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

预测创伤性下肢骨折患者从急性疼痛转变为慢性疼痛的生理、心理和基因组因素

• 批准号: 10178118
• 负责人: SUSAN G DORSEY
• 金额: $ 61.08万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-10 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10178118
• 关键词: Accounting; Acute; Age; Amyloid beta-Protein; Ankle Fracture; Anxiety; Biological; Biological Markers; Blood; Caring; Characteristics; Chronic; Chronic disabling pain; Data; Databases; Detection; Development; Education; Emergency department visit; Emotional; Enrollment; Epilepsy; Esthesia; Ethnic Origin; Female; Fiber; Fracture; Fracture Healing; Gene Expression; Gene Expression Profiling; Genes; Genetic; Genomics; Health Care Costs; Hyperalgesia; Hypesthesia; Income; Individual; Individual Differences; Injury; Liver diseases; Logistic Regressions; Longitudinal Studies; Low Back Pain; Lower Extremity; Lower Extremity Fracture; Measures; Mechanics; Medical; Mental Depression; Migraine; Mission; Modeling; Nerve Regeneration; Neurodegenerative Disorders; Nociception; Odds Ratio; Outcome; Pain; Pain intensity; Pain management; Participant; Pathway interactions; Patients; Perception; Peripheral; Peripheral Nerves; Persistent pain; Phenotype; Physiological; Pilot Projects; Play; Predictive Factor; Predisposition; Psychological Factors; Quality of life; RNA; Race; Regression Analysis; Reporting; Risk; Risk Factors; Role; Sample Size; Sensory; Severities; Site; Sleep; Source; Strategic Planning; Symptoms; Testing; Time; Tissues; Traumatic injury; Visceral pain; Whole Blood; Work; afferent nerve; allodynia; biomarker signature; chronic pain; chronic pain management; chronic painful condition; clinical pain; cohort; depressive symptoms; differential expression; experience; fibromyalgia pain; fibula; genome wide association study; improved; limb injury; multiple omics; new therapeutic target; osteoarthritis pain; pain catastrophizing; peripheral nerve damage; phenotypic biomarker; post-trauma; prevent; prospective; psychologic; sex; social; sociodemographic factors; somatosensory; spontaneous pain; tibia; transcriptome sequencing

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.

项目概要 慢性疼痛是下肢骨折患者的一个重要问题，其后果是 重大的。患有与骨折相关的慢性疼痛的人会更多地缺勤，并更多地寻求医疗护理 比那些没有慢性疼痛的人更频繁，并且报告了高水平的疼痛强度、焦虑和 沮丧。有几个因素（例如年龄较大、女性、受教育年限较少、疼痛强度高） 已被确定为慢性疼痛的危险因素，但预测谁会经历慢性疼痛的能力较低 四肢骨折尚未得到充分研究。虽然许多患者在骨折部位出现慢性疼痛， 症状的数量、类型和严重程度存在差异，表明组学机制可能是 关键贡献者。基因表达谱分析可以在较小的群体中进行，并且已经成功地 用于识别多种慢性疼痛病症（慢性内脏痛、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 解释了发生慢性疼痛的下肢骨折患者与那些发生慢性疼痛的患者之间的差异 谁不。这项研究将对 240 名腓骨和/或胫骨骨折患者以及一名 为期两年的 40 名健康对照队列。结果将使用慢性疼痛分级来衡量 规模。过去 3 个月内特征疼痛强度评分为 1 - 30 分的参与者将被分类 患有慢性疼痛，过去 3 个月报告无疼痛 (0) 的人将被归类为无疼痛 慢性疼痛。将使用直接输入多元逻辑回归分析来分析数据，结果将 以优势比的形式呈现。与基因表达数据的关联分析，将年龄和性别考虑为 个体间差异的潜在调节因素，将被用来识别表型和生物标志物 那些可能患有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病危险因素的理解 减轻下肢骨折后的疼痛，并加速确定新的治疗靶点以预防和/或 管理创伤后慢性疼痛，最终提高生活质量并降低医疗费用。 目标 1 将检查生理（周围感觉神经功能）、心理（焦虑、抑郁） 症状、睡眠、疼痛灾难化）、临床（疼痛强度、治疗）和社会人口因素（年龄、 种族、民族、收入、教育程度等）可预测 52 周后的慢性疼痛表型 四肢骨折。 目标 2 将检验基因表达差异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 概况以及新的治疗靶点和更好的疼痛管理途径。