Department of Anatomy and Neurosciences, Neuroscience Amsterdam, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Department of Anatomy and Neurosciences, Neuroscience Amsterdam, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Neuroimage Clin. 2021;29:102556. doi: 10.1016/j.nicl.2020.102556. Epub 2021 Jan 4.
More than 80% of multiple sclerosis (MS) patients experience symptoms of fatigue. MS-related fatigue is only partly explained by structural (lesions and atrophy) and functional (brain activation and conventional static functional connectivity) brain properties.
To investigate the relationship of dynamic functional connectivity (dFC) with fatigue in MS patients and to compare dFC with commonly used clinical and MRI parameters.
In 35 relapsing-remitting MS patients (age: 42.83 years, female/male: 20/15, disease duration: 11 years) and 19 healthy controls (HCs) (age: 41.38 years, female/male: 11/8), fatigue was measured using the CIS-20r questionnaire at baseline and at 6-month follow-up. All subjects underwent structural and resting-state functional MRI at baseline. Global static functional connectivity (sFC) and dynamic functional connectivity (dFC) were calculated. dFC was assessed using a sliding-window approach by calculating the summed difference (diff) and coefficient of variation (cv) across windows. Moreover, regional connectivity between regions previously associated with fatigue in MS was estimated (i.e. basal ganglia and regions of the Default Mode Network (DMN): medial prefrontal, posterior cingulate and precuneal cortices). Hierarchical regression analyses were performed with forward selection to identify the most important correlates of fatigue at baseline. Results were not corrected for multiple testing due to the exploratory nature of the study.
Patients were more fatigued than HCs at baseline (p = 0.001) and follow-up (p = 0.002) and fatigue in patients was stable over time (p = 0.213). Patients had significantly higher baseline global dFC than HCs, but no difference in basal ganglia-DMN dFC. In the regression model for baseline fatigue in patients, basal ganglia-DMN dFC-cv (standardized β = -0.353) explained 12.5% additional variance on top of EDSS (p = 0.032). Post-hoc analysis revealed higher basal ganglia-DMN dFC-cv in non-fatigued patients compared to healthy controls (p = 0.013), whereas fatigued patients and healthy controls showed similar basal ganglia-DMN dFC.
Less dynamic connectivity between the basal ganglia and the cortex is associated with greater fatigue in MS patients, independent of disability status. Within patients, lower dynamics of these connections could relate to lower efficiency and increased fatigue. Increased dynamics in non-fatigued patients compared to healthy controls might represent a network organization that protects against fatigue or signal early network dysfunction.
超过 80%的多发性硬化症 (MS) 患者会出现疲劳症状。MS 相关的疲劳仅部分由结构(病变和萎缩)和功能(大脑激活和常规静息态功能连接)大脑特性解释。
研究 MS 患者动态功能连接 (dFC) 与疲劳之间的关系,并将其与常用的临床和 MRI 参数进行比较。
在 35 例复发缓解型 MS 患者(年龄:42.83 岁,女性/男性:20/15,疾病持续时间:11 年)和 19 名健康对照者(HCs)(年龄:41.38 岁,女性/男性:11/8)中,在基线和 6 个月随访时使用 CIS-20r 问卷测量疲劳。所有受试者均在基线时进行结构和静息态功能 MRI 检查。计算全局静息态功能连接 (sFC) 和动态功能连接 (dFC)。通过在窗口之间计算总和差异 (diff) 和变异系数 (cv) 来评估 dFC。此外,还估计了与 MS 患者疲劳相关的区域之间的区域连接(即基底神经节和默认模式网络 (DMN) 的区域:内侧前额叶、后扣带和楔前叶皮质)。采用逐步选择法进行分层回归分析,以确定基线时疲劳的最重要相关因素。由于研究的探索性质,结果未经过多次检验校正。
患者在基线时比 HCs 更疲劳(p=0.001),在随访时更疲劳(p=0.002),且患者的疲劳随时间稳定(p=0.213)。与 HCs 相比,患者的基线全局 dFC 显著更高,但基底神经节-DMN dFC 没有差异。在患者基线疲劳的回归模型中,基底神经节-DMN dFC-cv(标准化β= -0.353)在 EDSS 之外解释了 12.5%的额外方差(p=0.032)。事后分析显示,与健康对照组相比,非疲劳患者的基底神经节-DMN dFC-cv 更高(p=0.013),而疲劳患者和健康对照组的基底神经节-DMN dFC 相似。
基底神经节与皮质之间的连接动态性降低与 MS 患者的疲劳程度增加有关,与残疾状况无关。在患者中,这些连接的动态性降低可能与效率降低和疲劳增加有关。与健康对照组相比,非疲劳患者的连接动态性增加可能代表一种网络组织,可预防疲劳或提示早期网络功能障碍。