Neurological Markers of Maladaptive Brain Activity in Fibromyalgia and their Relationship with Treatment Effectiveness

E. Valentini
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Abstract

Chronic pain (CP) is estimated to affect at least one-third of the population in the United Kingdom. Fibromyalgia (FM) is one of the most disabling CP conditions. Epidemiological research suggests its global prevalence to be between 2-8%. The unknown pathogenesis, lack of biological markers to monitor its development, and lack of successful treatment make FM a crucial target of pre-clinical research.The goal of this project is twofold. The project aims to 1) identify robust neurological markers (i.e., electrochemical brain activity) by applying a combination of advanced electroencephalography (EEG) signal processing (i.e., functional connectivity of oscillatory activity) and neuroinflammatory (NI) responses (i.e., estimation of pro-inflammatory cytokines intake), through which 2) characterizing successfully and unsuccessfully treated FM patients (compared to age-matched healthy controls). These measures, seldom combined, have been successfully applied to the study of psychiatric conditions and sleep. Crucially, the identification of neurological markers at rest and during arousing sensory stimulation will allow us to estimate the relationship between these neurological markers and treatment effectiveness. This proposal is important because it aims to generate a robust pre-clinical neurological tool to identify FM and its relationship with measures of treatment effectiveness. The successful identification of neurological markers will improve the assessment of the development of maladaptive changes in FM and will kick-start further research on treatment effectiveness.This project is of great medical relevance as it will identify pathological signatures of FM that can then inform research on etiology and treatment of this condition.
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纤维肌痛患者适应不良脑活动的神经学标志物及其与治疗效果的关系
据估计,英国至少有三分之一的人口患有慢性疼痛。纤维肌痛(FM)是最致残的CP条件之一。流行病学研究表明,其全球患病率在2-8%之间。由于发病机制未知,缺乏监测其发展的生物标志物,以及缺乏成功的治疗方法,使FM成为临床前研究的重要目标。这个项目的目标是双重的。该项目旨在1)通过结合先进的脑电图(EEG)信号处理(即振荡活动的功能连接)和神经炎症(NI)反应(即促炎细胞因子摄入的估计)来识别强大的神经标记物(即电化学脑活动),通过它2)表征治疗成功和治疗失败的FM患者(与年龄匹配的健康对照组相比)。这些措施,很少结合起来,已经成功地应用于精神疾病和睡眠的研究。至关重要的是,在休息和唤醒感觉刺激期间识别神经标志物将使我们能够估计这些神经标志物与治疗效果之间的关系。这个建议很重要,因为它旨在产生一个强大的临床前神经学工具来识别FM及其与治疗效果的关系。神经学标记物的成功识别将改善对FM中适应性不良变化发展的评估,并将启动对治疗效果的进一步研究。该项目具有重要的医学意义,因为它将确定FM的病理特征,从而为该病的病因和治疗研究提供信息。
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