Genetic Markers of Chronic Postsurgical Pain

项目概要/摘要 美国每年进行超过1亿例外科手术，其中高达80%的患者 术后疼痛手术后更高程度的疼痛与 慢性术后疼痛（CPSP）和慢性阿片类药物使用，导致疼痛流行， 每年的社会成本比癌症、心脏病和糖尿病的总和还要高。尽管有人 多种表型和环境因素已被确定为诱发发展 CPSP的遗传预测因子的数据少得多。以前的研究已经 受小样本或候选基因方法的限制，这些方法通常在不同的队列中不可重复。它 因此，仍然很难预测患者的遗传倾向于严重的术后疼痛或那些 将开发CPSP，并根据患者的特定遗传特征定制抗伤害性治疗。 易患疼痛。 这项工作的目标是通过使用最大和最好的基因型来克服这些限制。 队列迄今在术后疼痛遗传学研究中使用。超过3400名患者同时患有 术前/术后自我报告的疼痛和基因组测序数据将组成该队列。我们假设 1)基因和遗传途径中可识别的变异与术后疼痛相关，2）这些 变异可导致对药物治疗的不同反应。本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 术后疼痛然后，我将利用一个最精细的腰痛临床试验（NIH HEAL BACPAC）研究一种常见止痛药（度洛沙汀）反应性的遗传相关性。 这个指导以病人为导向的职业发展奖的候选人旨在补充他的 之前接受过大规模基因组学、生物统计学和临床试验设计方面的额外专业知识培训。在 为了促进未来与多学科同事的合作，与建议的 研究候选人也追求教学和经验的翻译科学培训有关他的 研究目的。密歇根大学承诺提供充足的资源来支持这一提议， 还得到了由遗传学，基因组学， 生物统计学，围手术期疼痛，临床试验设计和执行。这些研究将提供新的 深入了解慢性术后疼痛的遗传学，并为未来的个性化研究奠定基础。 疼痛治疗

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.