Abstract
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, R2 = 0.76, p < 0.001; GE(DMN): ρ = 0.82, R2 = 0.67, p < 0.001; GE(CBL): ρ = 0.80, R2 = 0.64, p < 0.001]. In CPMS the correlation between these measures was significantly lower [GE(CBL-DMN): ρ = 0.51, R2 = 0.26, p < 0.001; GE(DMN): ρ = 0.48, R2 = 0.23, p = 0.001; GE(CBL): ρ = 0.52, R2 = 0.27, p < 0.001] and SDMT scores correlated most with BPF (ρ = 0.57, R2 = 0.33, p < 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.
Highlights
Multiple sclerosis (MS) is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system and the most frequent non-traumatic cause of permanent neurological disability in young adults (Inglese, 2006)
The most significant result of this study is that the default mode network (DMN) structural connectivity as assessed by global efficiency of a network (GE) explains speed processing impairment in MS subjects, and that in cognitively impaired MS patients (CIMS) subjects damage to the extended extended DMN including cerebellar nodes (CBL-DMN) is the only predictor of symbol digit modalities test (SDMT) impairment in a multivariate model, while in cognitively preserved MS patients (CPMS) brain parenchymal fraction (BPF) and expanded disability status scale (EDSS) contribute to SDMT scores
Since the CBL-DMN represents the most comprehensive model and since the results it provided in both CIMS and CPMS were better than or similar to those obtained with DMN and CBL separately (Table 3), we considered only GE(CBLDMN) for the following partial correlation analysis and, later, for regression analysis
Summary
Multiple sclerosis (MS) is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system and the most frequent non-traumatic cause of permanent neurological disability in young adults (Inglese, 2006). Cognitive impairment occurs in about 50% of MS patients independently of physical disability (Chiaravalloti and DeLuca, 2008; Dineen et al, 2009; Hulst et al, 2013), but the mechanisms underlying this are still poorly understood and roles of the specific brain networks in MS are not clearly identified. Information processing speed is known to be one of the core deficits in MS (Chiaravalloti and DeLuca, 2008) and the SDMT (Smith, 1982) assesses this. Information processing speed, and SDMT performance, is associated with activity in the default mode network (DMN) (Rocca et al, 2010; Sumowski et al, 2010; Forn et al, 2013; Bonavita et al, 2015), which deactivates when cognitively demanding tasks are performed (Buckner et al, 2008; Broyd et al, 2009). The DMN’s role in MS-related cognitive impairment is not clear and the structural changes leading to dysfunction are not fully captured yet
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