Multiple sclerosis (MS) is a progressive demyelinating and degenerative disease of the central nervous system with symptoms depending on the disease type and the site of lesions and is featured by ...heterogeneity of clinical expressions and responses to treatment strategies. An individualized clinical follow-up and multidisciplinary treatment is required. Transforming the population-based management of today into an individualized, personalized and precision-level management is a major goal in research. Indeed, a complex and unique interplay between genetic background and environmental exposure in each case likely determines clinical heterogeneity. To reach insights at the individual level, extensive amount of data are required. Many databases have been developed over the last few decades, but access to them is limited, and data are acquired in different ways and differences in definitions and indexing and software platforms preclude direct integration. Most existing (inter)national registers and IT platforms are strictly observational or focus on disease epidemiology or access to new disease modifying drugs. Here, a method to revolutionize management of MS to a personalized, individualized and precision level is outlined. The key to achieve this next level is FAIR data.
Multiple sclerosis (MS) is the leading cause of chronic neurological disability in young adults. The clinical disease course of MS varies greatly between individuals, with some patients progressing ...much more rapidly than others, making prognosis almost impossible. We previously discovered that cytotoxic CD4+ T cells (CD4+ CTL), identified by the loss of CD28, are able to migrate to sites of inflammation and that they contribute to tissue damage. Furthermore, in an animal model for MS, we showed that these cells are correlated with inflammation, demyelination, and disability. Therefore, we hypothesize that CD4+ CTL drive progression of MS and have prognostic value. To support this hypothesis, we investigated whether CD4+ CTL are correlated with worse clinical outcome and evaluated the prognostic value of these cells in MS. To this end, the percentage of CD4+CD28null T cells was measured in the blood of 176 patients with relapsing-remitting MS (=baseline). Multimodal evoked potentials (EP) combining information on motoric, visual, and somatosensoric EP, as well as Kurtzke expanded disability status scale (EDSS) were used as outcome measurements at baseline and after 3 and 5 years. The baseline CD4+CD28null T cell percentage is associated with EP (
= 0.003,
= 0.28), indicating a link between these cells and disease severity. In addition, the baseline CD4+CD28null T cell percentage has a prognostic value since it is associated with EP after 3 years (
= 0.005,
= 0.29) and with EP and EDSS after 5 years (
= 0.008,
= 0.42 and
= 0.003,
= 0.27). To the best of our knowledge, this study provides the first direct link between the presence of CD4+ CTL and MS disease severity, as well as its prognostic value. Therefore, we further elaborate on two important research perspectives: 1° investigating strategies to block or reverse pathways in the formation of these cells resulting in new treatments that slow down MS disease progression, 2° including immunophenotyping in prediction modeling studies to aim for personalized medicine.
Evoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a ...few variables from the EPs, which are often further condensed into a single variable: the EP score. We perform a machine learning analysis of motor EP that uses the whole time series, instead of a few variables, to predict disability progression after two years. Obtaining realistic performance estimates of this task has been difficult because of small data set sizes. We recently extracted a dataset of EPs from the Rehabiliation & MS Center in Overpelt, Belgium. Our data set is large enough to obtain, for the first time, a performance estimate on an independent test set containing different patients.
We extracted a large number of time series features from the motor EPs with the highly comparative time series analysis software package. Mutual information with the target and the Boruta method are used to find features which contain information not included in the features studied in the literature. We use random forests (RF) and logistic regression (LR) classifiers to predict disability progression after two years. Statistical significance of the performance increase when adding extra features is checked.
Including extra time series features in motor EPs leads to a statistically significant improvement compared to using only the known features, although the effect is limited in magnitude (ΔAUC = 0.02 for RF and ΔAUC = 0.05 for LR). RF with extra time series features obtains the best performance (AUC = 0.75±0.07 (mean and standard deviation)), which is good considering the limited number of biomarkers in the model. RF (a nonlinear classifier) outperforms LR (a linear classifier).
Using machine learning methods on EPs shows promising predictive performance. Using additional EP time series features beyond those already in use leads to a modest increase in performance. Larger datasets, preferably multi-center, are needed for further research. Given a large enough dataset, these models may be used to support clinicians in their decision making process regarding future treatment.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cytotoxic CD4+ T cells (CD4 CTL) are terminally differentiated T helper cells that contribute to autoimmune diseases, such as multiple sclerosis. We developed a novel triple co-culture transwell ...assay to study mutual interactions between CD4 CTL, conventional TH cells, and regulatory T cells (Tregs) simultaneously. We show that, while CD4 CTL are resistant to suppression by Tregs in vitro, the conditioned medium of CD4 CTL accentuates the suppressive phenotype of Tregs by upregulating IL-10, Granzyme B, CTLA-4, and PD-1. We demonstrate that CD4 CTL conditioned medium skews memory TH cells to a TH17 phenotype, suggesting that the CD4 CTL induce bystander polarization. In our triple co-culture assay, the CD4 CTL secretome promotes the proliferation of TH cells, even in the presence of Tregs. However, when cell−cell contact is established between CD4 CTL and TH cells, the proliferation of TH cells is no longer increased and Treg-mediated suppression is restored. Taken together, our results suggest that when TH cells acquire cytotoxic properties, these Treg-resistant CD4 CTL affect the proliferation and phenotype of conventional TH cells in their vicinity. By creating such a pro-inflammatory microenvironment, CD4 CTL may favor their own persistence and expansion, and that of other potentially pathogenic TH cells, thereby contributing to pathogenic responses in autoimmune disorders.
Cytomegalovirus (CMV) is a latent virus which causes chronic activation of the immune system. Here, we demonstrate that cytotoxic and pro-inflammatory CD4
CD28
T cells are only present in CMV ...seropositive donors and that CMV-specific Immunoglobulin (Ig) G titers correlate with the percentage of these cells. In vitro stimulation of peripheral blood mononuclear cells with CMVpp65 peptide resulted in the expansion of pre-existing CD4
CD28
T cells. In vivo, we observed de novo formation, as well as expansion of CD4
CD28
T cells in two different chronic inflammation models, namely the murine CMV (MCMV) model and the experimental autoimmune encephalomyelitis (EAE) model for multiple sclerosis (MS). In EAE, the percentage of peripheral CD4
CD28
T cells correlated with disease severity. Pre-exposure to MCMV further aggravated EAE symptoms, which was paralleled by peripheral expansion of CD4
CD28
T cells, increased splenocyte MOG reactivity and higher levels of spinal cord demyelination. Cytotoxic CD4
T cells were identified in demyelinated spinal cord regions, suggesting that peripherally expanded CD4
CD28
T cells migrate towards the central nervous system to inflict damage. Taken together, we demonstrate that CMV drives the expansion of CD4
CD28
T cells, thereby boosting the activation of disease-specific CD4
T cells and aggravating autoimmune mediated inflammation and demyelination.
Multiple Sclerosis (MS) is an inflammatory autoimmune disease of the central nervous system, causing increased vulnerability to infections and disability among young adults. Ever since the outbreak ...of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infections, there have been concerns among people with MS (PwMS) about the potential interactions between various disease-modifying therapies and COVID-19. The COVID-19 in MS Global Data Sharing Initiative (GDSI) was initiated in 2020 with the aim of addressing these concerns. This paper focuses on the anonymisation and publicly releasing of a GDSI sub-dataset, comprising data entered by PwMS and clinicians using a fast data entry tool. The dataset includes information on demographics, comorbidities and hospital stay and COVID-19 symptoms of PwMS. The dataset can be used to perform different statistical analyses to improve our understanding of COVID-19 in MS. Furthermore, this dataset can also be used within the context of educational activities to educate different stakeholders on the complex data science topics that were used within the GDSI.
•Cladribine tablets are an immune-reconstitution therapy for relapsing MS (RMS).•Belgian, single-center, retrospective cohort of 84 cladribine-treated RMS patients.•72.6% of included patients ...retained NEDA-3 at mean follow-up (22.6 months).•More events in year 1 for patients with ≥2 prior DMTs and switching from FNG.•Valuable real-world insights that might inform treatment decisions.
Cladribine tablets are a highly effective immune reconstitution therapy licensed for treating relapsing multiple sclerosis (RMS) in Europe since 2017. Currently, there is a high demand for real-world data from different clinical settings on the effectiveness and safety profile of cladribine in MS.
Within this report, we retrospectively evaluated the outcomes of RMS patients who received cladribine between August 2018 and November 2021 at our Belgian institute. Patients with data for three effectiveness endpoints, more specifically, relapses, MRI observations, and confirmed disability worsening were incorporated into the analysis of 'no evidence of disease activity' (NEDA-3) re-baselined at 3 months. Safety endpoints included lymphopenia, liver transaminases, and adverse events (AEs) during follow-up. Descriptive statistics and time-to-event analysis were performed, including subgroup analysis by pre-treatment.
Of the 84 RMS patients included in this study (age 42 33–50, 64.3% female, diagnosis duration 6 2–11 years, baseline EDSS 2.5 1.5–3.6), 14 (16.7%) patients experienced relapses, while disability progression and brain MRI activity occurred in 8.5% (6/71) and 6.3% (5/79). This resulted in 72.6% (n = 69, standard error 6%) retaining NEDA-3 status at the mean follow-up time of 22.6 ± 11.5 months. During the first year after cladribine initiation, disease activity prevailed more in patients with ≥2 prior DMTs and those switching from fingolimod, although both trends were not statistically significant. In terms of safety, 67.9% reported at least one AE during follow-up, the most frequent being fatigue (64.9%) and skin-related problems (38.6%).
Overall, our research results confirm cladribine's safety and effectiveness among RMS patients in real-world conditions. After the re-baseline, we observed high rates of NEDA-3-retention, and no new safety signals were noted.
Multiple sclerosis (MS) is a chronic disease affecting millions of people worldwide. Through the demyelinating and axonal pathology of MS, the signal conduction in the central nervous system is ...affected. Evoked potential measurements allow clinicians to monitor this process and can be used for decision support. We share a dataset that contains motor evoked potential (MEP) measurements, in which the brain is stimulated and the resulting signal is measured in the hands and feet. This results in time series of 100 milliseconds long. Typically, both hands and feet are measured in one hospital visit. The dataset contains 5586 visits of 963 patients, performed in day-to-day clinical care over a period of 6 years. The dataset consists of approximately 100,000 MEP. Clinical metadata such as the expanded disability status scale, sex, and age is also available. This dataset can be used to explore the role of evoked potentials in MS research and patient care. It may also be used as a benchmark for time series analysis and predictive modelling.
Background:
As of September 2022, there was no globally recommended set of core data elements for use in multiple sclerosis (MS) healthcare and research. As a result, data harmonisation across ...observational data sources and scientific collaboration is limited.
Objectives:
To define and agree upon a core dataset for real-world data (RWD) in MS from observational registries and cohorts.
Methods:
A three-phase process approach was conducted combining a landscaping exercise with dedicated discussions within a global multi-stakeholder task force consisting of 20 experts in the field of MS and its RWD to define the Core Dataset.
Results:
A core dataset for MS consisting of 44 variables in eight categories was translated into a data dictionary that has been published and disseminated for emerging and existing registries and cohorts to use. Categories include variables on demographics and comorbidities (patient-specific data), disease history, disease status, relapses, magnetic resonance imaging (MRI) and treatment data (disease-specific data).
Conclusion:
The MS Data Alliance Core Dataset guides emerging registries in their dataset definitions and speeds up and supports harmonisation across registries and initiatives. The straight-forward, time-efficient process using a dedicated global multi-stakeholder task force has proven to be effective to define a concise core dataset.
Background
Investigating low-prevalence diseases such as multiple sclerosis is challenging because of the rather small number of individuals affected by this disease and the scattering of real-world ...data across numerous data sources. These obstacles impair data integration, standardization, and analysis, which negatively impact the generation of significant meaningful clinical evidence.
Objective
This study aims to present a comprehensive, research question–agnostic, multistakeholder-driven end-to-end data analysis pipeline that accommodates 3 prevalent data-sharing streams: individual data sharing, core data set sharing, and federated model sharing.
Methods
A demand-driven methodology is employed for standardization, followed by 3 streams of data acquisition, a data quality enhancement process, a data integration procedure, and a concluding analysis stage to fulfill real-world data-sharing requirements. This pipeline’s effectiveness was demonstrated through its successful implementation in the COVID-19 and multiple sclerosis global data sharing initiative.
Results
The global data sharing initiative yielded multiple scientific publications and provided extensive worldwide guidance for the community with multiple sclerosis. The pipeline facilitated gathering pertinent data from various sources, accommodating distinct sharing streams and assimilating them into a unified data set for subsequent statistical analysis or secure data examination. This pipeline contributed to the assembly of the largest data set of people with multiple sclerosis infected with COVID-19.
Conclusions
The proposed data analysis pipeline exemplifies the potential of global stakeholder collaboration and underlines the significance of evidence-based decision-making. It serves as a paradigm for how data sharing initiatives can propel advancements in health care, emphasizing its adaptability and capacity to address diverse research inquiries.
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