ABSTRACT
Little is known about how the brain's functional organization changes over time with respect to structural damage. Using multiple sclerosis as a model of structural damage, we assessed how much functional connectivity (FC) changed within and between preselected resting-state networks (RSNs) in 122 subjects (72 with multiple sclerosis and 50 healthy controls). We acquired the structural, diffusion, and functional MRI to compute functional connectomes and structural disconnectivity profiles. Change in FC was calculated by comparing each multiple sclerosis participant's pairwise FC to controls, while structural disruption (SD) was computed from abnormalities in diffusion MRI via the Network Modification tool. We used an ordinary least squares regression to predict the change in FC from SD for 9 common RSNs. We found clear differences in how RSNs functionally respond to structural damage, namely that higher-order networks were more likely to experience changes in FC in response to structural damage (default mode R2 = 0.160-0.207, P < 0.001) than lower-order sensory networks (visual network 1 R2 = 0.001-0.007, P = 0.157-0.387). Our findings suggest that functional adaptability to structural damage depends on how involved the affected network is in higher-order processing.
Subject(s)
Brain , Multiple Sclerosis , Humans , Brain/diagnostic imaging , Multiple Sclerosis/diagnostic imaging , Magnetic Resonance Imaging/methods , Diffusion Magnetic Resonance ImagingABSTRACT
Cognitive reserve is one's mental resilience or resistance to the effects of structural brain damage. Reserve effects are well established in people with multiple sclerosis (PwMS) and Alzheimer's disease, but the neural basis of this phenomenon is unclear. We aimed to investigate whether preservation of functional connectivity explains cognitive reserve. Seventy-four PwMS and 29 HCs underwent neuropsychological assessment and 3 T MRI. Structural damage measures included gray matter (GM) atrophy and network white matter (WM) tract disruption between pairs of GM regions. Resting-state functional connectivity was also assessed. PwMS exhibited significantly impaired cognitive processing speed (t = 2.14, p = .037) and visual/spatial memory (t = 2.72, p = .008), and had significantly greater variance in functional connectivity relative to HCs within relevant networks (p < .001, p < .001, p = .016). Higher premorbid verbal intelligence, a proxy for cognitive reserve, predicted relative preservation of functional connectivity despite accumulation of GM atrophy (standardized-ß = .301, p = .021). Furthermore, preservation of functional connectivity attenuated the impact of structural network WM tract disruption on cognition (ß = -.513, p = .001, for cognitive processing speed; ß = -.209, p = .066, for visual/spatial memory). The data suggests that preserved functional connectivity explains cognitive reserve in PwMS, helping to maintain cognitive capacity despite structural damage.
Subject(s)
Brain/diagnostic imaging , Cognitive Reserve/physiology , Magnetic Resonance Imaging/methods , Multiple Sclerosis/diagnostic imaging , Nerve Net/diagnostic imaging , Adult , Aged , Brain/physiology , Case-Control Studies , Female , Humans , Male , Mental Status and Dementia Tests , Middle Aged , Multiple Sclerosis/psychology , Nerve Net/physiologyABSTRACT
BACKGROUND: New/enlarging T2 lesion count and T2-lesion volume (LV) are used as conventional secondary endpoints in clinical trials of patients with multiple sclerosis (PwMS). However, those outcomes may have several limitations, such as inability to account for heterogeneity of lesion formation/enlargement frequency and their dynamic volumetric behavior. Measurement of volume rather than count of new/enlarging lesions may be more representative outcome of dynamic changes over time. OBJECTIVES: To investigate whether new/enlarging T2-LV is more predictive of confirmed disability progression (CDP), compared to total T2-LV or new/enlarging T2 lesion count over long-term follow-up. METHODS: We studied 176 early relapsing-remitting PwMS who were followed with annual MRI examinations over 10 years. T2-LV, new/enlarging T2-LV, and new/enlarging lesion count were determined. Cumulative count/volumes were obtained. 10-year CDP was confirmed after 48-weeks. ANCOVA analysis detected MRI outcome differences in stable (n = 76) and CDP (n = 100) groups at different time points, after correction for multiple comparisons. RESULTS: PwMS with CDP had greater cumulative new/enlarging T2-LV at 4 years (p = 0.049), and enlarging T2-LV at 4- (p = 0.039) and 6-year follow-up (p = 0.032), compared to stable patients. PwMS with CDP did not differ from stable ones in new/enlarging T2 lesion count or total T2-LV at any of the study timepoints. PwMS with Expanded Disability Status Scale change >2.0 had significantly greater enlarging T2 lesion count (p = 0.01) and enlarging T2-LV (p = 0.038) over the 10-year follow-up. CONCLUSION: Enlargement of T2 lesions is more strongly associated with long-term disability progression compared to other conventional T2 lesion-based outcomes.
Subject(s)
Multiple Sclerosis, Relapsing-Remitting , Multiple Sclerosis , Humans , Atrophy/pathology , Brain/pathology , Disease Progression , Magnetic Resonance Imaging , Multiple Sclerosis/diagnostic imaging , Multiple Sclerosis/pathology , Multiple Sclerosis, Relapsing-Remitting/diagnostic imaging , Multiple Sclerosis, Relapsing-Remitting/pathologyABSTRACT
BACKGROUND: Persons with multiple sclerosis (PwMS) are at an elevated risk of depression. Decreased Conscientiousness may affect patient outcomes in PwMS. Low Conscientiousness has a strong correlation with depression. Previous work has also reported that white matter (WM) tract disruption in frontal-parietal networks explains reduced Conscientiousness in PwMS. OBJECTIVE: We hypothesized that Conscientiousness-associated WM tract disruption predicts new-onset depression over 5 years in PwMS and evaluated this by assessing the predictive power of mean Conscientiousness associated frontal-parietal network (CFPN) disruption in PwMS for clinically diagnosed depression over 5 years. METHODS: This longitudinal retrospective analysis included 53 PwMS who were not previously diagnosed as depressed. All participants underwent structural MRI. Medical records were reviewed to evaluate diagnosis of depression for these patients over 5 years. WM tract damage between pairs of gray matter regions in the CFPN was measured using diffusion imaging. The relationship between CFPN disruption and depression was analyzed using logistic regression. RESULTS: Participants with MS had a mean age of 46.0 years (SD = 11.2). 22.6% (n = 12) acquired a diagnosis of clinical depression over the 5-year period. Baseline disruption in the CFPN was a significant predictor (ROC AUC = 61.8%). of new-onset clinical depression, accounting for age, sex, lateral ventricular volume, disease modifying treatment, and lesion volume. CONCLUSION: Baseline CFPN disruption is associated with progression to clinical depression over 5 years in PwMS. Development of new WM pathology within this network may be a risk factor for depression.
Subject(s)
Multiple Sclerosis , White Matter , Depression/etiology , Gray Matter , Humans , Magnetic Resonance Imaging , Middle Aged , Multiple Sclerosis/complications , Multiple Sclerosis/diagnostic imaging , Retrospective Studies , White Matter/diagnostic imagingABSTRACT
BACKGROUND AND PURPOSE: Efficacy of restorative cognitive rehabilitation can be predicted from baseline patient factors. In addition, patient profiles of functional connectivity are associated with cognitive reserve and moderate the structure-cognition relationship in people with multiple sclerosis (PwMS). Such interactions may help predict which PwMS will benefit most from cognitive rehabilitation. Our objective was to determine whether patient response to restorative cognitive rehabilitation is predictable from baseline structural network disruption and whether this relationship is moderated by functional connectivity. METHODS: For this single-arm repeated measures study, we recruited 25 PwMS for a 12-week program. Following magnetic resonance imaging, participants were tested using the Symbol Digit Modalities Test (SDMT) pre- and postrehabilitation. Baseline patterns of structural and functional connectivity were characterized relative to healthy controls. RESULTS: Lower white matter tract disruption in a network of region-pairs centered on the precuneus and posterior cingulate (default-mode network regions) predicted greater postrehabilitation SDMT improvement (P = .048). This relationship was moderated by profiles of functional connectivity within the network (R2 = .385, P = .017, Interaction ß = -.415). CONCLUSION: Patient response to restorative cognitive rehabilitation is predictable from the interaction between structural network disruption and functional connectivity in the default-mode network. This effect may be related to cognitive reserve.
Subject(s)
Brain/diagnostic imaging , Cognition/physiology , Default Mode Network/diagnostic imaging , Multiple Sclerosis/diagnostic imaging , White Matter/diagnostic imaging , Adult , Aged , Female , Humans , Magnetic Resonance Imaging/methods , Male , Middle Aged , Multiple Sclerosis/psychology , Neuropsychological Tests , Treatment OutcomeABSTRACT
BACKGROUND: Growing evidence supports the efficacy of restorative cognitive training in people with multiple sclerosis (PwMS), but the effects vary across individuals. Differences in treatment efficacy may be related to baseline individual differences. We investigated clinical characteristics and MRI variables to predict response to a previously validated approach to home-based restorative cognitive training. METHODS: In a single-arm repeated measures study, 51 PwMS completed a 12-week at-home restorative cognitive training program called BrainHQ, shown to be effective in a placebo-controlled clinical trial. Baseline demographic, clinical, neuropsychological, and brain MRI factors were captured and the effects of treatment were quantified with Symbol Digit Modalities Test (SDMT). Also measured were indices of treatment compliance. Regression modeling was employed to identify the factors associated with greatest SDMT improvement. RESULTS: As a group, patients improved significantly after training: mean SDMT improving from 49.6⯱â¯14.7 to 52.6⯱â¯15.6 (tâ¯=â¯3.91, p<0.001). Greater SDMT improvement correlated positively with treatment exposure (râ¯=â¯0.38, pâ¯=â¯0.007). Increased post-rehabilitation improvement on SDMT was predicted by baseline relapsing-remitting course (ß=-0.34, pâ¯=â¯0.017), higher trait Conscientiousness-Orderliness (ß=0.29, pâ¯=â¯0.040), and higher baseline gray matter volume (GMV; ß=0.31, pâ¯=â¯0.030). CONCLUSION: The study was designed to explore the variables that predict favorable outcome in a home-based application of a validated restorative cognitive training program. We find good outcomes are most likely in patients with higher trait Conscientiousness-Orderliness, and relapsing-remitting course. The same was found for individuals with higher GMV. Future work in larger cohorts is needed to support these findings and to investigate the unique needs of individuals according to baseline factors.