与者的DNA样品， 包括Illumina Omniexpressexome（HOEE）基因分型和整个外显子组序列（WES）数据， 包括常见和稀有变体，其中超过60,000名受试者。这个发现队列包含 成千上万的慢性肌肉骨骼疼痛患者的服用超过120毫克 吗啡超过3个月，他们被认为是患POA的高风险。使用EHR和 自我报告工具以开发案例定义和对POA的定量评分，我们将进行强大的基因组 广泛的协会研究（GWAS）。从顶级GWAS候选人中，我们将确定附近的基因并使用 WES数据以搜索可能有助于POA的稀有变体。使用此信息，我们将得出一个 POA的临床/遗传特征。通过整合神经成像数据，将增强此概况。正在进行的 在接下来的三名中，使用Regeneron的努力将在总共25万参与者中产生基因型和WES数据 多年，提供其他样本进行复制分析。在长期阿片类药物疗法的背景下 结果将允许鉴定有POA发展风险的慢性非促进性疼痛患者 提供预防措施的基础（非阿片类药物治疗，常规咨询，频繁尿液 药物筛选）和/或替代性疼痛专业治疗（针灸，刺激剂，神经阻滞）。这 个性化医学方法将通过最大程度地降低慢性POA的风险，从而产生重大的临床影响 疼痛人群。