Savini Giovanni, Pardini Matteo, Castellazzi Gloria, Lascialfari Alessandro, Chard Declan, D'Angelo Egidio, Gandini Wheeler-Kingshott Claudia A M
Department of Physics, University of Milan, Milan, Italy.
Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy.
Front Cell Neurosci. 2019 Feb 11;13:21. doi: 10.3389/fncel.2019.00021. eCollection 2019.
Cognitive impairment affects about 50% of multiple sclerosis (MS) patients, but the mechanisms underlying this remain unclear. The default mode network (DMN) has been linked with cognition, but in MS its role is still poorly understood. Moreover, within an extended DMN network including the cerebellum (CBL-DMN), the contribution of cortico-cerebellar connectivity to MS cognitive performance remains unexplored. The present study investigated associations of DMN and CBL-DMN structural connectivity with cognitive processing speed in MS, in both cognitively impaired (CIMS) and cognitively preserved (CPMS) MS patients. 68 MS patients and 22 healthy controls (HCs) completed a symbol digit modalities test (SDMT) and had 3T brain magnetic resonance imaging (MRI) scans that included a diffusion weighted imaging protocol. DMN and CBL-DMN tracts were reconstructed with probabilistic tractography. These networks (DMN and CBL-DMN) and the cortico-cerebellar tracts alone were modeled using a graph theoretical approach with fractional anisotropy (FA) as the weighting factor. Brain parenchymal fraction (BPF) was also calculated. In CIMS SDMT scores strongly correlated with the FA-weighted global efficiency (GE) of the network [GE(CBL-DMN): ρ = 0.87, = 0.76, < 0.001; GE(DMN): ρ = 0.82, = 0.67, < 0.001; GE(CBL): ρ = 0.80, = 0.64, < 0.001]. In CPMS the correlation between these measures was significantly lower [GE(CBL-DMN): ρ = 0.51, = 0.26, < 0.001; GE(DMN): ρ = 0.48, = 0.23, = 0.001; GE(CBL): ρ = 0.52, = 0.27, < 0.001] and SDMT scores correlated most with BPF (ρ = 0.57, = 0.33, < 0.001). In a multivariable regression model where SDMT was the independent variable, FA-weighted GE was the only significant explanatory variable in CIMS, while in CPMS BPF and expanded disability status scale were significant. No significant correlation was found in HC between SDMT scores, MRI or network measures. DMN structural GE is related to cognitive performance in MS, and results of CBL-DMN suggest that the cerebellum structural connectivity to the DMN plays an important role in information processing speed decline.
认知障碍影响约50%的多发性硬化症（MS）患者，但其潜在机制尚不清楚。默认模式网络（DMN）与认知有关，但在MS中其作用仍知之甚少。此外，在包括小脑的扩展DMN网络（CBL-DMN）中，皮质-小脑连接对MS认知表现的贡献仍未得到探索。本研究调查了DMN和CBL-DMN结构连接与MS患者认知处理速度之间的关联，这些患者既有认知受损的（CIMS），也有认知未受损的（CPMS）。68例MS患者和22名健康对照者（HCs）完成了符号数字模态测试（SDMT），并进行了3T脑磁共振成像（MRI）扫描，其中包括弥散加权成像协议。使用概率纤维束成像重建DMN和CBL-DMN纤维束。这些网络（DMN和CBL-DMN）以及单独的皮质-小脑纤维束使用以分数各向异性（FA）作为加权因子的图论方法进行建模。还计算了脑实质分数（BPF）。在CIMS中，SDMT分数与网络的FA加权全局效率（GE）密切相关[GE（CBL-DMN）：ρ = 0.87， = 0.76， < 0.001；GE（DMN）：ρ = 0.82， = 0.67， < 0.001；GE（CBL）：ρ = 0.80， = 0.64， < 0.001]。在CPMS中，这些指标之间的相关性显著较低[GE（CBL-DMN）：ρ = 0.51， = 0.26， < 0.001；GE（DMN）：ρ = 0.48， = 0.23， = 0.001；GE（CBL）：ρ = 0.52， = 0.27， < 0.001]，且SDMT分数与BPF的相关性最高（ρ = 0.57， = 0.33， < 0.001）。在以SDMT为自变量的多变量回归模型中，FA加权GE是CIMS中唯一显著的解释变量，而在CPMS中BPF和扩展残疾状态量表是显著的。在HC中，SDMT分数、MRI或网络指标之间未发现显著相关性。DMN结构GE与MS中的认知表现相关，CBL-DMN的结果表明小脑与DMN的结构连接在信息处理速度下降中起重要作用。
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