Multiple Sclerosis Data Research Articles

A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis

BackgroundThere exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules.ResultWe assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omic integration of 20 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor-associated genes from several independent cohorts. Our benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS genes. The multi-omic case study using MS data revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module were differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10− 47) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS.ConclusionsWe believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omic approaches for complex diseases.

Improved particle swarm optimized deep convolutional neural network with super-pixel clustering for multiple sclerosis lesion segmentation in brain MRI imaging.

A central nervous system (CNS) disease affecting the insulating myelin sheaths around the brain axons is called multiple sclerosis (MS). In today's world, MS is extensively diagnosed and monitored using the MRI, because of the structural MRI sensitivity in dissemination of white matter lesions with respect to space and time. The main aim of this study is to propose Multiple Sclerosis Lesion Segmentation in Brain MRI imaging using Optimized Deep Convolutional Neural Network and Super-pixel Clustering. Three stages included in the proposed methodology are: (a) preprocessing, (b) segmentation of super-pixel, and (c) classification of super-pixel. In the first stage, image enhancement and skull stripping is done through performing a preprocessing step. In the second stage, the MS lesion and Non-MS lesion regions are segmented through applying SLICO algorithm over each slice of the volume. In the fourth stage, a CNN training and classification is performed using this segmented lesion and non-lesion regions. To handle this complex task, a newly developed Improved Particle Swarm Optimization (IPSO) based optimized convolutional neural network classifier is applied. On clinical MS data, the approach exhibits a significant increase in the accuracy segmenting of WM lesions when compared with the rest of evaluated methods.

Relevance of the Bulgarian SmartMS system to regional real-world data analysis in patients with multiple sclerosis

Background Multiple sclerosis (MS) is a chronic inflammatory and degenerative disease of the central nervous system, which affects 2.5 million people worldwide. In a 2019 survey of 19 European registers, the number of European patients with MS was estimated to be 500 000–700 000 (Glaser et al., 2019). In Bulgaria, about 7000 patients with the disease have been recorded. The national System for Monitoring, Aid, Registration and Therapy of Multiple Sclerosis (SmartMS; https://www.smartms.bg ) was introduced in 2016 as a web-based repository for providing structured information, sharing MS data features and providing better quality of care and collaborative research. Methods Permitted access to SmartMS professional register was used to analyze demographics, distribution, risk factors, disease progression and pharmacotherapy. We assessed the opportunity for digital improvement of patient–doctor communication by using SmartMS in daily clinical practice and scientific research. Results Since January 2018, when the Neurology Clinic of University Hospital “Dr. Georgi Stranski” – Pleven joined SmartMS, 88 patients with MS have been included in the regional register according to McDonald criteria. We analyzed the following characteristics: gender distribution (41/47 male/female); age (mean±standard deviation) 41.75±9.84 (40.65±8.2/42.7±11.06) years; time from disease onset (11.38±6.86 years); number of episodes (4.95±3.17); and number of drug therapies over time (1–4). Conclusion Our results are comparable to the disease-specific MS register statistics for the country. We consider SmartMS very useful for data tracking, monitoring and disease management. The analysis of disease-specific risk factors will be helpful in a next-step research on dietary recommendations for patients with MS.

Circulating Interleukins and Risk of Multiple Sclerosis: A Mendelian Randomization Study.

BackgroundPrevious research have implicated critical roles of systemic inflammation in the development of Multiple Sclerosis (MS). But the causal relationship between interleukins (ILs) and MS has not been fully elucidated.ObjectiveIn this study, we applied Mendelian randomization (MR) approaches to address the causal associations between genetically determined circulating levels of ILs and the risk of MS.MethodsGenetic instruments for circulating IL-1 receptor antagonist (IL-1Ra), IL-2 receptor α subunit (IL-2Rα), IL-6, IL-16, IL-17, and IL-18 were obtained from recently published genome-wide association studies (GWAS). Summary-level data for MS were obtained from the International Multiple Sclerosis Genetics Consortium. MR analyses were performed using the R software (version 3.6.1, The R Foundation) and the TwoSampleMR package.ResultsGenetic predisposition to higher circulating levels of IL-2Rα were significantly associated with MS risk. The odds ratio (OR) was 1.22 (95% confidence interval [CI], 1.12–1.32; p < 0.001) per one standard deviation increase in circulating IL-2Rα levels. There was a suggestive association of circulating IL-1Ra with MS risk (OR, 0.94; 95% CI, 0.88–0.99; p = 0.027). The other ILs were not associated with the outcome.ConclusionOur results indicated that circulating IL-2Rα was causally associated with risk of MS.

Treatment Switching and Discontinuation Over 20 Years in the Big Multiple Sclerosis Data Network.

Background: Although over a dozen disease modifying treatments (DMTs) are available for relapsing forms of multiple sclerosis (MS), treatment interruption, switching and discontinuation are common challenges. The objective of this study was to describe treatment interruption and discontinuation in the Big MS data network.Methods: We merged information on 269,822 treatment episodes in 110,326 patients from 1997 to 2016 from five clinical registries in this cohort study. Treatment stop was defined as a clinician recorded DMT end for any reason and included treatment interruptions, switching to alternate DMTs and long-term or permanent discontinuations.Results: The incidence of DMT stopping cross the full observation period was lowest in FTY (19.7 per 100 person-years (PY) of treatment; 95% CI 19.2–20.1), followed by NAT (22.6/100 PY; 95% CI 22.2–23.0), IFNβ (23.3/100 PY; 95% CI 23.2–23.5). Of the 184,013 observed DMT stops, 159,309 (86.6%) switched to an alternate DMT within 6 months. Reasons for stopping a drug were stable during the observation period with lack of efficacy being the most common reason followed by lack of tolerance and side effects. The proportion of patients continuing on most DMTs were similarly stable until 2014 and 2015 when drop from 83 to 75% was noted.Conclusions: DMT stopping reasons and rates were mostly stable over time with a slight increase in recent years, with the availability of more DMTs. The overall results suggest that discontinuation of MS DMTs is mostly due to DMT properties and to a lesser extent to risk management and a competitive market.

Characterisation of MS phenotypes across the age span using a novel data set integrating 34 clinical trials (NO.MS cohort): Age is a key contributor to presentation

Background: The Oxford Big Data Institute, multiple sclerosis (MS) physicians and Novartis aim to address unresolved questions in MS with a novel comprehensive clinical trial data set. Objective: The objective of this study is to describe the Novartis–Oxford MS (NO.MS) data set and to explore the relationships between age, disease activity and disease worsening across MS phenotypes. Methods: We report key characteristics of NO.MS. We modelled MS lesion formation, relapse frequency, brain volume change and disability worsening cross-sectionally, as a function of patients’ baseline age, using phase III study data (≈8000 patients). Results: NO.MS contains data of ≈35,000 patients (>200,000 brain images from ≈10,000 patients), with >10 years follow-up. (1) Focal disease activity is highest in paediatric patients and decreases with age, (2) brain volume loss is similar across age and phenotypes and (3) the youngest patients have the lowest likelihood (<25%) of disability worsening over 2 years while risk is higher (25%–75%) in older, disabled or progressive MS patients. Young patients benefit most from treatment. Conclusion: NO.MS will illuminate questions related to MS characterisation, progression and prognosis. Age modulates relapse frequency and, thus, the phenotypic presentation of MS. Disease worsening across all phenotypes is mediated by age and appears to some extent be independent from new focal inflammatory activity.

Standardization and digitization of clinical data in multiple sclerosis.

Standardization is necessary to ensure the reliability of clinical data and to enable longitudinal and cross-sectional comparisons of data obtained in different centres and countries. In patients with multiple sclerosis (MS), standardized clinical data are needed for monitoring of disability and for collecting real-world evidence for use in research. This Perspective describes attempts to improve the standardization and digitization of clinical data in MS, including digital electronic health recording systems and applications that attempt to offer a comprehensive assessment of patients' neurological deficits and their effects on daily life. Despite the challenges raised by regulatory, ethical and data-privacy considerations, the standardization and digitization of clinical data in MS is expected to generate new insights into the pathophysiology of the disease and to contribute to personalized patient care.

Relationships between accelerometer-measured and multiple sclerosis: a 2-sample Mendelian randomization study.

Observational studies suggest that physical activity (PA) can independently modify the risk of developing multiple sclerosis (MS). To investigate the causal effect of PA on MS by Mendelian randomization (MR) approaches. Through a genome-wide association study including 91,105 participants from UK Biobank, we obtained 5 single-nucleotide polymorphisms (SNPs) associated with accelerometer-measured PA (P < 5 × 10-8). Summary-level data for MS were obtained from a meta-analysis, incorporating 14,802 subjects with MS and 26,703 healthy controls of European ancestry. MR analyses were performed using the inverse-variance-weighted method, weighted median estimator, and MR-PRESSO method. Additional analyses were further performed using MR-Egger intercept and Cochran's Q statistic to verify the robustness of our findings. We failed to detect a causal effect of PA on MS (OR, 0.60; 95% confidence interval [CI], 0.30-1.20; P = 0.15) per in the random-effects IVW analysis. Additional MR methods yielded consistent results. MR-Egger regression suggested no evidence of horizontal pleiotropy (Intercept = 0.14, P = 0.21) and there seemed no substantial heterogeneity (I2 = 29.8%, P = 0.22) among individual SNPs. Our findings suggest that enhancing PA might not modify the risk of developing MS independent of established risk factors.

Association of the global distribution of multiple sclerosis with ultraviolet radiation and air pollution: an ecological study based on GBD data.

Given the growing global trend of multiple sclerosis (MS), this study was designed to evaluate environmental determinates of the worldwide distribution of MS in the presence of socioeconomic and geographic indices. MS data was obtained from the Institute for Health Metrics and Evaluation website. The air pollution parameters, including particles with aerodynamic diameter less than 2.5μm (PM2.5), tropospheric ozone, and solid fuel use, were acquired from global burden of disease resources and the World Health Organization. Ultraviolet index (UVI) values were obtained from the Tropospheric Emission Monitoring Internet Service website. Correlation and linear regression analyses were used to investigate the relationship between air pollution and environmental parameters with MS variables. The average prevalence and incidence rates in countries with high UVI were 5.17 and 0.25 per 100,000, respectively, and in countries with low UVI were 101.37 and 0.78, respectively. The results showed negative associations between prevalence, incidence and mortality of MS with ozone concentrations (β = - 1.04, - 0.04, and - 0.01 respectively; P < 0.01). Also, the fully adjusted model showed significant negative correlation of UVI with the MS variables in the presence of other variables (P < 0.01). Our findings demonstrated that UVI had the strongest significant inverse association with MS distribution. Consequently, vitamin D intake may be a major contributor to MS development. However, this study showed a slight influence of air pollution on the prevalence of MS in the presence of other parameters. Given the inconsistent results of previous studies, further studies may be required.

Subcutaneous cladribine to treat multiple sclerosis: experience in 208 patients.

Objective:To report on safety and effectiveness of subcutaneous cladribine (Litak®) in multiple sclerosis (MS) patients.Methods:Litak® was offered to MS-patients irrespective of disease course. Litak® 10 mg was administered for 3–4 days during week 1. Based on lymphocyte count at week 4, patients received another 0–3 doses at week 5. A second course was administered 11 months later. Follow-up included adverse events, relapses, expanded disability status scale (EDSS), 9-hole-peg and Timed-25-foot-walking tests, no-evidence-of-disease-activity (NEDA), no-evidence-of-progression-or-active-disease (NEPAD), MRI, cerebrospinal fluid (CSF) neurofilament light chain (NfL), and lymphocyte counts.Results:In all, 208 patients received at least one course of treatment. Age at baseline was 44 (17–72) years and EDSS 0–8.5. Cladribine was generally well tolerated. One myocardial infarction, one breast cancer, and three severe skin reactions occurred without long-term sequelae. Two patients died (one pneumonia, one encephalitis). Lymphopenia grade 3 occurred in 5% and grade 4 in 0.5%. In 94 out of 116 pwMS with baseline and follow-up (BaFU) data after two treatment courses, EDSS remained stable or improved. At 18 months, 64% of patients with relapsing MS and BaFU data (n = 39) had NEDA. At 19 months, 62% of patients with progressive MS and BaFU data (n = 13) had NEPAD. Of n = 13 patients whose CSF-NfL at baseline was elevated, 77% were normalised within 12 months.Conclusions:Litak® was well tolerated. Effectiveness in relapsing MS appeared similar to cladribine tablets and was encouraging in progressive MS. Our data suggest cladribine may be safe and effective in MS-patients irrespective of their disease stage.

LesionQuant for Assessment of MRI in Multiple Sclerosis-A Promising Supplement to the Visual Scan Inspection.

Background and Goals: Multiple sclerosis (MS) is a central nervous system inflammatory disease where magnetic resonance imaging (MRI) is an important tool for diagnosis and disease monitoring. Quantitative measurements of lesion volume, lesion count, distribution of lesions, and brain atrophy have a potentially significant value for evaluating disease progression. We hypothesize that utilizing software designed for evaluating MRI data in MS will provide more accurate and detailed analyses compared to the visual neuro-radiological evaluation.Methods: A group of 56 MS patients (mean age 35 years, 70% females and 96% relapsing-remitting MS) was examined with brain MRI one and 5 years after diagnosis. The T1 and FLAIR brain MRI sequences for all patients were analyzed using the LesionQuant (LQ) software. These data were compared with data from structured visual evaluations of the MRI scans performed by neuro-radiologists, including assessments of atrophy, and lesion count. The data from LQ were also compared with data from other validated research methods for brain segmentation, including assessments of whole brain volume and lesion volume. Correlations with clinical tests like the timed 25-foot walk test (T25FT) were performed to explore additional value of LQ analyses.Results: Lesion count assessments by LQ and by the neuro-radiologist were significantly correlated one year (cor = 0.92, p = 2.2 × 10−16) and 5 years (cor = 0.84, p = 2.7 × 10−16) after diagnosis. Analyzes of the intra- and interrater variability also correlated significantly (cor = 0.96, p < 0.001, cor = 0.97, p < 0.001). Significant positive correlation was found between lesion volume measured by LQ and by the software Cascade (cor = 0.7, p < 0.001. LQ detected a reduction in whole brain percentile >10 in 10 patients across the time-points, whereas the neuro-radiologist assessment identified six of these. The neuro-radiologist additionally identified five patients with increased atrophy in the follow-up period, all of them displayed decreasing low whole brain percentiles (median 11, range 8–28) in the LQ analysis. Significant positive correlation was identified between lesion volume measured by LQ and test performance on the T25FT both at 1 and 5 years after diagnosis.Conclusion: For the number of MS lesions at both time-points, we demonstrated strong correlations between the assessments done by LQ and the neuro-radiologist. Lesion volume evaluated with LQ correlated with T25FT performance. LQ-analyses classified more patients to have brain atrophy than the visual neuro-radiological evaluation. In conclusion, LQ seems like a promising supplement to the evaluation performed by neuro-radiologists, providing an automated tool for evaluating lesions in MS patients and also detecting early signs of atrophy in both a longitudinal and cross-sectional setting.

Associations of DMT Therapies with COVID-19 Severity in Multiple Sclerosis: An International Cohort Study

Associations of DMT Therapies with COVID-19 Severity in Multiple Sclerosis: An International Cohort Study

Italian multiple sclerosis register as the basis for post-authorization safety studies

Abstract While the safety and efficacy of Disease Modifying Therapy (DMT) in multiple sclerosis (MS) are assessed in clinical trials, these are of relatively short duration and always confined to highly selected patient groups. The evaluation of real-world data such as patient registries, is vital as it offers long-term data collection and is patient rather than product-focused during the lifetime of MS, and allows to document a patient's treatment history throughout the disease course. Patient registries can play an important role in monitoring the safety of drus. Regulators and the pharmaceutical industry have shown interest in complementing or even replacing phase 4 clinical studies with data from MS registries. The Italian MS Register (IMSR), in collaboration with the Big MS Data initiative, that also includes the national MS registries of Denmark, France, and Sweden and the international database network MSBase, came together with industry to conduct studies on post-authorization safety (PASS) and treatment effectiveness. The IMSR includes the clinical history of approximately 55,000 patients, or approximatively 45% of the estimated cases of MS in Italy. More than 10,000 patients have a follow-up duration of over 10 years. A Core Protocol outlining principles of PASS projects was created in which aggregated results made available to sponsors and health authorities. The Core Protocol specifies variables, emphasizes improved capture of adverse events, in particular cancer, non-melanoma skin cancers and immunosuppression-related infections, all MedDRA-coded. EUROCAT codes for pregnancy outcomes are also documented. Regulators, the pharmaceutical industry and national-level registries have jointly identified a format of collaboration on PASS for DMT in MS to benefit patients and the larger society. In this way, we hope to contribute to a framework that will include emerging and existing registries with the common goal of contributing to the advancement of knowledge in MS. Key messages The real-world data can contribute to understanding of the impact of disease-modifying therapy on long term. A format of collaboration among clinical research, regulators and pharmaceutical industry could be a winning framework to improve the knowledge on safety and treatment effectiveness in MS.

Coffee consumption is not associated with risk of multiple sclerosis: A Mendelian randomization study

Objective. Coffee consumption has been suggested to decrease the risk of multiple sclerosis (MS). In this study, we aim to investigate the causal effect of coffee consumption on risk of MS by Mendelian randomization (MR) approaches. Methods. Through a genome-wide association study including 375,833 participants from UK Biobank, we obtained single-nucleotide polymorphisms (SNPs) associated with habitual coffee consumption (P < 5 × 10−8). Summary-level data for MS were obtained from a meta-analysis, incorporating 14,802 subjects with MS and 26,703 healthy controls of European ancestry, which was conducted by the International Multiple Sclerosis Genetics Consortium. MR analyses were performed using inverse-variance-weighted method, weighted median estimator, and MR-Egger regression. Additional analyses were further performed using MR-Egger intercept and Cochran's Q statistic to verify the robustness of our findings. Results. Nine coffee-associated SNPs were selected as instrumental variables. We failed to detect a causal effect of coffee consumption on MS risk (odds ratio, 1,00; 95% confidence interval, 0.98-1.01; P = 0.48). In the main MR analysis. Consistent results were yielded in sensitivity analyses using the weighted median and MR-Egger methods, and no horizontal pleiotropy (P = 0.49) was identified. Conclusion. Our MR results indicated that coffee consumption might not be causally associated with risk of MS occurrence. Further well-designed genetic-epidemiological studies investigating the effect of coffee intake on the disease course, such as relapse and progression, are warranted.

Race, ethnicity, and cognition in persons newly diagnosed with multiple sclerosis.

To determine whether black or Hispanic patients with newly diagnosed multiple sclerosis (MS) are more likely to have cognitive impairment than white patients when compared to controls matched on age, sex, and race/ethnicity. Whether black or Hispanic patients have a more aggressive MS disease course than white patients remains unclear. No prior studies have examined differences in early cognitive impairment. The oral Symbol Digit Modalities Test (SDMT) is sensitive to early cognitive impairment in MS but normative data in nonwhite patients are limited. We studied 1,174 adults who enrolled in the MS Sunshine Study. SDMT and verbal fluency were measured in 554 incident cases of MS or clinically isolated syndrome (CIS) and 620 matched controls. Multivariable regression was used to examine correlates of abnormal SDMT in the entire cohort. The strongest independent predictors of lower oral SDMT scores in rank order were having MS/CIS, lower educational attainment, and being black or Hispanic. Black and Hispanic patients and controls had lower SDMT scores than white participants even after controlling for age, sex, and education. However, no interaction between race/ethnicity and MS case status on SDMT scores was detected. Easy-to-use reference scores stratified by age and educational attainment for black and Hispanic patients are provided. Persons with newly diagnosed MS/CIS are more likely to have subtly impaired cognitive function than controls regardless of race/ethnicity. Lower absolute SDMT scores among black and Hispanic patients compared to white patients highlight underlying US population differences rather than differences in MS disease severity.

Head-to-head drug comparisons in multiple sclerosis

Disease-modifying drugs are changing the natural history of multiple sclerosis (MS). However, currently available clinical trial data are insufficient to develop accurate personalized treatment algorithms to assign the best possible treatment to each person with MS according to disease features, treatment history, and comorbidities. Such accurate algorithms would require the presence of numerous head-to-head trials of long duration, which is virtually impossible, given the economic costs, required time, and difficulties with attrition. Thus, efforts are being made to compare relative treatment efficacy through observational designs, using large multicenter prospective cohorts or "big MS data," and network meta-analyses. Although such studies can yield useful information, they are liable to biases and their results should be confirmed in other study populations, including smaller, single-center cohorts, where some of these biases can be minimized. In this View article, we analyze the potential benefits and biases of all these strategies alternative to head-to-head trials in MS. Finally, we propose the combination of all these types of studies to obtain reliable head-to-head drug comparisons in the absence of randomized designs.

Association Between Serum Neurofilament Light Chain Levels and Long-term Disease Course Among Patients With Multiple Sclerosis Followed up for 12 Years

Blood sample-based biomarkers that are associated with clinically meaningful outcomes for patients with multiple sclerosis (MS) have not been developed. To evaluate the potential of serum neurofilament light chain (sNFL) measurements as a biomarker of disease activity and progression in a longitudinal MS data set. Single-center, ongoing, prospective observational cohort study of 607 patients with MS from the longitudinal EPIC (Expression, Proteomics, Imaging, Clinical) study at the University of California, San Francisco from July 1, 2004, through August 31, 2017. Clinical evaluations and sample collection were performed annually for 5 years, then at different time points for up to 12 years, with a median follow-up duration of 10 (interquartile range, 7-11) years. Serum NFL levels were measured using a sensitive single molecule array platform and compared with clinical and magnetic resonance imaging variables with the use of univariable and multivariable analyses. The main outcomes were disability progression defined as clinically significant worsening on the Expanded Disability Status Scale (EDSS) score and brain fraction atrophy. Mean (SD) age of the 607 study participants at study entry was 42.5 (9.8) years; 423 (69.7%) were women; and all participants were of non-Hispanic European descent. Of 3911 samples sequentially collected, 3904 passed quality control for quantification of sNFL. Baseline sNFL levels showed significant associations with EDSS score (β, 1.080; 95% CI, 1.047-1.114; P < .001), MS subtype (β, 1.478; 95% CI, 1.279-1.707; P < .001), and treatment status (β, 1.120; 95% CI, 1.007-1.245; P = .04). A significant interaction between EDSS worsening and change in levels of sNFL over time was found (β, 1.015; 95% CI, 1.007-1.023; P < .001). Baseline sNFL levels alone were associated with approximately 11.6% of the variance in brain fraction atrophy at year 10. In a multivariable analysis that considered sex, age, and disease duration, baseline sNFL levels were associated with 18.0% of the variance in brain fraction atrophy at year 10. After 5 years' follow-up, active treatment was associated with lower levels of sNFL, with high-potency treatments associated with the greater decreases in sNFL levels compared with platform therapies (high-potency vs untreated: β, 0.946; 95% CI, 0.915-0.976; P < .001; high-potency vs platform: β, 0.972; 95% CI, 0.948-0.998; P = .04). This study found that statistically significant associations of sNFL with relevant clinical and neuroimaging outcomes in MS were confirmed and extended, supporting the potential of sNFL as an objective surrogate of ongoing MS disease activity. In this data set of patients with MS who received early treatment, the prognostic power of sNFL for relapse activity and long-term disability progression was limited. Further prospective studies are necessary to assess the assay's utility for decision-making in individual patients.

Constrained Tensor Decomposition for Longitudinal Analysis of Diffusion Imaging Data

Analysis of complex data is still a challenge in medical image analysis. Due to the heterogeneous information that can be extracted from magnetic resonance imaging (MRI) it can be difficult to fuse such data in a proper way. One interesting case is given by the analysis of diffusion imaging (DI) data. DI techniques give an important variety of information about the status of microstructure in the brain. This is interesting information to use especially in longitudinal setting where the temporal evolution of the pathology is an important added value. In this paper, we propose a new tensor-based framework capable to detect longitudinal changes appearing in DI data in multiple sclerosis (MS) patients. We focus our attention to the analysis of longitudinal changes occurring along different white matter (WM) fiber-bundles. Our main goal is to detect which subset of fibers (within a bundle) and which sections of these fibers contain "pathological" longitudinal changes. The framework consists of three main parts: i) preprocessing of longitudinal diffusion acquisitions and WM fiber-bundles extraction, ii) data tensorization and rank selection, iii) application of a parallelized constrained tensor factorization algorithm to detect longitudinal "pathological" changes. The proposed method was applied on simulated longitudinal variations and on real MS data. High level of accuracy and precision were obtained in the detection of small longitudinal changes along the WM fiber-bundles.

Multiple sclerosis in Finland 2018—Data from the national register

Finland is a high-risk multiple sclerosis (MS) region, but a national MS register has not existed until 2014. In this paper, we present the Finnish MS register variables and data collected by 31 December 2018. Numbers and data counts of MS patients in the register (ICD-10 code G35) are presented. The disease types and proportion of patients receiving disease-modifying treatments (DMTs) were analysed in five hospital districts with most complete data sets. MS prevalence in Finland was estimated using administrative hospital discharge data as an additional resource. There were a total of 8722 MS patients in the Finnish MS register by 31 December 2018 (71.5% females). Mean age at MS diagnosis was 38.7years and peak prevalence was at age 50-54years. Disease course was relapsing remitting (RRMS) in 66.7%, secondary progressive (SPMS) in 13.5%, and primary progressive (PPMS) in 7.9% of the 5365 MS patients in the selected districts with most complete data. A total of 66.0% of RRMS patients, 19.6% of SPMS patients and 9.9% of PPMS patients were receiving DMTs. By combining MS register data with databases of those hospitals that had not joined the register, the nationwide prevalence estimate was between 10 and 11 thousand patients (corresponding to crude prevalence 180-200/100000). The Finnish MS register is currently used in 15/21 Finnish hospital districts. By register integration into the electronic patient files, the coverage of the register has increased to approximately 80% of the estimated Finnish MS population.

Multiple sclerosis: clinical trial design 2019.

Recent years have seen the approval of more than 15 disease-modifying drugs for multiple sclerosis (MS), mainly for its relapsing-remitting form (RRMS). The focus of the MS clinical trials is moving toward clinical trials aimed at progressive patients or based on putatively neuroprotective compounds. Here we reviewed the challenges of this paradigm shift. Progressive MS and neuroprotective drugs trials will both need a change in patients' enrollment criteria, outcome selection, and clinical trials design. Published ocrelizumab Primary Progressive MS data, as well as translational neuroimaging and clinical research suggest that MRI markers of inflammation could be used to enrich progressive MS trials population, albeit with the risk of overestimating the relevance of antiinflammatory therapeutic effects in this population and that conventional MRI-based metrics need to be complemented with volumetric and multiparametric approaches to disease severity quantification. Lastly, regarding statistical design, Bayesian approaches are at last making their way from oncology to neurology improving our ability to evaluate multiple treatments in the same trials' population. Adequate clinical trials design was one of the key factors in the RRMS treatment success story. Multidisciplinary collaborations are needed to adequately plan the progressive MS and restorative therapies trials that lay ahead in the near future.