Brain-based and clinical phenotyping of pain pharmacotherapy in knee OA

膝关节 OA 疼痛药物治疗的脑基和临床表型

• 批准号: 10735060
• 负责人: Apkar Vania Apkarian
• 金额: $ 72.37万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10735060
• 关键词: Aftercare; Age; Anatomy; Anxiety; Attention; Back; Behavioral; Biochemical; Biological Markers; Blinded; Brain; Brain imaging; C-reactive protein; Caring; Characteristics; Clinic; Clinical; Clinical Data; Clinical Trials; Collection; Data; Degenerative polyarthritis; Development; Disease; Emotional; Etiology; Exposure to; Formulation; Funding Opportunities; Future; Goals; Image; Individual; Inflammation; Intervention; Joints; Knee; Knee Osteoarthritis; Magnetic Resonance Imaging; Measures; Mental Depression; Modality; Modeling; Naproxen; Nociception; Non-Steroidal Anti-Inflammatory Agents; Norepinephrine; Pain; Pain intensity; Parents; Participant; Pathway interactions; Patient Outcomes Assessments; Patient Selection; Patient risk; Patients; Peripheral; Personality; Persons; Pharmaceutical Preparations; Pharmacotherapy; Phenotype; Physiological; Placebo Effect; Placebos; Prognostic Factor; Prognostic Marker; Property; Prospective Studies; Psychological Factors; Psychometrics; Questionnaires; Randomized; Randomized, Controlled Trials; Research Project Grants; Risk; Sensory; Serotonin; Serum; Site; Specificity; Spinal Cord; Testing; Therapeutic; Therapeutic Agents; Therapeutic Intervention; Validation; Work; arm; brain based; brain circuitry; central sensitization; chronic pain; clinical biomarkers; clinical outcome measures; clinical phenotype; conditioning; cost effective; daily pain; demographics; design; duloxetine; emotional functioning; epidemiology study; improved; indexing; individual patient; individual variation; inhibitor; innovation; machine learning prediction; neurosensory; novel therapeutics; opioid use; osteoarthritis pain; pain perception; pain relief; patient oriented; patient response; patient variability; personalized medicine; pharmacologic; predictive modeling; prognostic; prognostication; prospective; psychologic; radiological imaging; randomized trial; research clinical testing; response; response biomarker; reuptake; sex; side effect; specific biomarkers; success; treatment response

ABSTRACT This proposal is in response to the funding opportunity Research Project Grant (Parent R01 Clinical Trial Required), FOA number PAR-20-183. This proposal aims to identify specific biomarkers in individual people with osteoarthritis (OA) pain that will allow definition of responder phenotypes distinct for different therapeutic interventions. A mechanistic, prospective randomized trial will be undertaken, treating people having moderate to severe OA pain with either naproxen (a non-steroidal anti-inflammatory agent (NSAID)), duloxetine (a selective serotonin-norepinephrine reuptake inhibitor) or placebo in a 1:1:1 ratio. Randomization will be stratified by sex and prior opioid use. Naproxen, duloxetine and placebo are known to have different mechanisms of action and work at different sites in the pain pathway. Hence, it would be expected that these distinctions would be reflected in differences in individuals who would respond to each of these interventions. To this end, during the study we will collect a wide variety of biomarkers including demographics (sex, age), clinical outcome measures, questionnaires of patient-reported outcomes, neurosensory status (quantitative sensory testing indices), serum- based biomarkers, and joint and brain imaging. The treatment for each participant and collection of biomarkers will occur during an initial 6-week period and then be repeated after a 4-week washout to account for the known within-patient variability. The results obtained will permit the identification of responders (defined by 30% or greater improvement in pain from baseline with other thresholds also evaluated), and the correlation of biomarker status at baseline to response. We will then build a model to define the responder phenotype for each intervention, first using only clinical data and secondly using both clinical and MRI-based brain data. The latter will permit a further understanding of the mechanisms involved in modulation of the pain pathways by each of the agents. Particular attention will be given to treatment by sex interactions. The characterization of responder phenotypes to NSAID, duloxetine and placebo will allow for the practice of personalized medicine, providing the right drug to the right patient, enhancing therapeutic success, and reducing the risks involved with being treated with ineffective drugs having serious potential side effects. In addition, this approach will allow for more targeted and more efficient development of potential new therapeutic agents to treat OA pain.

摘要 这项建议是对资助机会研究项目资助(Parent R01临床试验)的回应 必填)，FOA编号PAR-20-183。这项提案旨在确定个体中的特定生物标记物。 对于骨关节炎(OA)疼痛，将允许定义不同治疗方法的不同应答者表型 干预措施。将进行一项机械性的前瞻性随机试验，治疗中度 对于严重的骨性关节炎疼痛，可以使用萘普生(一种非类固醇抗炎药)，度洛西汀(选择性的 5-羟色胺-去甲肾上腺素再摄取抑制剂)或安慰剂，比例为1：1：1。随机化将按性别分层 以及之前使用过阿片类药物。已知的萘普生、度洛西汀和安慰剂有不同的作用机制和 在疼痛路径的不同位置工作。因此，预计这些区别将得到反映。 不同的人会对这些干预措施做出反应。为此，在研究期间，我们 将收集各种各样的生物标志物，包括人口统计数据(性别、年龄)、临床结果指标、 患者报告的结果、神经感觉状态(定量感觉测试指数)、血清- 基于生物标志物，以及关节和脑成像。每个参与者的治疗和生物标记物的收集 将在最初的6周内发生，然后在4周的清洗后重复，以解释已知的 患者内部的可变性。获得的结果将允许识别响应者(定义为30%或 与其他阈值相比，疼痛改善更大)，以及生物标记物的相关性 响应的基线状态。然后，我们将构建一个模型来定义每个响应者的表型 干预，首先只使用临床数据，其次使用临床和基于MRI的脑数据。后者 将有助于进一步了解每一个人调节疼痛通路所涉及的机制 特工们。将特别注意通过性行为互动进行治疗。应答者的特征 非甾体抗炎药、度洛西汀和安慰剂的表型将允许个性化药物的实践，提供 将正确的药物提供给正确的患者，提高治疗成功率，并降低接受治疗的风险 无效的药物有严重的潜在副作用。此外，这种方法将允许更有针对性地 以及更有效地开发潜在的新的治疗药物来治疗骨性关节炎疼痛。