Progressive Multiple Sclerosis Research Articles

A glia-enriched stem cell 3D model of the human brain mimics the glial-immune neurodegenerative phenotypes of multiple sclerosis

The role of central nervous system (CNS) glia in sustaining self-autonomous inflammation and driving clinical progression in multiple sclerosis (MS) is gaining scientific interest. We applied a single transcription factor (SOX10)-based protocol to accelerate oligodendrocyte differentiation from human induced pluripotent stem cell (hiPSC)-derived neural precursor cells, generating self-organizing forebrain organoids. These organoids include neurons, astrocytes, oligodendroglia, and hiPSC-derived microglia to achieve immunocompetence. Over 8weeks, organoids reproducibly generated mature CNS cell types, exhibiting single-cell transcriptional profiles similar to the adult human brain. Exposed to inflamed cerebrospinal fluid (CSF) from patients with MS, organoids properly mimic macroglia-microglia neurodegenerative phenotypes and intercellular communication seen in chronic active MS. Oligodendrocyte vulnerability emerged by day 6 post-MS-CSF exposure, with nearly 50% reduction. Temporally resolved organoid data support and expand on the role of soluble CSF mediators in sustaining downstream events leading to oligodendrocyte death and inflammatory neurodegeneration. Such findings support the implementation of this organoid model for drug screening to halt inflammatory neurodegeneration.

Multiple sclerosis: the NLRP3 inflammasome, gasdermin D, and therapeutics.

Multiple sclerosis (MS) stands as a chronic inflammatory disease characterized by its neurodegenerative impacts on the central nervous system. The complexity of MS and the significant challenges it poses to patients have made the exploration of effective treatments a crucial area of research. Among the various mechanisms under investigation, the role of inflammation in MS progression is of particular interest. Inflammatory responses within the body are regulated by various cellular mechanisms, one of which involves the nucleotide-binding oligomerization domain (NOD)-, leucine-rich repeat (LRR)-, and pyrin domains (PYD)-containing protein 3 (NLRP3). NLRP3 acts as a sensor within cells, playing a pivotal role in controlling the inflammatory response. Its activation is a critical step leading to the assembly of the NLRP3 inflammasome complex, a process that has profound implications for inflammatory diseases like MS. The NLRP3 inflammasome's activation is intricately linked to the subsequent activation of caspase 1 and gasdermin D (GsdmD), signaling pathways that are central to the inflammatory process. GsdmD, a prominent member of the Gasdermin protein family, is particularly noteworthy for its role in pyroptotic cell death, a form of programmed cell death that is distinct from apoptosis and is characterized by its inflammatory nature. This pathway's activation contributes significantly to the pathology of MS by exacerbating inflammatory responses within the nervous system. Given the detrimental effects of unregulated inflammation in MS, therapeutics targeting these inflammatory processes offer a promising avenue for alleviating the symptoms experienced by patients. This review delves into the intricacies of the pyroptotic pathways, highlighting how the formation of the NLRP3 inflammasome induces such pathways and the potential intervention points for therapeutic agents. By inhibiting key steps within these pathways, it is possible to mitigate the inflammatory response, thereby offering relief to those suffering from MS. Understanding these mechanisms not only sheds light on the pathophysiology of MS but also paves the way for the development of novel therapeutic strategies aimed at controlling the disease's progression through the modulation of the body's inflammatory response.

Radiomics nomograms based on multi-sequence MRI for identifying cognitive impairment and predicting cognitive progression in relapsing-remitting multiple sclerosis

Rationale and ObjectivesTo build radiomics nomograms based on multi-sequence MRI to facilitate the identification of cognitive impairment (CI) and prediction of cognitive progression (CP) in patients with relapsing-remitting multiple sclerosis (RRMS). Materials and MethodsWe retrospectively included two RRMS cohorts with multi-sequence MRI and Symbol Digit Modalities Test (SDMT) data: dataset1 (n=149, for training and validation) and dataset2 (n=29, for external validation). 80 patients of dataset1 had a 2-year follow-up SDMT. CI and CP were evaluated using SDMT scores at baseline and follow-up. The included DIR sequence aided in identifying cortical lesions. Lesion radiomics and structural features were extracted and selected from multi-sequence MRI, followed by the computation of radiomics and structural scores. The nomogram was developed through multivariate logistic regression, integrating clinical data, radiomics and structural scores to identify CI in patients. Moreover, a similar method was employed to further construct a nomogram predicting CP in patients. ResultsThe nomogram demonstrated superior performance in identifying patients with CI, with area under the curve (AUC) values of 0.937 (95% Conf. Interval: 0.898-0.975) and 0.876 (0.810-0.943) in internal and external validation sets, compared to models solely based on clinical data, lesion radiomics, and structural features. Furthermore, another nomogram constructed in predicting CP also exhibited outstanding performance, with an AUC value of 0.969 (0.875-1.000) in the validation set. ConclusionThese nomograms, integrating clinical data, multi-sequence lesions radiomics and structural features, enable more effective identification of CI and early prediction of CP in RRMS patients, providing important support for clinical decision-making.

Investigation of the Relationship Between Heavy Metals (Cadmium, Arsenic, and Lead) and Metallothionein in Multiple Sclerosis.

Multiple sclerosis (MS) is one of the most common neurological disorders. Metals are important for the maintenance and preservation of homeostasis and dysregulated metal homeostasis has an impact on neurodegeneration. Environmental factors are considered to contribute to MS risk and progression. Heavy metals such as arsenic (As), cadmium (Cd), and lead (Pb) are widely found in the environment and because of their toxic nature, they pose a great danger to human health. Metallothioneins (MTs) play important roles in metal homeostasis and detoxification of heavy metals. The aim of this study was to investigate the relationship between levels of heavy metals (As, Cd, and Pb) andMT levels in MS patients and also to assess the oxidative stress status of patients. Fifty subjects (20 healthy subjects and 30 MS patients) were included. Demographic characteristics of the patients, plasma MT levels, blood Cd, As, and Pb levels, as well as iron (Fe), copper (Cu), and zinc (Zn) levels, were determined. Malondialdehyde (MDA) levels were investigated as a marker of oxidative stress. MT levels were slightly higher in the MS group (p > 0.05). As Cd and Pb levels were significantly higher in the control subjects. MDA levels were significantly higher in MS patients. Our results support the relevance of MT and MDA levels in MS. Further clinical studies with larger cohorts will provide more insights into these factors.

Creating an automated tool for a consistent and repeatable evaluation of disability progression in clinical studies for multiple sclerosis

Background: The lack of standardized disability progression evaluation in multiple sclerosis (MS) hinders reproducibility of clinical study results, due to heterogeneous and poorly reported criteria. Objective: To demonstrate the impact of using different parameters when evaluating MS progression, and to introduce an automated tool for reproducible outcome computation. Methods: Re-analyzing BRAVO clinical trial data (NCT00605215), we examined the fluctuations in computed treatment effect on confirmed disability progression (CDP) and progression independent of relapse activity (PIRA) when varying different parameters. These analyses were conducted using the msprog package for R, which we developed as a tool for CDP assessment from longitudinal data, given a set of criteria that can be specified by the user. Results: The BRAVO study reported a hazard ratio (HR) of 0.69 (95% confidence interval (CI): 0.46–1.02) for CDP. Using the different parameter configurations, the resulting treatment effect on CDP varied considerably, with HRs ranging from 0.59 (95% CI: 0.41–0.86) to 0.72 (95% CI: 0.48–1.07). The treatment effect on PIRA varied from an HR = 0.62 (95% CI: 0.41–0.93) to an HR = 0.65 (95% CI: 0.40–1.04). Conclusions: The adoption of an open-access tool validated by the research community, with clear parameter specification and standardized output, could greatly reduce heterogeneity in CDP estimation and promote repeatability of study results.

A Literature Review and Meta-Analysis on the Potential Use of miR-150 as a Novel Biomarker in the Detection and Progression of Multiple Sclerosis.

MicroRNA-150 (miR-150) plays a critical role in immune regulation and has been implicated in autoimmune diseases like Multiple Sclerosis (MS). This review aims to evaluate miR-150's potential as a biomarker for MS, necessitating this review to consolidate current evidence and highlight miR-150's utility in improving diagnostic accuracy and monitoring disease progression. A comprehensive literature search was conducted in databases like PubMed, Scopus, Google Scholar, SciSpace, MDPI and Web of Science, adhering to PRISMA guidelines. Studies focusing on miR-150 implications in MS were included. Data extraction was conducted, while quality assessment was done using the NOS and AMSTAR 2 tools. With the extracted data a statistical analyses conducted. 10 eligible articles were included in review. Findings show that miR-150 levels were consistently deregulated in MS patients compared to healthy controls, correlating with disease severity and clinical parameters such as (EDSS) scores and disease activity. Additionally, miR-150 is implicated in the inflammatory pathogenesis of MS, affecting immune cell regulation and inflammatory pathways. MiR-150 is a promising biomarker for MS, showing significant potential for improving diagnostic accuracy and monitoring disease progression. Its consistent deregulation in MS patients and correlation with clinical parameters underscore its clinical utility. Further research should validate miR-150's salivary presence and its possible usage as a novel biomarker and therapeutic potential in the development of MS.

Siponimod following Alemtuzumab in secondary progressive MS: investigating sequential therapy–A case series

Alemtuzumab, a humanized anti‐CD52 monoclonal antibody, is approved for treatment of highly active relapsing multiple sclerosis (MS) but requires vigilant post-treatment monitoring due to associated risks. The prescription of subsequent therapies following Alemtuzumab, as mandated by label guidance for a treatment-free period of at least 5 years, presents a complex challenge, particularly if there is concurrent conversion to secondary progressive disease course.We described a case-series of five patients starting therapy with Siponimod and followed up for 12 months period converted to secondary progressive MS previously exposed to Alemtuzumab. All patients received Siponimod 2 mg. Clinical evaluation measured with Expanded Disability Status Scale and cognitive evaluation measured with Brief International Cognitive Assessment for Multiple Sclerosis were stable after 12 months on therapy. No severe lymphopenia was recorded, nor serious adverse events.In conclusion, the long-term management of patients treated with Alemtuzumab transitioning to secondary progressive MS requires a proactive and multidisciplinary approach.By addressing the challenges associated with treatment limitations and short-term monitoring recommendations while considering alternative therapeutic options like Siponimod, clinicians can optimize outcomes and ensure continuity of care for individuals with MS.

A genetic-epigenetic interplay at 1q21.1 locus underlies CHD1L-mediated vulnerability to primary progressive multiple sclerosis

Multiple Sclerosis (MS) is a heterogeneous inflammatory and neurodegenerative disease with an unpredictable course towards progressive disability. Treating progressive MS is challenging due to limited insights into the underlying mechanisms. We examined the molecular changes associated with primary progressive MS (PPMS) using a cross-tissue (blood and post-mortem brain) and multilayered data (genetic, epigenetic, transcriptomic) from independent cohorts. In PPMS, we found hypermethylation of the 1q21.1 locus, controlled by PPMS-specific genetic variations and influencing the expression of proximal genes (CHD1L, PRKAB2) in the brain. Evidence from reporter assay and CRISPR/dCas9 experiments supports a causal link between methylation and expression and correlation network analysis further implicates these genes in PPMS brain processes. Knock-down of CHD1L in human iPSC-derived neurons and knock-out of chd1l in zebrafish led to developmental and functional deficits of neurons. Thus, several lines of evidence suggest a distinct genetic-epigenetic-transcriptional interplay in the 1q21.1 locus potentially contributing to PPMS pathogenesis.

Disease-modifying therapies, outcomes, risk factors and severity of COVID-19 in multiple sclerosis: A MENACTRIMS registry based study

BackgroundThere is a lack information regarding risk factors associated with worse COVID-19 outcomes in patients with multiple sclerosis (MS) in the MENA region. MethodsThis is a multicenter, retrospective cohort study that included all MS patients with a suspected or confirmed COVID-19 infection using the MENACTRIMS registry. The association of demographics, disease characteristics, and use of disease-modifying therapies (DMTs) with outcomes and severity of COVID-19 were evaluated by multivariate logistic model. ResultsA total of 600 MS patients with confirmed (n = 542) or highly suspected (n = 58) COVID-19 were analyzed. Seventy-three patients (12.2 %) had a COVID-19 severity score of ≥3 on a 7-point ordinal scale (ranging from 1 [not hospitalized with no limitations on activities] to 7 [death] with a cutoff at 3 [hospitalized and not requiring supplemental oxygen]), and 15 patients (2.5 %) died. Out of 73 patients with a severity score ≥3, 90.4 % were on DMTs; 50.6 % of them were on anti-CD20, including ocrelizumab and rituximab. Multivariate logistic regression showed that older age (odds ratio per 10 years, 1.4 [95 %CI, 1.0–1.8]), disability (OR for EDSS 3.0–5.5, 2.9 [95 %CI. 1.5–5.7], OR for EDSS ≥6.0, 2.3 [95 %CI. 1.0–5.1]), obesity (OR, 3.0 [95 %CI, 1.5–6.0]), and treatment with rituximab (OR, 9.0 [95 %CI, 3.1–25.3]) or off-label immunosuppressive medications (OR, 5.6 [95 %CI. 1.1–27.8]) were risk factors for moderate or severe COVID-19. ConclusionIn this registry-based study of MS patients, age, sex, EDSS, obesity, progressive MS were risk factors for severe COVID-19. Moreover, there was an association found between exposure to anti-CD20 DMTs and COVID-19 severity.

Analyzing the impact of pulse steroid therapy on relapse rates and disease progression in relapsing-remitting multiple sclerosis: a comprehensive retrospective study

Background and Objective: Relapsing remitting MS (RRMS) is characterized by recurrent relapses with remissions. Over an extended time-frame, high-dose steroid administration has primarily centered on the treatment of acute relapses, rather than relapse prevention. The objective of this retrospective study is to assess the long-term impact of administering three monthly pulse steroid therapy for three days on relapse rates and the Expanded Disability Status Scale (EDSS) scores in patients with RRMS. Methods: This study was conducted at Neurology ward of Chandka Medical College Hospital in Larkana from January 2021 to January 2023. A retrospective analysis of historical patient data, focusing on individuals with RRMS who received three monthly pulse steroid therapy over a specified period. Data was collected through patient records, including details of treatment, relapse history, and EDSS scores. Results: Thirty MS patients including 25 females and five males received one gram methylprednisolone intravenously every three months for three days. The mean age range was 18-50 years. Among them, three experienced no relapses, 11 had one relapse, 13 encountered two relapses, and three had three relapses over next consecutive two years. The severity of relapses varied, with 20 classified as moderate and seven as severe. A reduction in relapse rates and notable improvements in EDSS scores were observed. Conclusion: The initial findings from this retrospective analysis suggest that three monthly pulse steroid therapy is associated with positive outcomes in RRMS patients. These results support the need for further investigation into the potential benefits of continuous steroid therapy in managing RRMS.

Arm Swing Movements during Walking as an Early Predictor of Multiple Sclerosis Progression

Persons with Multiple Sclerosis (pwMS) are at a high risk of falling, with abnormal gait pattern. The upper limbs play an important role in postural control and gait stability. The presence of arm swing changes during walking in pwMS, especially in the early period, may be an indicator of balance problems. The current study aimed to assess arm swing during walking in early MS. A total of 18 pwMS were evaluated in two time points. The first time was after their first (stable) diagnosis (pre-evaluation) and the second time was 3 months after the pre-evaluation. In addition, 10 healthy controls were evaluated once. Arm swing analysis during walking, using video recording, was applied to both groups. Additionally, the MS group performed the Two-Minute Walk Test, Timed Up and Go, and Timed 25-Foot Walk Test. The pwMS showed similar joint angles at both the first and second evaluations. Only the elbow ROM value on the least affected side was lower in pwMS than healthy controls at the second evaluation (p = 0.027). The early MS patients showed altered arm swing pattern. As walking speed and mobility scores did not change over time, the decrease in elbow amplitude over a 3-month period indicates that the arm swing may present a pattern resulting from MS-specific disorders rather than being a compensatory mechanism in walking. From the earliest stages of the disease, variations in arm swing movements during walking may be considered as a disease progression-predictor for MS.

Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center study.

Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking. Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS. Machine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history. Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study.

Best practice exercise for emerging depression in multiple sclerosis: A systematic review and meta-analysis

Objective To examine the effects of instructor-led exercise on depression symptoms in adults with multiple sclerosis, with a focus on moderating factors to treatment response. Data sources Cochrane Library, Embase, PEDro, PsycINFO and PubMed databases were searched until 21 April 2024. Review methods The reporting quality of included studies assessed (PEDro and TESTEX scales). Hedges’ g effect sizes were calculated and pooled using random and mixed-effects modelling. Results Twenty-two independent studies (k), representing 785 participants with relapsing remitting or progressive MS, were included. Individual studies varied in their reporting quality (PEDro range: 3–8) and did not routinely detail exercise parameters (TESTEX range: 5–13). Nonetheless, exercise reduced core symptoms of depression (gw = .52, CI: .30–.73, P < .01). Treatment effects were, however, not maintained once training had ceased (gw = −.53, CI: −.80 to .24, P ≤ .01, k = 5). Both aerobic and non-aerobic exercise groups experienced a significant (P < .01) reduction in depression scores. Larger gains were noted by those with better ambulation at baseline (P = .03). Conclusion Regular exercise can help to stabilise mood for people living with multiple sclerosis, regardless of session frequency or duration. Treatment efficacy could be maximised by addressing potential barriers for those with limited mobility, including exercise type, delivery and intensity. Protocol registered on Open Science Framework [https://osf.io/zfymq/].

Beneficial therapeutic plasma exchange response in the treatment of severe relapses in patients with multiple sclerosis.

Therapeutic plasma exchange (PLEX) is effective as a second-line treatment of severe relapses of multiple sclerosis (MS) that failed to respond to standard steroid therapy. Our objective was to evaluate the effectiveness of PLEX in the severe MS relapses in a cohort of patients treated at Neurology Clinic, University Clinical Centre of Serbia, Belgrade, from 2007 until 2020. This retrospective study comprised 107 MS patients with 127 severe relapses treated with PLEX. Majority of our patients suffered from relapsing remitting MS (83.2%), 12.1% had secondary progressive MS and 4.7% had primary progressive MS. Mean age was 39.2 years (range, 19-79 years), female/male ratio 2.3:1. Pulse corticosteroid treatment was used before PLEX in 99.3% of patients. Median EDSS score at nadire during relapse was 6.0 (range 2.0-10.0). After PLEX, 73.8% relapses showed a marked clinical improvement, 7.1% showed mild improvement and in 19.0% there was no improvement. Median EDSS at discharge was 4.0 (6.0 at nadir of relapse vs. 4.0 at discharge; p<0.0001) and it was sustained at the same level, 6 month after PLEX. Multivariate regression analysis showed that higher EDSS at nadir during relapse (OR=0.63, 95% CI 0.41-0.96, p=0.039) and older age (OR=1.07, 95% CI 1.02- 1.12, p=0.010) were significantly associated with poor treatment response after 6- month follow-up. Adverse events occurred in 17.3 of procedures and they were completely resolved. Our study in a large cohort of MS patients confirmed that PLEX is effective.

Circulating MAIT cells in multiple sclerosis and amyotrophic lateral sclerosis.

Neurological disorders, including multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS), may be associated with alterations in blood cell composition and phenotype. Here, we focused our attention on circulating mucosal-associated invariant T (MAIT) cells, a CD8+ T cell memory population expressing the invariant Vα7.2 region in the T cell receptor and high surface levels of the CD161 marker. Transcriptomics data relative to peripheral blood mononuclear cells (PBMC) highlighted downregulation of CD161 and other MAIT-associated markers in progressive MS and not relapsing remitting (RR)-MS when gene expressions relative to each disease course were compared to those from healthy controls. Multiparametric flow cytometry of freshly isolated PBMC samples from untreated RR-MS, primary or secondary progressive MS (PP- or SP-MS), ALS and age- and sex-matched healthy controls revealed specific loss of circulating CD8+ MAIT cells in PP-MS and no other MS courses or another neurological disorder such as ALS. Overall, these observations point to the existence of immunological changes in blood specific for the primary progressive course of MS that may support clinical definition of disease.

The evolving contribution of MRI measures towards the prediction of secondary progressive multiple sclerosis

BackgroundIn multiple sclerosis (MS), both lesion accrual and brain atrophy predict clinical outcomes. However, it is unclear whether these prognostic features are equally relevant throughout the course of MS. Among...

Investigating cortical hypoxia in multiple sclerosis via time-domain near-infrared spectroscopy.

Hypoperfusion and tissue hypoxia have been implicated as contributory mechanisms in the neuropathology of multiple sclerosis (MS). Our objective has been to study cortical oxygenation in vivo in patients with MS and age-matched controls. A custom, multiwavelength time-domain near-infrared spectroscopy system was developed for assessing tissue hypoxia from the prefrontal cortex. A cross-sectional case-control study was undertaken assessing patients with secondary progressive MS (SPMS) and age-matched controls. Co-registered magnetic resonance imaging was used to verify the location from which near-infrared spectroscopy data were obtained through Monte Carlo simulations of photon propagation. Additional clinical assessments of MS disease severity were carried out by trained neurologists. Linear mixed effect models were used to compare cortical oxygenation between cases and controls, and against measures of MS severity. Thirty-three patients with secondary progressive MS (median expanded disability status scale 6 [IQR: 5-6.5]; median age 53.0 [IQR: 49-58]) and 20 age-matched controls were recruited. Modeling of photon propagation confirmed spectroscopy data were obtained from the prefrontal cortex. Patients with SPMS had significantly lower cortical hemoglobin oxygenation compared with controls (-6.0% [95% CI: -10.0 to -1.9], P = 0.004). There were no significant associations between cortical oxygenation and MS severity. Using an advanced, multiwavelength time-domain near-infrared spectroscopy system, we demonstrate that patients with SPMS have lower cortical oxygenation compared with controls.

Ocrelizumab in people with primary progressive multiple sclerosis: A real-world multicentric study

BackgroundOcrelizumab is the only disease-modifying therapy (DMT) approved for the treatment of people with primary progressive multiple sclerosis (pwPPMS). ObjectivesTo provide real-world evidence of ocrelizumab effectiveness and safety in pwPPMS in Croatian MS centers. MethodsA retrospective observational multi-center study of pwPPMS who were started on ocrelizumab in 7 MS centers in Croatia. ResultsWe identified 230 pwPPMS of whom 176 fulfilled the inclusion criteria. The median follow-up of the cohort was 2.73 (0.51–5.77) years. During the follow-up, 50 (28.4%) pwPPMS experienced confirmed disability worsening (CDW) and 19 (10.8%) stopped treatment with ocrelizumab. Baseline EDSS >5 was a statistically significant positive predictor for the development of CDW and/or stop of the treatment due to any cause (OR 2.482, 95% C.I. 1.192–5.166, p = 0.015). However, there was no significant difference in the development of CDW and/or stop of the treatment due to any cause if stratifying the patients based on active PPMS, age at treatment start (≤55 years vs >55 years), disease duration at treatment start (≤10 years vs >10 years), or EDSS at treatment start (≤5.0 vs >5.0). During the follow-up, 26 (14.8%) pwPPMS experienced infusion reactions, 64 (36.4%) had an infection and 4 (2.3%) developed a tumor. The percentage of pwPPMS with low levels of IgG was persistently above 10% and with low levels of IgM was persistently above 20% after cycle 4. ConclusionOur real-world data support the use of ocrelizumab in a much broader pwPPMS population than in the original randomized controlled trial.

Explainable machine learning on baseline MRI predicts multiple sclerosis trajectory descriptors.

Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges in timely diagnosis and personalized patient management. The application of Artificial Intelligence (AI) to MS holds promises for early detection, accurate diagnosis, and predictive modeling. The objectives of this study are: 1) to propose new MS trajectory descriptors that could be employed in Machine Learning (ML) regressors and classifiers to predict patient evolution; 2) to explore the contribution of ML models in discerning MS trajectory descriptors using only baseline Magnetic Resonance Imaging (MRI) studies. This study involved 446 MS patients who had a baseline MRI, at least two measurements of Expanded Disability Status Scale (EDSS), and a 1-year follow-up. Patients were divided into two groups: 1) for model development and 2) for evaluation. Three descriptors: β1, β2, and EDSS(t), were related to baseline MRI parameters using regression and classification XGBoost models. Shapley Additive Explanations (SHAP) analysis enhanced model transparency by identifying influential features. The results of this study demonstrate the potential of AI in predicting MS progression using the proposed patient trajectories and baseline MRI scans, outperforming classic Multiple Linear Regression (MLR) methods. In conclusion, MS trajectory descriptors are crucial; incorporating AI analysis into MRI assessments presents promising opportunities to advance predictive capabilities. SHAP analysis enhances model interpretation, revealing feature importance for clinical decisions.

Effectiveness of autologous haematopoietic stem cell transplantation versus natalizumab in progressive multiple sclerosis

BackgroundNatalizumab was not shown to modify disability in progressive multiple sclerosis (MS). This matched observational study compared the effectiveness of autologous haematopoietic stem cell transplantation (AHSCT) with natalizumab in progressive...