Clinical, MRI, and CSF markers of disability progression in multiple sclerosis

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.

Long-term outcomes of ADEM-like and tumefactive presentations of CNS demyelination: a case-comparison analysis

A minority of initial multiple sclerosis (MS) presentations clinically or radiologically resemble other central nervous system (CNS) pathologies, acute disseminated encephalomyelitis (ADEM) or tumefactive demyelination (atypical demyelination presentations). With the aim of better defining the long-term outcomes of this group we have performed a retrospective cohort comparison of atypical demyelination versus 'typical' MS presentations. Twenty-seven cases with atypical presentations (both first and subsequent demyelinating events) were identified and compared with typical MS cases. Disease features analysed included relapse rates, disability severity, whole brain and lesion volumes, lesion number and distribution. Atypical cases represented 3.9% of all MS cases. There was considerable overlap in the magnetic resonance imaging (MRI) features of ADEM-like and tumefactive demyelination cases. ADEM-like cases tended to be younger but not significantly so. Atypical cases showed a trend towards higher peak expanded disability severity score (EDSS) score at the time of their atypical presentation. Motor, cranial nerve, cerebellar, cerebral and multifocal presentations were all more common in atypical cases, and less likely to present with optic neuritis. Cerebrospinal fluid (CSF) white cell counts were higher in atypical cases (p = 0.002). One atypical case was associated with peripheral blood myelin oligodendrocyte glycoprotein (MOG) antibodies, but subsequent clinical and radiological course was in keeping with MS. There was no difference in long-term clinical outcomes including annualised relapse rates (ARR), brain volume, lesion numbers or lesion distributions. Atypical demyelination cases were more likely to receive high potency disease modifying therapy early in the course of their illness. Despite the severity of initial illness, our cohort analysis suggests that atypical demyelination presentations do not confer a higher risk of long-term adverse outcomes.

Modeling and simulation for prediction of multiple sclerosis progression

In light of extensive work that has created a wide range of techniques for predicting the course of multiple sclerosis (MS) disease, this paper attempts to provide an overview of these approaches and put forth an alternative way to predict the disease progression. For this purpose, the existing methods for estimating and predicting the course of the disease have been categorized into clinical, radiological, biological, and computational or artificial intelligence-based markers. Weighing the weaknesses and strengths of these prognostic groups is a profound method that is yet in need and works directly at the level of diseased connectivity. Therefore, we propose using the computational models in combination with established connectomes as a predictive tool for MS disease trajectories. The fundamental conduction-based Hodgkin-Huxley model emerged as promising from examining these studies. The advantage of the Hodgkin-Huxley model is that certain properties of connectomes, such as neuronal connection weights, spatial distances, and adjustments of signal transmission rates, can be taken into account. It is precisely these properties that are particularly altered in MS and that have strong implications for processing, transmission, and interactions of neuronal signaling patterns. The Hodgkin-Huxley (HH) equations as a point-neuron model are used for signal propagation inside a small network. The objective is to change the conduction parameter of the neuron model, replicate the changes in myelin properties in MS and observe the dynamics of the signal propagation across the network. The model is initially validated for different lengths, conduction values, and connection weights through three nodal connections. Later, these individual factors are incorporated into a small network and simulated to mimic the condition of MS. The signal propagation pattern is observed after inducing changes in conduction parameters at certain nodes in the network and compared against a control model pattern obtained before the changes are applied to the network. The signal propagation pattern varies as expected by adapting to the input conditions. Similarly, when the model is applied to a connectome, the pattern changes could give an insight into disease progression. This approach has opened up a new path to explore the progression of the disease in MS. The work is in its preliminary state, but with a future vision to apply this method in a connectome, providing a better clinical tool.

Efficacy and safety of autologous haematopoietic stem cell transplantation versus alemtuzumab, ocrelizumab, ofatumumab or cladribine in relapsing remitting multiple sclerosis (StarMS): protocol for a randomised controlled trial

INTRODUCTION

Autologous haematopoietic stem cell transplantation (aHSCT) is increasingly used as treatment for patients with active multiple sclerosis (MS), typically after failure of disease-modifying therapies (DMTs). A recent phase III trial, 'Multiple Sclerosis International Stem Cell Transplant, MIST', showed that aHSCT resulted in prolonged time to disability progression compared with DMTs in patients with relapsing remitting MS (RRMS). However, the MIST trial did not include many of the current high-efficacy DMTs (alemtuzumab, ocrelizumab, ofatumumab or cladribine) in use in the UK within the control arm, which are now offered to patients with rapidly evolving severe MS (RES-MS) who are treatment naïve. There remain, therefore, unanswered questions about the relative efficacy and safety of aHSCT over these high-efficacy DMTs in these patient groups. The StarMS trial (Autologous Stem Cell Transplantation versus Alemtuzumab, Ocrelizumab, Ofatumumab or Cladribine in Relapsing Remitting Multiple Sclerosis) will assess the efficacy, safety and long-term impact of aHSCT compared with high-efficacy DMTs in patients with highly active RRMS despite the use of standard DMTs or in patients with treatment naïve RES-MS.

METHODS AND ANALYSIS

StarMS is a multicentre parallel-group rater-blinded randomised controlled trial with two arms. A total of 198 participants will be recruited from 19 regional neurology secondary care centres in the UK. Participants will be randomly allocated to the aHSCT arm or DMT arm in a 1:1 ratio. Participants will remain in the study for 2 years with follow-up visits at 3, 6, 9, 12, 18 and 24 months postrandomisation. The primary outcome is the proportion of patients who achieve 'no evidence of disease activity' during the 2-year postrandomisation follow-up period in an intention to treat analysis. Secondary outcomes include efficacy, safety, cost-effectiveness and immune reconstitution of aHSCT and the four high-efficacy DMTs.

ETHICS AND DISSEMINATION

The study was approved by the Yorkshire and Humber-Leeds West Research Ethics Committee (20/YH/0061). Participants will provide written informed consent prior to any study specific procedures. The study results will be submitted to a peer-reviewed journal and abstracts will be submitted to relevant national and international conferences.

TRIAL REGISTRATION NUMBER

ISRCTN88667898.

Predictors of long-term disability in multiple sclerosis patients using routine magnetic resonance imaging data: A 15-year retrospective study

INTRODUCTION

Early identification of patients at high risk of progression could help with a personalised treatment strategy. Magnetic resonance imaging (MRI) measures have been proposed to predict long-term disability in multiple sclerosis (MS), but a reliable predictor that can be easily implemented clinically is still needed.

AIM

Assess MRI measures during the first 5 years of the MS disease course for the ability to predict progression at 10+ years.

METHODS

Eighty-two MS patients (53 females), with ≥10 years of clinical follow-up and having two MRI scans, were included. Clinical data were obtained at baseline, follow-up and at ≥10 years. White matter lesion (WML) counts and volumes, and four linear brain sizes were measured on T2/FLAIR 'Fluid-Attenuated-Inversion-Recovery' and T1-weighted images.

RESULTS

Baseline and follow-up inter-caudate diameter (ICD) and third ventricular width (TVW) measures correlated positively with Expanded Disability Status Scale, ≥10 or more of WMLs showed a high sensitivity in predicting progression, at ≥10 years. A steeper rate of lesion volume increase was observed in subjects converting to secondary progressive MS. The sensitivity and specificity of both ICD and TVW, to predict disability at ≥10 years were 60% and 64%, respectively.

CONCLUSION

Despite advances in brain imaging and computerised volumetric analysis, ICD and TVW remain relevant as they are simple, fast and have the potential in predicting long-term disability. However, in this study, despite the statistical significance of these measures, the clinical utility is still not reliable.

Patient-reported outcomes are the strongest predictors of disease disability in intramuscular interferon beta-1a users

Introduction: Patient-reported outcomes (PROs) are valuable measures for routine clinical care of people with multiple sclerosis (pwMS). Materials: 646 pwMS treated with interferon-β-1a (IFN-β-1a) were retrospectively included from the New York State Multiple Sclerosis Consortium. Clinical and PRO data at enrollment and 3 year follow-up were collected. PwMS with stable disease and disability worsening were matched (1:1) based on age, Expanded Disability Status Scale (EDSS) scores and disease duration. Disability worsening was determined based on trial criteria. Results: PwMS with future EDSS worsening had higher baseline and follow-up timed-25-foot walk (6.6 vs 5.5 s; 9.1 vs 5.5 s; p < .001) when compared with stable pwMS. Worsening pwMS reported higher baseline difficulties in getting up (odds ratio [OR] = 2.4; p = 0.009), climbing stairs (OR = 1.6; p = 0.024) and standing (OR = 2.2; p < 0.001). Worsening pwMS reported greater lower limb limitations (OR = 2.3; p = 0.004) and fatigue (OR = 1.8; p = 0.002). Conclusion: Higher fatigue and lower limb functional limitations are significant predictors of future disability worsening in pwMS.

Retrospective cohort study to devise a treatment decision score predicting adverse 24-month radiological activity in early multiple sclerosis

Background

Multiple sclerosis (MS) is a chronic neuroinflammatory disease affecting about 2.8 million people worldwide. Disease course after the most common diagnoses of relapsing-remitting multiple sclerosis (RRMS) and clinically isolated syndrome (CIS) is highly variable and cannot be reliably predicted. This impairs early personalized treatment decisions.

Objectives

The main objective of this study was to algorithmically support clinical decision-making regarding the options of early platform medication or no immediate treatment of patients with early RRMS and CIS.

Design

Retrospective monocentric cohort study within the Data Integration for Future Medicine (DIFUTURE) Consortium.

Methods

Multiple data sources of routine clinical, imaging and laboratory data derived from a large and deeply characterized cohort of patients with MS were integrated to conduct a retrospective study to create and internally validate a treatment decision score [Multiple Sclerosis Treatment Decision Score (MS-TDS)] through model-based random forests (RFs). The MS-TDS predicts the probability of no new or enlarging lesions in cerebral magnetic resonance images (cMRIs) between 6 and 24 months after the first cMRI.

Results

Data from 65 predictors collected for 475 patients between 2008 and 2017 were included. No medication and platform medication were administered to 277 (58.3%) and 198 (41.7%) patients. The MS-TDS predicted individual outcomes with a cross-validated area under the receiver operating characteristics curve (AUROC) of 0.624. The respective RF prediction model provides patient-specific MS-TDS and probabilities of treatment success. The latter may increase by 5-20% for half of the patients if the treatment considered superior by the MS-TDS is used.

Conclusion

Routine clinical data from multiple sources can be successfully integrated to build prediction models to support treatment decision-making. In this study, the resulting MS-TDS estimates individualized treatment success probabilities that can identify patients who benefit from early platform medication. External validation of the MS-TDS is required, and a prospective study is currently being conducted. In addition, the clinical relevance of the MS-TDS needs to be established.

Multiple sclerosis clinical decision support system based on projection to reference datasets

OBJECTIVE

Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective is to use on-demand computational power to address the challenges of dynamically managing MS.

METHODS

A phase 3 clinical trial data (NCT00906399) were used to contextualize the medication efficacy of peg-interferon beta-1a vs placebo on patients with relapsing-remitting MS (RRMS). Using a set of reference patients (PORs), selected based on adequate features similar to those of an individual patient, we visualize disease activity by measuring the percentage of relapses, accumulation of new T2 lesions on MRI, and worsening EDSS during the clinical trial.

RESULTS

We developed MS Vista, a functional prototype of clinical decision support system (CDSS), with a user-centered design and distributed infrastructure. MS Vista shows the medication efficacy of peginterferon beta-1a versus placebo for each individual patient with RRMS. In addition, MS Vista initiated the integration of a longitudinal magnetic resonance imaging (MRI) viewer and interactive dual physician-patient data display to facilitate communication.

INTERPRETATION

The pioneer use of PORs for each individual patient enables personalized analytics sustaining the dialog between neurologists, patients and caregivers with quantified evidence.

Experimental and Clinical Biomarkers for Progressive Evaluation of Neuropathology and Therapeutic Interventions for Acute and Chronic Neurological Disorders

This article describes commonly used experimental and clinical biomarkers of neuronal injury and neurodegeneration for the evaluation of neuropathology and monitoring of therapeutic interventions. Biomarkers are vital for diagnostics of brain disease and therapeutic monitoring. A biomarker can be objectively measured and evaluated as a proxy indicator for the pathophysiological process or response to therapeutic interventions. There are complex hurdles in understanding the molecular pathophysiology of neurological disorders and the ability to diagnose them at initial stages. Novel biomarkers for neurological diseases may surpass these issues, especially for early identification of disease risk. Validated biomarkers can measure the severity and progression of both acute neuronal injury and chronic neurological diseases such as epilepsy, migraine, Alzheimer's disease, Parkinson's disease, Huntington's disease, traumatic brain injury, amyotrophic lateral sclerosis, multiple sclerosis, and other brain diseases. Biomarkers are deployed to study progression and response to treatment, including noninvasive imaging tools for both acute and chronic brain conditions. Neuronal biomarkers are classified into four core subtypes: blood-based, immunohistochemical-based, neuroimaging-based, and electrophysiological biomarkers. Neuronal conditions have progressive stages, such as acute injury, inflammation, neurodegeneration, and neurogenesis, which can serve as indices of pathological status. Biomarkers are critical for the targeted identification of specific molecules, cells, tissues, or proteins that dramatically alter throughout the progression of brain conditions. There has been tremendous progress with biomarkers in acute conditions and chronic diseases affecting the central nervous system.

Basic Analysis of the Cerebrospinal Fluid: An Important Framework for Laboratory Diagnostics of the Impairment of the Central Nervous System

Laboratory analysis of basic cerebrospinal fluid (CSF) parameters is considered as essential for any CSF evaluation. It can provide rapidly very valuable information about the status of the central nervous system (CNS). Our retrospective study evaluated parameters of basic CSF analysis in cases of either infectious or non-infectious CNS involvement. Neutrophils are effector cells of innate immunity. Predominance of neutrophils was found in 98.2% of patients with purulent inflammation in CNS. Lymphocytes are cellular substrate of adaptive immunity. We found their predominance in 94.8% of patients with multiple sclerosis (MS), 66.7% of patients with tick-borne encephalitis (TBE), 92.2% of patients with neuroborreliosis, 83.3% of patients with inflammatory response with oxidative burst of macrophages in CNS and 75.0% of patients with malignant infiltration of meninges (MIM). The simultaneous assessment of aerobic and anaerobic metabolism in CSF using the coefficient of energy balance (KEB) allows us to specify the type of inflammation in CNS. We found predominantly aerobic metabolism (KEB > 28.0) in 100.0% CSF of patients with normal CSF findings and in 92.8% CSF of patients with MS. Predominant faintly anaerobic metabolism (28.0 > KEB > 20.0) in CSF was found in 71.8% patients with TBE and in 64.7% patients with neuroborreliosis. Strong anaerobic metabolism (KEB < 10.0) was found in the CSF of 99.1% patients with purulent inflammation, 100.0% patients with inflammatory response with oxidative burst of macrophages and in 80.6% patients with MIM. Joint evaluation of basic CSF parameters provides sufficient information about the immune response in the CSF compartment for rapid and reliable diagnosis of CNS involvement.

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.

The impairment of the functional system and fatigue at the onset of the disease predict reaching disability milestones in relapsing-remitting multiple sclerosis differently in female and male patients

Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system with variable types of disability progression (DP). Previous studies, defining different disability milestones (DMs), have reported symptoms at MS onset to be the predictors of DP and sex as a risk factor. Meanwhile, accounting for sex differences in MS, predictors in female and male patients might differ. To investigate whether the symptoms at MS onset predict reaching DMs in patients with relapsing-remitting (RR) MS and whether the predictors vary between different DMs and female and male patients. Data from 128 RR MS patients (84 females, 44 males) was retrospectively studied. EDSS scores 4 and 6 (associated with impaired ambulation) were taken as DMs. Association between symptoms at MS onset and time to reach DMs was assessed with Cox multiple regression model. Pyramidal symptoms and fatigue at MS onset predicted the progression to EDSS 4 in the whole study population (HR 1.84, 95% CI 1.07-3.2, p = 0.028 and HR 2.01, 95% CI 1.12-3.4, p = 0.011, correspondingly). The same symptoms predicted reaching DM in female, but not male patients. Bowel/bladder symptoms predicted reaching EDSS 6 in the whole study population (HR 4.31, 95% CI 1.47-12.6, p = 0.008) and female patients only (HR 3.93, 95% CI 1.04-14.8, p = 0.043). In female patients, fatigue was also the predictor of reaching EDSS 6 (HR 3.54, 95% CI 1.16-10.8, p = 0.026). Impairment of functional symptoms at MS onset can predict reaching DMs in patients with RR-MS, but the predictors for EDSS 4 and EDSS 6 differ in female and male patients.

Diffusion imaging of fornix and interconnected limbic deep grey matter is linked to cognitive impairment in multiple sclerosis

Diffusion tensor imaging (DTI) and volumetric magnetic resonance imaging (MRI) have shown white matter (WM) and deep grey matter (GM) abnormalities in the limbic system of multiple sclerosis (MS) participants. Structures like the fornix have been associated with cognitive impairment (CI) in MS, but the diffusion metrics are often biased by partial volume effects from cerebrospinal fluid (CSF) due to its small bundle size and intraventricular location. These errors in DTI parameter estimation worsen with atrophy in MS. The goal here was to evaluate DTI parameters and volumes of the fornix, as well as associated deep GM structures like the thalamus and hippocampus, with high-resolution fluid-attenuated inversion recovery (FLAIR)-DTI at 3T in 43 MS patients, with and without CI, versus 43 controls. The fornix, thalamus and hippocampus displayed atrophy and/or abnormal diffusion metrics, with the fornix showing the most extensive changes within the structures studied here, mainly in CI MS. The affected fornix volumes and diffusion metrics were associated with thalamic atrophy and atypical diffusion metrics in interconnected limbic GM, larger total lesion volume and global brain atrophy. Lower fractional anisotropy (FA) and higher mean and radial diffusivity in the fornix, lower hippocampus FA and lower thalamus volume were strongly correlated with CI in MS. Hippocampus FA and thalamus atrophy were negatively correlated with fatigue and longer time since MS symptoms onset, respectively. FLAIR-DTI and volumetric analyses provided methodologically superior evidence for microstructural abnormalities and extensive atrophy of the fornix and interconnected deep GM in MS that were associated with cognitive deficits.

Prognostic utility of the IgM oligoclonal bands against myelin lipids in multiple sclerosis

IgM oligoclonal bands (OCMBs) against myelin-specific lipids have been identified as a marker for poor prognosis in multiple sclerosis (MS). The aim is to examine the relation between lipid-specific OCMBs (LS-OCMBs) and the evolution of MS. An analytical, ambispective and individual-based study was conducted. We selected 116 patients, out of whom 95 had LS-OCMBs. The predominant lipid recognized was phosphatidylcholine. The positive gangliosides OCMB group reached better scores in the 9HPT, and the phosphatidylcholine, sphingolipids and phosphatidylethanolamine OCMB groups showed statistical differences in the magnetic resonance parameters. In conclusion: some LS-OCMBs showed statistically significant differences with functional or imaging tests.

The Evolution of Neurofilament Light Chain in Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune, inflammatory neurodegenerative disease of the central nervous system characterized by demyelination and axonal damage. Diagnosis and prognosis are mainly assessed through clinical examination and neuroimaging. However, more sensitive biomarkers are needed to measure disease activity and guide treatment decisions in MS. Prompt and individualized management can reduce inflammatory activity and delay disease progression. Neurofilament Light chain (NfL), a neuron-specific cytoskeletal protein that is released into the extracellular fluid following axonal injury, has been identified as a biomarker of disease activity in MS. Measurement of NfL levels can capture the extent of neuroaxonal damage, especially in early stages of the disease. A growing body of evidence has shown that NfL in cerebrospinal fluid (CSF) and serum can be used as reliable indicators of prognosis and treatment response. More recently, NfL has been shown to facilitate individualized treatment decisions for individuals with MS. In this review, we discuss the characteristics that make NfL a highly informative biomarker and depict the available technologies used for its measurement. We further discuss the growing role of serum and CSF NfL in MS research and clinical settings. Finally, we address some of the current topics of debate regarding the use of NfL in clinical practice and examine the possible directions that this biomarker may take in the future.

Predicting disability worsening in relapsing and progressive multiple sclerosis

PURPOSE OF REVIEW

Multiple sclerosis (MS) is a clinically heterogeneous disease, which complicates expectant management as well as treatment decisions. This review provides an overview of both well established and emerging predictors of disability worsening, including clinical factors, imaging factors, biomarkers and treatment strategies.

RECENT FINDINGS

In addition to well known clinical predictors (age, male sex, clinical presentation, relapse behaviour), smoking, obesity, vascular and psychiatric comorbidities are associated with subsequent disability worsening in persons with MS. A number of imaging features are predictive of disability worsening and are present to varying degrees in relapsing and progressive forms of MS. These include brain volumes, spinal cord atrophy, lesion volumes and optical coherence tomography features. Cerebrospinal and more recently blood biomarkers including neurofilament light show promise as more easily attainable biomarkers of future disability accumulation. Importantly, recent observational studies suggest that initiation of early-intensive therapy, as opposed to escalation based on breakthrough disease, is associated with decreased accumulation of disability overall, although randomized controlled trials investigating this question are underway.

SUMMARY

Understanding risk factors associated with disability progression can help to both counsel patients and enhance the clinician's availability to provide evidence-based treatment recommendations.

The relevance of multiple sclerosis cortical lesions on cortical thinning and their clinical impact as assessed by 7.0-T MRI

OBJECTIVE

This study aimed to investigate at 7.0-T MRI a) the role of multiple sclerosis (MS) cortical lesions in cortical tissue loss b) their relation to neurological disability.

METHODS

In 76 relapsing remitting and 26 secondary progressive MS patients (N = 102) and 56 healthy subjects 7.0-T T₂^*-weighted images were acquired for lesion segmentation; 3.0-T T₁-weighted structural scans for cortical surface reconstruction/cortical thickness estimation. Patients were dichotomized based on the median cortical lesion volume in low and high cortical lesion load groups that differed by age, MS phenotype and degree of neurological disability. Group differences in cortical thickness were tested on reconstructed cortical surface. Patients were evaluated clinically by means of the Expanded Disability Status Scale (EDSS).

RESULTS

Cortical lesions were detected in 96% of patients. White matter lesion load was greater in the high than in the low cortical lesion load MS group (p = 0.01). Both MS groups disclosed clusters (prevalently parietal) of cortical thinning relative to healthy subjects, though these regions did not show the highest cortical lesion density, which predominantly involved frontal regions. Cortical thickness decreased on average by 0.37 mm, (p = 0.002) in MS patients for each unit standard deviation change in white matter lesion volume. The odds of having a higher EDSS were associated with cortical lesion volume (1.78, p = 0.01) and disease duration (1.15, p < 0.001).

CONCLUSION

Cortical thinning in MS is not directly related to cortical lesion load but rather with white matter lesion volume. Neurological disability in MS is better explained by cortical lesion volume assessment.

Approaches and challenges in the diagnosis and management of secondary progressive multiple sclerosis: A Central Eastern European perspective from healthcare professionals

Secondary progressive multiple sclerosis (SPMS) is a debilitating condition characterized by gradual worsening after an initial relapsing disease course. Despite the recent advances in our understanding of the disease, the diagnosis and treatment of SPMS continue to be challenging in routine clinical practice. The aim of this review article is to present the views of leading MS experts on the challenges in the diagnosis and management of SPMS and clinicians' perspectives in Central and Eastern Europe. This article also provides recommendations of MS experts to improve the situation with diagnosis and management of SPMS. Many countries within Central and Eastern Europe have high prevalence of MS (>100 per 100,000 population). Consistent with the global trend, in the absence of reliable tests or biomarkers, SPMS at early stage remains undiagnosed. Due to diagnostic uncertainty and lack of a universally accepted disease definition, clinicians rely more on retrospective analysis of the clinical symptoms to confirm the diagnosis. With the lack of awareness and poor understanding of the timing of the onset of SPMS, clinicians may tend to direct attention to relapses than the symptoms of progression, which leads to underestimation of SPMS. Although several predictors of progression to SPMS have been identified, their predictive value is highly variable. Therefore, defining the transitioning period as a separate stage of MS is essential. According to experts' opinion, frequent follow-up of patients and periodic assessment of progression are recommended for the timely identification of patients transitioning from RRMS to SPMS. MSProDiscuss Tool is an example of a quick assessment tool for identifying patients progressing from RRMS to SPMS. MS progression is usually assessed by changes in Expanded Disability Status Scale (EDSS) scores. As EDSS scores tend to fluctuate when measured in the short term (3-6 months), a longer period (≥12 months) may be needed to confirm the progression. Assessment of cognitive function is also important for evaluating secondary progression. Compartmentalization of inflammation within the central nervous system is an important reason behind the limited success of disease-modifying therapies (DMTs) for treating SPMS. Most of the DMTs fail to cross the blood-brain barrier; only 38% of the tested DMTs achieved their primary endpoint in SPMS. In Europe, siponimod is the first oral treatment for adults with active SPMS. Particularly, in Central and Eastern Europe, patients with SPMS are still being prescribed less efficacious DMTs and interferons. The absence of alternative treatments in SPMS supports the use of new products (siponimod and others); however the decision to initiate siponimod therapy in more severe patients (EDSS score of 7 or higher) should be individualized in consultation with the payers. The focus should be on early treatment initiation to delay disease progression.

Dual task training effects on gait and balance outcomes in multiple sclerosis: A systematic review

BACKGROUND

People with Multiple Sclerosis (PwMS) exhibit deteriorated balance and gait performance during dual task (DT) conditions. Impaired dual tasking is related to increased fall risk and lower quality of life in PwMS. While dual task interventions have proven effective in various patient populations, evidence is lacking to support the use of DT interventions to improve clinical measures of balance and gait in PwMS. Therefore, the purpose of this systematic review was to synthesize the effectiveness of DT intervention at improving balance and gait in PwMS.

METHODS

A systematic search was completed using CINHAL, PubMed and MEDLINE. Methodological quality, level of evidence and recommendations for included studies was assessed by two reviewers. Effect sizes with 95% confidence intervals comparing single and DT outcomes were calculated for all balance and gait variables.

RESULTS

Five randomized control trials (RCTs) were included for review. Of the 23 effect sizes calculated, three had 95% confidence intervals which did not pass zero and were therefore interpreted as strong. Due to inconsistent level one evidence of DT interventions being superior to single task balance and gait interventions a grade B recommendation was given.

CONCLUSION

There is inconsistent evidence supporting the use of DT interventions to improve clinical balance measures in PwMS. There is supportive evidence for the use of DT interventions to improve both single and DT gait speed. However, there was heterogeneity between interventions and dosage among RCTs. Despite multiple promising findings, DT interventions appear to have minimal impact on clinical balance and gait measures in PwMS.

Thalamic Atrophy Predicts 5-Year Disability Progression in Multiple Sclerosis

Purpose: Thalamus is among the first brain regions to become atrophic in multiple sclerosis (MS). We studied whether thalamic atrophy predicts disability progression at 5 years in a cohort of Finnish MS patients.

Methods: Global and regional brain volumes were measured from 24 newly diagnosed relapsing MS (RMS) patients 6 months after initiation of therapy and from 36 secondary progressive MS (SPMS) patients. The patients were divided into groups based on baseline whole brain parenchymal (BP) and thalamic atrophy. Standard scores (z scores) were computed by comparing individual brain volumes with healthy controls. A z score cutoff of −1.96 was applied to separate atrophic from normal brain volumes. The Expanded Disability Status Scale (EDSS), brain magnetic resonance imaging (MRI) findings, and relapses were assessed at baseline and at 2 years and EDSS progression at 5 years.

Results: Baseline thalamus volume predicted disability in 5 years in a logistic regression model (p = 0.031). At 5 years, EDSS was same or better in 12 of 18 patients with no brain atrophy at baseline but only in 5 of 18 patients with isolated thalamic atrophy [odds ratio (OR) (95% CI) = 5.2 (1.25, 21.57)]. The patients with isolated thalamic atrophy had more escalations of disease-modifying therapies during follow-up.

Conclusion: Patients with thalamic atrophy at baseline were at a higher risk for 5-year EDSS increase than patients with no identified brain atrophy. Brain volume measurement at a single time point could help predict disability progression in MS and complement clinical and routine MRI evaluation in therapeutic decision-making.

Clinico-radiological dissociation of disease activity in MS patients: frequency and clinical relevance

OBJECTIVE

To investigate the prevalence and clinical relevance regarding disability progression in multiple sclerosis patients with a dissociation in clinical and radiological disease expression.

METHODS

We prospectively selected patients with early relapsing-remitting multiple sclerosis (MS) or a clinically isolated syndrome (CIS) from the Amsterdam MS cohort. Patients underwent clinical examination at baseline, after 2 years, 6 years and a subset also after 11 years, including the Expanded Disability Status Scale (EDSS), 25-foot walk test (25-FWT) and 9-hole peg test (9-HPT). Brain and spinal cord MRI scans were obtained at baseline and after 2 years. Two years after baseline, patients with dissociation in their clinical and radiological disease progression were identified as: (1) patients with high clinical disease activity (defined by relapses) and low radiological disease activity (defined by white-matter lesions on T2-weighted imaging); or (2) patients with low clinical disease activity and high radiological disease activity. Binary logistic regression analyses were performed to predict disability progression after 6 and 11 years of follow-up. Patients with low clinical and low radiological disease activity were used as the reference group.

RESULTS

The prevalence of clinico-radiological dissociation was low (6.4% had high clinical and low radiological disease activity and 5.1% had a combination of low clinical and high radiological disease activity) compared to 88.5% of patients without a dissociation. Patients with a dissociation of clinical and radiological disease activity did not show a statistically significant difference in risk of disability progression after 6 and 11 years.

CONCLUSIONS

A clinico-radiological dissociation is rather a rare phenomenon in MS patients. The clinical relevance of such a dissociation regarding the prediction of disability progression is questionable.

Association of Intrathecal Immunoglobulin G Synthesis With Disability Worsening in Multiple Sclerosis

Importance

Reliable biomarkers associated with disability worsening in multiple sclerosis (MS) are still needed.

Objective

To determine a possible association of intrathecal IgG synthesis and early disability worsening as measured by Expanded Disability Status Scale (EDSS) scoring in patients with relapsing-remitting MS or clinically isolated syndrome.

Design, Setting, and Participants

Cerebrospinal fluid measurements and clinical data from the observational longitudinal German national multiple sclerosis cohort were analyzed. Patients were recruited between August 2010 and November 2015 from 18 centers. Data analysis was completed from August 2018 to December 2018.

Exposure

Patients were offered standard immunotherapies per national treatment guidelines.

Main Outcomes and Measures

A possible association between intrathecal IgG synthesis and risk of EDSS worsening 4 years after study inclusion was tested as the primary end point by multivariable binomial regression analysis. Kaplan-Meier analysis with a log-rank test was used to assess the association of intrathecal IgG synthesis with the time to EDSS worsening. Associations between intrathecal IgM or IgA synthesis and other cerebrospinal fluid parameters and EDSS worsening were analyzed as exploratory end points. Data collection began before the hypotheses were formulated.

Results

Of all 1376 patients in the German Competence Network of Multiple Sclerosis cohort, 703 patients were excluded owing to missing cerebrospinal fluid or EDSS data. Of the 673 included patients, 459 (68.2%) were women. The mean (SD) age at baseline was 34 (10) years. Intrathecal IgG synthesis was associated with a higher risk of EDSS worsening after 4 years (odds ratio, 2.02 [95% CI, 1.15-3.58]; P = .01), independent of the occurrence of relapses and disease-modifying therapy. Additionally, intrathecal IgG synthesis was associated with earlier EDSS worsening; 4 years after study entry, worsening occurred in 28.4% (95% CI, 22.7%-34.1%) and 18.1% (95% CI, 12.4%-23.9%) of patients with and without intrathecal IgG synthesis, respectively. No association of other routine cerebrospinal fluid parameters with EDSS worsening was found.

Conclusions and Relevance

Patients with new diagnoses of relapsing-remitting multiple sclerosis or clinically isolated syndrome with intrathecal IgG synthesis had a higher risk of and shorter time to EDSS worsening across a 4-year period of follow-up. Intrathecal IgG synthesis is a potentially useful marker for disability worsening in patients with multiple sclerosis and may be useful for early treatment decisions.

Expansion of Neutrophils and Classical and Nonclassical Monocytes as a Hallmark in Relapsing-Remitting Multiple Sclerosis

Neutrophils and monocytes encompassing the classical, intermediate, and nonclassical population constitute the majority of circulating myeloid cells in humans and represent the first line of innate immune defense. As such, changes in their relative and absolute amounts serve as sensitive markers of diverse inflammatory conditions. Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, causing demyelination and axonal loss, affecting various neuron functions and often causing irreversible neurological disability. MS disease course is individually highly heterogeneous but can be classified as progressive (PMS) or relapsing-remitting (RRMS). Each MS course type may be further characterized as active or inactive, depending on the recent disability progression and/or current relapses. Data on specific alterations of the myeloid compartment in association with MS disease course are scarce and conflicting. In the current study, we systematically immunophenotyped blood myeloid leukocytes by flow cytometry in 15 healthy and 65 MS subjects. We found a highly significant expansion of granulocytes, CD15⁺ neutrophils, and classical and nonclassical monocytes in inactive RRMS (RRMSi) with concomitant shrinkage of the lymphocyte compartment, which did not correlate with biochemical readouts of systemic inflammation. Each of these leukocyte populations and the combined myeloid signature accurately differentiated RRMSi from other MS forms. Additionally, nonclassical monocyte proportions were particularly elevated in RRMSi individuals receiving disease-modifying therapy (DMT), such as natalizumab. Our results suggest that flow cytometry-based myeloid cell immunophenotyping in MS may help to identify RRMSi earlier and facilitate monitoring of DMT response.

Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis

Background

Evoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a few variables from the EPs, which are often further condensed into a single variable: the EP score. We perform a machine learning analysis of motor EP that uses the whole time series, instead of a few variables, to predict disability progression after two years. Obtaining realistic performance estimates of this task has been difficult because of small data set sizes. We recently extracted a dataset of EPs from the Rehabiliation & MS Center in Overpelt, Belgium. Our data set is large enough to obtain, for the first time, a performance estimate on an independent test set containing different patients.

Methods

We extracted a large number of time series features from the motor EPs with the highly comparative time series analysis software package. Mutual information with the target and the Boruta method are used to find features which contain information not included in the features studied in the literature. We use random forests (RF) and logistic regression (LR) classifiers to predict disability progression after two years. Statistical significance of the performance increase when adding extra features is checked.

Results

Including extra time series features in motor EPs leads to a statistically significant improvement compared to using only the known features, although the effect is limited in magnitude (ΔAUC = 0.02 for RF and ΔAUC = 0.05 for LR). RF with extra time series features obtains the best performance (AUC = 0.75±0.07 (mean and standard deviation)), which is good considering the limited number of biomarkers in the model. RF (a nonlinear classifier) outperforms LR (a linear classifier).

Conclusions

Using machine learning methods on EPs shows promising predictive performance. Using additional EP time series features beyond those already in use leads to a modest increase in performance. Larger datasets, preferably multi-center, are needed for further research. Given a large enough dataset, these models may be used to support clinicians in their decision making process regarding future treatment.

Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis

Multiple Sclerosis (MS) progresses at an unpredictable rate, but predictions on the disease course in each patient would be extremely useful to tailor therapy to the individual needs. We explore different machine learning (ML) approaches to predict whether a patient will shift from the initial Relapsing-Remitting (RR) to the Secondary Progressive (SP) form of the disease, using only "real world" data available in clinical routine. The clinical records of 1624 outpatients (207 in the SP phase) attending the MS service of Sant'Andrea hospital, Rome, Italy, were used. Predictions at 180, 360 or 720 days from the last visit were obtained considering either the data of the last available visit (Visit-Oriented setting), comparing four classical ML methods (Random Forest, Support Vector Machine, K-Nearest Neighbours and AdaBoost) or the whole clinical history of each patient (History-Oriented setting), using a Recurrent Neural Network model, specifically designed for historical data. Missing values were handled by removing either all clinical records presenting at least one missing parameter (Feature-saving approach) or the 3 clinical parameters which contained missing values (Record-saving approach). The performances of the classifiers were rated using common indicators, such as Recall (or Sensitivity) and Precision (or Positive predictive value). In the visit-oriented setting, the Record-saving approach yielded Recall values from 70% to 100%, but low Precision (5% to 10%), which however increased to 50% when considering only predictions for which the model returned a probability above a given "confidence threshold". For the History-oriented setting, both indicators increased as prediction time lengthened, reaching values of 67% (Recall) and 42% (Precision) at 720 days. We show how "real world" data can be effectively used to forecast the evolution of MS, leading to high Recall values and propose innovative approaches to improve Precision towards clinically useful values.

Outcomes-Based Contracting for Disease-Modifying Therapies in Multiple Sclerosis: Necessary Conditions for Paradigm Adoption

BACKGROUND

In therapeutic areas with uncertainty regarding clinical outcomes that are dependent on high-cost specialty medications, outcomes-based contracts can be a tool to reduce financial risk for payers and for drug manufacturers. With a high treatment cost, large number of therapy choices, and variability of responses to therapy across patients, multiple sclerosis is a compelling therapeutic area to support outcomes-based contracts.

OBJECTIVE

To identify the necessary conditions to support the widespread adoption of outcomes-based contracts for high-cost drug therapy, with a focus on disease-modifying therapies for multiple sclerosis.

METHODS

We conducted a series of in-depth, semi-structured phone interviews during fall 2018 with 17 healthcare stakeholders representing payers, manufacturers, and industry consultants, all of whom had some involvement in outcomes-based contract development or evaluation. The qualitative data management program from QSR International, N-VIVO 11, was used to store, organize, categorize, analyze, and produce visualization tools to explore, map ideas, and understand themes from the data.

RESULTS

Overall, payers and manufacturers agreed that outcomes-based contracts are an effective vehicle to mitigate financial risk and deliver value for disease-modifying therapies for multiple sclerosis, but they noted that the widespread adoption of outcomes-based contracts was tempered by 5 broad categories of challenges, including data-related issues, outcome measurement and confounding factors, regulatory barriers, levels of risk mitigation, and patient adherence. The majority of participants were receptive to using blood-based clinical biomarkers as outcomes-based contract end points, as long as the biomarkers are validated, accurately predict clinical outcomes, are well-established in the therapeutic area, and are readily accessible to various stakeholders.

CONCLUSION

Our findings indicate there is general support from payers and drug manufacturers to adopt outcomes-based contracts for disease-modifying therapies for multiple sclerosis. However, some conditions need to be met to allow their widespread adoption, including resolving data issues, ensuring patient adherence to therapy, having a level of risk mitigation that is significant for both parties to make the endeavor economically worthwhile, and fostering a supportive regulatory environment. Blood-based clinical biomarkers that meet certain criteria could be viable end points in outcomes-based contract for disease-modifying therapies for multiple sclerosis and can address many of the necessary conditions regarding data issues, including timeliness.

B-cell related biomarkers associated with severity of the first demyelinating event of acute optic neuritis

BACKGROUND

Optic neuritis (ON) is the most common cause of acute unilateral visual loss in young adults and frequently occurs as the presenting symptom of multiple sclerosis (MS). Recently, we reported activation of peripheral blood CD19 + ‏ B-cells in the early stage of ON. In the current study we aimed to identify peripheral blood ‏B-cell molecular markers associated with ON severity and visual outcome.

METHODS

Expression of B-cell related biomarkers were analysed in patients with the first clinical presentation of acute unilateral ON. Logarithm of the Minimum Angle of Resolution (LogMAR). visual acuity, Optical Coherence Tomography (OCT) imaging, Expanded Disability Status Scale (EDSS) visual score and visual evoked responses were evaluated at onset and visual acuity and EDSS visual score were repeated at 6 months post-ON.

RESULTS

Thirty patients with acute unilateral ON, 77% female, mean age 33 ± 2.0 years, were enroled in the study. Expression of CD19, CD79A and CD20 B-cell markers significantly correlated with LogMAR visual acuity of the affected eye (r = 0.44, p = 0.01, r = 0.37, p = 0.01 and r = 0.36, p = 0.04, respectively). The marker levels were elevated between 1.5 and 2.2-folds in the group with worse visual acuity (LogMAR>1.0) at onset (CD79A:×1.5, p = 0.013; CD19:×2.25, p = 0.007; CD20:×1.5, p = 0.015) and not correlated with 6 month visual outcome.

CONCLUSIONS

Among patient with a first event of acute ON, expression of B-cell biomarkers correlated with the severity of the disease. These results could add information on the role of B-cell dysfunction in the early stages of ON.

Does CSF pleocytosis have a predictive value for disease course in MS?

Objective

MS is a demyelinating CNS disorder with a spectrum of clinical patterns regarding course and prognosis. Although several prognostic factors are considered in the initial evaluation of patients, biological markers defining the disease course and guiding treatments are currently lacking. It is unknown whether patients with CSF pleocytosis differ in regard to symptoms, disease course, and prognosis from those without. The aim of this study was to evaluate whether CSF pleocytosis during the initial presentation has an impact on the clinical course and progression of MS.

Methods

We retrospectively evaluated patients attending the MS Clinic at Rabin Medical Center between January 1999 and January 2016 who underwent lumbar puncture (LP) at disease presentation, considering CSF cell count, clinical diagnosis (clinically isolated syndrome [CIS] and relapsing-remitting MS [RRMS]), annualized relapse rate (ARR), paraclinical findings (imaging, CSF oligoclonal bands, and evoked potentials), and disease progression, expressed by the Expanded Disability Status Scale (EDSS).

Results

One hundred fourteen patients (72 females) underwent LP at disease presentation (RRMS: n = 100, CIS: n = 14). Age at diagnosis was 32.4 ± 12.2 years, and the follow-up time was 9.4 ± 3.8 years. Forty-six patients showed a pleocytic CSF (≥5 cells per μL). Compared with patients with <4 cells per μL, patients with pleocytosis had a higher ARR (0.60 ± 0.09 vs 0.48 ± 0.04; p = 0.0267) and a steeper increase (slope) in the EDSS score throughout the follow-up period (correlation coefficient: r2 = 0.04; p = 0.0251).

Conclusions

CSF pleocytosis may be considered a biological unfavorable predictive factor regarding disease course and progression in MS.

Gene expression profiles of TNF-like cytokine 1A (TL1A) and its receptors death receptor 3 (DR3) and decoy receptor 3 (DcR3) in multiple sclerosis

TL1A/DR3/DcR3 pathway is an important mediator of inflammatory responses and contributes to the pathogenesis of several chronic inflammatory diseases. Therefore, we analysed PBMC gene expression of these molecules in 30 relapsing-remitting multiple sclerosis (RRMS) patients, 8 secondary progressive MS (SPMS), 9 primary progressive MS (PPMS), 11 clinically isolated syndrome (CIS) patients, and 16 healthy controls (HCs), to evaluate their biomarker potential in MS. The results showed significant decrease in TL1A expression in RRMS compared to other study groups. TL1A as a marker of inflammation, we found its higher expression among treatment näive RRMS patients as compared to HCs and among patients who were treated with DMTs. Moreover, TL1A expression was found to be associated with the clinical and MRI findings of MS patients suggesting its possible involvement in the establishment or preservation of immune system homeostasis or in the regulation of inflammatory activity. Taken together, these findings suggest the TL1A should be evaluated further for its potential as a candidate biomarker of inflammatory activity and the marker of therapeutic response to immunomodulatory treatments in MS.

A focus on secondary progressive multiple sclerosis (SPMS): challenges in diagnosis and definition

Secondary progressive multiple sclerosis (SPMS) is the second most common form of multiple sclerosis (MS). One in two relapse remitting multiple sclerosis (RRMS) patients will develop SPMS within 15 years and up to two-thirds after 30 years, leading to a progressive decrease of neurological function and limitation of daily activities. Nevertheless, the SPMS diagnosis is often established retrospectively and delayed up to 3 years due to several patient- and clinician-related factors. Definitive clinical diagnostic criteria are lacking and research is currently ongoing to identify imaging and biochemical biomarkers. As new therapies are introduced, early SPMS diagnosis may represent a window of opportunity for intervention. New approaches, endpoints or technologies could help physicians establishing a diagnosis. Here, we review SPMS in relation to its diagnostic and definition challenges and current screening techniques and tools.

Using biomarkers to predict clinical outcomes in multiple sclerosis

Long-term outcomes in multiple sclerosis (MS) are highly varied and treatment with disease-modifying therapies carries significant risks. Finding tissue biomarkers that can predict clinical outcomes would be valuable in individualising treatment decisions for people with MS. Several candidate biomarkers-reflecting inflammation, neurodegeneration and glial pathophysiology-show promise for predicting outcomes. However, many candidates still require validation in cohorts with long-term follow-up and evaluation for their independent contribution in predicting outcome when models are adjusted for known demographic, clinical and radiological predictors. Given the complexity of MS pathophysiology, heterogeneous panels comprising a combination of biomarkers that encompass the various aspects of neurodegenerative, glial and immune pathology seen in MS, may enhance future predictions of outcome.

A surface-in gradient of thalamic damage evolves in pediatric multiple sclerosis

OBJECTIVE

Central nervous system pathology in multiple sclerosis includes both focal inflammatory perivascular injury and injury to superficial structures, including the subpial region of the cortex, which reportedly exhibits a gradient of damage from the surface inward. We assessed how early in the multiple sclerosis course a "surface-in" process of injury suggesting progressive biology may begin.

METHODS

We focused on the thalamus, which notably has both a cerebrospinal fluid (CSF) interface and a white matter interface. Thalamic volume trajectories were assessed in a prospectively followed cohort of children from initial presentation with either multiple sclerosis or monophasic acquired demyelination, and healthy controls. Voxelwise volume changes were calculated using deformation-based morphometry, and analyzed in relation to distance from the CSF interface by mixed effects modeling and semiparametric smoothing methods.

RESULTS

Twenty-seven children with multiple sclerosis and 73 children with monophasic demyelination were prospectively followed with yearly brain scans (mean follow-up = 4.6 years, standard deviation = 1.9). A total of 282 healthy children with serial scans were included as controls. Relative to healthy controls, children with multiple sclerosis and children with monophasic demyelination demonstrated volume loss in thalamic regions adjacent to the white matter. However, only children with multiple sclerosis exhibited an additional surface-in gradient of thalamic injury on the ventricular side, which was already notable in the first year of clinical disease (asymptote estimate = 3.01, 95% confidence interval [CI] = 1.44-4.58, p = 0.0002) and worsened over time (asymptote:time estimate = 0.33, 95% CI = 0.12-0.54, p = 0.0021).

INTERPRETATION

Our results suggest that a multiple sclerosis disease-specific surface-in process of damage can manifest at the earliest stages of the disease. ANN NEUROL 2019;85:340-351.

Immunopathological Factors Associated with Disability in Multiple Sclerosis

In multiple sclerosis (MS), disability occurs as a result of complex interactions between glial cells and diverse components of acquired immunity. Microglial cells significantly contribute to disability progression by re-activating infiltrating lymphocytes, releasing neuro- and oligodendrocytotoxic mediators, inducing oxidative stress, and interfering with neuroplasticity. Recent research has emphasized the significance of meningeal B cell infiltrates in development of cognitive decline and disability. B cells are also involved in disability progression by way of production of neurotoxic antibodies directed against axoglial antigens. Among several immunological factors, neurofilament light chain antibodies, IgM-type oligoclonal bands, complement factor C3, and microglia-derived mediators stick out as potential reliable predictors of disability progression in MS patients. Better understanding of the interactions between innate immunity and neuroaxonal degeneration may result in development of novel and effective therapeutics for progressive types of MS.

Whole brain and deep gray matter atrophy detection over 5 years with 3T MRI in multiple sclerosis using a variety of automated segmentation pipelines

Background

Cerebral atrophy is common in multiple sclerosis (MS) and selectively involves gray matter (GM). Several fully automated methods are available to measure whole brain and regional deep GM (DGM) atrophy from MRI.

Objective

To assess the sensitivity of fully automated MRI segmentation pipelines in detecting brain atrophy in patients with relapsing-remitting (RR) MS and normal controls (NC) over five years.

Methods

Consistent 3D T1-weighted sequences were performed on a 3T GE unit in 16 mildly disabled patients with RRMS and 16 age-matched NC at baseline and five years. All patients received disease-modifying immunotherapy on-study. Images were applied to two pipelines to assess whole brain atrophy [brain parenchymal fraction (BPF) from SPM12; percentage brain volume change (PBVC) from SIENA] and two other pipelines (FSL-FIRST; FreeSurfer) to assess DGM atrophy (thalamus, caudate, globus pallidus, putamen). MRI change was compared by two sample t-tests. Expanded Disability Status Scale (EDSS) and timed 25-foot walk (T25FW) change was compared by repeated measures proportional odds models.

Results

Using FreeSurfer, the MS group had a ~10-fold acceleration in on-study volume loss than NC in the caudate (mean decrease 0.51 vs. 0.05 ml, p = 0.022). In contrast, caudate atrophy was not detected by FSL-FIRST (mean decrease 0.21 vs. 0.12 ml, p = 0.53). None of the other pipelines showed any difference in volume loss between groups, for whole brain or regional DGM atrophy (all p>0.38). The MS group showed on-study stability on EDSS (p = 0.47) but slight worsening of T25FW (p = 0.054).

Conclusions

In this real-world cohort of mildly disabled treated patients with RRMS, we identified ongoing atrophy of the caudate nucleus over five years, despite the lack of any significant whole brain atrophy, compared to healthy controls. The detectability of caudate atrophy was dependent on the MRI segmentation pipeline employed. These findings underscore the increased sensitivity gained when assessing DGM atrophy in monitoring MS.

Neurofilament light chain as a biological marker for multiple sclerosis: a meta-analysis study

PURPOSE

There is a need for biomarkers in multiple sclerosis (MS) to make an early diagnosis and monitor its progression. This study was designed to evaluate the value of neurofilament light (NFL) chain levels as cerebrospinal fluid (CSF) or blood biomarker in patients with MS by using a quantitative meta-analysis.

METHODS

The PubMed, Embase, and Web of Science databases were systematically searched for relevant studies. Articles in English that evaluated the utility of NFL in CSF and blood in the diagnosis of MS were included. Data were extracted by two independent researchers. Mean (± SD) NFL concentration for MS patients and control subjects were extracted. Review Manager version 5.3 software with a continuous-variable random-effects model was used to summarize the diagnostic indexes from eligible studies. The Newcastle-Ottawa Scale was used for assessing the quality and risk of bias of included studies. In addition, subgroup analysis and meta-regression were performed to assess potential heterogeneity sources.

RESULTS

The meta-analysis included 13 articles containing results from 15 studies. A total of 10 studies measured NFL levels in CSF and five studies measured NFL levels in blood. Data were available on 795 participants in CSF and 1,856 participants in blood. Moreover, CSF NFL in MS patients was higher than that in healthy control groups (pooled standard mean difference [Std.MD]=0.88, 95% CI [0.50, 1.26], P<0.00001) and serum NFL in MS patients was higher than that in control subjects (pooled Std.MD=0.47, 95% CI [0.24, 0.71], P<0.0001).

CONCLUSION

NFL chain has significantly increased in MS patients, which substantially strengthens the clinical evidence of the NFL in MS. The NFL may be used as a prognostic biomarker to monitor disease progression, disease activity, and treatment efficacy in the future.

ATX-MS-1467 Induces Long-Term Tolerance to Myelin Basic Protein in (DR2 × Ob1)F1 Mice by Induction of IL-10-Secreting iTregs

INTRODUCTION

Antigen-specific immunotherapy could provide a targeted approach for the treatment of multiple sclerosis that removes the need for broad-acting immunomodulatory drugs. ATX-MS-1467 is a mixture of four peptides identified as the main immune-dominant disease-associated T-cell epitopes in myelin basic protein (MBP), an autoimmune target for activated autoreactive T cells in multiple sclerosis. Previous animal studies have shown that ATX-MS-1467 treatment prevented the worsening of signs of disease in experimental autoimmune encephalitis (EAE) in the humanized (DR2 × Ob1)F1 mouse in a dose-dependent fashion.

METHODS AND RESULTS

Our study extends these observations to show that subcutaneous treatment with 100 µg of ATX-MS-1467 after induction of EAE in the same mouse model reversed established clinical disability (p < 0.0001) and histological markers of inflammation and demyelination (p < 0.001) compared with vehicle-treated animals; furthermore, in longitudinal magnetic resonance imaging analyses, disruption of blood-brain barrier integrity was reversed, compared with vehicle-treated animals (p < 0.05). Chronic treatment with ATX-MS-1467 was associated with an enduring shift from a pro-inflammatory to a tolerogenic state in the periphery, as shown by an increase in interleukin 10 secretion, relative to interleukin 2, interleukin 17 and interferon γ, a decrease in splenocyte proliferation and an increase in interleukin 10+ Foxp3- T cells in the spleen.

CONCLUSION

Our results suggest that ATX-MS-1467 can induce splenic iTregs and long-term tolerance to MBP with the potential to partially reverse the pathology of multiple sclerosis, particularly during the early stages of the disease.

FUNDING

EMD Serono, Inc., a business of Merck KGaA.

The Efficacy of Psychological Interventions for Managing Fatigue in People With Multiple Sclerosis: A Systematic Review and Meta-Analysis

Background

Multiple sclerosis (MS) is a complex, demyelinating disease of the central nervous system. Fatigue is commonly reported by people with MS (PwMS). MS-related fatigue severely affects daily activities, employment, socioeconomic status, and quality of life.

Objective

We conducted this systematic review and meta-analysis to determine whether psychological interventions are effective in managing fatigue in PwMS.

Data sources

We performed systematic searches of Medline, EMBASE, PsycINFO, and CINAHL to identify relevant articles published from database inception to April 5, 2017. Reference lists from relevant reviews were also searched.

Study selection and design

Two independent reviewers screened the papers, extracted data, and appraised the included studies. A clinical psychologist verified whether interventions were psychological approaches. A narrative synthesis was conducted for all included studies. For relevant randomized controlled trials that reported sufficient information to determine standardized mean differences (SMDs) and 95% confidence intervals (CIs), meta-analyses were conducted using a random-effects model.

Results

Of the 353 identified articles, 20 studies with 1,249 PwMS were included in this systematic review. Narrative synthesis revealed that psychological interventions reduced fatigue in PwMS. Meta-analyses revealed that cognitive behavioral therapy decreased levels of fatigue compared with non-active controls (SMD = −0.32; 95% CI: −0.63 to −0.01) and compared with active controls (relaxation or psychotherapy) (SMD = −0.71; 95% CI: −1.05 to −0.37). Meta-analyses further showed that both relaxation (SMD = −0.90; 95% CI: −1.30 to −0.51), and mindfulness interventions (SMD = −0.62; 95% CI: −1.12 to −0.12), compared with non-active control, decreased fatigue levels. The estimates of heterogeneity for the four meta-analyses varied between none and moderate.

Conclusion

This study found that the use of psychological interventions for MS-related fatigue management reduced fatigue in PwMS. While psychological interventions are generally considered first-line therapy for MS-related fatigue, further studies are needed to explore the long-term effect of this therapy.

The role of blood and CSF biomarkers in the evaluation of new treatments against multiple sclerosis

INTRODUCTION

Multiple sclerosis (MS) is an immune-mediated chronic neurodegenerative disease of the central nervous system (CNS). Therapeutic interventions with immunomodulatory agents reduce disease activity and disability development, which are monitored clinically and by magnetic resonance imaging (MRI). However, these measures largely lack information on the impact from these therapies on inflammation, demyelination and axonal injury, the essential pathophysiological features of MS. Several biomarkers for inflammation and neurodegeneration have been detected in cerebrospinal fluid (CSF). In MS, some of these biomarkers seem to reflect disease activity, disability progression, and therapeutic response. Areas covered: In this review, we describe the most promising CSF biomarkers of inflammation and degeneration for monitoring therapeutic interventions in MS. We also describe the evolution of highly sensitive immunoassays that enable determination of neuron-specific biomarkers in blood. Expert commentary: Together with clinical and MRI measures, CSF biomarkers may improve the assessment of therapeutic efficacy and make personalized treatment possible. One disadvantage has been the need of repetitive lumbar punctures to obtain CSF. However, the technical development of highly sensitive immunoassays allows determination of extremely low quantities of neuron-specific proteins in blood. This will potentially open a new era for monitoring disease activity and treatment response in MS.

Terahertz Spectroscopic Diagnosis of Myelin Deficit Brain in Mice and Rhesus Monkey with Chemometric Techniques

While myelin deficit of the central nervous system leads to several severe diseases, the definitive diagnostic means are lacking. We proposed and performed terahertz time-domain spectroscopy (THz-TDS) combined with chemometric techniques to discriminate and evaluate the severity of myelin deficit in mouse and rhesus monkey brains. The THz refractive index and absorption coefficient of paraffin-embedded brain tissues from both normal and mutant dysmyelinating mice are shown. Principal component analysis of time-domain THz signal (PCA-tdTHz) and absorption-refractive index relation of THz spectrum identified myelin deficit without exogenous labeling or any pretreatment. Further, with the established PCA-tdTHz, we evaluated the severity of myelin deficit lesions in rhesus monkey brain induced by experimental autoimmune encephalomyelitis, which is the most-studied animal model of multiple sclerosis. The results well matched the pathological analysis, indicating that PCA-tdTHz is a quick, powerful, evolving tool for identification and evaluation myelin deficit in preclinical animals and potentially in para-clinical human biopsy.

Translocator Protein-18 kDa (TSPO) Positron Emission Tomography (PET) Imaging and Its Clinical Impact in Neurodegenerative Diseases

In vivo exploration of activated microglia in neurodegenerative diseases is achievable by Positron Emission Tomography (PET) imaging, using dedicated radiopharmaceuticals targeting the translocator protein-18 kDa (TSPO). In this review, we emphasized the major advances made over the last 20 years, thanks to TSPO PET imaging, to define the pathophysiological implication of microglia activation and neuroinflammation in neurodegenerative diseases, including Parkinson’s disease, Huntington’s disease, dementia, amyotrophic lateral sclerosis, multiple sclerosis, and also in psychiatric disorders. The extent and upregulation of TSPO as a molecular biomarker of activated microglia in the human brain is now widely documented in these pathologies, but its significance, and especially its protective or deleterious action regarding the disease’s stage, remains under debate. Thus, we exposed new and plausible suggestions to enhance the contribution of TSPO PET imaging for biomedical research by exploring microglia’s role and interactions with other cells in brain parenchyma. Multiplex approaches, associating TSPO PET radiopharmaceuticals with other biomarkers (PET imaging of cellular metabolism, neurotransmission or abnormal protein aggregates, but also other imaging modalities, and peripheral cytokine levels measurement and/or metabolomics analysis) was considered. Finally, the actual clinical impact of TSPO PET imaging as a routine biomarker of neuroinflammation was put into perspective regarding the current development of diagnostic and therapeutic strategies for neurodegenerative diseases.

MtDNA T4216C variation in multiple sclerosis: a systematic review and meta-analysis

MtDNA T4216C variation has frequently been investigated in Multiple Sclerosis (MS) patients; nonetheless, controversy has existed about the evidence of association of this variation with susceptibility to MS. The present systematic review and meta-analysis converge the results of the preceding publications, pertaining to association of mtDNA T4216C variation with susceptibility to MS, into a common conclusion. A computerized literature search in English was carried out to retrieve relevant publications from which required data were extracted. Using a fixed effect model, pooled odds ratio (OR), 95 % confidence interval (95 % CI), and P value were calculated for association of mtDNA T4216C variation with susceptibility to MS. The pooled results showed that there was a significant association between mtDNA T4216C variation and MS (OR = 1.38, 95 % CI = 1.13-1.67, P = 0.001). The present systematic review and meta-analysis suggest that mtDNA T4216C variation is a contributory factor in susceptibility to MS.

Primary progressive multiple sclerosis: current therapeutic strategies and future perspectives

INTRODUCTION

Multiple sclerosis (MS) is a chronic inflammatory condition of the central nervous system with heterogeneous features. Primary progressive (PP) MS is a rare disease subtype characterized by continuous disability worsening from onset. No disease-modifying therapy is currently approved for PP MS due to the negative or inconsistent results of clinical trials conducted on a wide range of interventions, which are reviewed in the present paper. Areas covered: The features and results of randomized trials of disease-modifying treatments for PP MS are discussed, including immunosuppressants, immunomodulators, monoclonal antibodies, and putative neuroprotective agents. Expert commentary: The recent encouraging results of the ocrelizumab trial in PP MS, the first to reach the primary disability endpoint, indicate B cells as a promising therapeutic target to prevent disease progression. Other emerging treatment strategies include cell metabolism modulation and inflammatory pathways inhibition, which are being investigated in several ongoing phase II and III placebo-controlled trials. Future PP MS trials will need to systematically include efficacy endpoints other than physical disability alone, such as cognition, quality of life, advanced MRI measures and molecular biomarkers.

Grey matter atrophy is associated with disability increase in natalizumab-treated patients

Background:

Brain volume loss (BVL) is a key outcome in multiple sclerosis (MS) trials. Natalizumab is highly effective on inflammation with moderate impact on atrophy.

Objective:

To explore BVL in patients receiving natalizumab with an emphasis on grey matter (GM).

Methods:

We performed a retrospective post hoc analysis of BVL in 38 patients receiving natalizumab for 3 years using longitudinal voxel-based morphometry (VBM) and FreeSurfer.

Results:

Significant BVL was observed during first year: brain parenchymal fraction (BPF): −1.12% ( p < 0.001); white matter fraction (WMF): −0.9% ( p = 0.001); grey matter fraction (GMF): −1.28% ( p = 0.002). GM loss was found using VBM in bilateral cerebellum, cingulum, left > right fronto-parietal cortex, right > left hippocampus and left caudate. FreeSurfer showed significant volume losses in subcortical GM, brainstem and cerebellum, and cortical thinning in the left insula. In the second year, only WMF decrease (−0.6%; p = 0.015) was observed with no VBM changes, although FreeSurfer detected significant volume loss in thalamus, hippocampus and cerebellum. Baseline gadolinium enhancement influenced WMF and BPF changes during the first year, but not GMF. Patients with confirmed Expanded Disability Status Scale (EDSS) worsening at 3 years had lower baseline GMF and left thalamus volume and greater BVL over follow-up.

Conclusion:

BVL develops mainly during the first year of natalizumab therapy. GM changes are independent of baseline inflammation and correlate with disability.