Physiological, psychological, and genomic factors that predict the transition from acute to chronic pain in patients with traumatic lower extremity fracture

项目摘要 慢性疼痛是下肢骨折患者的一个重要问题，其后果是 相当可观患有与糖尿病相关的慢性疼痛的人会错过更多的工作日，并更多地寻求医疗护理 比那些没有慢性疼痛的人更频繁，沿着报告高水平的疼痛强度，焦虑， 萧条有几个因素（如年龄较大、女性、受教育年限较短、疼痛强度高） 被确定为慢性疼痛的危险因素，但预测谁将经历慢性疼痛后的能力较低 四肢骨折研究不足。虽然许多患者在骨折部位出现慢性疼痛， 在症状的数量、类型和严重程度上存在变异性，这表明组学机制可能是 关键贡献者。基因表达谱可以在较小的群体中进行，并且已经成功地进行了基因表达谱分析。 用于鉴定几种慢性疼痛状况（慢性内脏疼痛、骨关节炎疼痛和 急性腰痛）。因此，生理、心理和基因表达的差异可能 解释下肢骨折患者发生慢性疼痛与 谁不喜欢本研究将对240例腓骨和/或胫骨骨折患者进行严格的表型分析， 40名健康对照组为期两年。将使用慢性疼痛分级测量结局 规模将对过去3个月内特征性疼痛强度评分为1 - 30分的受试者进行分类 患有慢性疼痛，而在过去3个月内没有报告疼痛（0）的患者将被归类为没有 慢性疼痛将使用直接进入的多元逻辑回归分析对数据进行分析，结果将 以比值比表示。与基因表达数据的关联分析，考虑年龄和性别， 个体间差异的潜在调节因子，以确定表型和生物标志物 那些有可能患上慢性疼痛的人的特征。严格的表型分析与 遗传/基因组关联分析将增加我们对慢性疾病的危险因素的理解， 下肢骨折后疼痛，并加速识别新的治疗靶点，以预防和/或 管理创伤后慢性疼痛，最终提高生活质量，降低医疗成本。 目标1将检查生理（外周感觉神经功能），心理（焦虑，抑郁 症状、睡眠、疼痛恶化）、临床（疼痛强度、治疗）和社会人口因素（年龄， 种族、民族、收入、教育等）在较低的治疗后52周时预测慢性疼痛表型 四肢骨折 目的2将检验基因表达差异与慢性疼痛相关的假设 表型下肢骨折。分析将研究基因表达的变化如何不同 在基线和52周的极端表型之间， 以及新的治疗靶点和途径，以更好地管理疼痛。

PROJECT SUMMARY Chronic pain is a significant problem for patients with lower extremity fractures, and the consequences are substantial. Individuals with fracture-related chronic pain miss more days of work, and seek medical care more frequently than those without chronic pain, along with reporting high levels of pain intensity, anxiety, and depression. Several factors (e.g. older age, being female, fewer years of education, high pain intensity) have been identified as chronic pain risk factors, but the ability to predict who will experience chronic pain after lower extremity fracture has been understudied. While many patients develop chronic pain at the site of fracture, there is variability in the number, type, and severity of symptoms, suggesting that -omics mechanisms may be key contributors. Gene expression profiling can be conducted in smaller cohorts and has been successfully used to identify biomarkers of several chronic pain conditions (chronic visceral pain, osteoarthritis pain, and acute low back pain). Thus, physiological, psychological and differences in gene expression may account for the variability in lower extremity fracture patients who develop chronic pain versus those who do not. This study will rigorously phenotyping a cohort of 240 fibula and/or tibia fracture patients and a cohort of 40 healthy controls for two years. The outcome will be measured using the Chronic Pain Grading Scale. Participants scoring 1 - 30 on the characteristic pain intensity score in the last 3 months will be classified as having chronic pain, and those reporting no pain (0) in the last 3 months will be classified as having no chronic pain. Data will be analyzed using a direct-entry multiple logistic regression analysis and the results will be presented as odds ratios. Association analyses with gene expression data, accounting for age and sex as potential moderators of inter-individual differences, will be conducted to identify phenotypic and biomarker signatures of those who are likely to develop chronic pain. The combination of rigorous phenotyping with genetic/genomic association analyses will increase our understanding of the contributing risk factors of chronic pain after lower extremity fracture and accelerate the identification of new therapeutic targets to prevent and/or manage post-trauma chronic pain, ultimately leading to improved quality of life and decreased healthcare cost. Aim 1 will examine physiological (peripheral sensory nerve function), psychological (anxiety, depressive symptoms, sleep, pain catastrophizing), clinical (pain intensity, treatment), and sociodemographic factors (age, race, ethnicity, income, education, etc.) predictive of chronic pain phenotype at 52 weeks following lower extremity fracture. Aim 2 will test the hypothesis that differences in gene expression will be associated with the chronic pain phenotype following lower extremity fracture. Analyses will examine how changes in gene expression differ between extreme phenotypes at baseline and 52 weeks and construct a database of altered gene expression profiles as well as novel therapeutic targets and pathways for better pain management.