Clinical and Genetic Study of Prescription Opioid Addiction

阿片成瘾(OA)是一种多因素疾病，其特征是与获得和 使用阿片类药物。它通常产生于用处方阿片类药物(PO)治疗慢性疼痛患者 并被认为是一个主要的公共卫生问题。开发办公自动化的风险仍然很大 有争议，因为计算的利率存在不准确和定义不明确的术语。这是 文献中对PO成瘾(POA)的估计范围很大，从1%到1%不等，这突显了这一点 40%的患者长期接受POS治疗，以治疗慢性非进行性肌肉骨骼疼痛。值得注意的是， 关于POA的临床特征和遗传变异的数据很少。这个项目是 重点是确定传递POA风险的临床、遗传和神经特征。朝向这个方向 最后，我们已经组建了一个多学科团队来研究一大批有类似病史的患者。 慢性非进行性肌肉骨骼疼痛和接触PO药物。我们将利用中央银行 盖辛格健康系统的生物储存库和电子健康记录(EHR)数据库，以进行大规模- 规模基因组学研究和表型开发。通过与Regeneron合作 制药公司，盖辛格生物库目前包含约110,000名参与者的DNA样本 包括Illumina OmniExpressExome(HOEE)基因分型和整个外显子组序列(WES)数据， 包括常见和罕见的变种，来自60,000多个这样的受试者。这一发现队列包含 数千名慢性肌肉骨骼疼痛患者服用超过120毫克当量的 服用吗啡3个月以上，并被认为是发生POA的高危人群。使用EHR和 自我报告工具为POA制定病例定义和量化评分，我们将进行强大的基因组 广谱关联研究(GWAS)。从排名靠前的GWA候选基因中，我们将识别附近的基因并使用 WES数据，寻找可能导致POA的罕见变异。使用此信息，我们将推导出一个 POA的临床/遗传学特征。这一特征将通过整合神经成像数据来增强。正在进行的 与Regeneron的合作将在未来三年内产生总计25万名参与者的基因和WES数据 几年来，为复制分析提供了额外的样本。在长期阿片类药物治疗的背景下，这些 结果将使识别慢性非进行性疼痛患者有发生POA和 为预防措施(非阿片类药物治疗、定期咨询、频繁排尿)提供依据 药物筛选)和/或替代的疼痛专科治疗(针灸、刺激器、神经阻滞)。这 个性化医疗方法将对临床产生重大影响，将使慢性阻塞性肺病患者的POA风险降至最低。 痛苦人口。

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.