Towards a validated definition of the clinical transition to secondary progressive multiple sclerosis: A study from the Italian MS Register

BACKGROUND

Definitions for reliable identification of transition from relapsing-remitting multiple sclerosis (MS) to secondary progressive (SP)MS in clinical cohorts are not available.

OBJECTIVES

To compare diagnostic performances of two different data-driven SPMS definitions.

METHODS

Data-driven SPMS definitions based on a version of Lorscheider's algorithm (DDA) and on the EXPAND trial inclusion criteria were compared, using the neurologist's definition (ND) as gold standard, in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), Akaike information criterion (AIC) and area under the curve (AUC).

RESULTS

A cohort of 10,240 MS patients with ⩾5 years of follow-up was extracted from the Italian MS Registry; 880 (8.5%) patients were classified as SPMS according to the neurologist definition, 1806 (17.6%) applying the DDA and 1134 (11.0%) with the EXPAND definition. The DDA showed greater discrimination power (AUC: 0.8 vs 0.6) and a higher sensitivity (77.1% vs 38.0%) than the EXPAND definition, with similar specificity (88.0% vs 91.5%). PPV and NPV were higher using the DDA than considering EXPAND definition (37.5% vs 29.5%; 97.6% vs 94.0%).

CONCLUSION

Data-driven definitions demonstrated greater ability to capture SP transition than neurologist's definition and the global accuracy of DDA seems to be higher than the EXPAND definition.

Spatial and temporal distribution of the prevalence of unemployment and early retirement in people with multiple sclerosis: A systematic review with meta-analysis

Background

We aimed to summarise the prevalence of unemployment and early retirement among people with MS and analyze data according to a spatio-temporal perspective.

Methods

We undertook a systematic search of PubMed/MEDLINE, Scopus, SciVerse ScienceDirect, and Web of Science. We included any peer-reviewed original article reporting the prevalence of unemployment and early retirement in the working-age population with MS. We excluded articles off-topic, with other study designs, whose study sample were unlikely to be representative of the MS population and in case of unavailability of the full text or essential information. A random-effects meta-analysis was used to measure overall prevalence estimates of unemployment and early retirement. We used meta-regression and subgroup analysis to evaluate potential moderators of prevalence estimates and the leave-one-out method for sensitivity analyses.

Results

Our research identified 153 studies across 29 countries encompassing 188436 subjects with MS. The pooled overall effect size for unemployment and early retirement was 35.6% (95% CI 32.8–38.4; I² = 99.31) and 17.2% (95% CI 14.6–20.2; I² = 99.13), respectively. The prevalence of unemployment varied according to the year of publication (p < 0.001) and there was a statistically significant decrease in the prevalence of unemployment over time (p = 0.042). Regarding early retirement, only seven (31.8%) estimates obtained from studies that were published before 2010 were below the overall effect size in comparison to 27 (60.0%) estimates extracted from data published between 2010 and 2021 (p = 0.039). There was a significant difference in prevalence according to countries (p < 0.001). Psychiatric illness was an important clinical feature responsible for patients leaving the workforce in regions with a high MS prevalence.

Conclusions

Unemployment and early retirement due to MS remain highly prevalent, despite a slight decline in the last decade. The prevalence of unemployment and early retirement varies globally.

Upper Limb Sensory-Motor Control During Exposure to Different Mechanical Environments in Multiple Sclerosis Subjects With No Clinical Disability

Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease resulting in motor impairments associated with muscle weakness and lack of movement coordination. The goal of this work was to quantify upper limb motor deficits in asymptomatic MS subjects with a robot-based assessment including performance and muscle synergies analysis. A total of 7 subjects (MS: 3 M−4 F; 42 ± 10 years) with clinically definite MS according to McDonald criteria, but with no clinical disability, and 7 age- and sex-matched subjects without a history of neurological disorders participated in the study. All subjects controlled a cursor on the computer screen by moving their hand or applying forces in 8 coplanar directions at their self-selected speed. They grasped the handle of a robotic planar manipulandum that generated four different environments: null, assistive or resistive forces, and rigid constraint. Simultaneously, the activity of 15 upper body muscles was recorded. Asymptomatic MS subjects generated less smooth and less accurate cursor trajectories than control subjects in controlling a force profile, while the end-point error was significantly different also in the other environments. The EMG analysis revealed different muscle activation patterns in MS subjects when exerting isometric forces or when moving in presence of external forces generated by a robot. While the two populations had the same number and similar structure of muscle synergies, they had different activation profiles. These results suggested that a task requiring to control forces against a rigid environment allows better than movement tasks to detect early sensory-motor signs related to the onset of symptoms of multiple sclerosis and to differentiate between stages of the disease.

Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a co mplex disease of the central nervous system involving several types of brain pathology that are difficult to characterize using conventional imaging methods.

NEW METHOD

We originated novel texture analysis and machine learning approaches for classifying MS pathology subtypes as compared with 2 common advanced MRI measures: magnetization transfer ratio (MTR) and fractional anisotropy (FA). Texture analysis used an optimized grey level co-occurrence matrix method with histology-informed 7T T2-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) from 15 MS and 12 control brain specimens. DTI analysis took an innovative approach that assessed the texture across diffusion directions upsampled from 30 to 90. Tissue types included de- and re-myelinated lesions and normal-appearing areas in both grey and white matter, and diffusely abnormal white matter. Data analyses were stepwise, including: (1) group-wise classification using random forest algorithms based on all or individual imaging parameters; (2) parameter importance ranking; and (3) pairwise analysis using top-ranked features.

RESULTS

Texture analysis performed better than MTR and FA, with T2 texture performed the best. T2 texture measures ranked the highest in classifying most grey and white matter tissue types, including de- versus re-myelinated lesions and among grey matter lesion subtypes (accuracy=0.86-0.59; kappa=0.60-0.41). Diffusion texture best differentiated normal appearing and control white matter.

COMPARISON WITH EXISTING METHODS

There is no established method in imaging for differentiating MS pathology subtypes. In combined texture analysis and machine learning studies, there is also no direct evidence comparing conventional with advanced MRI measures for assessing MS pathology. Further, this study is unique in conducting innovative texture analysis with DTI following data-augmentation using robust methods.

CONCLUSIONS

T2 and diffusion MRI texture analysis integrated with machine learning may be valuable approaches for characterizing MS pathology.

Occupational outcomes of people with multiple sclerosis: a scoping review

OBJECTIVES

To update the knowledge on the occupational outcomes associated with multiple sclerosis (MS), systematically examine the extent, scope and nature of the pre-existing literature and identify research gaps in the existing literature.

DESIGN

Scoping review.

DATA SOURCES

A comprehensive database search of PubMed/MEDLINE, Scopus, SciVerse ScienceDirect and Web of Science was performed. There were no time limits.

ELIGIBILITY CRITERIA

We included any peer-reviewed original article reporting the occupational outcomes of people with MS between the ages of 18 and 65 years. We excluded those off-topic and with insufficient information.

METHODS

This review was conducted following the Joanna Briggs Institute recommendations and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for scoping review checklist. Screening, reading of full-texts and data extraction was performed in a standardised way by expert reviewers from 14 July 2021 to 31 October 2021. We provided a narrative synthesis and an overview of findings.

RESULTS

The initial systematic search yielded 104 228 results. After removing duplicates and applying the exclusion criteria, 403 articles were included in the review. In total, the studies evaluated 492 062 subjects with MS. One hundred fifty-four (38.2%) articles were published in the last 5 years, mostly from Europe and North America (50.9% and 33.0%, respectively). Concerning the occupational outcomes, studies mostly addressed unemployment (311, 77.2%), early retirement (120, 29.8%), disability pension (117, 29.0%), sick leave (77, 19.1%), the indirect cost of MS (74, 18.4%) and work characteristics (57, 14.1%). The results were categorised into seven subtopics: 'Changes in work and occupational status due to MS', 'work-related socio-economic consequences of MS', 'risk factors for unfavourable occupational outcomes', 'reported barriers to employment', 'reported job accommodations and vocational rehabilitation strategies', 'job satisfaction, stigma, and disclosing the diagnosis in the workplace' and 'rating clinical scales'.

CONCLUSIONS

There are several issues that deserve further in-depth study by the scientific community in order to improve the occupational outcomes of people with MS.

Improved detection of multiple sclerosis lesions with T2-prepared double inversion recovery at 3T

BACKGROUND AND PURPOSE

Double inversion recovery (DIR) imaging is used in multiple sclerosis (MS) clinical protocols to improve the detection of cortical and juxtacortical gray matter lesions by nulling confounding signals originating from the cerebrospinal fluid and white matter. Achieving a high isotropic spatial resolution, to depict the neocortex and its typically small lesions, is challenged by the reduced signal-to-noise ratio (SNR) determined by multiple tissue signal nulling. Here, we evaluate both conventional and optimized DIR implementations to improve tissue contrast (TC), SNR, and MS lesion conspicuity.

METHODS

DIR images were obtained from MS patients and healthy controls using both conventional and prototype implementations featuring a T2-preparation module (T2P), to improve SNR and TC, as well as an image reconstruction routine with iterative denoising (ID). We obtained quantitative measures of SNR and TC, and evaluated the visibility of MS cortical, cervical cord, and optic nerve lesions in the different DIR images.

RESULTS

DIR implementations adopting T2P and ID enabled improving the SNR and TC of conventional DIR. In MS patients, 34% of cortical, optic nerve, and cervical cord lesions were visible only in DIR images acquired with T2P, and not in conventional DIR images. In the studied cases, image reconstruction with ID did not improve lesion conspicuity.

CONCLUSIONS

DIR with T2P should be preferred to conventional DIR imaging in protocols studying MS patients, as it improves SNR and TC and determines an improvement in cortical, optic nerve, and cervical cord lesion conspicuity.

Anti-SARS-CoV-2 T-stem cell memory persists in ocrelizumab-treated MS patients

BACKGROUND

Development of long-lasting anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) T-cell responses in persons with multiple sclerosis (pwMS) treated with ocrelizumab is questioned.

OBJECTIVE

Investigate antiviral T-cell responses after infection with SARS-CoV-2 in ocrelizumab-treated pwMS. Control groups included ocrelizumab-treated pwMS without SARS-CoV-2 infection, and non-MS individuals with and without SARS-CoV-2 infection.

METHODS

Peripheral blood mononuclear cells were stimulated with SARS-CoV-2 peptide pools and T-cell reactivity was assessed by ELISPOT for interferon (IFN)-γ detection, and by multiparametric fluorescence-activated cell sorting (FACS) analyses for assessment and characterization of T-cell activation.

RESULTS

ELISPOT assay against the spike and the N protein of SARS-CoV-2 displayed specific T-cell reactivity in 28/29 (96%) pwMS treated with ocrelizumab and infected by SARS-CoV-2, similar to infected persons without MS. This reactivity was present 1 year after infection and independent from the time of ocrelizumab infusion. FACS analysis following stimulation with SARS-CoV-2 peptide pools showed the presence of activation-induced markers (AIMs) in both CD4⁺ and CD8⁺ T-cell subsets in 96% and 92% of these individuals, respectively. Within naïve AIM⁺ CD4⁺ and CD8⁺ T-cells, we detected T memory stem cells, suggesting the acquisition of long-term memory.

CONCLUSIONS

B-cell depletion using ocrelizumab does not impair the development of long-lasting anti-SARS-CoV-2 T-cell responses.

The role of disconnection in explaining disability in multiple sclerosis

Background

In multiple sclerosis, the correlation between white matter lesion volumes (LV) and expanded disability status scale (EDSS) is at best moderate, leading to the “clinico-radiological paradox”, influenced by many factors, including the lack of information on the spatial localisation of each lesion on synthetic metrics such as LV. We used a probabilistic approach to provide the volume of WM tracts that may be disconnected by lesions and to evaluate its correlation with EDSS.

Methods

Forty-five patients (aged 37.4 ± 6.8 years, mean ± standard deviation; 30 females; 29 relapsing-remitting, 16 progressive) underwent 3-T magnetic resonance imaging. Both LV and the volume of the tracts crossing the lesioned regions (disconnectome volume, DV) were calculated using BCBtoolkit and correlated with EDSS.

Results

T1-weighted LV and DV significantly correlated with EDSS (p ≤ 0.006 r ≥ 0.413) as it was for T2-weighted LV and T2-weighted DV (p ≤ 0.004 r ≥ 0.430), but only T1-weighetd and T2-weighted DVs were EDSS significant predictors (p ≤ 0.001). The correlations of T1-weighted and T2-weighted LV with EDSS were significantly mediated by DV, while no effect of LV on the EDSS-DV correlation was observed.

Conclusion

The volume of disconnected WM bundles mediates the LV-EDSS correlation, representing the lonely EDSS predictor.

Breakthrough SARS-CoV-2 infections after COVID-19 mRNA vaccination in MS patients on disease modifying therapies during the Delta and the Omicron waves in Italy

BACKGROUND

In this study we aimed to monitor the risk of breakthrough SARS-CoV-2 infection in patients with MS (pwMS) under different DMTs and to identify correlates of reduced protection.

METHODS

This is a prospective Italian multicenter cohort study, long-term clinical follow-up of the CovaXiMS (Covid-19 vaccine in Multiple Sclerosis) study. 1855 pwMS scheduled for SARS-CoV-2 mRNA vaccination were enrolled and followed up to a mean time of 10 months. The cumulative incidence of breakthrough Covid-19 cases in pwMS was calculated before and after December 2021, to separate the Delta from the Omicron waves and to account for the advent of the third vaccine dose.

FINDINGS

1705 pwMS received 2 m-RNA vaccine doses, 21/28 days apart. Of them, 1508 (88.5%) had blood assessment 4 weeks after the second vaccine dose and 1154/1266 (92%) received the third dose after a mean interval of 210 days (range 90-342 days) after the second dose. During follow-up, 131 breakthrough Covid-19 infections (33 during the Delta and 98 during the Omicron wave) were observed. The probability to be infected during the Delta wave was associated with SARS-CoV-2 antibody levels measured after 4 weeks from the second vaccine dose (HR=0.57, p < 0.001); the protective role of antibodies was preserved over the whole follow up (HR=0.57, 95%CI=0.43-0.75, p < 0.001), with a significant reduction (HR=1.40, 95%CI=1.01-1.94, p=0.04) for the Omicron cases. The third dose significantly reduced the risk of infection (HR=0.44, 95%CI=0.21-0.90,p=0.025) during the Omicron wave.

INTERPRETATION

The risk of breakthrough SARS-CoV-2 infections is mainly associated with reduced levels of the virus-specific humoral immune response.

FUNDING

Supported by FISM - Fondazione Italiana Sclerosi Multipla - cod. 2021/Special-Multi/001 and financed or co-financed with the '5 per mille' public funding.

Early use of high-efficacy disease‑modifying therapies makes the difference in people with multiple sclerosis: an expert opinion

Multiple sclerosis (MS) is a chronic and progressive neurological disease that is characterized by neuroinflammation, demyelination and neurodegeneration occurring from the earliest phases of the disease and that may be underestimated. MS patients accumulate disability through relapse-associated worsening or progression independent of relapse activity. Early intervention with high-efficacy disease-modifying therapies (HE-DMTs) may represent the best window of opportunity to delay irreversible central nervous system damage and MS-related disability progression by hindering underlying heterogeneous pathophysiological processes contributing to disability progression. In line with this, growing evidence suggests that early use of HE-DMTs is associated with a significant greater reduction not only of inflammatory activity (clinical relapses and new lesion formation at magnetic resonance imaging) but also of disease progression, in terms of accumulation of irreversible clinical disability and neurodegeneration compared to delayed HE-DMT use or escalation strategy. These beneficial effects seem to be associated with acceptable long-term safety risks, thus configuring this treatment approach as that with the most positive benefit/risk profile. Accordingly, it should be mandatory to treat people with MS early with HE-DMTs in case of prognostic factors suggestive of aggressive disease, and it may be advisable to offer an HE-DMT to MS patients early after diagnosis, taking into account drug safety profile, disease severity, clinical and/or radiological activity, and patient-related factors, including possible comorbidities, family planning, and patients’ preference in agreement with the EAN/ECTRIMS and AAN guidelines. Barriers for an early use of HE-DMTs include concerns for long-term safety, challenges in the management of treatment initiation and monitoring, negative MS patients’ preferences, restricted access to HE-DMTs according to guidelines and regulatory rules, and sustainability. However, these barriers do not apply to each HE-DMT and none of these appear insuperable.

The relationship between processing speed and verbal and non-verbal new learning and memory in progressive multiple sclerosis

Objective:

Processing speed (PS) deficits are the most common cognitive deficits in multiple sclerosis (MS), followed by learning and memory deficits, and are often an early cognitive problem. It has been argued that impaired PS is a primary consequence of MS, which in turn decreases learning. The current analysis examined the association between PS and learning in a large cohort of individuals with progressive MS.

Methods:

Baseline data from a randomized clinical trial on rehabilitation taking place at 11 centers across North America and Europe were analyzed. Participants included 275 individuals with clinically definite progressive MS (primary, secondary) consented into the trial.

Results:

Symbol Digit Modalities Test (SDMT) significantly correlated with California Verbal Learning Test-II (CVLT-II) ( r = 0.21, p = 0.0003) and Brief Visuospatial Memory Test–Revised (BVMT-R) ( r = 0.516, p < 0.0001). Receiver operating characteristic (ROC) analysis of the SDMT z score to distinguish between impaired and non-impaired CVLT-II performance demonstrated an area under the curve (AUC) of 0.61 (95% confidence interval (CI): 0.55–0.68) and a threshold of −1.62. ROC analysis between SDMT and BVMT-R resulted in an AUC of 0.77 (95% CI: 0.71–0.83) and threshold of −1.75 for the SDMT z score to predict impaired BVMT-R.

Conclusion:

Results indicate little ability beyond chance to predict CVLT-II from SDMT (61%), albeit statistically significant. In contrast, there was a 77% chance that the model could distinguish between impaired and non-impaired BVMT-R. Several potential explanations are discussed.

A multiparametric score for assessing the individual risk of severe Covid-19 among patients with Multiple Sclerosis

Background

Many risk factors for the development of severe forms of Covid-19 have been identified, some applying to the general population and others specific to Multiple Sclerosis (MS) patients. However, a score for quantifying the individual risk of severe Covid-19 in patients with MS is not available. The aim of this study was to construct such score and to evaluate its performance.

Methods

Data on patients with MS infected with Covid-19 in Italy, Turkey and South America were extracted from the Musc-19 platform. After imputation of missing values, data were separated into training data set (70%) and validation data set (30%). Univariable logistic regression models were performed in the training dataset to identify the main risk factors to be included in the multivariable logistic regression analyses. To select the most relevant variables we applied three different approaches: (1) multivariable stepwise, (2) Lasso regression, (3) Bayesian model averaging. Three scores were defined as the linear combination of the coefficients estimated in the models multiplied by the corresponding value of the variables and higher scores were associated to higher risk of severe Covid-19 course. The performances of the three scores were compared in the validation dataset based on the area under the ROC curve (AUC) and an optimal cut-off was calculated in the training dataset for the score with the best performance. The probability of showing a severe Covid-19 course was calculated based on the score with the best performance.

Results

3852 patients were included in the study (2696 in the training dataset and 1156 in the validation data set). 17% of the patients required hospitalization and risk factors for severe Covid-19 course were older age, male sex, living in Turkey or South America instead of living in Italy, presence of comorbidities, progressive MS, longer disease duration, higher Expanded Disability Status Scale, Methylprednisolone use and anti-CD20 treatment. The score with the best performance was the one derived using the Lasso selection approach (AUC= 0.72) and it was built with the following variables: age, sex, country, BMI, presence of comorbidities, EDSS, methylprednisolone use, treatment. An excel spreadsheet to calculate the score and the probability of severe Covid-19 is available at the following link: https://osf.io/ac47u/?view_only=691814d57b564a34b3596e4fcdcf8580.

Conclusions

The originality of this study consists in building a useful tool to quantify the individual risk for Covid-19 severity based on patient's characteristics. Due to the modest predictive ability and to the need of external validation, this tool is not ready for being fully used in clinical practice to make important decisions or interventions. However, it can be used as an additional instrument to identify high-risk patients and persuade them to take important measures to prevent Covid-19 infection (i.e. getting vaccinated against Covid-19, adhering to social distancing, and using of personal protection equipment).

Influence of Previous Disease-Modifying Drug Exposure on T-Lymphocyte Dynamic in Patients With Multiple Sclerosis Treated With Ocrelizumab

Background and Objectives

To investigate the longitudinal dynamic of lymphocyte subsets during treatment with ocrelizumab (OCR) in patients with multiple sclerosis (PwMS).

Methods

A multicenter retrospective study was conducted in 161 PwMS starting treatment with OCR grouped in naive (naive, n = 40), switching from fingolimod (FTY, n = 52), and switching from other immunomodulating drugs (other, n = 69). Mean lymphocyte subset (total, CD3+, CD4+, CD8+, CD20+, and natural killer) counts were analyzed at baseline, 6 months, and 12 months. Rate of lymphocytopenia for each subset was calculated at all time points in all groups.

Results

Mean total, CD3+, and CD4+ counts were significantly different among groups (p < 0.001) at all time points, whereas CD8+ and CD20+ counts only at baseline (p = 0.0157; p < 0.001), consistently lower in FTY. After adjustment for baseline values, interaction time*group was not statistically significant (p > 0.05 for each subset). The odds of lymphopenia were significantly higher among FTY patients compared with naive for total, CD3+, CD4+, and CD20+ cells at baseline, for total and CD4+ cells at the sixth month, and for total cells at the 12th month.

Discussion

OCR per se exerts a modest depleting effect on T cells that seems rather due to a carryover phenomenon of previous therapies, particularly FTY. These data may help in the overall evaluation of the risk/benefit profile of treatment sequencing.

Secondary Prevention in Radiologically Isolated Syndromes and Prodromal Stages of Multiple Sclerosis

Following the extraordinary progress in the treatment of multiple sclerosis (MS), two major unmet needs remain: understanding the etiology of the disease and, hence, designing definitive cures (this perspective is neither at hand, nor it can be taken for granted that the etiologic targets will be readily treatable); the prevention of an overt and disabling disease, which seems to be a more realistic and pragmatic perspective, as the integration of genetic data with endophenotypes, MRI, and other biomarkers ameliorates our ability to identify early neuroinflammation. Radiologically isolated syndrome (RIS; diagnosed when the unanticipated MRI finding of brain spatial dissemination of focal white matter lesions highly suggestive of MS occurs in subjects without symptoms of MS, and with normal neurological examinations) and the recently focused “prodromal MS” are conditions at risk of conversion toward overt disease. Here, we explore the possibility of secondary prevention approaches in these early stages of neuroinflammation. RIS and prodromal MS are rare conditions, which suggest the importance of Study Groups and Disease Registry to implement informative clinical trials. We summarize ongoing preventive approaches in the early stages of the demyelinating process, especially in RIS conditions. Moreover, we highlight the importance of the biomarkers and the predictors of evolution to overt disease, which may be useful to select the individuals at risk of conversion to clinically isolated syndrome (CIS) and/or clinically definite MS. Finally, we illustrate the importance of the endophenotypes to test the frontline immunomodulatory approach for preventive strategies. Future investigations, especially in relatives of patients, based on MRI techniques and biological studies (better with integrated approaches) may provide opportunities to understand the MS early causal cascade and may help to identify a “therapeutic window” to potentially reverse early disease processes.

Classification of multiple sclerosis patients based on structural disconnection: A robust feature selection approach

Background and Purpose

Although structural disconnection represents the hallmark of multiple sclerosis (MS) pathophysiology, classification attempts based on structural connectivity have achieved low accuracy levels. Here, we set out to fill this gap, exploring the performance of supervised classifiers on features derived from microstructure informed tractography and selected applying a novel robust approach.

Methods

Using microstructure informed tractography with diffusion MRI data, we created quantitative connectomes of 55 MS patients and 24 healthy controls. We then used a robust approach—based on two classical methods of feature selection— to select relevant features from three network representations (whole connectivity matrices, node strength, and local efficiency). Classification accuracy of the selected features was tested with five different classifiers, while their meaningfulness was tested via correlation with clinical scales. As a comparison, the same classifiers were run on features selected with the standard procedure in network analysis (thresholding).

Results

Our procedure identified 11 features for the whole net, five for local efficiency, and seven for node strength. For all classifiers, the accuracy was in the range 64.5%‐91.1%, with features extracted from the whole net reaching the maximum, and overcoming results obtained with the standard procedure in all cases. Correlations with clinical scales were identified across functional domains, from motor and cognitive abilities to fatigue and depression.

Conclusion

Applying a robust feature selection procedure to quantitative structural connectomes, we were able to classify MS patients with excellent accuracy, while providing information on the white matter connections and gray matter regions more affected by MS pathology.

mRNA-COVID19 Vaccination Can Be Considered Safe and Tolerable for Frail Patients

Background

Frail patients are considered at relevant risk of complications due to coronavirus disease 2019 (COVID-19) infection and, for this reason, are prioritized candidates for vaccination. As these patients were originally not included in the registration trials, fear related to vaccine adverse events and disease worsening was one of the reasons for vaccine hesitancy. Herein, we report the safety profile of the prospective, multicenter, national VAX4FRAIL study (NCT04848493) to evaluate vaccines in a large trans-disease cohort of patients with solid or hematological malignancies and neurological and rheumatological diseases.

Methods

Between March 3 and September 2, 2021, 566 patients were evaluable for safety endpoint: 105 received the mRNA-1273 vaccine and 461 the BNT162b2 vaccine. Frail patients were defined per protocol as patients under treatment with hematological malignancies (n = 131), solid tumors (n = 191), immune-rheumatological diseases (n = 86), and neurological diseases (n = 158), including multiple sclerosis and generalized myasthenia. The impact of the vaccination on the health status of patients was assessed through a questionnaire focused on the first week after each vaccine dose.

Results

The most frequently reported moderate–severe adverse events were pain at the injection site (60.3% after the first dose, 55.4% after the second), fatigue (30.1%–41.7%), bone pain (27.4%–27.2%), and headache (11.8%–18.9%). Risk factors associated with the occurrence of severe symptoms after vaccine administration were identified through a multivariate logistic regression analysis: age was associated with severe fever presentation (younger patients vs. middle-aged vs. older ones), female individuals presented a higher probability of severe pain at the injection site, fatigue, headache, and bone pain; and the mRNA-1237 vaccine was associated with a higher probability of severe pain at the injection site and fever. After the first dose, patients presenting a severe symptom were at a relevant risk of recurrence of the same severe symptom after the second one. Overall, 11 patients (1.9%) after the first dose and 7 (1.2%) after the second one required postponement or suspension of the disease-specific treatment. Finally, two fatal events occurred among our 566 patients. These two events were considered unrelated to the vaccine.

Conclusions

Our study reports that mRNA-COVID-19 vaccination is safe also in frail patients; as expected, side effects were manageable and had a minimum impact on patient care path.

Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach

OBJECTIVES

To stratify patients with multiple sclerosis (pwMS) based on brain MRI-derived volumetric features using unsupervised machine learning.

METHODS

The 3-T brain MRIs of relapsing-remitting pwMS including 3D-T1w and FLAIR-T2w sequences were retrospectively collected, along with Expanded Disability Status Scale (EDSS) scores and long-term (10 ± 2 years) clinical outcomes (EDSS, cognition, and progressive course). From the MRIs, volumes of demyelinating lesions and 116 atlas-defined gray matter regions were automatically segmented and expressed as z-scores referenced to external populations. Following feature selection, baseline MRI-derived biomarkers entered the Subtype and Stage Inference (SuStaIn) algorithm, which estimates subgroups characterized by distinct patterns of biomarker evolution and stages within subgroups. The trained model was then applied to longitudinal MRIs. Stability of subtypes and stage change over time were assessed via Krippendorf's α and multilevel linear regression models, respectively. The prognostic relevance of SuStaIn classification was assessed with ordinal/logistic regression analyses.

RESULTS

We selected 425 pwMS (35.9 ± 9.9 years; F/M: 301/124), corresponding to 1129 MRI scans, along with healthy controls (N = 148; 35.9 ± 13.0 years; F/M: 77/71) and external pwMS (N = 80; 40.4 ± 11.9 years; F/M: 56/24) as reference populations. Based on 11 biomarkers surviving feature selection, two subtypes were identified, designated as "deep gray matter (DGM)-first" subtype (N = 238) and "cortex-first" subtype (N = 187) according to the atrophy pattern. Subtypes were consistent over time (α = 0.806), with significant annual stage increase (b = 0.20; p < 0.001). EDSS was associated with stage and DGM-first subtype (p ≤ 0.02). Baseline stage predicted long-term disability, transition to progressive course, and cognitive impairment (p ≤ 0.03), with the latter also associated with DGM-first subtype (p = 0.005).

CONCLUSIONS

Unsupervised learning modelling of brain MRI-derived volumetric features provides a biologically reliable and prognostically meaningful stratification of pwMS.

KEY POINTS

• The unsupervised modelling of brain MRI-derived volumetric features can provide a single-visit stratification of multiple sclerosis patients. • The so-obtained classification tends to be consistent over time and captures disease-related brain damage progression, supporting the biological reliability of the model. • Baseline stratification predicts long-term clinical disability, cognition, and transition to secondary progressive course.

Impact of Natural Killer (NK) Cells on Immune Reconstitution, and Their Potential as a Biomarker of Disease Activity, in Alemtuzumab-Treated Patients with Relapsing Remitting Multiple Sclerosis: An Observational Study

BACKGROUND

Defining immune mechanisms leading to multiple sclerosis (MS) is difficult, due to the great inter-individual difference in immune system responses. The anti-CD52 antibody alemtuzumab transiently abolishes differences in immune parameters among individuals, allowing analysis of subsequent immune cell repopulation patterns, and their possible role in MS.

OBJECTIVE

To evaluate the correlation between innate and adaptive immune cell subsets and disease activity in MS in the context of treatment with alemtuzumab.

METHODS

A two-center observational cohort of patients treated with alemtuzumab underwent immune profiling of T, B, and natural killer (NK) cells, biomarker, clinical and radiological follow-up.

RESULTS

After treatment, the percentage of NK and B cells increased; NK, T- and B-cell populations underwent a profound rearrangement. Within the effector T-cell compartment, treatment led to a transient decrease, followed by an increase, of T-helper 1 cells, and to a transient decrease of T-helper 17 cells. Within the T-regulatory compartment, naïve T-regulatory cells increased. Within the B-cell compartment, memory B cells and mature B cells decreased, whereas transitional B cells increased. Within the NK cell compartment, CD56^bright NK cells increased. Subjects without disease activity had a greater decrease in serum NfL and greater NK cell/CD3+ T cell ratio. NK cell numbers at baseline and after treatment influenced reconstitution of T and B cells, being inversely correlated with the reconstitution of proinflammatory CD3+ T cells and mature B cells, and directly correlated to the increase in transitional B cells.

CONCLUSIONS

The results of this study provide novel evidence that NK cells influence reconstitution of adaptive immune cells upon alemtuzumab and that patients with a successful response to alemtuzumab have an early immune reconstitution dominated by NK cells.

MR spectroscopy and diffusion imaging in people with human immunodeficiency virus: Relationships to clinical and immunologic findings

BACKGROUND AND PURPOSE

People with human immunodeficiency virus (HIV; PWH) present a complex array of immunologic and medical disorders that impact brain structure and metabolism, complicating the interpretation of neuroimaging. This pilot study of well-characterized multi-morbid PWH examined how medical and immunologic factors predicted brain characteristics on proton MR spectroscopy (1H-MRS) and diffusion-weighted imaging (DWI).

METHODS

Eighteen individuals on combination antiretroviral therapy (cART), with mean age of 56 years, underwent medical history review, neuroimaging, and on the day of imaging, blood draw for assay of 20 plasma cytokines and flow cytometric characterization of peripheral blood mononuclear cell subsets. Predictors of n-acetyl aspartate, choline, myoinositol, glutamate/glutamine, fractional anisotropy and mean diffusivity were identified through bivariate correlation; those significant at p < .1000 were advanced to multivariate analysis, with models created for each neuroimaging outcome.

RESULTS

Monocyte subsets and diverse cytokines accounted for 16 of 25 (64%) variables predicting 1H-MRS spectra in frontal gray and white matter and basal ganglia; monocyte subsets did not predict any DWI characteristic. In contrast, age, presence of hypertension, and duration of HIV infection accounted for 13 of 25 (52%) variables predicting diffusion characteristics in the corpus callosum, thalamic radiations, and basal ganglia but only 3 of 25 (12%) predictors of 1H-MRS features.

CONCLUSIONS

1H-MRS neurometabolites were most often predicted by immunologic factors sensitive to temporal variation, whereas DWI metrics were more often related to longer-term disease state. In multi-morbid cART-era populations, selection and interpretation of neuroimaging modalities should account for complex temporal and pathogenetic influences of immunologic abnormality, disease state, and aging.

Effect of Multiple Sclerosis and Its Treatments on Male Fertility: Cues for Future Research

Multiple sclerosis is a chronic disease that may lead to different types of symptoms and disabilities. with the better quality of life and decreased disability due to early diagnosis and the availability of disease-modifying therapies (DMTs), the treating physician is increasingly asked to counsel patients on its effects on fertility and reproduction. In particular, reproductive issues are still scarcely studied and discussed in men. Among the still open questions are the following: (a) Does multiple sclerosis cause infertility per sè? (b) Is multiple sclerosis correlated with conditions that increase the risk of infertility? (c) Do DMTs or other therapies for multiple sclerosis impact gonadal function in men? The aim of this review is to provide an overview on the available literature data about the reproductive issues unique to men with multiple sclerosis, underlining the numerous areas where evidence is lacking and, therefore, the priorities for future research.

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and Objectives

It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19–related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population.

Methods

Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score > 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ² test, and the risk excess was quantified by risk ratios (RRs).

Results

The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p < 0.001), RR = 2.19 for ICU admission (p < 0.001), and RR = 2.43 for death (p < 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04).

Discussion

Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon.

The effect of air pollution on COVID-19 severity in a sample of patients with multiple sclerosis

Background and purpose

Some studies have shown that air pollution, often assessed by thin particulate matter with diameter below 2.5 µg/m³ (PM2.5), may contribute to severe COVID‐19 courses, as well as play a role in the onset and evolution of multiple sclerosis (MS). However, the impact of air pollution on COVID‐19 has never been explored specifically amongst patients with MS (PwMS). This retrospective observational study aims to explore associations between PM2.5 and COVID‐19 severity amongst PwMS.

Methods

Data were retrieved from an Italian web‐based platform (MuSC‐19) which includes PwMS with COVID‐19. PM2.5 2016–2018 average concentrations were provided by the Copernicus Atmospheric Monitoring Service. Italian patients inserted in the platform from 15 January 2020 to 9 April 2021 with a COVID‐19 positive test were included. Ordered logistic regression models were used to study associations between PM2.5 and COVID‐19 severity.

Results

In all, 1087 patients, of whom 13% required hospitalization and 2% were admitted to an intensive care unit or died, were included. Based on the multivariate analysis, higher concentrations of PM2.5 increased the risk of worse COVID‐19 course (odds ratio 1.90; p = 0.009).

Conclusions

Even if several other factors explain the unfavourable course of COVID‐19 in PwMS, the role of air pollutants must be considered and further investigated.

Cerebellar pathology and disability worsening in relapsing-remitting multiple sclerosis: A retrospective analysis from the CombiRx trial

BACKGROUND AND PURPOSE

Cerebellar damage is a valuable predictor of disability, particularly in progressive multiple sclerosis. It is not clear if it could be an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype.

AIM

We aimed to determine whether cerebellar damage is an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype.

METHODS

Cerebellar lesion loads and volumes were estimated using baseline magnetic resonance imaging from the CombiRx trial (n = 838). The relationship between cerebellar damage and time to disability worsening (confirmed disability progression [CDP], timed 25-foot walk test [T25FWT] score worsening, nine-hole peg test [9HPT] score worsening) was tested in stagewise and stepwise Cox proportional hazards models, accounting for demographics and supratentorial damage.

RESULTS

Shorter time to 9HPT score worsening was associated with higher baseline Expanded Disability Status Scale (EDSS) score (hazard ratio [HR] 1.408, p = 0.0042) and higher volume of supratentorial and cerebellar T2 lesions (HR 1.005 p = 0.0196 and HR 2.211, p = 0.0002, respectively). Shorter time to T25FWT score worsening was associated with higher baseline EDSS (HR 1.232, p = 0.0006). Shorter time to CDP was associated with older age (HR 1.026, p = 0.0010), lower baseline EDSS score (HR 0.428, p < 0.0001) and higher volume of supratentorial T2 lesions (HR 1.024, p < 0.0001).

CONCLUSION

Among the explored outcomes, single time-point evaluation of cerebellar damage only allows the prediction of manual dexterity worsening. In clinical studies the selection of imaging biomarkers should be informed by the outcome of interest.

Cardiorespiratory fitness and free-living physical activity are not associated with cognition in persons with progressive multiple sclerosis: Baseline analyses from the CogEx study

BACKGROUND

Aerobic exercise training (physical activity for improving cardiorespiratory fitness) represents a promising approach for managing cognitive impairment in multiple sclerosis (MS). However, there is limited evidence that levels of physical activity and fitness are associated with cognition in progressive MS.

OBJECTIVE

We examined associations among cardiorespiratory fitness, moderate-to-vigorous physical activity (MVPA), and cognitive performance in a large, international progressive MS sample.

METHODS

Two hundred forty European and North American persons with progressive MS underwent cardiorespiratory fitness measurement on a recumbent stepper, wore an ActiGraph GT3X + accelerometer for 7 days for measuring MVPA, and underwent the Brief International Cognitive Assessment in MS.

RESULTS

Cardiorespiratory fitness was not significantly correlated with Symbol Digit Modalities Test (SDMT; r = -0.01; r = -0.04), California Verbal Learning Test-II (CVLT-II; r = 0.05; r = 0.05), or Brief Visuospatial Memory Test-Revised (BVMT-R; r = -0.14; r = -0.14) z-scores controlling for age, sex, and education. MVPA and SDMT (r = 0.05), CVLT-II (r = -0.07), and BVMT-R (r = 0.01) z-scores were not significantly correlated.

CONCLUSION

Cardiorespiratory fitness and MVPA were not associated with cognition in this large progressive MS sample, yet these outcomes represent critical manipulation checks for documenting the success of the CogEx trial. This highlights the importance of examining other exercise-related mechanisms-of-action for improving cognition in progressive MS.

Predictors of Ocrelizumab Effectiveness in Patients with Multiple Sclerosis

Data regarding effectiveness and safety of ocrelizumab in the post-marking setting are lacking. The aim of our study was to provide effectiveness and safety data of ocrelizumab treatment in patients with relapsing-remitting (RR-) and progressive multiple sclerosis (PMS) and to evaluate clinical and immunological predictors of early treatment response. In this single-center prospective observational study, we investigated effectiveness outcomes (time-to-confirmed disability worsening, time-to-first relapse, time-to-first evidence of MRI activity and time-to-first evidence of disease activity), clinical and immunological predictors of early treatment response, and incidence of adverse events (AEs). One hundred and fifty-three subjects were included (93 RRMS; 84 females). Median follow-up was 1.9 (1.3-2.7). At 2-year follow-up (FU), disability worsening-free survival were 90.5%, 64.7%, and 68.8% for RRMS, primary-progressive MS (PPMS), and secondary-progressive MS (SPMS) patients, respectively. At 2-year FU, 67.1%, 72.7%, and 81.3% of patients with RRMS, PPMS, and SPMS were free of MRI activity, with NEDA-3 percentages of 62.1%, 54.6%, and 55.1%, respectively. Lower baseline EDSS was independently associated with a reduced risk of disability worsening (HR(95%CI) = 1.45(1.05-2.00), p = 0.024) and previous treatment exposure was independently associated with increased probability of radiological activity (HR = 2.53(1.05-6.10), p = 0.039). At 6-month FU, CD8 + cell decrease was less pronounced in patients with inflammatory activity (p = 0.022). Six patients (3.9%) discontinued ocrelizumab due to severe AEs. Our findings suggest that ocrelizumab is an effective treatment in real-world patients with RRMS and PMS, with a manageable safety profile. Better outcomes were observed in treatment-naïve patients and in patients with a low baseline disability level. Depletion of CD8 + cells could underlie early therapeutic effects of ocrelizumab.