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Background: Literature on the intricate relationship between self-reported and objectively assessed cognitive functioning suggests a discrepancy between self-reported cognitive complaints (SCC) and actual test performance. Objectives: To investigate the interplay between patient-reported outcome measures (PROMs) and objective cognitive functioning using network analysis in people with multiple sclerosis (PwMS). Methods: We collected PROMs on anxiety, depression, fatigue and SCC, and cognitive functioning across six domains (n = 703 PwMS; 71% female, mean age = 46.3 ± 11.2 years). We constructed cognitive symptom networks using Gaussian Graphical Models, in which the aforementioned variables were presented as nodes linked by regularized partial correlations. We compared global network strength between relevant subgroups. Results: The networks primarily showed clustering of PROMs and cognitive domains into two separate modules, with weaker links connecting both modules. Global network strength was lower for PwMS with impaired information processing speed (IPS; indicating lower symptom interrelatedness) compared to those with preserved IPS (3.57 versus 4.51, p = 0.001), but not when comparing SCC subgroups (p = 0.140). Conclusions: Cognitive symptom networks deepen our understanding of the discrepancy between self-reported and objectively assessed cognitive functioning. Lower symptom interrelatedness in PwMS with impaired IPS might suggest a nonlinear relation between PROMs and cognitive domains, which depends on the cognitive status. [ABSTRACT FROM AUTHOR]

Background: Suboptimal performance during neuropsychological testing frequently occurs in multiple sclerosis (MS), leading to unreliable cognitive outcomes. Neurophysiological alterations correlate with MS-related cognitive impairment, but studies have not yet considered performance validity. Objectives: To investigate neurophysiological markers of cognitive impairment in MS, while explicitly addressing performance validity. Methods: Magnetoencephalography recordings, neuropsychological assessments, and performance validity testing were obtained from 90 MS outpatients with cognitive complaints. Spectral and resting-state functional connectivity (rsFC) properties were compared between cognitively impaired (CI), cognitively preserved (CP), and suboptimally performing (SUB) patients using regression models and permutation testing. Results: CI had higher power in low-frequency bands and lower power in high bands compared to CP, indicating neuronal slowing. CI also showed lower beta power compared to SUB. Overall power spectra visually differed between CI and CP, and SUB showed overlap with both groups. CI had lower rsFC than CP and SUB patients. CP and SUB patients showed no differences. Conclusion: Neuronal slowing and altered rsFC can be considered cognitive markers in MS. Patients who performed suboptimally showed resemblance with patients with and without cognitive impairments, and although their overall neurophysiological profile was more similar to patients without impairments, it suggests heterogeneity regarding their pathophysiology. [ABSTRACT FROM AUTHOR]

Objective: To assess the interrelationship between cortical lesions and cortical thinning and volume loss in people with multiple sclerosis within cortical networks, and how this relates to future cognition., Methods: In this longitudinal study, 230 people with multiple sclerosis and 60 healthy controls underwent 3 Tesla MRI at baseline and neuropsychological assessment at baseline and 5-year follow-up. Cortical regions (N = 212) were divided into seven functional networks. Regions were defined as either lesional or normal-appearing cortex based on presence of a cortical lesion on artificial intelligence-generated double inversion-recovery scans. Cortical volume and thickness were determined within lesional or normal-appearing cortex., Results: Prevalence of at least one cortical lesion was highest in the limbic (73%) followed by the default mode network (70.9%). Multiple sclerosis-related cortical thinning was more pronounced in lesional (mean Z-score = 0.70 ± 0.84) compared to normal-appearing cortex (-0.45 ± 0.60; P < 0.001) in all, except sensorimotor, networks. Cognitive dysfunction, particularly of verbal memory, visuospatial memory, and inhibition, at follow-up was best predicted by baseline network volume of normal-appearing cortex of the default mode network [B (95% CI) = 0.31 (0.18; 0.43), P < 0.001]. Mediation analysis showed that the effect of cortical lesions on future cognition was mediated by volume loss of the normal-appearing instead of lesional cortex, independent of white matter lesion volume., Interpretation: Multiple sclerosis-related cortical thinning was worse in lesional compared to normal-appearing cortex, while volume loss of normal-appearing cortex was most predictive of subsequent cognitive decline, particularly in the default mode network. Mediation analyses indicate that cortical lesions impact cognitive decline plausibly by inducing atrophy, rather than through a direct effect., (© 2024 The Author(s). Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Background: Suboptimal performance during neuropsychological testing frequently occurs in multiple sclerosis (MS), leading to unreliable cognitive outcomes. Neurophysiological alterations correlate with MS-related cognitive impairment, but studies have not yet considered performance validity., Objectives: To investigate neurophysiological markers of cognitive impairment in MS, while explicitly addressing performance validity., Methods: Magnetoencephalography recordings, neuropsychological assessments, and performance validity testing were obtained from 90 MS outpatients with cognitive complaints. Spectral and resting-state functional connectivity (rsFC) properties were compared between cognitively impaired (CI), cognitively preserved (CP), and suboptimally performing (SUB) patients using regression models and permutation testing., Results: CI had higher power in low-frequency bands and lower power in high bands compared to CP, indicating neuronal slowing. CI also showed lower beta power compared to SUB. Overall power spectra visually differed between CI and CP, and SUB showed overlap with both groups. CI had lower rsFC than CP and SUB patients. CP and SUB patients showed no differences., Conclusion: Neuronal slowing and altered rsFC can be considered cognitive markers in MS. Patients who performed suboptimally showed resemblance with patients with and without cognitive impairments, and although their overall neurophysiological profile was more similar to patients without impairments, it suggests heterogeneity regarding their pathophysiology.

Background: Despite highly effective treatment strategies for patients with relapsing-remitting multiple sclerosis (RRMS), long-term neurodegeneration and disease progression are often considerable. Accurate blood-based biomarkers that predict long-term neurodegeneration are lacking., Objective: To assess the predictive value of serum neurofilament-light (sNfL) and serum contactin-1 (sCNTN1) for long-term magnetic resonance imaging (MRI)-derived neurodegeneration in natalizumab-treated patients with RRMS., Methods: sNfL and sCNTN1 were measured in an observational cohort of natalizumab-treated patients with RRMS at baseline (first dose) and at 3 months, Year 1, Year 2, and last follow-up (median = 5.2 years) of treatment. Disability progression was quantified using "EDSS-plus" criteria. Neurodegeneration was measured by calculating annualized percentage brain, ventricular, and thalamic volume change (PBVC, VVC, and TVC, respectively). Linear regression analysis was performed to identify longitudinal predictors of neurodegeneration., Results: In total, 88 patients (age = 37 ± 9 years, 75% female) were included, of whom 48% progressed. Year 1 sNfL level (not baseline or 3 months) was associated with PBVC (standardized (std.) β = -0.26, p  = 0.013), VVC (standardized β = 0.36, p  < 0.001), and TVC (standardized β = -0.24, p  = 0.02). For sCNTN1, only 3-month level was associated with VVC (standardized β = -0.31, p  = 0.002)., Conclusion: Year 1 (but not baseline) sNfL level was predictive for long-term brain atrophy in patients treated with natalizumab. sCNTN1 level did not show a clear predictive value.