Identifying neural pathophysiology in juvenile fibromyalgia

确定青少年纤维肌痛的神经病理生理学

• 批准号: 10242702
• 负责人: Robert C Coghill
• 金额: $ 39.1万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10242702
• 关键词: Adolescent; Adult; Aerobic Exercise; Affect; Affective; Aftercare; Ancillary Study; Anxiety; Brain; Brain Mapping; Brain imaging; Characteristics; Child; Clinical; Cognitive Therapy; Data; Development; Dimensions; Disease; Disease Management; Early Diagnosis; Exercise; Fatigue; Female; Female Adolescents; Fibromyalgia; Foundations; Functional Magnetic Resonance Imaging; Functional disorder; Funding; Goals; Hypersensitivity; Judgment; Kentucky; Laboratory Finding; Lead; Location; Machine Learning; Measures; Mental Depression; Modeling; Motor; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Neurologic; Ohio; Output; Pain; Pain Measurement; Pain Research; Pain intensity; Painless; Parents; Parietal; Patients; Pattern; Persistent pain; Physical Function; Physiological; Prediction of Response to Therapy; Randomized Clinical Trials; Recommendation; Research; Sampling; Sensory; Site; Specific qualifier value; Stigmatization; Stimulus; Symptoms; Techniques; Testing; Time; Training; United States National Institutes of Health; base; brain abnormalities; chronic painful condition; cingulate cortex; clinical pain; clinical predictors; cohort; critical period; depressive symptoms; disability; fibromyalgia patients; hands-on learning; innovation; multisensory; neural correlate; neural patterning; neuromuscular; neurophysiology; pain symptom; parent project; physical symptom; psychologic; psychological symptom; relating to nervous system; response; treatment effect; treatment response; Adolescent; Adult; Aerobic Exercise; Affect; Affective; Aftercare; Ancillary Study; Anxiety; Brain; Brain Mapping; Brain imaging; Characteristics; Child; Clinical; Cognitive Therapy; Data; Development; Dimensions; Disease; Disease Management; Early Diagnosis; Exercise; Fatigue; Female; Female Adolescents; Fibromyalgia; Foundations; Functional Magnetic Resonance Imaging; Functional disorder; Funding; Goals; Hypersensitivity; Judgment; Kentucky; Laboratory Finding; Lead; Location; Machine Learning; Measures; Mental Depression; Modeling; Motor; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Neurologic; Ohio; Output; Pain; Pain Measurement; Pain Research; Pain intensity; Painless; Parents; Parietal; Patients; Pattern; Persistent pain; Physical Function; Physiological; Prediction of Response to Therapy; Randomized Clinical Trials; Recommendation; Research; Sampling; Sensory; Site; Specific qualifier value; Stigmatization; Stimulus; Symptoms; Techniques; Testing; Time; Training; United States National Institutes of Health; base; brain abnormalities; chronic painful condition; cingulate cortex; clinical pain; clinical predictors; cohort; critical period; depressive symptoms; disability; fibromyalgia patients; hands-on learning; innovation; multisensory; neural correlate; neural patterning; neuromuscular; neurophysiology; pain symptom; parent project; physical symptom; psychologic; psychological symptom; relating to nervous system; response; treatment effect; treatment response

ABSTRACT Juvenile-onset fibromyalgia (JFM) is a debilitating, chronic pain condition affecting adolescents, primarily females, during a critical period for brain development, and that persists into adulthood for the majority of patients. Due to the lack of definite physical or laboratory findings, JFM has been questioned as a clinical entity, and sometimes regarded as merely an expression of anxiety or depression. This leads to poor understanding, stigmatization, and appropriate disease management, underscoring the need for identifying objective pathophysiology. We have previously used machine learning applied to fMRI data to yield multivariate patterns of distributed brain activity that, together, can identify test subjects as adult FM patients vs. healthy adults with high cross-validated accuracy (93%). However, extrapolating adult FM brain abnormalities to JFM is problematic, given the many factors impacting the developing adolescent brain and the clinical differences between adult and juvenile forms of the disease. The goal of this proposal is to identify brain pathophysiology characteristic of JFM during tailored symptom provocation tasks. There is currently a complete lack of research into the brain correlates of pain in children with widespread pain/JFM. This study will lay the foundation for a line of research in understanding the neurophysiologic underpinnings of JFM, discovering whether brain pathophysiology in JFM differs from adult FM, and assessing treatment effects on specific markers of brain pathophysiology. This study is an R01 ancillary study to the NIH/NIAMS-funded trial (R01 AR070474; Kashikar-Zuck), “Multi-site randomized clinical trial of Fibromyalgia Integrative Training for Juvenile Fibromyalgia (FIT Teens)”. The exceptionally well characterized cohort of JFM patients from the parent trial presents a unique opportunity to study JFM neural correlates. Our time-sensitive study will transform the scientific output of the parent project by identifying neurophysiological correlates of pain, psychological and physical symptoms in this large, representative, extensively-characterized sample of JFM patients before and after treatment. We hypothesize that machine learning applied to fMRI data during tailored symptom-provocation tasks will identify patterns of neural activity predictive of JFM status (vs. healthy), which will correlate with JFM symptom dimensions (pain, non-painful sensory hypersensitivity, fatigue, and depressive symptoms). This ancillary study will utilize the comprehensive psychological and physical functioning profiles already being captured in the parent R01 trial to identify clinically meaningful neurologic measures in JFM and explore the potential for these measures to change with treatment. This line of research has the potential for a profound impact on understanding and identifying JFM pathophysiology and providing neuro-physiologically informed treatment recommendations.

抽象的 少年发作的纤维肌痛（JFM）是一种令人衰弱的慢性疼痛状况，影响青少年，主要 女性，在大脑发育的关键时期，大多数人都持续到成年 患者。由于缺乏明确的物理或实验室发现，JFM被质疑为临床 实体，有时被视为焦虑或抑郁的表达。这导致贫穷 理解，污名化和适当的疾病管理，强调识别的需求 客观的病理生理学。我们以前已使用机器学习应用于fMRI数据来产生 分布式大脑活动的多元模式，可以将测试受试者识别为成人FM患者 与健康的成年人相对于具有高跨验证精度的健康成年人（93％）。但是，推断成人FM大脑 鉴于影响发展中的大脑的许多因素和 疾病的成人和少年形式之间的临床差异。该提议的目的是确定 JFM在量身定制的症状挑衅任务中的脑病理生理特征。当前有一个 完全缺乏对宽度疼痛/JFM儿童疼痛的大脑相关的研究。这项研究会 为理解JFM的神经生理基础的研究奠定基础 发现JFM中的脑病理生理学是否与成人FM不同，并评估治疗对 脑病理生理学的特定标记。这项研究是NIH/NIAMS资助试验的R01辅助研究 （R01 AR070474； Kashikar-Zuck），“纤维肌痛整合训练的多站点随机临床试验 青少年纤维肌痛（适合青少年）”。 家长试验为研究JFM神经相关性提供了独特的机会。我们的时间敏感研究将 通过识别疼痛的神经生理学相关性来改变父项目的科学输出， 在这个大型，代表性，广泛特征的JFM样本中的心理和身体症状 治疗前后的患者。我们假设机器学习在量身定制期间应用于fMRI数据 症状证明任务将确定JFM状态（与健康）的神经活动模式 将与JFM符号维度（疼痛，无pain的感觉超敏反应，疲劳和 抑郁症状）。这项辅助研究将利用全面的心理和身体 在父r01试验中已经捕获的功能轮廓，以识别临床上有意义的神经系统 JFM中的措施并探索了这些措施随着治疗而改变的潜力。这条研究线 有可能对理解和识别JFM病理生理学产生深远影响并提供 神经生理学知情的治疗建议。