Genetic Markers of Chronic Postsurgical Pain

项目摘要/摘要 美国每年进行的外科手术超过1亿例，高达80%的患者 经历手术后的疼痛。术后疼痛程度较高与糖尿病的发生有关。 慢性术后疼痛(CPSP)和慢性阿片类药物的使用，助长了疼痛的流行，其 每年的社会成本比癌症、心脏病和糖尿病的总和还要高。尽管已经有了 多个表型和环境因素已被确定为易感的发展 在CPSP中，关于CPSP的遗传预测因素的数据要少得多。之前的研究一直是 受到小样本或候选基因方法的限制，这些方法在不同的队列中往往不能重复。它 因此，仍然很难预测那些遗传倾向于术后剧烈疼痛的患者或那些 将在开发CPSP和根据患者的特定基因量身定制抗伤害疗法方面取得进展 易患上疼痛。 拟议工作的目标是通过使用最大和最好的基因分型来克服这些限制 到目前为止在术后疼痛遗传学研究中使用的队列。超过3400名患者同时患有这两种疾病 手术前/术后自我报告的疼痛和基因组测序数据将组成这个队列。我们假设 1)基因和遗传途径的可识别变异与手术后疼痛有关，以及2)这些 变异可能会导致对药物治疗的不同反应。这项研究将使用候选基因， 全基因组关联研究和基于路径的分析，以确定影响 手术后疼痛。然后，我将利用下腰痛最细粒度的临床试验之一(NIH Hear Bacpac)研究一种常见止痛药(度洛西汀)反应的遗传关联。 这项以患者为导向的导师职业发展奖的候选人旨在补充他的 之前的培训具有大规模基因组学、生物统计学和临床试验设计方面的额外专业知识。在……里面 以促进未来与跨多个学科的同事的协作，与拟议的 学习应聘者，并进行与其相关的主动和体验式翻译科学培训 研究目的。密歇根大学已经投入了大量的资源来支持这项提议，它 还得到了一个由遗传学、基因组学、 生物统计学、围手术期疼痛和临床试验设计与实施。拟议的研究将提供新的 对慢性术后疼痛的遗传学的洞察，并为未来个性化研究奠定基础 疼痛疗法。

PROJECT SUMMARY / ABSTRACT Over 100 million surgical procedures are performed in the United States each year, with up to 80% of patients experiencing postoperative pain. Higher levels of pain after surgery are associated with the development chronic post-surgical pain (CPSP) and chronic opioid use, feeding into a pain epidemic that has a greater annual societal cost than that for cancer, heart disease, and diabetes combined. Though there have been multiple phenotypic and environmental factors that have been identified to be predisposing for the development of CPSP, much less data is available regarding genetic predictors of CPSP. Previous studies have been limited by small samples or candidate-gene approaches that are often not reproducible in different cohorts. It therefore remains difficult to predict patients genetically predisposed to severe postoperative pain or those who will progress to develop CPSP, and to tailor antinociceptive therapy to a patient’s specific genetic predisposition to the development of pain. The goal of the proposed work is to overcome these limitations by using the largest and most well genotyped cohort employed thus far in the study of postsurgical pain genetics. Over 3400 patients with both pre/postsurgical self-reported pain and genomic sequencing data will make up this cohort. We hypothesize that 1) identifiable variations in genes and genetic pathways are associated with postsurgical pain, and 2) these variations can contribute to differing responses to pharmacologic therapy. This study will use candidate gene, genome-wide association study, and pathway-based analyses to identify genetic variations that influence postsurgical pain. I will then leverage one of the most granular clinical trials of low back pain (NIH HEAL BACPAC) to study genetic associations of responsiveness for a common pain medication (duloxetine). The candidate for this mentored Patient-Oriented Career Development Award aims to complement his previous training with additional expertise in large-scale genomics, biostatistics, and clinical trial design. In order to facilitate future collaboration with colleagues across multiple disciplines, in concert with the proposed study the candidate with also pursue didactive and experiential translational science training related to his research aims. The University of Michigan has committed abundant resources to support this proposal, and it is also supported by a multidisciplinary mentorship group comprised of authorities in genetics, genomics, biostatistics, perioperative pain, and clinical trial design and execution. The proposed studies will provide novel insights into the genetics of chronic postoperative pain and form the basis for future studies into personalized pain therapy.