Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study

Multiple Sclerosis-Specific Reference Curves for Brain Volumes to Explain Disease Severity

BACKGROUND AND OBJECTIVES

Brain atrophy is relevant for understanding disease progression and treatment response in people with multiple sclerosis (pwMS). Automatic brain volume-reporting tools often rely on healthy control (HC) reference curves to interpret brain volumes, whereas brain volume loss is different in pwMS. This observational study aimed to develop an MS-specific reference model for brain volumes and evaluate its performance compared with HC-based curves, as a proof-of-concept.

METHODS

Participants, pwMS and HCs, from the Amsterdam MS cohort were included based on the availability of T1-weighted MR scans. Normalized brain volumes (NBVs) were obtained using commercially available software. The software program also provides NBV percentiles, based on age-specific and sex-specific HC curves, grouped into NBV quartiles, describing deviation from expected NBVs. Disease severity was determined with the MS severity score (MSSS), Symbol Digit Modalities Test (SDMT), and 9-Hole Peg Test (9HPT). An MS-specific model was developed by regressing NBVs against age, sex, disease duration, and MS phenotype. The resulting MS model was also used to classify pwMS into quartiles describing deviation from expected NBV, given the modeled patient characteristics, with leave-one-out predictions. Quartile classification from HC-based and MS-based reference curves was compared with MSSS using analysis of variance (ANOVA).

RESULTS

Regressions for NBVs from 713 pwMS and 259 HCs (mean age: 49.1 ± 9.7 and 48.3 ± 10.1, %female: 70.4% and 67.2%, respectively) were significant for age, sex, disease duration, and phenotype, which were included in the MS-specific model. MS-specific model quartile designations significantly improved associations with MSSS values (p = 2.2*10-9, η2 = 0.06) compared with HC-based quartiles. MSSS values worsened with lower NBV quartiles in the MS-specific model (difference between quartiles 1-4 = -0.84, p = 6.1*10-3, 95% CI [-1.5 to -0.18])), which was not observed for HC-based quartiles (p = 0.98). Quartile group differences were observed for 9HPT (MS: p = 3.5*10-3, η2 = 0.02, HC: p = 6.6*10-3, η2 = 0.02) and SDMT (MS: p = 3.1*10-4, η2 = 0.05, HC: p = 5.4*10-4, η2 = 0.04) values, but MS-specific quartiles again improved quartile associations (p = 0.036, η2 = 0.01 and p = 0.02, η2 = 0.01, respectively).

DISCUSSION

NBV values derived from an MS-specific reference model offer improved relevance for assessing disease severity compared with curves derived from age-specific and sex-specific HC reference models. Improving the model toward application in individual people could enhance clinical implementation.

An update on the treatment and management of cognitive dysfunction in patients with multiple sclerosis

INTRODUCTION

Cognitive impairment (CI) occurs in 34-70% of multiple sclerosis (MS) patients, significantly impacting quality of life. CI can occur independently of physical disability, even in those with 'benign MS.' Cognitive deficits are heterogeneous, but common areas affected include processing speed, memory, and executive functions.

AREAS COVERED

A comprehensive literature search was conducted across databases such as PubMed and Google Scholar, using keywords like 'MS,' 'cognition,' and 'cognitive rehabilitation.' We focused on clinical assessment tools, emerging cognitive phenotypes, and both pharmacological and non-pharmacological treatments, including disease-modifying therapies and cognitive rehabilitation techniques.

EXPERT OPINION

Current evidence underscores the need for a multifaceted approach to managing CI in MS, incorporating emerging pharmacological treatments, cognitive rehabilitation strategies, and exercise programs. Future research should prioritize defining optimal training intensities, integrating therapies for sustained cognitive enhancement, and exploring neuromodulation and neuroimaging biomarkers within randomized controlled trials aimed at improving cognitive functioning in MS.

Cortical lesions impact cognitive decline in multiple sclerosis via volume loss of nonlesional cortex

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.

CSF Parvalbumin Levels at Multiple Sclerosis Diagnosis Predict Future Worse Cognition, Physical Disability, Fatigue, and Gray Matter Damage

BACKGROUND AND OBJECTIVES

Cognitive impairment (CI) in multiple sclerosis (MS) is frequent and determined by a complex interplay between inflammatory and neurodegenerative processes. We aimed to investigate whether CSF parvalbumin (PVALB), measured at the time of diagnosis, may have a prognostic role in patients with MS.

METHODS

In this cohort study, CSF analysis of PVALB and Nf-L levels was performed on all patients at diagnosis (T0) and combined with physical, cognitive, and MRI assessment after an average of 4 years of follow-up (T4) from diagnosis. Cognitive performance was evaluated with a comprehensive neuropsychologic battery: both global (cognitively normal, CN, mildly CI, mCI, and severely CI, sCI) and domain cognitive status (normal/impaired in memory, attention/information processing speed, and executive functions) were considered. Cortical thickness and gray matter volume data were acquired using 3T MRI scanner.

RESULTS

A total of 72 patients with MS were included. At diagnosis, PVALB levels were higher in those patients who showed a worsening physical disability after 4 years of follow-up (p = 0.011). CSF PVALB levels were higher in sCI patients than in CN (p = 0.033). Moreover, higher PVALB levels significantly correlated with worse global cognitive (p = 0.024) and memory functioning (p = 0.044). A preliminary clinical threshold for PVALB levels at diagnosis was proposed (2.57 ng/mL), which maximizes the risk of showing CI (in particular, sCI) at follow-up, with a sensitivity of 91% (specificity 30%). No significant results were found for these associations with Nf-L. In addition, patients with higher levels of PVALB at diagnosis showed higher cognitive (p = 0.024) and global fatigue (p = 0.043) at follow-up. Finally, higher PVALB levels also correlated significantly with more pronounced CTh/volume at T4 in the inferior frontal gyrus (p = 0.044), postcentral gyrus (p = 0.025), frontal pole (p = 0.042), transverse temporal gyrus (p = 0.008), and cerebellar cortex (p = 0.041) and higher atrophy (change T0-T4) in the right thalamus (p = 0.038), pericalcarine cortex (p = 0.009), lingual gyrus (p = 0.045), and medial frontal gyrus (p = 0.028).

DISCUSSION

The significant association found between parvalbumin levels in the CSF at diagnosis and cognitive, clinical, and neuroradiologic worsening after 4 years of follow-up support the idea that parvalbumin, in addition to Nf-L, might represent a new potential prognostic biomarker, reflecting MS neurodegenerative processes occurring since early disease stages.

The contribution of paramagnetic rim and cortical lesions to physical and cognitive disability at multiple sclerosis clinical onset: evaluating the power of MRI and OCT biomarkers

BACKGROUND

In multiple sclerosis (MS), imaging biomarkers play a crucial role in characterizing the disease at the time of diagnosis. MRI and optical coherence tomography (OCT) provide readily available biomarkers that may help to define the patient's clinical profile. However, the evaluation of cortical and paramagnetic rim lesions (CL, PRL), as well as retinal atrophy, is not routinely performed in clinic.

OBJECTIVE

To identify the most significant MRI and OCT biomarkers associated with early clinical disability in MS.

METHODS

Brain, spinal cord (SC) MRI, and OCT scans were acquired from 45 patients at MS diagnosis to obtain: brain PRL and non-PRL, CL, SC lesion volumes and counts, brain volumetric metrics, SC C2-C3 cross-sectional area, and retinal layer thickness. Regression models assessed relationships with physical disability (Expanded Disability Status Scale [EDSS]) and cognitive performance (Brief International Cognitive Assessment for Multiple Sclerosis [BICAMS]).

RESULTS

In a stepwise regression (R2 = 0.526), PRL (β = 0.001, p = 0.023) and SC lesion volumes (β = 0.001, p = 0.017) were the most significant predictors of EDSS, while CL volume and age were strongly associated with BICAMS scores. Moreover, in a model where PRL and non-PRL were pooled, only the contribution of SC lesion volume was retained in EDSS prediction. OCT measures did not show associations with disability at the onset.

CONCLUSION

At MS onset, PRL and SC lesions exhibit the strongest association with physical disability, while CL strongly contribute to cognitive performance. Incorporating the evaluation of PRL and CL into the initial MS patient assessment could help define their clinical profile, thus supporting the treatment choice.

Predicting multiple sclerosis disease progression and outcomes with machine learning and MRI-based biomarkers: a review

Multiple sclerosis (MS) is a demyelinating neurological disorder with a highly heterogeneous clinical presentation and course of progression. Disease-modifying therapies are the only available treatment, as there is no known cure for the disease. Careful selection of suitable therapies is necessary, as they can be accompanied by serious risks and adverse effects such as infection. Magnetic resonance imaging (MRI) plays a central role in the diagnosis and management of MS, though MRI lesions have displayed only moderate associations with MS clinical outcomes, known as the clinico-radiological paradox. With the advent of machine learning (ML) in healthcare, the predictive power of MRI can be improved by leveraging both traditional and advanced ML algorithms capable of analyzing increasingly complex patterns within neuroimaging data. The purpose of this review was to examine the application of MRI-based ML for prediction of MS disease progression. Studies were divided into five main categories: predicting the conversion of clinically isolated syndrome to MS, cognitive outcome, EDSS-related disability, motor disability and disease activity. The performance of ML models is discussed along with highlighting the influential MRI-derived biomarkers. Overall, MRI-based ML presents a promising avenue for MS prognosis. However, integration of imaging biomarkers with other multimodal patient data shows great potential for advancing personalized healthcare approaches in MS.

Predictive value of synaptic plasticity for functional decline in patients with multiple sclerosis

Background

Previous research suggested that quadripulse (QPS)-induced synaptic plasticity is associated with both cognitive and motor function in patients with multiple sclerosis (MS) and does not appear to be reduced compared to healthy controls (HCs).

Objective

This study aimed to explore the relationship between the degree of QPS-induced plasticity and clinically significant decline in motor and cognitive functions over time. We hypothesized that MS patients experiencing functional decline would exhibit lower levels of baseline plasticity compared to those without decline.

Methods

QPS-induced plasticity was evaluated in 80 MS patients (56 with relapsing-remitting MS and 24 with progressive MS), and 69 age-, sex-, and education-matched HCs. Cognitive and motor functions, as well as overall disability status were evaluated annually over a median follow-up period of 2 years. Clinically meaningful change thresholds were predefined for each outcome measure. Linear mixed-effects models, Cox proportional hazard models, logistic regression, and receiver-operating characteristic analysis were applied to analyse the relationship between baseline plasticity and clinical progression in the symbol digit modalities test, brief visuospatial memory test revised (BVMT-R), nine-hole peg test (NHPT), timed 25-foot walk test, and expanded disability status scale.

Results

Overall, the patient cohort showed no clinically relevant change in any functional outcome over time. Variability in performance was observed across time points in both patients and HCs. MS patients who experienced clinically relevant decline in manual dexterity and/or visuospatial learning and memory had significantly lower levels of synaptic plasticity at baseline compared to those without such decline (NHPT: β = -0.25, p = 0.02; BVMT-R: β = -0.50, p = 0.005). Receiver-operating characteristic analysis underscored the predictive utility of baseline synaptic plasticity in discerning between patients experiencing functional decline and those maintaining stability only for visuospatial learning and memory (area under the curve = 0.85).

Conclusion

Our study suggests that QPS-induced plasticity could be linked to clinically relevant functional decline in patients with MS. However, to solidify these findings, longer follow-up periods are warranted, especially in cohorts with higher prevalences of functional decline. Additionally, the variability in cognitive performance in both patients with MS and HCs underscores the importance of conducting further research on reliable change based on neuropsychological tests.

Intrinsic and extrinsic contributors to subregional thalamic volume loss in multiple sclerosis

OBJECTIVE

To evaluate the intrinsic and extrinsic microstructural factors contributing to atrophy within individual thalamic subregions in multiple sclerosis using in vivo high-gradient diffusion MRI.

METHODS

In this cross-sectional study, 41 people with multiple sclerosis and 34 age and sex-matched healthy controls underwent 3T MRI with up to 300 mT/m gradients using a multi-shell diffusion protocol consisting of eight b-values and diffusion time of 19 ms. Each thalamus was parcellated into 25 subregions for volume determination and diffusion metric estimation. The soma and neurite density imaging model was applied to obtain estimates of intra-neurite, intra-soma, and extra-cellular signal fractions for each subregion and within structurally connected white matter trajectories and cortex.

RESULTS

Multiple sclerosis-related volume loss was more pronounced in posterior/medial subregions than anterior/ventral subregions. Intra-soma signal fraction was lower in multiple sclerosis, reflecting reduced cell body density, while the extra-cellular signal fraction was higher, reflecting greater extra-cellular space, both of which were observed more in posterior/medial subregions than anterior/ventral subregions. Lower intra-neurite signal fraction in connected normal-appearing white matter and lower intra-soma signal fraction of structurally connected cortex were associated with reduced subregional thalamic volumes. Intrinsic and extrinsic microstructural measures independently related to subregional volume with heterogeneity across atrophy-prone thalamic nuclei. Extrinsic microstructural alterations predicted left anteroventral, intrinsic microstructural alterations predicted bilateral medial pulvinar, and both intrinsic and extrinsic factors predicted lateral geniculate and medial mediodorsal volumes.

INTERPRETATION

Our results might be reflective of the involvement of anterograde and retrograde degeneration from white matter demyelination and cerebrospinal fluid-mediated damage in subregional thalamic volume loss.

An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression

INTRODUCTION

While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear.

AREAS COVERED

The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning.

EXPERT OPINION

Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.

Don't be late! Postponing cognitive decline and preventing early unemployment in people with multiple sclerosis: a study protocol

BACKGROUND

Up to 65% of people with multiple sclerosis (PwMS) develop cognitive deficits, which hampers their ability to work, participating in day-to-day life and ultimately reducing quality of life (QoL). Early cognitive symptoms are often less tangible to PwMS and their direct environment and are noticed only when symptoms and work functioning problems become more advanced, i.e., when (brain) damage is already advanced. Treatment of symptoms at a late stage can lead to cognitive impairment and unemployment, highlighting the need for preventative interventions in PwMS.

AIMS

This study aims to evaluate the (cost-) effectiveness of two innovative preventative interventions, aimed at postponing cognitive decline and work functioning problems, compared to enhanced usual care in improving health-related QoL (HRQoL).

METHODS

Randomised controlled trial including 270 PwMS with mild cognitive impairment, who have paid employment ≥ 12 h per week and are able to participate in physical exercise (Expanded Disability Status Scale < 6.0). Participants are randomised across three study arms: 1) 'strengthening the brain' - a lifestyle intervention combining personal fitness, mental coaching, dietary advice, and cognitive training; 2) 'strengthening the mind' - a work-focused intervention combining the capability approach and the participatory approach in one-on-one coaching by trained work coaches who have MS themselves; 3) Control group-receiving general information about cognitive impairment in MS and receiving care as usual. Intervention duration is four months, with short-term and long-term follow-up measurements at 10 and 16 months, respectively. The primary outcome measure of the Don't be late! intervention study will be HRQoL as measured with the 36-item Short Form. Secondary outcomes include cognition, work related outcomes, physical functioning, structural and functional brain changes, psychological functioning, and societal costs. Semi-structured interviews and focus groups with stakeholders will be organised to qualitatively reflect on the process and outcome of the interventions.

DISCUSSION

This study seeks to prevent (further) cognitive decline and job loss due to MS by introducing tailor-made interventions at an early stage of cognitive symptoms, thereby maintaining or improving HRQoL. Qualitative analyses will be performed to allow successful implementation into clinical practice.

TRIAL REGISTRATION

Retrospectively registered at ClinicalTrials.gov with reference number NCT06068582 on 10 October 2023.

Reliability of brain atrophy measurements in multiple sclerosis using MRI: an assessment of six freely available software packages for cross-sectional analyses

PURPOSE

Volume measurement using MRI is important to assess brain atrophy in multiple sclerosis (MS). However, differences between scanners, acquisition protocols, and analysis software introduce unwanted variability of volumes. To quantify theses effects, we compared within-scanner repeatability and between-scanner reproducibility of three different MR scanners for six brain segmentation methods.

METHODS

Twenty-one people with MS underwent scanning and rescanning on three 3 T MR scanners (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) to obtain 3D T1-weighted images. FreeSurfer, FSL, SAMSEG, FastSurfer, CAT-12, and SynthSeg were used to quantify brain, white matter and (deep) gray matter volumes both from lesion-filled and non-lesion-filled 3D T1-weighted images. We used intra-class correlation coefficient (ICC) to quantify agreement; repeated-measures ANOVA to analyze systematic differences; and variance component analysis to quantify the standard error of measurement (SEM) and smallest detectable change (SDC).

RESULTS

For all six software, both between-scanner agreement (ICCs ranging 0.4-1) and within-scanner agreement (ICC range: 0.6-1) were typically good, and good to excellent (ICC > 0.7) for large structures. No clear differences were found between filled and non-filled images. However, gray and white matter volumes did differ systematically between scanners for all software (p < 0.05). Variance component analysis yielded within-scanner SDC ranging from 1.02% (SAMSEG, whole-brain) to 14.55% (FreeSurfer, CSF); and between-scanner SDC ranging from 4.83% (SynthSeg, thalamus) to 29.25% (CAT12, thalamus).

CONCLUSION

Volume measurements of brain, GM and WM showed high repeatability, and high reproducibility despite substantial differences between scanners. Smallest detectable change was high, especially between different scanners, which hampers the clinical implementation of atrophy measurements.

Comparing individual and group-level simulated neurophysiological brain connectivity using the Jansen and Rit neural mass model

Computational models are often used to assess how functional connectivity (FC) patterns emerge from neuronal population dynamics and anatomical brain connections. It remains unclear whether the commonly used group-averaged data can predict individual FC patterns. The Jansen and Rit neural mass model was employed, where masses were coupled using individual structural connectivity (SC). Simulated FC was correlated to individual magnetoencephalography-derived empirical FC. FC was estimated using phase-based (phase lag index (PLI), phase locking value (PLV)), and amplitude-based (amplitude envelope correlation (AEC)) metrics to analyze their goodness of fit for individual predictions. Individual FC predictions were compared against group-averaged FC predictions, and we tested whether SC of a different participant could equally well predict participants' FC patterns. The AEC provided a better match between individually simulated and empirical FC than phase-based metrics. Correlations between simulated and empirical FC were higher using individual SC compared to group-averaged SC. Using SC from other participants resulted in similar correlations between simulated and empirical FC compared to using participants' own SC. This work underlines the added value of FC simulations using individual instead of group-averaged SC for this particular computational model and could aid in a better understanding of mechanisms underlying individual functional network trajectories.

Altered social cognition in early relapsing remitting multiple sclerosis

INTRODUCTION

People with multiple sclerosis (pwMS) may suffer from some degree of impaired social cognition (SC), the process that integrates the mental operations underlying social interactions. SC is still not clearly characterized in the early stages of MS, and it is not defined whether SC is independent of cognitive impairment.

METHODS

In this cross-sectional study, we aimed to compare SC measures in a population of early (≤5 years) relapsing-remitting MS (RRMS) with an age, sex, and education-matched control group. All participants performed a clinical and a comprehensive neuropsychological assessment. SC evaluation included assessment of facial emotion recognitionn by the Emotion Recognition Task, affective theory of mind (ToM) by the Reading the Mind in the eyes Test (RMET) and cognitive ToM by the Faux Pas test (FPT). Depression, anxiety, fatigue, and quality of life were also assessed. We included 38 pwMS (mean age 34.8 ± 8.7, 78.9% female sex, mean disease duration 1.9±1.3 years) and 38 healthy controls (mean age 34.9 ± 8.4, 81.6% female sex).

RESULTS

Altered social cognition was present in 34.2% of pwMS. Participants with MS performed worse than controls on measures of cognitive ToM, and affective ToM. There were no differences regarding FER. Cognitive ToM and FER correlated with cognitive functions, but no correlation was found between affective ToM and cognitive tests. The only clinical factor associated with altered SC was poor quality of life.

CONCLUSIONS

Social cognition impairment is already present in a significant percentage of early RRMS patients, namely ToM deficits. While cognitive ToM and FER appears to correlate with impaired cognitive results, affective ToM is likely independent of other cognitive functions.

Neurodegeneration and its potential markers in the diagnosing of secondary progressive multiple sclerosis. A review

Approximately 70% of relapsing-remitting multiple sclerosis (RRMS) patients will develop secondary progressive multiple sclerosis (SPMS) within 10-15 years. This progression is characterized by a gradual decline in neurological functionality and increasing limitations of daily activities. Growing evidence suggests that both inflammation and neurodegeneration are associated with various pathological processes throughout the development of MS; therefore, to delay disease progression, it is critical to initiate disease-modifying therapy as soon as it is diagnosed. Currently, a diagnosis of SPMS requires a retrospective assessment of physical disability exacerbation, usually over the previous 6-12 months, which results in a delay of up to 3 years. Hence, there is a need to identify reliable and objective biomarkers for predicting and defining SPMS conversion. This review presents current knowledge of such biomarkers in the context of neurodegeneration associated with MS, and SPMS conversion.

Brain Atrophy as an Outcome of Disease-Modifying Therapy for Remitting-Relapsing Multiple Sclerosis

Introduction

Currently, clinical trials of DMTs strive to determine their effect on neuroinflammation and neurodegeneration. We aimed to determine the impact of currently used DMTs on brain atrophy and disability in RRMS. The main goal of this review is to evaluate the neuroprotective potential of MS therapy and assess its impact on disability.

Methods

We performed a systematic analysis of clinical trials that used brain atrophy as an outcome or performed post hoc analysis of volumetric MRI parameters to assess the neuroprotective potential of applied therapies. Trials between 2008 and 2019 that included published results of brain parenchymal fraction (BPF) change and brain volume loss (BVL) in the period from baseline to week 96 or longer were considered.

Results

Twelve from 146 clinical trials met the inclusion criteria and were incorporated into the analysis. DMTs that presented a large reduction in BVL also exhibited robust effects on clinical disability worsening, e.g., alemtuzumab with a 42% risk reduction in 6-month confirmed disability accumulation (p = 0.0084), ocrelizumab with a 40% risk reduction in 6-month confirmed disability progression (p = 0.003), and other DMTs (cladribine and teriflunomide) with moderate influence on brain atrophy were also associated with a marked impact on disability worsening. Dimethyl fumarate (DEFINE) and fingolimod (FREEDOMS I) initially exhibited significant effect on BVL; however, this effect was not confirmed in further clinical trials: CONFIRM and FREEDOMS II, respectively. Peg-IFN-β1a shows a modest effect on BVL and disability worsening.

Conclusion

Our results show that BVL in one of the components of clinical disability worsening, together with other variables (lesion volume and annualized relapse rate). Standardization of atrophy measurement technique as well as harmonization of disability worsening and progression criteria in further clinical trials are of utmost importance as they enable a reliable comparison of neuroprotective potential of DMTs.

The impact of disease modifying therapies on cognitive functions typically impaired in multiple sclerosis patients: a clinician's review

Objective

Over the last few decades clinicians have become aware that cognitive impairment might be a major cause of disability, loss of employment and poor quality of life in patients suffering from multiple sclerosis [MS].The impact of disease modifying therapies [DMTs] on cognition is still a matter of debate. Theoretically, DMTs could exert a substantial beneficial effect by means of reducing neuroinflammation and brain atrophy, which are established correlates of cognitive dysfunction. The aim of the study was to review the evidence concerning the effect of DMTs on cognitive functions.

Methods

PubMed, Scopus, and the European Committee for Treatment and Research in Multiple Sclerosis [ECTRIMS] Library were searched for articles concerning the pediatric and adult populations of patients with multiple sclerosis, including clinical trials and RWD, where psychometric results were analyzed as secondary or exploratory endpoints.

Results

We reviewed a total of 44 studies that were found by our search strategy, analyzed the psychological tests that were applied, the length of the follow-up, and possible limitations. We pointed out the difficulties associated with assessing of DMTs' effects on cognitive functions, and pitfalls in cognitive tools used for evaluating of MS patients.

Conclusion

There is a need to highlight this aspect of MS therapies, and to collect adequate data to make informed therapeutic decisions, to improve our understanding of MS-related cognitive dysfunction and provide new therapeutic targets.

Central nervous system demyelinating diseases: glial cells at the hub of pathology

Inflammatory demyelinating diseases (IDDs) are among the main causes of inflammatory and neurodegenerative injury of the central nervous system (CNS) in young adult patients. Of these, multiple sclerosis (MS) is the most frequent and studied, as it affects about a million people in the USA alone. The understanding of the mechanisms underlying their pathology has been advancing, although there are still no highly effective disease-modifying treatments for the progressive symptoms and disability in the late stages of disease. Among these mechanisms, the action of glial cells upon lesion and regeneration has become a prominent research topic, helped not only by the discovery of glia as targets of autoantibodies, but also by their role on CNS homeostasis and neuroinflammation. In the present article, we discuss the participation of glial cells in IDDs, as well as their association with demyelination and synaptic dysfunction throughout the course of the disease and in experimental models, with a focus on MS phenotypes. Further, we discuss the involvement of microglia and astrocytes in lesion formation and organization, remyelination, synaptic induction and pruning through different signaling pathways. We argue that evidence of the several glia-mediated mechanisms in the course of CNS demyelinating diseases supports glial cells as viable targets for therapy development.

[A case of primary progressive multiple sclerosis with improvement in cognitive impairment by anti-CD20 monoclonal antibody therapy]

The patient was a 44-year-old man who developed cognitive impairment beginning at the age of 35 years that gradually worsened. The cognitive impairment led to a difficult social life, and he retired from his company. After hospitalization and workup, he was diagnosed with primary progressive multiple sclerosis (PPMS) that presented only with cognitive impairment for 10 years. Since he had multiple predictive factors for poor prognosis, anti-CD20 monoclonal antibody therapy was implemented. Cognitive impairment and cerebral blood flow SPECT findings improved, and he returned to a social life 3 months later. Anti-CD20 monoclonal antibody therapy was effective in improving cognitive impairment in a case of an advanced stage of PPMS.

Electroacupuncture promotes remyelination and alleviates cognitive deficit via promoting OPC differentiation in a rat model of subarachnoid hemorrhage

Subarachnoid hemorrhage (SAH) is a devastating cerebral vascular disease which causes neurological deficits including long-term cognitive deficit. Demyelination of white matter is correlated with cognitive deficit in SAH. Electroacupuncture (EA) is a traditional Chinese medical treatment which protects against cognitive deficit in varies of neurological diseases. However, whether EA exerts protective effect on cognitive function in SAH has not been investigated. The underlying mechanism of remyelination regulated by EA remains unclear. This study aimed to investigate the protective effects of EA on cognitive deficit in a rat model of SAH. SAH was induced in SD rats (n = 72) by endovascular perforation. Rats in EA group received EA treatment (10 min per day) under isoflurane anesthesia after SAH. Rats in SAH and sham groups received the same isoflurane anesthesia with no treatment. The mortality rate, neurological score, cognitive function, cerebral blood flow (CBF), and remyelination in sham, SAH and EA groups were assessed at 21 d after SAH.EA treatment alleviated cognitive deficits and myelin injury of rats compared with that in SAH group. Moreover, EA treatment enhanced remyelination in white matter and promoted the differentiation of OPCs after SAH. EA treatment inhibited the expression of Id2 and promoted the expression of SOX10 in oligodendrocyte cells. Additionally, the cerebral blood flow (CBF) of rats was increased by EA compared with that in SAH group. EA treatment exerts protective effect against cognitive deficit in the late phase of SAH. The underlying mechanisms involve promoting oligodendrocyte progenitor cell (OPC) differentiation and remyelination in white matter via regulating the expression of Id2 and SOX10. The improvement of CBF may also account for the protective effect of EA on cognitive function. EA treatment is a potential therapy for the treatment of cognitive deficit after SAH.

NODDI, diffusion tensor microstructural abnormalities and atrophy of brain white matter and gray matter contribute to cognitive impairment in multiple sclerosis

BACKGROUND

Pathologically specific MRI measures may elucidate in-vivo the heterogeneous processes contributing to cognitive impairment in multiple sclerosis (MS).

PURPOSE

Using diffusion tensor and neurite orientation dispersion and density imaging (NODDI), we explored the contribution of focal lesions and normal-appearing (NA) tissue microstructural abnormalities to cognitive impairment in MS.

METHODS

One hundred and fifty-two MS patients underwent 3 T brain MRI and a neuropsychological evaluation. Forty-eight healthy controls (HC) were also scanned. Fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (ICV_f) and orientation dispersion index (ODI) were assessed in cortical and white matter (WM) lesions, thalamus, NA cortex and NAWM. Predictors of cognitive impairment were identified using random forest.

RESULTS

Fifty-two MS patients were cognitively impaired. Compared to cognitively preserved, impaired MS patients had higher WM lesion volume (LV), lower normalized brain volume (NBV), cortical volume (NCV), thalamic volume (NTV), and WM volume (p ≤ 0.021). They also showed lower NAWM FA, higher NAWM, NA cortex and thalamic MD, lower NAWM ICV_f, lower WM lesion ODI, and higher NAWM ODI (false discovery rate-p ≤ 0.026). Cortical lesion number and microstructural abnormalities were not significantly different. The best MRI predictors of cognitive impairment (relative importance) (out-of-bag area under the curve = 0.727) were NAWM FA (100%), NTV (96.0%), NBV (84.7%), thalamic MD (43.4%), NCV (40.6%), NA cortex MD (26.0%), WM LV (23.2%) and WM lesion ODI (17.9%).

CONCLUSIONS

Our multiparametric MRI study including NODDI measures suggested that neuro-axonal damage and loss of microarchitecture integrity in focal WM lesions, NAWM, and GM contribute to cognitive impairment in MS.

Magnetic Resonance Imaging in Primary Progressive Multiple Sclerosis Patients : Review

The recently developed effective treatment of primary progressive multiple sclerosis (PPMS) requires the accurate diagnosis of patients with this type of disease. Currently, the diagnosis of PPMS is based on the 2017 McDonald criteria, although the contribution of magnetic resonance imaging (MRI) to this process is fundamental. PPMS, one of the clinical types of MS, represents 10%-15% of all MS patients. Compared to relapsing-remitting MS (RRMS), PPMS differs in terms of pathology, clinical presentation and MRI features. Regarding conventional MRI, focal lesions on T2-weighted images and acute inflammatory lesions with contrast enhancement are less common in PPMS than in RRMS. On the other hand, MRI features of chronic inflammation, such as slowly evolving/expanding lesions (SELs) and leptomeningeal enhancement (LME), and brain and spinal cord atrophy are more common MRI characteristics in PPMS than RRMS. Nonconventional MRI also shows differences in subtle white and grey matter damage between PPMS and other clinical types of disease. In this review, we present separate diagnostic criteria, conventional and nonconventional MRI specificity for PPMS, which may support and simplify the diagnosis of this type of MS in daily clinical practice.

Eating Hubs in Multiple Sclerosis: Exploring the Relationship Between Mediterranean Diet and Disability Status in Italy

Background

Multiple Sclerosis (MS) is a complex disease in which multiple factors contribute to disability accrual. Mediterranean Diet (MeDi) has shown beneficial effects across neurodegenerative diseases. We hypothesize that specific food habits, rather than global adherence to MeDi, might impact on MS. We aimed to (i) evaluate differences in adherence to MeDi between people living with MS (PwMS) and healthy controls (HC); (ii) characterize eating patterns in PwMS and HC, identifying the most influential MeDi items for each group by the use of network analysis; (iii) explore the relationship between patients' eating habits and disability.

Materials and Methods

In this cross-sectional study, we consecutively recruited 424 PwMS and 165 matched HC. Data were obtained through the administration of self-reported questionnaires. Expanded Disability Status Scale (EDSS) and Fatigue Severity Scale (FSS) were evaluated in the MS population. We performed between-groups comparisons via unpaired two-sample t-test and X² test as appropriate. We calculated food networks in both MS cases and HC using and tested the association between hub nodes and disability. Finally, we conducted a post-hoc analysis, investigating the relationship between food items, lifestyle factors (smoking, exercise) and clinical outcomes.

Results

Most participants adhered sufficiently to MeDi. Exploring each group separately, fruit, vegetables, cereal, and fish were identified as hubs in PwMS, while meat and alcohol were identified as hubs in HC. Hubs were all inter-correlated, indicating that eating habits of PwMS include a large intake of all the foods identified as hubs. EDSS was predicted by the intake of vegetables (beta = −0.36, p < 0.03) and fish (beta = −0.34, p < 0.02). The model including smoking pack/year, International Physical Activity Questionnaire (IPAQ) score and intake of “negative foods” predicted 6% of the variance in EDSS (p < 0.001), while the model including smoking pack/year and IPAQ score predicted 4% of the variance in FSS (p < 0.001).

Conclusions

We identified a sufficient adherence to MeDi in our population. PwMS showed overall a healthier dietary pattern than HC. Vegetables and fish intake were associated with disability outcomes. Future longitudinal studies applying integrated approaches are needed to understand lifestyle added value to the use of standard pharmacological therapies.

Establishing an individualized model of conversion from normal cognition to Alzheimer's disease after 4 years, based on cognitive, brain morphology and neuropsychiatric characteristics

OBJECTIVES

The impact of neuropsychiatric symptoms (NPS) on cognitive performance has been reported, and this impact was better defined in the aging population. Yet the potential of using the impact of NPS on brain and cognitive performance in a longitudinal setting, as prediction of conversion - have remained questionable. This study proposes to establish a predictive model of conversion to Alzheimer's disease (AD) and mild cognitive impairment (MCI) based on current cognitive performance, NPS and their associations with brain morphology.

METHODS

156 participants with MCI from the Alzheimer's Disease Neuroimaging Initiative database cognitively stable after a 4-year follow-up were compared to 119 MCI participants who converted to AD. Each participant underwent a neuropsychological assessment evaluating verbal memory, language, executive and visuospatial functions, a neuropsychiatric inventory evaluation and a 3 Tesla MRI. The statistical analyses consisted of 1) baseline comparison between the groups; 2) analysis of covariance model (controlling demographic parameters including functional abilities) to specify the variables that distinguish the two subgroups and; 3) used the significant ANCOVA variables to construct a binary logistic regression model that generates a probability equation to convert to a lower cognitive performance state.

RESULTS

Results showed that MCI who converted to AD in comparison to stable MCI, exhibited a higher NPS prevalence, a lower cognitive performance and a higher number of involved brain structures. Functional abilities, memory performance and the sizes of inferior temporal, hippocampal and amygdala sizes were significant predictors of MCI to AD conversion. We also report two models of conversion that can be implemented on an individual basis for calculating the percentage risk of conversion after 4 years.

CONCLUSION

These analytical methods might be a good way to anticipate cognitive and brain declines.

The Application of Diffusion Kurtosis Imaging on the Heterogeneous White Matter in Relapsing-Remitting Multiple Sclerosis

Objectives

To evaluate the microstructural damage in the heterogeneity of different white matter areas in relapsing-remitting multiple sclerosis (RRMS) patients by using diffusion kurtosis imaging (DKI) and its correlation with clinical and cognitive status.

Materials and Methods

Kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), and mean diffusivity (MD) in T1-hypointense lesions (T1Ls), pure T2-hyperintense lesions (pure-T2Ls), normal-appearing white matter (NAWM), and white matter in healthy controls (WM in HCs) were measured in 48 RRMS patients and 26 sex- and age-matched HCs. All the participants were assessed with the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Symbol Digit Modalities Test (SDMT) scores as the cognitive status. The Kurtzke Expanded Disability Status Scale (EDSS) scores were used to evaluate the clinical status in RRMS patients.

Results

The lowest KFA, FA, and MK values and the highest MD values were found in T1Ls, followed by pure-T2Ls, NAWM, and WM in HCs. The T1Ls and pure-T2Ls were significantly different in FA (p = 0.002) and MK (p = 0.013), while the NAWM and WM in HCs were significantly different in KFA, FA, and MK (p < 0.001; p < 0.001; p = 0.001). The KFA, FA, MK, and MD values in NAWM (r = 0.360, p = 0.014; r = 0.415, p = 0.004; r = 0.369, p = 0.012; r = −0.531, p < 0.001) were correlated with the MMSE scores and the FA, MK, and MD values in NAWM (r = 0.423, p = 0.003; r = 0.427, p = 0.003; r = −0.359, p = 0.014) were correlated with the SDMT scores.

Conclusion

Applying DKI to the imaging-based white matter classification has the potential to reflect the white matter damage and is correlated with cognitive impairment.

Predictive MRI Biomarkers in MS—A Critical Review

Background and Objectives: In this critical review, we explore the potential use of MRI measurements as prognostic biomarkers in multiple sclerosis (MS) patients, for both conventional measurements and more novel techniques such as magnetization transfer, diffusion tensor, and proton spectroscopy MRI. Materials and Methods: All authors individually and comprehensively reviewed each of the aspects listed below in PubMed, Medline, and Google Scholar. Results: There are numerous MRI metrics that have been proven by clinical studies to hold important prognostic value for MS patients, most of which can be readily obtained from standard 1.5T MRI scans. Conclusions: While some of these parameters have passed the test of time and seem to be associated with a reliable predictive power, some are still better interpreted with caution. We hope this will serve as a reminder of how vast a resource we have on our hands in this versatile tool—it is up to us to make use of it.

Cognitive trajectories in multiple sclerosis: a long-term follow-up study

BACKGROUND

Cognitive impairment occurs in multiple sclerosis (MS) and undergoes a progressive worsening over disease course. However, clinicians still struggle to predict the course of cognitive function. To evaluate baseline clinical and imaging predictors of cognitive abilities worsening over time, we performed a latent trajectory analysis for cognitive performances in MS patients, up to 15 years from disease onset.

METHODS

We collected age, sex, education, dominant and non-dominant 9-hole peg test (9HP) and timed 25-foot walk (T25-FW) as well as MRI measures (grey matter volume and lesion load) within 6 months from disease diagnosis for relapsing-remitting MS (RR-MS) patients. At diagnosis and over the follow-up, we also assessed cognitive status through the symbol digit modalities test (SDMT). Cognitive impairment was defined by applying age-, gender- and education-adjusted normative values. Group-based trajectory analysis was performed to determine trajectories, and the predictive value of clinical and imaging variables at baseline was assessed through multinomial logistic regression.

RESULTS

We included 148 RR-MS (98 females and 50 males). Over 11 ± 4 year follow-up, 51.4% remained cognitively stable whereas 48.6% cognitively worsened. Cognitively worsening patients had a higher T25FW time (p = 0.004) and a reduced hippocampal volume at baseline (p = 0.04).

CONCLUSION

Physical disability as well as hippocampal atrophy might depict patients at risk of cognitive worsening over the disease course. Therefore, using such predictors, clinicians may select patients to carefully evaluate for cognitive impairment as to eventually introduce cognitive rehabilitation treatments.

Cognitive Impairment in Secondary Progressive Multiple Sclerosis: Effect of Disease Duration, Age, and Progressive Phenotype

Background: Cognitive deficits are common in multiple sclerosis (MS) and affect patients at all stages of the disease, regardless of phenotype. Aims: This literature review focuses the cognitive deficits observed in secondary progressive MS (SPMS). It is mainly based on studies that compared the frequency and main characteristics of cognitive deficits in SPMS with other phenotypes. Methods: A bibliographic search was carried out using the PubMed database with the following keywords: multiple sclerosis, secondary-progressive, cognition. Results: Thirteen studies were initially selected that were published in English, reporting the neuropsychological data of a sample of at least 30 patients with SPMS, comparing them with patients with other phenotypes. Studies suggest that there is an association between the duration of the disease and the frequency and extent of the cognitive disorders. Studies also showed that the SP form is associated with an increased frequency of cognitive impairment and with an increased severity as compared to relapsing-remitting MS (RRMS). Compared to RRMS, progressive forms of MS are associated with more severe impairment in certain cognitive areas, such as episodic verbal memory, information processing speed, working memory, or verbal fluency. Two studies showed that cognitive performances decline overtime in SPMS. Conclusion: Cognitive disorders are more frequent and more severe in the SP form than in relapsing course of MS. The profile of cognitive impairment encountered in the SP form also appears to be different from those found in the other phenotypes.

Real-world effectiveness of dimethyl fumarate versus fingolimod in a cohort of patients with multiple sclerosis using standardized, quantitative outcome metrics

Background

Prior studies suggest comparable effectiveness of dimethyl fumarate (DMF) and fingolimod (FTY) in multiple sclerosis (MS) using relapse, Expanded Disability Status Score (EDSS), and magnetic resonance imaging (MRI) lesion metrics.

Objective

Compare the real-world effectiveness of DMF versus FTY using quantitative, validated neuroperformance tests, MRI, and serum neurofilament light chain (sNfL) outcomes while controlling for between-group differences.

Methods

Patients were eligible if on DMF or FTY when first enrolled in the MS Partners Advancing Technology and Health Solutions (MS PATHS) network and had ≥1-year follow-up in MS PATHS. Sensitivity analysis included a subgroup who started DMF/FTY ≤2 years from enrolment. After propensity score weighting, differences in means and in mean 1-year change of neuroperformance and MRI outcomes were compared. sNfL levels were assessed. This was a non-randomized comparison.

Results

In the overall cohort, no significant differences were observed between DMF (n = 702) and FTY (n = 600) in neuroperformance or MRI outcomes including brain volume loss; mean time (SD) since treatment initiation was 1.98 (0.68) years for DMF and 2.02 (0.75) years for FTY. A sensitivity analysis controlling for DMF and FTY treatment duration yielded similar results.

Conclusion

In this study, DMF and FTY demonstrated similar effects on physical and cognitive neuroperformance and MRI outcomes. Direct comparisons to other fumarates and S1P receptor modulators were not conducted.

Low‑field magnetic stimulation improved cuprizone‑induced depression‑like symptoms and demyelination in female mice

Depression is a common and disabling comorbidity of multiple sclerosis (MS), with currently no clear guidelines for treatment. Low-field magnetic stimulation (LFMS), a novel non-invasive neuromodulation intervention, has been previously demonstrated to rapidly alleviate mood disorders. The aim of the present study was to investigate the effects of LFMS on depression-like behaviors and demyelination in a well-established mouse model of MS. C57BL/6 female mice were fed a 0.2% cuprizone (CPZ) diet for 3 or 6 weeks to induce acute demyelination. During this time, the mice were treated with either sham or LFMS for 20 min/day, 5 days/week. After 3 or 6 weeks of treatment, behavior was assessed with the open field task, Y-maze and the forced swim test. The prefrontal cortex and hippocampus were then collected to perform immunohistochemistry and western blot analysis to verify myelination status. The CPZ diet did not cause significant locomotor deficits; however, working memory, measured using the Y maze, depression-like behavior and adaptive learning, assayed using the forced swim test, were significantly impaired in these animals. LFMS treatment demonstrated a significant antidepressant-like effect and markedly attenuated the CPZ-induced demyelination in the prefrontal cortex after 3- and 6-weeks of treatment, as observed by changes in myelin basic protein immunostaining and western blot analysis. Therefore, the results of the present study indicated that LFMS may be a promising therapy for demyelinating diseases due to the improvement of depressive symptoms via regulation of myelination in cortical areas.

Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis

Multiple sclerosis (MS) features extensive connectivity changes, but how structural and functional connectivity relate, and whether this relation could be a useful biomarker for cognitive impairment in MS is unclear.

This study included 79 MS patients and 40 healthy controls (HCs). Patients were classified as cognitively impaired (CI) or cognitively preserved (CP). Structural connectivity was determined using diffusion MRI and functional connectivity using resting-state magnetoencephalography (MEG) data (theta, alpha1 and alpha2 bands). Structure-function coupling was assessed by correlating modalities, and further explored in frequency bands that significantly correlated with whole-brain structural connectivity. Functional correlates of short- and long-range structural connections (based on tract length) were then specifically assessed. ROC analyses were performed on coupling values to identify biomarker potential.

Only the theta band showed significant correlations between whole-brain structural and functional connectivity (rho = −0.26, p = 0.023, only in MS). Long-range structure-function coupling was higher in CI patients compared to HCs (p = 0.005). Short-range coupling showed no group differences. Structure-function coupling was not a significant classifier of cognitive impairment for any tract length (short-range AUC = 0.498, p = 0.976, long-range AUC = 0.611, p = 0.095).

Long-range structure-function coupling was higher in CI-MS compared to HC, but more research is needed to further explore this measure as biomarkers in MS.

Synaptic Loss in Multiple Sclerosis: A Systematic Review of Human Post-mortem Studies

Background: Gray matter pathology plays a central role in the progression of multiple sclerosis (MS). The occurrence of synaptic loss appears to be important but, to date, still poorly investigated aspect of MS pathology. In this systematic review, we drew from the recent knowledge about synaptic loss in human post-mortem studies. Methods: We conducted a systematic search with PubMed to identify relevant publications. Publications available from15 June 2021 were taken into account. We selected human post-mortem studies that quantitatively assessed the synapse number in MS tissue. Results: We identified 14 relevant publications out of which 9 reported synaptic loss in at least one investigated subregion. The most commonly used synaptic marker was synaptophysin; non-etheless, we found substantial differences in the methodology and the selection of reference tissue. Investigated regions included the cortex, the hippocampus, the cerebellum, the thalamus, and the spinal cord. Conclusion: Synaptic loss seems to take place throughout the entire central nervous system. However, the results are inconsistent, probably due to differences in the methodology. Moreover, synaptic loss appears to be a dynamic process, and thus the nature of this pathology might be captured using in vivo synaptic density measurements.

Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis

Multiple sclerosis (MS) manifests heterogeneously among persons suffering from it, making its disease course highly challenging to predict. At present, prognosis mostly relies on biomarkers that are unable to predict disease course on an individual level. Machine learning is a promising technique, both in terms of its ability to combine multimodal data and through the capability of making personalized predictions. However, most investigations on machine learning for prognosis in MS were geared towards predicting physical deterioration, while cognitive deterioration, although prevalent and burdensome, remained largely overlooked. This review aims to boost the field of machine learning for cognitive prognosis in MS by means of an introduction to machine learning and its pitfalls, an overview of important elements for study design, and an overview of the current literature on cognitive prognosis in MS using machine learning. Furthermore, the review discusses new trends in the field of machine learning that might be adopted for future studies in the field.

MRI Prognostic Factors in Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorder, and Myelin Oligodendrocyte Antibody Disease

Several MRI measures have been developed in the last couple of decades, providing a number of imaging biomarkers that can capture the complexity of the pathological processes occurring in multiple sclerosis (MS) brains. Such measures have provided more specific information on the heterogeneous pathologic substrate of MS-related tissue damage, being able to detect, and quantify the evolution of structural changes both within and outside focal lesions. In clinical practise, MRI is increasingly used in the MS field to help to assess patients during follow-up, guide treatment decisions and, importantly, predict the disease course. Moreover, the process of identifying new effective therapies for MS patients has been supported by the use of serial MRI examinations in order to sensitively detect the sub-clinical effects of disease-modifying treatments at an earlier stage than is possible using measures based on clinical disease activity. However, despite this has been largely demonstrated in the relapsing forms of MS, a poor understanding of the underlying pathologic mechanisms leading to either progression or tissue repair in MS as well as the lack of sensitive outcome measures for the progressive phases of the disease and repair therapies makes the development of effective treatments a big challenge. Finally, the role of MRI biomarkers in the monitoring of disease activity and the assessment of treatment response in other inflammatory demyelinating diseases of the central nervous system, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte antibody disease (MOGAD) is still marginal, and advanced MRI studies have shown conflicting results. Against this background, this review focused on recently developed MRI measures, which were sensitive to pathological changes, and that could best contribute in the future to provide prognostic information and monitor patients with MS and other inflammatory demyelinating diseases, in particular, NMOSD and MOGAD.

Assessing the presence of oligoclonal IgM bands as a prognostic biomarker of cognitive decline in the early stages of multiple sclerosis

BACKGROUND

An association has been found between the presence of lipid-specific oligoclonal IgM bands (LS-OCMB) in cerebrospinal fluid and a more severe clinical multiple sclerosis course.

OBJECTIVE

To investigate lipid-specific oligoclonal IgM bands as a prognostic biomarker of cognitive impairment in the early stages of multiple sclerosis.

METHODS

Forty-four patients underwent neuropsychological assessment at baseline and 4 years. Cognitive performance at follow-up was compared adjusting by age, education, anxiety-depression, and baseline performance.

RESULTS

LS-OCMB+ patients only performed worse for Long-Term Storage in the Selective Reminding Test (p = .018).

CONCLUSION

There are no remarkable cognitive differences between LS-OCMB- and LS-OCMB+ patients in the early stages of MS.

Validation of Discrete and Regression-Based Performance and Cognitive Fatigability Normative Data for the Paced Auditory Serial Addition Test in Multiple Sclerosis

Cognitive fatigability is an objective performance decrement that occurs over time during a task requiring sustained cognitive effort. Although cognitive fatigability is a common and debilitating symptom in multiple sclerosis (MS), there is currently no standard for its quantification. The objective of this study was to validate the Paced Auditory Serial Addition Test (PASAT) discrete and regression-based normative data for quantifying performance and cognitive fatigability in an Ontario-based sample of individuals with MS. Healthy controls and individuals with MS completed the 3″ and 2″ versions of the PASAT. PASAT performance was measured with total correct, dyad, and percent dyad scores. Cognitive fatigability scores were calculated by comparing performance on the first half (or third) of the task to the last half (or third). The results revealed that the 3″ PASAT was sufficient to detect impaired performance and cognitive fatigability in individuals with MS given the increased difficulty of the 2″ version. In addition, using halves or thirds for calculating cognitive fatigability scores were equally effective methods for detecting impairment. Finally, both the discrete and regression-based norms classified a similar proportion of individuals with MS as having impaired performance and cognitive fatigability. These newly validated discrete and regression-based PASAT norms provide a new tool for clinicians to document statistically significant cognitive fatigability in their patients.

Clinical and Paraclinical Biomarkers and the Hitches to Assess Conversion to Secondary Progressive Multiple Sclerosis: A Systematic Review

Conversion to secondary progressive (SP) course is the decisive factor for long-term prognosis in relapsing multiple sclerosis (MS), generally considered the clinical equivalent of progressive MS-associated neuroaxonal degeneration. Evidence is accumulating that both inflammation and neurodegeneration are present along a continuum of pathologic processes in all phases of MS. While inflammation is the prominent feature in early stages, its quality changes and relative importance to disease course decreases while neurodegenerative processes prevail with ongoing disease. Consequently, anti-inflammatory disease-modifying therapies successfully used in relapsing MS are ineffective in SPMS, whereas specific treatment for the latter is increasingly a focus of MS research. Therefore, the prevention, but also the (anticipatory) diagnosis of SPMS, is of crucial importance. The problem is that currently SPMS diagnosis is exclusively based on retrospectively assessing the increase of overt physical disability usually over the past 6–12 months. This inevitably results in a delay of diagnosis of up to 3 years resulting in periods of uncertainty and, thus, making early therapy adaptation to prevent SPMS conversion impossible. Hence, there is an urgent need for reliable and objective biomarkers to prospectively predict and define SPMS conversion. Here, we review current evidence on clinical parameters, magnetic resonance imaging and optical coherence tomography measures, and serum and cerebrospinal fluid biomarkers in the context of MS-associated neurodegeneration and SPMS conversion. Ultimately, we discuss the necessity of multimodal approaches in order to approach objective definition and prediction of conversion to SPMS.

Longitudinal Network Changes and Conversion to Cognitive Impairment in Multiple Sclerosis

OBJECTIVE

To characterize functional network changes related to conversion to cognitive impairment in a large sample of patients with multiple sclerosis (MS) over a period of 5 years.

METHODS

Two hundred twenty-seven patients with MS and 59 healthy controls of the Amsterdam MS cohort underwent neuropsychological testing and resting-state fMRI at 2 time points (time interval 4.9 ± 0.9 years). At both baseline and follow-up, patients were categorized as cognitively preserved (CP; n = 123), mildly impaired (MCI; z < -1.5 on ≥2 cognitive tests, n = 32), or impaired (CI; z < -2 on ≥2 tests, n = 72), and longitudinal conversion between groups was determined. Network function was quantified with eigenvector centrality, a measure of regional network importance, which was computed for individual resting-state networks at both time points.

RESULTS

Over time, 18.9% of patients converted to a worse phenotype; 22 of 123 patients who were CP (17.9%) converted from CP to MCI, 10 of 123 from CP to CI (8.1%), and 12 of 32 patients with MCI converted to CI (37.5%). At baseline, default-mode network (DMN) centrality was higher in CI individuals compared to controls (p = 0.05). Longitudinally, ventral attention network (VAN) importance increased in CP, driven by stable CP and CP-to-MCI converters (p < 0.05).

CONCLUSIONS

Of all patients, 19% worsened in their cognitive status over 5 years. Conversion from intact cognition to impairment is related to an initial disturbed functioning of the VAN, then shifting toward DMN dysfunction in CI. Because the VAN normally relays information to the DMN, these results could indicate that in MS normal processes crucial for maintaining overall network stability are progressively disrupted as patients clinically progress.

Comparison of Thalamus and Basal Ganglia Signs Between Multiple Sclerosis and Primary Angiitis of the Central Nervous System: An Exploratory Study

Based on the symptoms, especially those affecting small vessels, it is difficult to distinguish multiple sclerosis (MS) from primary angiitis of the central nervous system (PACNS). Magnetic resonance imaging (MRI) helps understand the characteristics of deep gray matter lesions (DGML) in MS and PACNS. We aimed to compare the MRI characteristics of thalamus and basal ganglia lesions between relapsing-remitting MS and PACNS. In our study, 49 relapsing-remitting MS patients and 16 PACNS with MRI-confirmed thalamus or basal ganglia lesions were enrolled. Among the DGMLs in basal ganglia, putamen had significantly higher (P = 0.037) involvement in PACNS than in MS. More importantly, larger lesion sizes in thalamus helps to distinguish PACNS (12.4 ± 4.3 mm) from MS (7.9 ± 3.7 mm) (P = 0.006). But using lesions in basal ganglia, researchers were unable to differentiate the two disorders. Presently, our study shows that MRI performances of deep gray matter differ between MS and PACNS.

Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis

Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.

Meningeal inflammation in multiple sclerosis induces phenotypic changes in cortical microglia that differentially associate with neurodegeneration

Meningeal inflammation strongly associates with demyelination and neuronal loss in the underlying cortex of progressive MS patients, thereby contributing significantly to clinical disability. However, the pathological mechanisms of meningeal inflammation-induced cortical pathology are still largely elusive. By extensive analysis of cortical microglia in post-mortem progressive MS tissue, we identified cortical areas with two MS-specific microglial populations, termed MS1 and MS2 cortex. The microglial population in MS1 cortex was characterized by a higher density and increased expression of the activation markers HLA class II and CD68, whereas microglia in MS2 cortex showed increased morphological complexity and loss of P2Y12 and TMEM119 expression. Interestingly, both populations associated with inflammation of the overlying meninges and were time-dependently replicated in an in vivo rat model for progressive MS-like chronic meningeal inflammation. In this recently developed animal model, cortical microglia at 1-month post-induction of experimental meningeal inflammation resembled microglia in MS1 cortex, and microglia at 2 months post-induction acquired a MS2-like phenotype. Furthermore, we observed that MS1 microglia in both MS cortex and the animal model were found closely apposing neuronal cell bodies and to mediate pre-synaptic displacement and phagocytosis, which coincided with a relative sparing of neurons. In contrast, microglia in MS2 cortex were not involved in these synaptic alterations, but instead associated with substantial neuronal loss. Taken together, our results show that in response to meningeal inflammation, microglia acquire two distinct phenotypes that differentially associate with neurodegeneration in the progressive MS cortex. Furthermore, our in vivo data suggests that microglia initially protect neurons from meningeal inflammation-induced cell death by removing pre-synapses from the neuronal soma, but eventually lose these protective properties contributing to neuronal loss.

Case Report: Antibodies to the N-Methyl-D-Aspartate Receptor in a Patient With Multiple Sclerosis

The association between multiple sclerosis and anti-N-Methyl-D-Aspartate receptor encephalitis is limited to merely a few case reports, and the exploration of the pathogenic mechanisms underlying the overlap of these two disease entities is very limited. Therefore, case reports and literature review on N-Methyl-D-aspartate receptor antibody in patients with multiple sclerosis are unusual and noteworthy. A young female had the first episode of paresthesia and motor symptoms with positive anti-N-Methyl-D-Aspartate receptor antibody and recovered after immunotherapy, and at the first relapse, the patient developed disorders of consciousness with positive anti-N-Methyl-D-Aspartate receptor antibody, findings of magnetic resonance imaging showed features of autoimmune encephalitis, which was also controlled by immunotherapy. At the second relapse, anti-N-Methyl-D-Aspartate receptor antibody turned negative while oligoclonal bands presented positive, and findings of magnetic resonance imaging showed features of multiple sclerosis. Afterwards, we followed the patient after receiving disease modifying treatment to monitor the efficacy and safety of teriflunomide. Based on literature review, demyelinating diseases patients with anti-neuronal antibody have complex, diverse and atypical symptoms; therefore, high attention and increased alertness are necessary for neurologists. Conclusively, anti-neuronal antibody may present in many neuroinflammatory conditions, and diagnostic criteria should be used with caution if the clinical presentation is atypical, and neurologists should not rely excessively on laboratory tests to diagnose neurological diseases. Timely and comprehensive examination and consideration as well as early standardized treatment are the key factors to reduce patient recurrence and obtain a good prognosis.

Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis

Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.

Isolated Cognitive Decline in Neurologically Stable Patients with Multiple Sclerosis

(1) Background: Cognitive deterioration is an important marker of disease activity in multiple sclerosis (MS). It is vital to detect cognitive decline as soon as possible. Cognitive deterioration can take the form of isolated cognitive decline (ICD) with no other clinical signs of disease progression present. (2) Methods: We investigated 1091 MS patients from the longitudinal GQ (Grant Quantitative) study, assessing their radiological, neurological, and neuropsychological data. Additionally, the confirmatory analysis was conducted. Clinical disease activity was defined as the presence of new relapse or disability worsening. MRI activity was defined as the presence of new or enlarged T2 lesions on brain MRI. (3) Results: Overall, 6.4% of patients experienced cognitive decline and 4.0% experienced ICD without corresponding clinical activity. The vast majority of cognitively worsening patients showed concomitant progression in other neurological and radiologic measures. There were no differences in disease severity between completely stable patients and cognitively worsening patients but with normal cognition at baseline. (4) Conclusions: Only a small proportion of MS patients experience ICD over short-term follow-up. Patients with severe MS are more prone to cognitive decline; however, patients with normal cognitive performance and mild MS might benefit from the early detection of cognitive decline the most.

Transcranial magnetic stimulation (TMS) and repetitive TMS in multiple sclerosis

Multiple sclerosis (MS) is the most well-known autoimmune disorder of the central nervous system, and constitutes a major cause of disability, especially in young individuals. A wide array of pharmacological treatments is available, but they have often been proven to be ineffective in ameliorating disease symptomatology or slowing disease progress. As such, non-invasive and non-pharmacological techniques have been gaining more ground. Transcranial magnetic stimulation (TMS) utilizes the electric field generated by a magnetic coil to stimulate neurons and has been applied, usually paired with electroencephalography, to study the underlying pathophysiology of MS, and in repetitive trains, in the form of repetitive transcranial magnetic stimulation (rTMS), to induce long-lasting changes in neuronal circuits. In this review, we present the available literature on the application of TMS and rTMS in the context of MS, with an emphasis on its therapeutic potential on various clinical aspects, while also naming the ongoing trials, whose results are anticipated in the future.

Histopathology-validated recommendations for cortical lesion imaging in multiple sclerosis

Cortical demyelinating lesions are clinically important in multiple sclerosis, but notoriously difficult to visualize with MRI. At clinical field strengths, double inversion recovery MRI is most sensitive, but still only detects 18% of all histopathologically validated cortical lesions. More recently, phase-sensitive inversion recovery was suggested to have a higher sensitivity than double inversion recovery, although this claim was not histopathologically validated. Therefore, this retrospective study aimed to provide clarity on this matter by identifying which MRI sequence best detects histopathologically-validated cortical lesions at clinical field strength, by comparing sensitivity and specificity of the thus far most commonly used MRI sequences, which are T₂, fluid-attenuated inversion recovery (FLAIR), double inversion recovery and phase-sensitive inversion recovery. Post-mortem MRI was performed on non-fixed coronal hemispheric brain slices of 23 patients with progressive multiple sclerosis directly after autopsy, at 3 T, using T₁ and proton-density/T₂-weighted, as well as FLAIR, double inversion recovery and phase-sensitive inversion recovery sequences. A total of 93 cortical tissue blocks were sampled from these slices. Blinded to histopathology, all MRI sequences were consensus scored for cortical lesions. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesion types I–IV (mixed grey matter/white matter, intracortical, subpial and cortex-spanning lesions, respectively). MRI scores were compared to histopathological scores to calculate sensitivity and specificity per sequence. Next, a retrospective (unblinded) scoring was performed to explore maximum scoring potential per sequence. Histopathologically, 224 cortical lesions were detected, of which the majority were subpial. In a mixed model, sensitivity of T₁, proton-density/T₂, FLAIR, double inversion recovery and phase-sensitive inversion recovery was 8.9%, 5.4%, 5.4%, 22.8% and 23.7%, respectively (20, 12, 12, 51 and 53 cortical lesions). Specificity of the prospective scoring was 80.0%, 75.0%, 80.0%, 91.1% and 88.3%. Sensitivity and specificity did not significantly differ between double inversion recovery and phase-sensitive inversion recovery, while phase-sensitive inversion recovery identified more lesions than double inversion recovery upon retrospective analysis (126 versus 95; P < 0.001). We conclude that, at 3 T, double inversion recovery and phase-sensitive inversion recovery sequences outperform conventional sequences T₁, proton-density/T₂ and FLAIR. While their overall sensitivity does not exceed 25%, double inversion recovery and phase-sensitive inversion recovery are highly pathologically specific when using existing scoring criteria and their use is recommended for optimal cortical lesion assessment in multiple sclerosis.

Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study

Objectives

To identify Magnetic Resonance Imaging (MRI), clinical and demographic biomarkers predictive of worsening information processing speed (IPS) as measured by Symbol Digit Modalities Test (SDMT).

Methods

Demographic, clinical data and 1.5 T MRI scans were collected in 76 patients at time of inclusion, and after 5 and 10 years. Global and tissue-specific volumes were calculated at each time point. For the primary outcome of analysis, SDMT was used.

Results

Worsening SDMT at 5-year follow-up was predicted by baseline age, Expanded Disability Status Scale (EDSS), SDMT, whole brain volume (WBV) and T2 lesion volume (LV), explaining 30.2% of the variance of SDMT. At 10-year follow-up, age, EDSS, grey matter volume (GMV) and T1 LV explained 39.4% of the variance of SDMT change.

Conclusion

This longitudinal study shows that baseline MRI-markers, demographic and clinical data can help predict worsening IPS. Identification of patients at risk of IPS decline is of importance as follow-up, treatment and rehabilitation can be optimized.

Thalamic Injury and Cognition in Multiple Sclerosis

Multiple sclerosis (MS) produces demyelination and degeneration in both gray and white matter. Both cortical and deep gray matter injury is observed during the course of MS. Among deep gray matter structures, the thalamus has received special attention, as it undergoes volume loss in different MS subtypes and is involved in the earliest form of the disease, radiologically isolated syndrome. The thalamus plays an important role as an information relay center, and involvement of the thalamus in MS has been associated with a variety of clinical manifestations in MS, including fatigue, movement disorders, pain, and cognitive impairment (CI). Similar to thalamic volume loss, CI is seen from the earliest stages of MS and is potentially one of the most debilitating manifestations of the disease. The thalamus, particularly the dorsomedial nucleus as part of the basolateral limbic circuit and anterior thalamic nuclei through connections with the prefrontal cortex, has been shown to be involved in CI. Specifically, several cognitive performance measures such as processing speed and memory correlate with thalamic volume. Thalamic atrophy is one of the most important predictors of CI in MS, and both thalamic volume, diffusion tensor imaging measures, and functional activation correlate with the degree of CI in MS. Although the exact mechanism of thalamic atrophy is not well-understood, it is hypothesized to be secondary to degeneration following white matter injury resulting in secondary neurodegeneration and neuronal loss. The thalamus may represent an ideal biomarker for studies aiming to test neuroprotective or restorative therapies aimed at cognition.

Effects of Ibudilast on MRI Measures in the Phase 2 SPRINT-MS Study

OBJECTIVE

To determine whether ibudilast has an effect on brain volume and new lesions in progressive forms of multiple sclerosis (MS).

METHODS

A randomized, placebo-controlled, blinded study evaluated ibudilast at a dose of up to 100 mg over 96 weeks in primary and secondary progressive MS. In this secondary analysis of a previously reported trial, secondary and tertiary endpoints included gray matter atrophy, new or enlarging T2 lesions as measured every 24 weeks, and new T1 hypointensities at 96 weeks. Whole brain atrophy measured by structural image evaluation, using normalization, of atrophy (SIENA) was a sensitivity analysis.

RESULTS

A total of 129 participants were assigned to ibudilast and 126 to placebo. New or enlarging T2 lesions were observed in 37.2% on ibudilast and 29.0% on placebo (p = 0.82). New T1 hypointense lesions at 96 weeks were observed in 33.3% on ibudilast and 23.5% on placebo (p = 0.11). Gray matter atrophy was reduced by 35% for those on ibudilast vs placebo (p = 0.038). Progression of whole brain atrophy by SIENA was slowed by 20% in the ibudilast group compared with placebo (p = 0.08).

CONCLUSION

Ibudilast treatment was associated with a reduction in gray matter atrophy. Ibudilast treatment was not associated with a reduction in new or enlarging T2 lesions or new T1 lesions. An effect on brain volume contributes to prior data that ibudilast appears to affect markers associated with neurodegenerative processes, but not inflammatory processes.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that for people with MS, ibudilast does not significantly reduce new or enlarging T2 lesions or new T1 lesions.

Mind the gap: from neurons to networks to outcomes in multiple sclerosis

MRI studies have provided valuable insights into the structure and function of neural networks, particularly in health and in classical neurodegenerative conditions such as Alzheimer disease. However, such work is also highly relevant in other diseases of the CNS, including multiple sclerosis (MS). In this Review, we consider the effects of MS pathology on brain networks, as assessed using MRI, and how these changes to brain networks translate into clinical impairments. We also discuss how this knowledge can inform the targeting of MS treatments and the potential future directions for research in this area. Studying MS is challenging as its pathology involves neurodegenerative and focal inflammatory elements, both of which could disrupt neural networks. The disruption of white matter tracts in MS is reflected in changes in network efficiency, an increasingly random grey matter network topology, relative cortical disconnection, and both increases and decreases in connectivity centred around hubs such as the thalamus and the default mode network. The results of initial longitudinal studies suggest that these changes evolve rather than simply increase over time and are linked with clinical features. Studies have also identified a potential role for treatments that functionally modify neural networks as opposed to altering their structure.