Identifying neural pathophysiology in juvenile fibromyalgia

摘要 青少年纤维肌痛（JFM）是一种使人衰弱的慢性疼痛，主要影响青少年， 女性，在大脑发育的关键时期，并持续到成年的大多数 患者由于缺乏明确的身体或实验室检查结果，JFM被质疑为临床 实体，有时被视为仅仅是焦虑或抑郁的表现。这导致穷人 理解，污名化和适当的疾病管理，强调需要确定 客观病理生理学我们以前使用机器学习应用于fMRI数据， 分布的大脑活动的多变量模式，这些模式一起可以将测试对象识别为成年FM患者 vs.健康成年人具有较高的交叉验证准确性（93%）。然而，将成年FM大脑 JFM的异常是有问题的，考虑到影响青少年大脑发育的许多因素， 成人和青少年形式的疾病之间的临床差异。本提案的目的是确定 在定制的症状激发任务期间JFM的脑病理生理学特征。目前有一个 完全缺乏对广泛性疼痛儿童疼痛与大脑相关性的研究/JFM。本研究将 为理解JFM的神经生理学基础奠定了基础， 发现JFM的脑病理生理学是否与成人FM不同，并评估治疗效果。 大脑病理生理学的特定标志物。本研究是NIH/NIAMS资助试验的R 01辅助研究 (R01 AR 070474; Kashikar-Zuck），“纤维肌痛综合训练的多中心随机临床试验 青少年纤维肌痛（FIT青少年）"。JFM患者的特征非常好的队列来自 母体试验为研究JFM神经相关性提供了一个独特的机会。我们的时间紧迫的研究将 通过识别疼痛的神经生理学相关性来转化母项目的科学成果， 心理和身体症状在这个大的，代表性的，广泛的特点样本JFM 患者治疗前后我们假设，机器学习应用于功能磁共振成像数据在定制的 刺激任务将识别预测JFM状态（与健康）的神经活动模式， 将与JFM症状维度（疼痛、非疼痛性感觉超敏反应、疲劳和 抑郁症状）。这项辅助研究将利用全面的心理和生理 已在母R 01试验中采集功能特征，以确定具有临床意义的神经功能 在JFM的措施，并探讨这些措施的潜力，以改变治疗。这一系列研究 有可能对理解和识别JFM病理生理学产生深远影响，并提供 神经生理学的治疗建议。

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.