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

项目总结 慢性疼痛是下肢骨折患者的一个重大问题，其后果是 相当可观。患有骨折相关慢性疼痛的人会错过更多的工作天数，并更多地寻求医疗护理 通常比那些没有慢性疼痛的人更常见，并报告了高水平的疼痛强度、焦虑和 抑郁症。几个因素(例如，年龄较大、女性、受教育年限较少、疼痛强度较高) 被确定为慢性疼痛风险因素，但预测谁将经历慢性疼痛的能力较低 四肢骨折一直没有得到充分的研究。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差异，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队列中进行，并已成功 用于确定几种慢性疼痛状况的生物标记物(慢性内脏痛、骨关节炎痛和 急性腰背痛)。因此，生理、心理和基因表达的差异可能 解释了发生慢性疼痛的下肢骨折患者与那些 谁不会呢。这项研究将严格分型240例腓骨和/或胫骨骨折患者和 40名健康对照组，为期两年。结果将使用慢性疼痛分级来衡量 比例。参与者在过去3个月内的典型疼痛强度得分为1-30分将被分类 为慢性疼痛，最近3个月内报告没有疼痛(0)的人将被归类为没有疼痛 慢性疼痛。数据将使用直接进入多元Logistic回归分析进行分析，结果将 以赔率比的形式呈现。与基因表达数据的关联分析，考虑了年龄和性别 将进行潜在的个体间差异的调节，以确定表型和生物标志物 那些可能发展为慢性疼痛的人的签名。严格的表型鉴定与 遗传/基因组关联分析将增加我们对慢性阻塞性肺疾病致病危险因素的理解 并加速确定预防和/或预防和/或治疗的新靶点 管理创伤后慢性疼痛，最终提高生活质量并降低医疗成本。 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、疼痛灾难)、临床(疼痛强度、治疗)和社会人口因素(年龄、 种族、民族、收入、教育程度等)LOW后52周慢性疼痛表型的预测 四肢骨折。 目标2将验证基因表达差异将与慢性疼痛相关的假设 下肢骨折后的表型。分析将检查基因表达的变化有何不同 在基线和52周的极端表型之间进行比较，并构建基因表达改变的数据库 简介以及新的治疗目标和途径，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.