Grey Matter Atrophy and its Relationship with White Matter Lesions in Patients with Myelin Oligodendrocyte Glycoprotein Antibody-associated Disease, Aquaporin-4 Antibody-Positive Neuromyelitis Optica Spectrum Disorder, and Multiple Sclerosis.

OBJECTIVE: To evaluate: (1) the distribution of gray matter (GM) atrophy in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4+NMOSD), and relapsing-remitting multiple sclerosis (RRMS); and (2) the relationship between GM volumes and white matter lesions in various brain regions within each disease. METHODS: A retrospective, multicenter analysis of magnetic resonance imaging data included patients with MOGAD/AQP4+NMOSD/RRMS in non-acute disease stage. Voxel-wise analyses and general linear models were used to evaluate the relevance of regional GM atrophy. For significant results (p < 0.05), volumes of atrophic areas are reported. RESULTS: We studied 135 MOGAD patients, 135 AQP4+NMOSD, 175 RRMS, and 144 healthy controls (HC). Compared with HC, MOGAD showed lower GM volumes in the temporal lobes, deep GM, insula, and cingulate cortex (75.79 cm3); AQP4+NMOSD in the occipital cortex (32.83 cm3); and RRMS diffusely in the GM (260.61 cm3). MOGAD showed more pronounced temporal cortex atrophy than RRMS (6.71 cm3), whereas AQP4+NMOSD displayed greater occipital cortex atrophy than RRMS (19.82 cm3). RRMS demonstrated more pronounced deep GM atrophy in comparison with MOGAD (27.90 cm3) and AQP4+NMOSD (47.04 cm3). In MOGAD, higher periventricular and cortical/juxtacortical lesions were linked to reduced temporal cortex, deep GM, and insula volumes. In RRMS, the diffuse GM atrophy was associated with lesions in all locations. AQP4+NMOSD showed no lesion/GM volume correlation. INTERPRETATION: GM atrophy is more widespread in RRMS compared with the other two conditions. MOGAD primarily affects the temporal cortex, whereas AQP4+NMOSD mainly involves the occipital cortex. In MOGAD and RRMS, lesion-related tract degeneration is associated with atrophy, but this link is absent in AQP4+NMOSD. ANN NEUROL 2024.

Prognostic value of single-subject grey matter networks in early multiple sclerosis.

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.

Myelin Oligodendrocyte Glycoprotein Antibodies in Adults with a First Demyelinating Event Suggestive of Multiple Sclerosis.

OBJECTIVE: Myelin oligodendrocyte glycoprotein antibodies (MOG-Ab) distinguish multiple sclerosis (MS) from MOG-associated disease in most cases. However, studies analyzing MOG-Ab at the time of a first demyelinating event suggestive of MS in adults are lacking. We aimed to (1) evaluate the prevalence of MOG-Ab in a first demyelinating event suggestive of MS and (2) compare clinical and paraclinical features between seropositive (MOG-Ab+) and seronegative (MOG-Ab-) patients. METHODS: Six hundred thirty adult patients with available serum samples obtained within 6 months from the first event were included. MOG-Ab were analyzed using a live cell-based assay. Statistical analyses included parametric and nonparametric tests, logistic regression, and survival models. RESULTS: MOG-Ab were positive in 17 of 630 (2.7%). Fourteen out of 17 (82.4%) MOG-Ab+ patients presented with optic neuritis (ON) compared to 227of 613 (37.0%) MOG-Ab- patients (p = 0.009). Cerebrospinal fluid-restricted oligoclonal bands (CSF-OBs) were found in 2 of 16 (12.5%) MOG-Ab+ versus 371 of 601 (61.7%) MOG-Ab- subjects (p < 0.001). Baseline brain magnetic resonance imaging (MRI) was normal in 9 of 17 (52.9%) MOG-Ab+ versus 153 of 585 (26.2%) MOG-Ab- patients (p = 0.029). Absence of CSF-OBs and ON at onset were independently associated with MOG-Ab positivity (odds ratio [OR] = 9.03, 95% confidence interval [CI] = 2.04-53.6, p = 0.009; and OR = 4.17, 95% CI = 1.15-19.8, p = 0.042, respectively). Of MOG-Ab+ patients, 22.9% (95% CI = 0.0-42.7) compared to 67.6% (95% CI = 63.3-71.3) of MOG-Ab- patients fulfilled McDonald 2017 criteria at 5 years (log-rank p = 0.003). INTERPRETATION: MOG-Ab are infrequent in adults with a first demyelinating event suggestive of MS. However, based on our results, we suggest to determine these antibodies in those patients with ON and absence of CSF-OBs, as long as the brain MRI is not suggestive of MS. ANN NEUROL 2023.

Serum biomarker levels predict disability progression in patients with primary progressive multiple sclerosis.

BACKGROUND: We aimed to investigate the potential of serum biomarker levels to predict disability progression in a multicentric real-world cohort of patients with primary progressive multiple sclerosis (PPMS). METHODS: A total of 141 patients with PPMS from 18 European MS centres were included. Disability progression was investigated using change in Expanded Disability Status Scale (EDSS) score over three time intervals: baseline to 2 years, 6 years and to the last follow-up. Serum levels of neurofilament light chain (sNfL), glial fibrillar acidic protein (sGFAP) and chitinase 3-like 1 (sCHI3L1) were measured using single-molecule array assays at baseline. Correlations between biomarker levels, and between biomarkers and age were quantified using Spearman's r. Univariable and multivariable linear models were performed to assess associations between biomarker levels and EDSS change over the different time periods. RESULTS: Median (IQR) age of patients was 52.9 (46.4-58.5) years, and 58 (41.1%) were men. Median follow-up time was 9.1 (7.0-12.6) years. Only 8 (5.7%) patients received treatment during follow-up. sNfL and sGFAP levels were moderately correlated (r=0.43) and both weakly correlated with sCHI3L1 levels (r=0.19 and r=0.17, respectively). In multivariable analyses, levels of the three biomarkers were associated with EDSS changes across all time periods. However, when analysis was restricted to non-inflammatory patients according to clinical and radiological parameters (n=64), only sCHI3L1 levels remained associated with future EDSS change. CONCLUSIONS: Levels of sNfL, sGFAP and sCHI3L1 are prognostic biomarkers associated with disability progression in patients with PPMS, being CHI3L1 findings less dependent on the inflammatory component associated with disease progression.

Optic nerve topography in multiple sclerosis diagnostic criteria: Existing knowledge and future directions.

Current diagnostic criteria for multiple sclerosis (MS) do not consider the optic nerve as a typical topography for establishing the diagnosis. Recent studies have proved the utility of optic nerve magnetic resonance imaging, optical coherence tomography and visual evoked potentials in detecting optic nerve lesions during the early stages of MS. In addition, emerging evidence supports the inclusion of optic nerve topography as a fifth region to fulfil the dissemination in space criteria. Anticipating a modification in the McDonald criteria, it is crucial for neurologists to familiarize with the diagnostic properties of each test in detecting optic nerve lesions and understand how to incorporate them into the MS diagnostic process. Therefore, the objective of this article is to review the existing evidence supporting the use of these tests in the diagnostic process of MS and provide a practical algorithm that can serve as a valuable guide for clinical practice.

T1/T2-weighted ratio: A feasible MRI biomarker in multiple sclerosis.

T1/T2-weighted ratio is a novel magnetic resonance imaging (MRI) biomarker based on conventional sequences, related to microstructural integrity and with increasing use in multiple sclerosis (MS) research. Different from other advanced MRI techniques, this method has the advantage of being based on routinely acquired MRI sequences, a feature that enables analysis of retrospective cohorts with considerable clinical value. This article provides an overview of this method, describing the previous cross-sectional and longitudinal findings in the main MS clinical phenotypes and in different brain tissues: focal white matter (WM) lesions, normal-appearing white matter (NAWM), cortical gray matter (GM), and deep normal-appearing gray matter (NAGM). We also discuss the clinical associations, possible reasons for conflicting results, correlations with other MRI-based measures, and histopathological associations. We highlight the limitations of the biomarker itself and the methodology of each study. Finally, we update the reader on its potential use as an imaging biomarker in research.

Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis.

Artificial intelligence (AI) is the branch of science aiming at creating algorithms able to carry out tasks that typically require human intelligence. In medicine, there has been a tremendous increase in AI applications thanks to increasingly powerful computers and the emergence of big data repositories. Multiple sclerosis (MS) is a chronic autoimmune condition affecting the central nervous system with a complex pathogenesis, a challenging diagnostic process strongly relying on magnetic resonance imaging (MRI) and a high and largely unexplained variability across patients. Therefore, AI applications in MS have the great potential of helping us better support the diagnosis, find markers for prognosis to eventually design more powerful randomised clinical trials and improve patient management in clinical practice and eventually understand the mechanisms of the disease. This topical review aims to summarise the recent advances in AI applied to MRI data in MS to illustrate its achievements, limitations and future directions.

Prediction of disease activity and treatment failure in relapsing-remitting MS patients initiating daily oral DMTs.

BACKGROUND: Limited data exist regarding treatment response prediction to oral disease-modifying therapies (DMTs) in multiple sclerosis (MS). OBJECTIVES: We assessed the capacity of available scoring systems to anticipate disease activity parameters in naïve relapsing-remitting MS (RRMS) patients initiating daily oral DMTs, hypothesizing that they exhibit different predictive potentials. METHODS: We conducted a retrospective study and applied the Rio Score (RS), modified Rio Score (mRS), and MAGNIMS Score 12 months after DMT initiation. At 36 months, we examined their ability to predict evidence of disease activity (EDA) components and treatment failure by logistic regression analysis. RESULTS: Notably, 218 patients (62.4% females) initiating dimethyl fumarate, teriflunomide, and fingolimod were included. At 36 months, the RS high-risk group predicted evidence of clinical activity (odds ratio (OR) 10 [2.7-36.9]) and treatment failure (OR 10.6 [3.4-32.5]) but did not predict radiological activity (OR 1.9 [0.7-5]). The mRS non-responders group did not predict EDA and treatment failure. RS, mRS, and MAGNIMS 0 categories showed significantly lower EDA and treatment failure than the remainder. CONCLUSION: Scoring systems present different predictive abilities for disease activity parameters at 36 months in MS patients initiating daily oral therapies, warranting further adjustments (i.e. introduction of fluid biomarkers) to depict disease activity status fully.

Clinical and MRI measures to identify non-acute MOG-antibody disease in adults.

MRI and clinical features of myelin oligodendrocyte glycoprotein (MOG)-antibody disease may overlap with those of other inflammatory demyelinating conditions posing diagnostic challenges, especially in non-acute phases and when serologic testing for MOG antibodies is unavailable or shows uncertain results. We aimed to identify MRI and clinical markers that differentiate non-acute MOG-antibody disease from aquaporin 4 (AQP4)-antibody neuromyelitis optica spectrum disorder and relapsing remitting multiple sclerosis, guiding in the identification of patients with MOG-antibody disease in clinical practice. In this cross-sectional retrospective study, data from 16 MAGNIMS centres were included. Data collection and analyses were conducted from 2019 to 2021. Inclusion criteria were: diagnosis of MOG-antibody disease; AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis; brain and cord MRI at least 6 months from relapse; and Expanded Disability Status Scale (EDSS) score on the day of MRI. Brain white matter T2 lesions, T1-hypointense lesions, cortical and cord lesions were identified. Random forest models were constructed to classify patients as MOG-antibody disease/AQP4-neuromyelitis optica spectrum disorder/multiple sclerosis; a leave one out cross-validation procedure assessed the performance of the models. Based on the best discriminators between diseases, we proposed a guide to target investigations for MOG-antibody disease. One hundred and sixty-two patients with MOG-antibody disease [99 females, mean age: 41 (±14) years, median EDSS: 2 (0-7.5)], 162 with AQP4-neuromyelitis optica spectrum disorder [132 females, mean age: 51 (±14) years, median EDSS: 3.5 (0-8)], 189 with multiple sclerosis (132 females, mean age: 40 (±10) years, median EDSS: 2 (0-8)] and 152 healthy controls (91 females) were studied. In young patients (<34 years), with low disability (EDSS < 3), the absence of Dawson's fingers, temporal lobe lesions and longitudinally extensive lesions in the cervical cord pointed towards a diagnosis of MOG-antibody disease instead of the other two diseases (accuracy: 76%, sensitivity: 81%, specificity: 84%, P < 0.001). In these non-acute patients, the number of brain lesions < 6 predicted MOG-antibody disease versus multiple sclerosis (accuracy: 83%, sensitivity: 82%, specificity: 83%, P < 0.001). An EDSS < 3 and the absence of longitudinally extensive lesions in the cervical cord predicted MOG-antibody disease versus AQP4-neuromyelitis optica spectrum disorder (accuracy: 76%, sensitivity: 89%, specificity: 62%, P < 0.001). A workflow with sequential tests and supporting features is proposed to guide better identification of patients with MOG-antibody disease. Adult patients with non-acute MOG-antibody disease showed distinctive clinical and MRI features when compared to AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis. A careful inspection of the morphology of brain and cord lesions together with clinical information can guide further analyses towards the diagnosis of MOG-antibody disease in clinical practice.

Using The Virtual Brain to study the relationship between structural and functional connectivity in patients with multiple sclerosis: a multicenter study.

The relationship between structural connectivity (SC) and functional connectivity (FC) captured from magnetic resonance imaging, as well as its interaction with disability and cognitive impairment, is not well understood in people with multiple sclerosis (pwMS). The Virtual Brain (TVB) is an open-source brain simulator for creating personalized brain models using SC and FC. The aim of this study was to explore SC-FC relationship in MS using TVB. Two different model regimes have been studied: stable and oscillatory, with the latter including conduction delays in the brain. The models were applied to 513 pwMS and 208 healthy controls (HC) from 7 different centers. Models were analyzed using structural damage, global diffusion properties, clinical disability, cognitive scores, and graph-derived metrics from both simulated and empirical FC. For the stable model, higher SC-FC coupling was associated with pwMS with low Single Digit Modalities Test (SDMT) score (F=3.48, P$\lt$0.05), suggesting that cognitive impairment in pwMS is associated with a higher SC-FC coupling. Differences in entropy of the simulated FC between HC, high and low SDMT groups (F=31.57, P$\lt$1e-5), show that the model captures subtle differences not detected in the empirical FC, suggesting the existence of compensatory and maladaptive mechanisms between SC and FC in MS.

Spinal cord reserve in multiple sclerosis.

BACKGROUND: The spinal cord (SC) is a preferential target of multiple sclerosis (MS) damage highly relevant towards disability. Differential impact of such damage could be due to the initial amount of SC tissue, as described for the brain parenchyma (brain reserve concept). We aimed to test the existence of SC reserve by using spinal canal area (SCaA) as a proxy. METHODS: Brain sagittal three-dimensional T1-weighted scans covering down to C5 level were acquired in 2930 people with MS and 43 healthy controls (HCs) in a cross-sectional, multicentre study. SC area (SCA) and SCaA were obtained with the Spinal Cord Toolbox. Demographical data and patient-derived disability scores were obtained. SC parameters were compared between groups with age-adjusted and sex-adjusted linear regression models. The main outcome of the study, the existence of an association between SCaA and Patient Determined Disease Steps, was tested with scaled linear models. RESULTS: 1747 persons with MS (mean age: 46.35 years; 73.2% female) and 42 HCs (mean age: 45.56 years; 78.6% female) were analysed after exclusion of post-processing errors and application of quality criteria. SCA (60.41 mm2 vs 65.02 mm2, p<0.001) was lower in people with MS compared with HC; no differences in SCaA were observed (213.24 mm2 vs 212.61 mm2, p=0.125). Adjusted scaled linear models showed that a larger SCaA was significantly associated with lower scores on Patient Determined Disease Steps (beta coefficient: -0.12, p=0.0124) independently of spinal cord atrophy, brain T2 lesion volume, age and sex. CONCLUSIONS: A larger SCaA may be protective against disability in MS, possibly supporting the existence of SC reserve.

Spinal cord lesions and brain grey matter atrophy independently predict clinical worsening in definite multiple sclerosis: a 5-year, multicentre study.

OBJECTIVES: To evaluate the combined contribution of brain and cervical cord damage in predicting 5-year clinical worsening in a multicentre cohort of definite multiple sclerosis (MS) patients. METHODS: Baseline 3.0T brain and cervical cord T2-weighted and three-dimensional T1-weighted MRI was acquired in 367 patients with MS (326 relapse-onset and 41 progressive-onset) and 179 healthy controls. Expanded Disability Status Scale (EDSS) score was obtained at baseline and after a median follow-up of 5.1 years (IQR=4.8-5.2). At follow-up, patients were classified as clinically stable/worsened according to EDSS changes. Generalised linear mixed models identified predictors of clinical worsening, evolution to secondary progressive (SP) MS and reaching EDSS=3.0, 4.0 and 6.0 milestones at 5 years. RESULTS: At follow-up, 120/367 (33%) patients with MS worsened clinically; 36/256 (14%) patients with relapsing-remitting evolved to SPMS. Baseline predictors of EDSS worsening were progressive-onset versus relapse-onset MS (standardised beta (ß)=0.97), higher EDSS (ß=0.41), higher cord lesion number (ß=0.41), lower normalised cortical volume (ß=-0.15) and lower cord area (ß=-0.28) (C-index=0.81). Older age (ß=0.86), higher EDSS (ß=1.40) and cord lesion number (ß=0.87) independently predicted SPMS conversion (C-index=0.91). Predictors of reaching EDSS=3.0 after 5 years were higher baseline EDSS (ß=1.49), cord lesion number (ß=1.02) and lower normalised cortical volume (ß=-0.56) (C-index=0.88). Baseline age (ß=0.30), higher EDSS (ß=2.03), higher cord lesion number (ß=0.66) and lower cord area (ß=-0.41) predicted EDSS=4.0 (C-index=0.92). Finally, higher baseline EDSS (ß=1.87) and cord lesion number (ß=0.54) predicted EDSS=6.0 (C-index=0.91). CONCLUSIONS: Spinal cord damage and, to a lesser extent, cortical volume loss helped predicting worse 5-year clinical outcomes in MS.

Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes.

BACKGROUND: We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes. METHODS: Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups. RESULTS: Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes. CONCLUSIONS: In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor.

Global and Regional Deep Learning Models for Multiple Sclerosis Stratification From MRI.

BACKGROUND: The combination of anatomical MRI and deep learning-based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. However, studies assessing the effect of different input strategies on model's performance are lacking. PURPOSE: To compare whole-brain input sampling strategies and regional/specific-tissue strategies, which focus on a priori known relevant areas for disability accrual, to stratify MS patients based on their disability level. STUDY TYPE: Retrospective. SUBJECTS: Three hundred nineteen MS patients (382 brain MRI scans) with clinical assessment of disability level performed within the following 6 months (~70% training/~15% validation/~15% inference in-house dataset) and 440 MS patients from multiple centers (independent external validation cohort). FIELD STRENGTH/SEQUENCE: Single vendor 1.5 T or 3.0 T. Magnetization-Prepared Rapid Gradient-Echo and Fluid-Attenuated Inversion Recovery sequences. ASSESSMENT: A 7-fold patient cross validation strategy was used to train a 3D-CNN to classify patients into two groups, Expanded Disability Status Scale score (EDSS) ≥ 3.0 or EDSS < 3.0. Two strategies were investigated: 1) a global approach, taking the whole brain volume as input and 2) regional approaches using five different regions-of-interest: white matter, gray matter, subcortical gray matter, ventricles, and brainstem structures. The performance of the models was assessed in the in-house and the independent external cohorts. STATISTICAL TESTS: Balanced accuracy, sensitivity, specificity, area under receiver operating characteristic (ROC) curve (AUC). RESULTS: With the in-house dataset, the gray matter regional model showed the highest stratification accuracy (81%), followed by the global approach (79%). In the external dataset, without any further retraining, an accuracy of 72% was achieved for the white matter model and 71% for the global approach. DATA CONCLUSION: The global approach offered the best trade-off between internal performance and external validation to stratify MS patients based on accumulated disability. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Relationship between paramagnetic rim lesions and slowly expanding lesions in multiple sclerosis.

BACKGROUND: Magnetic resonance imaging (MRI) markers for chronic active lesions in MS include slowly expanding lesions (SELs) and paramagnetic rim lesions (PRLs). OBJECTIVES: To identify the relationship between SELs and PRLs in MS, and their association with disability. METHODS: 61 people with MS (pwMS) followed retrospectively with MRI including baseline susceptibility-weighted imaging, and longitudinal T1 and T2-weighted scans. SELs were computed using deformation field maps; PRLs were visually identified. Mixed-effects models assessed differences in Expanded Disability Status Scale (EDSS) score changes between the group defined by the presence of SELs and or PRLs. RESULTS: The median follow-up time was 3.2 years. At baseline, out of 1492 lesions, 616 were classified as SELs, and 80 as PRLs. 92% of patients had ⩾ 1 SEL, 56% had ⩾ 1 PRL, while both were found in 51%. SELs compared to non-SELs were more likely to also be PRLs (7% vs. 4%, p = 0.027). PRL counts positively correlated with SEL counts (ρ= 0.28, p = 0.03). SEL + PRL + patients had greater increases in EDSS over time (beta = 0.15/year, 95% confidence interval (0.04, 0.27), p = 0.009) than SEL+PRL-patients. CONCLUSION: SELs are more numerous than PRLs in pwMS. Compared with either SELs or PRLs found in isolation, their joint occurrence was associated with greater clinical progression.

A single-dose strategy for immunization with live attenuated vaccines is an effective option before treatment initiation in multiple sclerosis patients.

BACKGROUND: Mumps-Measles-Rubella (MMR) and Varicella zoster vaccines (VAR) are live attenuated vaccines, usually administered in a two-dose scheme at least 4 weeks apart. However, single-dose immunization schemes may also be effective and can reduce delays in immunosuppressive treatment initiation in patients with multiple sclerosis (pwMS) who need to be immunized. OBJECTIVES: To evaluate the immunogenicity of a single-dose attempt (SDA) versus the standard immunization scheme (SIS) with VAR and/or MMR in pwMS. METHODS: Retrospective observational study in pwMS vaccinated against VAR and/or MMR. We compared seroprotection rates and antibody geometric mean titers (GMTs) between the two strategies. RESULTS: Ninety-six patients were included. Thirty-one patients received VAR and 67 MMR. In the SDA group, the seroprotection rate was 66.7% (95% confidence interval (CI): 53.3-78.3) versus 97.2% (95% CI: 85.5-99.9) in the SIS (p < 0.001). For the seroprotected patients, GMTs were similar for both schemes. CONCLUSION: An SDA of VAR and/or MMR vaccines could be sufficient to protect almost two-thirds of patients. Testing immunogenicity after a single dose of VZ and/or MMR could be included in routine clinical practice to achieve rapid immunization.

The kappa free light chain index and oligoclonal bands have a similar role in the McDonald criteria.

Intrathecal production of kappa free light chains occurs in multiple sclerosis and can be measured using the kappa free light chain index. Kappa free light chain index values can be determined more easily than oligoclonal bands detection and seem more sensitive than the immunoglobulin (Ig)G index to diagnose multiple sclerosis. We assessed the value of oligoclonal bands, kappa free light chain index cut-offs 5.9, 6.6 and 10.61, and IgG index to diagnose multiple sclerosis with prospectively acquired data from a clinically isolated syndrome inception cohort. We selected patients with sufficient data to determine oligoclonal bands positivity, MRI dissemination in space and time, IgG index and sufficient quantities of paired CSF and blood samples to determine kappa free light chain indexes (n = 214). We used Kendall's Tau coefficient to estimate concordance, calculated the number of additional diagnoses when adding each positive index to dissemination in space and positive oligoclonal bands, performed survival analyses for oligoclonal bands and each index with the outcomes second attack and 2017 MRI dissemination in space and time and estimated the diagnostic properties of oligoclonal bands and the different indexes for the previously mentioned outcomes at 5 years. Oligoclonal bands were positive in 138 patients (64.5%), kappa free light chain-5.9 in 136 (63.6%), kappa free light chain-6.6 in 135 (63.1%), kappa free light chain-10.61 in 126 (58.9%) and IgG index in 101 (47.2%). The highest concordance was between oligoclonal bands and kappa free light chain-6.6 (τ = 0.727) followed by oligoclonal bands and kappa free light chain-5.9 (τ = 0.716). Combining dissemination in space plus oligoclonal bands or kappa free light chain-5.9 increased the number of diagnosed patients by 11 (5.1%), with kappa free light chain-6.6 by 10 (4.7%), with kappa free light chain-10.61 by 9 (4.2%) and with IgG index by 3 (1.4%). Patients with positive oligoclonal bands or indexes reached second attack and MRI dissemination in space and time faster than patients with negative results (P < 0.0001 except IgG index in second attack: P = 0.016). In multivariable Cox models [adjusted hazard ratio (95% confidence interval)], the risk for second attack was very similar between kappa free light chain-5.9 [2.0 (0.9-4.3), P = 0.068] and kappa free light chain-6.6 [2.1 (1.1-4.2), P = 0.035]. The highest risk for MRI dissemination in space and time was demonstrated with kappa free light chain-5.9 [4.9 (2.5-9.6), P < 0.0001], followed by kappa free light chain-6.6 [3.4 (1.9-6.3), P < 0.0001]. Kappa free light chains-5.9 and -6.6 had a slightly higher diagnostic accuracy than oligoclonal bands for second attack (70.5, 71.1 and 67.8) and MRI dissemination in space and time (85.7, 85.1 and 81.0). Kappa free light chain indexes 5.9 and 6.6 performed slightly better than oligoclonal bands to assess multiple sclerosis risk and in terms of diagnostic accuracy. Given the concordance between oligoclonal bands and these indexes, we suggest using dissemination in space plus positive oligoclonal bands or positive kappa free light chain index as a modified criterion to diagnose multiple sclerosis.

Serum neurofilament light chain levels predict long-term disability progression in patients with progressive multiple sclerosis.

ObjectiveThere is a lack of sensitive and specific biomarkers for use in progressive multiple sclerosis (MS). The study aimed to assess the potential of serum neurofilament light chain (sNfL) levels as biomarker of disability progression in patients with progressive MS. METHODS: We performed a prospective observational cohort study in 51 patients with progressive MS who participated in a 2-year phase II single-centre, randomised, double-blind, placebo-controlled trial of interferon-beta. Mean (SD) follow-up duration was 13.9 (6.2) years. Levels of sNfL were measured using a single molecule array immunoassay at baseline, 1, 2 and 6 years. Univariable and multivariable analyses were carried out to evaluate associations between sNfL levels and disability progression at short term (2 years), medium term (6 years) and long term (at the time of the last follow-up). RESULTS: A sNfL cut-off value of 10.2 pg/mL at baseline discriminated between long-term progressors and non-progressors with a 75% sensitivity and 67% specificity (adjusted OR 7.8; 95% CI 1.8 to 46.4; p=0.01). Similar performance to discriminate between long-term progressors and non-progressors was observed using age/body mass index-adjusted sNfL Z-scores derived from a normative database of healthy controls. A cut-off increase of 5.1 pg/mL in sNfL levels between baseline and 6 years also discriminated between long-term progressors and non-progressors with a 71% sensitivity and 86% specificity (adjusted OR 49.4; 95% CI 4.4 to 2×103; p=0.008). CONCLUSIONS: sNfL can be considered a prognostic biomarker of future long-term disability progression in patients with progressive MS. These data expand the little knowledge existing on the role of sNfL as long-term prognostic biomarker in patients with progressive MS.

Exploring in vivo multiple sclerosis brain microstructural damage through T1w/T2w ratio: a multicentre study.

OBJECTIVES: To evaluate white matter and grey matter T1-weighted (w)/T2w ratio (T1w/T2w ratio) in healthy controls and patients with multiple sclerosis, and its association with clinical disability. METHODS: In this cross-sectional study, 270 healthy controls and 434 patients with multiple sclerosis were retrospectively selected from 7 European sites. T1w/T2w ratio was obtained from brain T2w and T1w scans after intensity calibration using eyes and temporal muscle. RESULTS: In healthy controls, T1w/T2w ratio increased until 50-60 years both in white and grey matter. Compared with healthy controls, T1w/T2w ratio was significantly lower in white matter lesions of all multiple sclerosis phenotypes, and in normal-appearing white matter and cortex of patients with relapsing-remitting and secondary progressive multiple sclerosis (p≤0.026), but it was significantly higher in the striatum and pallidum of patients with relapsing-remitting, secondary progressive and primary progressive multiple sclerosis (p≤0.042). In relapse-onset multiple sclerosis, T1w/T2w ratio was significantly lower in white matter lesions and normal-appearing white matter already at Expanded Disability Status Scale (EDSS) <3.0 and in the cortex only for EDSS ≥3.0 (p≤0.023). Conversely, T1w/T2w ratio was significantly higher in the striatum and pallidum for EDSS ≥4.0 (p≤0.005). In primary progressive multiple sclerosis, striatum and pallidum showed significantly higher T1w/T2w ratio beyond EDSS=6.0 (p≤0.001). In multiple sclerosis, longer disease duration, higher EDSS, higher brain lesional volume and lower normalised brain volume were associated with lower lesional and cortical T1w/T2w ratio and a higher T1w/T2w ratio in the striatum and pallidum (ß from -1.168 to 0.286, p≤0.040). CONCLUSIONS: T1w/T2w ratio may represent a clinically relevant marker sensitive to demyelination, neurodegeneration and iron accumulation occurring at the different multiple sclerosis phases.

CSF chitinase 3-like 1 is associated with iron rims in patients with a first demyelinating event.

BACKGROUND: Chronic active lesions with iron rims have prognostic implications in patients with multiple sclerosis. OBJECTIVE: To assess the relationship between iron rims and levels of chitinase 3-like 1 (CHI3L1), neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in patients with a first demyelinating event. METHODS: Iron rims were identified using 3T susceptibility-weighted imaging. Serum NfL and GFAP levels were measured by single-molecule array assays. CSF (cerebrospinal fluid) CHI3L1 levels were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: Sixty-one patients were included in the study. The presence of iron rims was associated with higher T2 lesion volume and higher number of gadolinium-enhancing lesions. In univariable analysis, having ⩾2 iron rims (vs 0) was associated with increased CSF CHI3L1 levels (ß = 1.41; 95% confidence interval (CI) = 1.10-1.79; p < 0.01) and serum NfL levels (ß = 2.30; 95% CI = 1.47-3.60; p < 0.01). In multivariable analysis, however, only CSF CHI3L1 levels remained significantly associated with the presence of iron rim lesions (ß = 1.45; 95% CI = 1.11-1.90; p < 0.01). The presence of ⩾2 iron rims was not associated with increased serum GFAP levels in univariable or multivariable analyses. CONCLUSION: These findings support an important contribution of activated microglia/macrophages to the pathophysiology of chronic active lesions with iron rims in patients with a first demyelinating event.