Longitudinal changes of structural and functional connectivity in multiple sclerosis in a natural history cohort and during an exercise trial

多发性硬化症（MS）是最常见的中枢神经系统（CNS）自身免疫性疾病。它主要影响年轻人，并通过炎症和进行性神经变性导致残疾的积累。运动是目前最好的神经保护治疗方法，因为经批准的药物只能减少炎症。磁共振断层扫描（MRI）监测炎症，但量化神经退行性变是有限的，与认知、活动能力或视力的关系很弱。从神经科学的角度来看，大脑可以被认为是一个紧密连接的网络，而多发性硬化症影响了网络的结构和功能。MRI允许通过静息状态功能MRI （fMRI）以及结构连接来研究功能连接。图论测度是分析这类网络的数学模型。该方法仅在一项MS患者的纵向研究中得到应用。在疾病的早期阶段，功能连接的代偿性增加似乎先于与残疾积累相关的长期减少。自然历史数据和运动试验为进一步开发基于核磁共振的连通性分析提供了最佳的科学框架，以证明它是与残疾相关的高度特异性生物标志物。该项目的总体目标是提供复发缓解型多发性硬化症患者结构和功能中枢神经系统网络紊乱和重组的全面概况及其临床相关性。这项分析是在马赛主办机构的功能磁共振成像研究和我已经建立的结构网络分析之后进行的。该提案包括基于相同MRI协议和每个时间点广泛的神经心理学概况的两个数据集：自然史队列（n = 38和匹配的健康对照，每年随访两年，于2017年2月完成）和随机等待组对照运动试验（n = 60，随访3个月和6个月，于2016年7月完成）。我将重建结构和功能网络，并调查结构变化（例如连接的丧失）是否会导致两年内自然历史队列的功能重组。认知将作为主要的临床结果，并将全局图指标和网络结构的变化与健康对照进行比较。接下来，我的目标是将标准静息状态MRI分析与所谓的功能连接动力学进行比较，这尚未应用于ms。这种方法考虑到在记录期间网络的激活是不同的。对于运动试验，我将比较运动前后以及等待组和干预组之间的图表指标和网络架构。我的发现将阐明运动对功能性和结构性大脑网络的影响。我将进一步开发网络连通性作为MS神经变性的高度特异性和临床意义的结果测量。

Multiple Sclerosis (MS) is the most common autoimmune disease of the central nervous system (CNS). It affects mainly young adults and leads to an accumulation of disability by inflammation as well as by progressive neurodegeneration. Exercises are currently the best neuroprotective treatment as approved drugs reduce inflammation only. Magnetic resonance tomography (MRI) monitors inflammation but quantifying neurodegeneration is restricted and weakly associated with cognition, mobility or vision.From a neuroscientific perspective, the brain can be considered a densely connected network and MS affects the networks architecture and function. MRI allows investigating functional connectivity by resting state functional MRI (fMRI) as well as structural connectivity. Graph theoretic measures are mathematical models to analyse such networks. This approach has only been applied in one longitudinal study with MS patients. A compensatory increase in functional connectivity in the early phase of the diseases seems preceding a long-term decrease associated with disability accumulation. Natural history data and exercise trials are providing the best scientific framework to further develop MRI-based connectivity analysis for proving as a highly specific biomarker linked to disability. The overarching aim of this project is to provide a comprehensive profile of structural and functional CNS network disturbance and reorganisation in relapsing-remitting MS patients and their clinical correlates. The analysis follows a fMRI study from the hosting institution in Marseille combined with structural network analyses, which I have established already. The proposal includes two datasets based on the same MRI protocol and extensive neuropsychological profile at each time-point: A natural history cohort (n = 38 and matched healthy controls, annual follow-up of two years, completed in February 2017) and a randomised waiting-group controlled exercise trial (n = 60, follow-up after three and six months, completed in July 2016). I will reconstruct structural and functional networks and investigate if structural changes (e.g. loss of connections) lead to functional reorganisation over two years in the natural history cohort. Cognition will serve as the main clinical outcome and changes of global graph metrics and network architecture are compared to healthy controls. Next, I aim to compare standard resting state MRI analysis with so called functional connectivity dynamics, which have not been applied to MS. This approach takes into account that activation of networks varies during the recording period. For the exercise trial, I will compare graph metrics and network architecture pre-post exercise as well as between waiting and intervention group. My findings will elucidate the impact of exercises on functional and structural brain networks. I will further develop network connectivity as highly specific and clinically meaningful outcome measure of neurodegeneration in MS.