Abstract
Resting state functional MRI (rs-fMRI) has provided important insights into functional reorganization in subjects with Multiple Sclerosis (MS) at different stage of disease. In this cross-sectional study we first assessed, by means of rs-fMRI, the impact of overall T2 lesion load (T2LL) and MS severity score (MSSS) on resting state networks (RSNs) in 62 relapsing remitting MS (RRMS) patients with mild disability (MSSS < 3). Independent Component Analysis (ICA) followed by dual regression analysis confirmed functional connectivity (FC) alterations of many RSNs in RRMS subjects compared to healthy controls. The anterior default mode network (DMNa) and the superior precuneus network (PNsup) showed the largest areas of decreased FC, while the sensory motor networks area M1 (SMNm1) and the medial visual network (MVN) showed the largest areas of increased FC. In order to better understand the nature of these alterations as well as the mechanisms of functional alterations in MS we proposed a method, based on linear regression, that takes into account FC changes and their correlation with T2LL and MSSS. Depending on the sign of the correlation between FC and T2LL, and furthermore the sign of the correlation with MSSS, we suggested the following possible underlying mechanisms to interpret altered FC: (1) FC reduction driven by MS lesions, (2) “true” functional compensatory mechanism, (3a) functional compensation attempt, (3b) “false” functional compensation, (4a) neurodegeneration, (4b) pre-symptomatic condition (damage precedes MS clinical manifestation). Our data shows areas satisfying 4 of these 6 conditions (i.e., 1,2,3b,4b), supporting the suggestion that increased FC has a complex nature that may exceed the simplistic assumption of an underlying compensatory mechanism attempting to limit the brain damage caused by MS progression. Exploring differences between RRMS subjects with short disease duration (MSshort) and RRMS with similar disability but longer disease duration (MSlong), we found that MSshort and MSlong were characterized by clearly distinct pattern of FC, involving predominantly sensory and cognitive networks respectively. Overall, these results suggest that the analysis of FC alterations in multiple large-scale networks in relation to radiological (T2LL) and clinical (MSSS, disease duration) status may provide new insights into the pathophysiology of relapse onset MS evolution.
Highlights
Multiple Sclerosis (MS) is a chronic disease characterized by the presence of multifocal inflammatory demyelinated plaques distributed over space and time within the central nervous system (CNS) [1, 2]
The mean MS Functional Composite (MSFC) score was significantly reduced in both MSshort and MSlong compared with healthy controls (HC) (Mann-Whitney test, MSshort: p = 0.003; MSlong: p = 0.012), but no significant differences were observed in MSFC between MSshort and MSlong
resting state networks (RSNs) functional connectivity (FC) analysis shows that functional alterations in MS at a network level cannot be described in terms of compensatory mechanisms or of loss of function
Summary
Multiple Sclerosis (MS) is a chronic disease characterized by the presence of multifocal inflammatory demyelinated plaques distributed over space and time within the central nervous system (CNS) [1, 2]. Magnetic Resonance Imaging (MRI) has contributed significantly to diagnosis, by depicting white matter demyelinating lesions, and to the study of mechanisms of disease and of functional alterations. Increasing brain lesion load and brain atrophy have been found to correlate with the progression of cognitive impairment in MS [4]. Changes in brain gray matter—rather than the white matter— have been shown to predict long-term physical disability and cognitive impairment in a number of studies [5,6,7,8]. Thalamic atrophy has been found to correlate with cognitive decline and disability, suggesting that thalamic volume may be a clinically relevant biomarker to assess the neurodegenerative disease process in MS [11, 12]
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