SUMMIT (Serially Unified Multicenter Multiple Sclerosis Investigation): creating a repository of deeply phenotyped contemporary multiple sclerosis cohorts

Clinical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis

An 18-protein multiple sclerosis (MS) disease activity (DA) test was validated based on associations between algorithm scores and clinical/radiographic assessments (N = 614 serum samples; Train [n = 426; algorithm development] and Test [n = 188; evaluation] subsets). The multi-protein model was trained based on presence/absence of gadolinium-positive (Gd+) lesions and was also strongly associated with new/enlarging T2 lesions, and active versus stable disease (composite of radiographic and clinical evidence of DA) with improved performance (p < 0.05) compared to the neurofilament light single protein model. The odds of having ≥1 Gd + lesions with a moderate/high DA score were 4.49 times that of a low DA score, and the odds of having ≥2 Gd + lesions with a high DA score were 20.99 times that of a low/moderate DA score. The MSDA Test was clinically validated with improved performance compared to the top-performing single-protein model and can serve as a quantitative tool to enhance the care of MS patients.

Early miR-320b and miR-25-3p miRNA levels correlate with multiple sclerosis severity at 10 years: a cohort study

BACKGROUND

Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder which may cause long-term disability. MicroRNA (miRNA) are stable, non-coding molecules that have been identified in our Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB)-cohort, as well as other international cohorts, as potential disease biomarkers in MS. However, few studies have evaluated the association of miRNA expression early in the MS disease course with long-term outcomes. Therefore, we aimed to evaluate the potential role of three candidate serum miRNAs previously correlated with MS disability in patients with MS, miR-320b, miR-25-3p and miRNA 486-5p, as early biomarkers of MS disability at 10-year follow-up.

MAIN BODY

We included 144 patients with serum obtained within three years of MS onset. miRNA expression was measured by RNA extraction followed by RT-PCR. Demographic, clinical, brain MRI and other biomarkers were collected. The primary outcome was the association between early miRNA expression and retaining benign MS, defined as EDSS ≤ 2 at 10-year follow-up. Among the 144 patients, 104 were benign and 40 were not benign at 10-year follow-up. 89 (62%) were women, with mean age at onset 37.7 (SD: 9.6) years. Patients who retained benign MS had lower values of miR-25-3p (p = 0.047) and higher miR-320b (p = 0.025) values. Development of SPMS was associated with higher miR-320b (p = 0.002) levels. Brain parenchymal fraction at year 10 was negatively correlated with miR-25-3p (p = 0.0004) and positively correlated with miR-320b (p = 0.006). No association was found between miR-486-5p and any outcome, and 10-year T2-lesion volume was not associated with any miRNA.

CONCLUSIONS

Our results show that miR-320b and miR-25-3p expression are early biomarkers associated with MS severity and brain atrophy. This study provides class III evidence of that miR-320b and miR-25-3p are associated with long-term MS disability which may be a potential tool to risk-stratify patients with MS for early treatment decisions.

Subtypes of relapsing-remitting multiple sclerosis identified by network analysis

We used network analysis to identify subtypes of relapsing-remitting multiple sclerosis subjects based on their cumulative signs and symptoms. The electronic medical records of 113 subjects with relapsing-remitting multiple sclerosis were reviewed, signs and symptoms were mapped to classes in a neuro-ontology, and classes were collapsed into sixteen superclasses by subsumption. After normalization and vectorization of the data, bipartite (subject-feature) and unipartite (subject-subject) network graphs were created using NetworkX and visualized in Gephi. Degree and weighted degree were calculated for each node. Graphs were partitioned into communities using the modularity score. Feature maps visualized differences in features by community. Network analysis of the unipartite graph yielded a higher modularity score (0.49) than the bipartite graph (0.25). The bipartite network was partitioned into five communities which were named fatigue, behavioral, hypertonia/weakness, abnormal gait/sphincter, and sensory, based on feature characteristics. The unipartite network was partitioned into five communities which were named fatigue, pain, cognitive, sensory, and gait/weakness/hypertonia based on features. Although we did not identify pure subtypes (e.g., pure motor, pure sensory, etc.) in this cohort of multiple sclerosis subjects, we demonstrated that network analysis could partition these subjects into different subtype communities. Larger datasets and additional partitioning algorithms are needed to confirm these findings and elucidate their significance. This study contributes to the literature investigating subtypes of multiple sclerosis by combining feature reduction by subsumption with network analysis.

Temporal trends of multiple sclerosis disease activity: Electronic health records indicators

BACKGROUND

Long-term data on multiple sclerosis (MS) inflammatory disease activity are limited. We examined electronic health records (EHR) indicators of disease activity in people with MS.

METHODS

We analyzed prospectively collected research registry data and linked EHR data in a clinic-based cohort from 2000 to 2016. We used the trend of the yearly incident relapse rate from the registry data as benchmark. We then calculated the temporal trends of potentially relevant EHR measures, including mean count of the MS diagnostic code, mentions of MS-related concepts, MS-related health utilizations and selected prescriptions.

RESULTS

1,555 MS patients had both registry and EHR data. Between 2000 and 2016, the registry data showed a declining trend in the yearly incident relapse rate, parallel to an increasing trend of DMT usage. Among the EHR measures, covariate-adjusted frequency of diagnostic code of MS, procedure codes of MS-related imaging studies and emergency room visits, and electronic prescription for steroids declined over time, mirroring the temporal trend of the benchmark yearly incident relapse rate.

CONCLUSION

This study highlights EHR indicators of MS relapse that could enable large-scale examination of long-term disease activities or inform individual patient monitoring in clinical settings where EHR data are available.

Oral contraceptives do not modify the risk of a second attack and disability accrual in a prospective cohort of women with a clinically isolated syndrome and early multiple sclerosis

Objective:

To evaluate whether oral contraceptive (OC) use is associated with the risk of a second attack and disability accrual in women with a clinically isolated syndrome (CIS) and early multiple sclerosis (MS).

Methods:

Reproductive information from women included in the Barcelona CIS prospective cohort was collected through a self-reported cross-sectional survey. We examined the relationship of OC exposure with the risk of a second attack and confirmed Expanded Disability Status Scale of 3.0 using multivariate Cox regression models, adjusted by age, topography of CIS, oligoclonal bands, baseline brain T2 lesions, body size at menarche, smoking, and disease-modifying treatment (DMT). OC and DMT exposures were considered as time-varying variables. Findings were confirmed with sensitivity analyses using propensity score models.

Results:

A total of 495 women were included, 389 (78.6%) referred to ever use OC and 341 (68.9%) started OC before the CIS. Exposure to OC was not associated with a second attack (adjusted hazard ratio (aHR) = 0.73, 95% confidence interval (CI) = 0.33–1.61) or disability accrual (aHR = 0.81, 95% CI = 0.17–3.76). Sensitivity analyses confirmed these results.

Conclusion:

OC use does not modify the risk of second attack or disability accrual in patients with CIS and early MS, once considered as a time-dependent exposure and adjusted by other potential confounders.

The North American Registry for Care and Research in Multiple Sclerosis (NARCRMS)

Although many regional multiple sclerosis (MS) databases existed in the United States and Canada, there was no single clinician-derived registry that examined this disease as a group across the North American continent. This distinction is important because information that results from such a database can potentially give perspectives about MS that cannot be derived from any single regional registry. A partnership was forged between the pharmaceutical industry and the Consortium of Multiple Sclerosis Centers (CMSC) to create a registry of patients with MS from Canada and the United States, including Puerto Rico. Case report forms were created to collect physician-derived information, and the Patient-Reported Outcomes Measurement Information System (PROMIS) was selected to capture patient-reported outcomes. As of November 2021, 754 of 1000 patients have been enrolled. Completion of recruitment is expected by the end of 2021. Twenty-five centers are participating, with an expected total of 30, including five centers from Canada. Clinical status, health economic outcomes, magnetic resonance images, and, soon, biomarkers relevant to understanding relapses and progression are collected. The short-term goal is to understand and better treat MS disease progression, and the long-term goal is its prevention. The North American Registry for Care and Research in Multiple Sclerosis (NARCRMS) is one of few clinician/patient-generated registries that examines MS across North America, including Puerto Rico. Information derived from the natural history studies should help physicians, the pharmaceutical industry, and regulatory bodies understand MS better and improve quality of life for patients with MS worldwide.

The Canadian prospective cohort study to understand progression in multiple sclerosis (CanProCo): rationale, aims, and study design

Background

Neurological disability progression occurs across the spectrum of people living with multiple sclerosis (MS). Although there are a handful of disease-modifying treatments approved for use in progressive phenotypes of MS, there are no treatments that substantially modify the course of clinical progression in MS. Characterizing the determinants of clinical progression can inform the development of novel therapeutic agents and treatment approaches that target progression in MS, which is one of the greatest unmet needs in clinical practice. Canada, having one of the world’s highest rates of MS and a publicly-funded health care system, represents an optimal country to achieve in-depth analysis of progression. Accordingly, the overarching aim of the Canadian Prospective Cohort Study to Understand Progression in MS (CanProCo) is to evaluate a wide spectrum of factors associated with the clinical onset and rate of disease progression in MS, and to describe how these factors relate to one another to influence progression.

Methods

CanProCo is a prospective, observational cohort study with investigators specializing in epidemiology, neuroimaging, neuroimmunology, health services research and health economics. CanProCo’s study design was approved by an international review panel, comprised of content experts and key stakeholders. One thousand individuals with radiologically-isolated syndrome, relapsing-remitting MS, and primary-progressive MS within 10–15 years of disease onset will be recruited from 5 academic MS centres in Canada. Participants will undergo detailed clinical evaluation annually over 5 years (including advanced, app-based clinical data collection). In a subset of participants within 5–10 years of disease onset (n = 500), blood, cerebrospinal fluid, and research MRIs will be collected allowing an integrated, in-depth evaluation of factors contributing to progression in MS from multiple perspectives. Factors of interest range from biological measures (e.g. single-cell RNA-sequencing), MRI-based microstructural assessment, participant characteristics (self-reported, performance-based, clinician-assessed, health-system based), and micro and macro-environmental factors.

Discussion

Halting the progression of MS remains a fundamental need to improve the lives of people living with MS. Achieving this requires leveraging transdisciplinary approaches to better characterize why clinical progression occurs. CanProCo is a pioneering multi-dimensional cohort study aiming to characterize these determinants to inform the development and implementation of efficacious and effective interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02447-7.

Ensemble learning predicts multiple sclerosis disease course in the SUMMIT study

The rate of disability accumulation varies across multiple sclerosis (MS) patients. Machine learning techniques may offer more powerful means to predict disease course in MS patients. In our study, 724 patients from the Comprehensive Longitudinal Investigation in MS at Brigham and Women's Hospital (CLIMB study) and 400 patients from the EPIC dataset, University of California, San Francisco, were included in the analysis. The primary outcome was an increase in Expanded Disability Status Scale (EDSS) ≥ 1.5 (worsening) or not (non-worsening) at up to 5 years after the baseline visit. Classification models were built using the CLIMB dataset with patients' clinical and MRI longitudinal observations in first 2 years, and further validated using the EPIC dataset. We compared the performance of three popular machine learning algorithms (SVM, Logistic Regression, and Random Forest) and three ensemble learning approaches (XGBoost, LightGBM, and a Meta-learner L). A "threshold" was established to trade-off the performance between the two classes. Predictive features were identified and compared among different models. Machine learning models achieved 0.79 and 0.83 AUC scores for the CLIMB and EPIC datasets, respectively, shortly after disease onset. Ensemble learning methods were more effective and robust compared to standalone algorithms. Two ensemble models, XGBoost and LightGBM were superior to the other four models evaluated in our study. Of variables evaluated, EDSS, Pyramidal Function, and Ambulatory Index were the top common predictors in forecasting the MS disease course. Machine learning techniques, in particular ensemble methods offer increased accuracy for the prediction of MS disease course.

Serum antibodies to phosphatidylcholine in MS

OBJECTIVE

To evaluate the value of serum immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies reactive with phosphatidylcholine (PC) and lactosylceramide (LC) as biomarkers in MS.

METHODS

We developed an ultrasensitive ELISA technique to analyze serum IgG and IgM antibodies to LC and PC, which we used to analyze samples from 362 patients with MS, 10 patients with non-MS myelin diseases (Non-MSMYDs), 11 patients with nonmyelin neurologic diseases (Non-MYNDs), and 80 controls. MS serum samples included clinically isolated syndrome (CIS, n = 17), relapsing-remitting MS (RRMS, n = 62), secondary progressive MS (SPMS, n = 50), primary progressive MS (PPMS, n = 37), and benign MS (BENMS, n = 36).

RESULTS

We detected higher levels of serum IgM antibodies to PC (IgM-PC) in MS than control samples; patients with CIS and RRMS showed higher IgM-PC levels than patients with SPMS, PPMS, and BENMS and controls. MS and control samples did not differ in serum levels of IgM antibodies reactive with LC, nor in IgG antibodies reactive with LC or PC.

CONCLUSIONS

Serum IgM-PC antibodies are elevated in patients with MS, particularly during the CIS and RRMS phases of the disease. Thus, serum IgM-PC is a candidate biomarker for early inflammatory stages of MS.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that serum antibodies to PC are elevated in patients with MS. The study is rated Class III because of the case control design and the risk of spectrum bias: antibody levels in patients with MS were compared with healthy controls.

Monitoring of radiologic disease activity by serum neurofilaments in MS

Objective

To determine whether serum neurofilament light chain (sNfL) levels are associated with recent MRI activity in patients with relapsing-remitting MS (RRMS).

Methods

This observational study included 163 patients (405 samples) with early RRMS from the Study of Early interferon-beta1a (IFN-β1a) Treatment (SET) cohort and 179 patients (664 samples) with more advanced RRMS from the Genome-Wide Association Study of Multiple Sclerosis (GeneMSA) cohort. Based on annual brain MRI, we assessed the ability of sNfL cutoffs to reflect the presence of combined unique active lesions, defined as new/enlarging lesion compared with MRI in the preceding year or contrast-enhancing lesion. The probability of active MRI lesions among patients with different sNfL levels was estimated with generalized estimating equations models.

Results

From the sNfL samples ≥90th percentile, 81.6% of the SET (OR = 3.4, 95% CI = 1.8-6.4) and 48.9% of the GeneMSA cohort samples (OR = 2.6, 95% CI = 1.7-3.9) was associated with radiological disease activity on MRI. The sNfL level between the 10th and 30th percentile was reflective of negligible MRI activity: 1.4% (SET) and 6.5% (GeneMSA) of patients developed ≥3 active lesions, 5.8% (SET) and 6.5% (GeneMSA) developed ≥2 active lesions, and 34.8% (SET) and 11.8% (GeneMSA) showed ≥1 active lesion on brain MRI. The sNfL level <10th percentile was associated with even lower MRI activity. Similar results were found in a subgroup of clinically stable patients.

Conclusions

Low sNfL levels (≤30th percentile) help identify patients with MS with very low probability of recent radiologic disease activity during the preceding year. This result suggests that in future, sNfL assessment may substitute the need for annual brain MRI monitoring in considerable number (23.1%–36.4%) of visits in clinically stable patients.

Association of Rituximab Treatment With Disability Progression Among Patients With Secondary Progressive Multiple Sclerosis

Importance

Therapeutic options for patients with secondary progressive multiple sclerosis (SPMS) are limited.

Objective

To analyze disability progression in patients with SPMS treated with rituximab compared with matched control patients never treated with rituximab.

Design, Setting, and Participants

This retrospective cohort study analyzed data obtained from patients with SPMS at 3 multiple sclerosis centers located in Basel and Lugano, Switzerland, and Amsterdam, the Netherlands, from 2004 to 2017. Patients were included for analysis if they had received a diagnosis of SPMS, were treated (57 eligible; 54 included) or never treated (504 eligible; 59 included) with rituximab, and had at least 1 follow-up visit. The variables used for propensity score matching were sex, age, Expanded Disability Status Scale (EDSS) score, and disease duration. Follow-up duration was up to 10 years, with a mean (SD) of 3.5 (2.6) years for rituximab-treated patients and 5.4 (2.4) years for controls in the total cohort and a mean (SD) of 3.5 (2.7) years for rituximab-treated patients and 4.8 (2.2) years for controls in the matched cohort.

Exposures

Comparing EDSS score progression in patients with SPMS (treated with rituximab vs not treated with rituximab) using propensity score matching.

Main Outcomes and Measures

The primary end point was progression of EDSS score after baseline, and the secondary end point was time to confirmed disability progression.

Results

After 1:1 propensity score matching, 44 matched pairs (88 patients) were included in the analysis. At baseline, patients treated with rituximab had a mean (SD) age of 49.7 (10.0) years, mean (SD) disease duration of 18.2 (9.4) years, and mean (SD) EDSS score of 5.9 (1.4), and 26 (59%) were women, whereas controls had a mean (SD) age of 51.3 (7.4) years, mean (SD) disease duration of 19.4 (8.7) years, and mean (SD) EDSS score of 5.70 (1.29), and 27 (61%) were women. In the covariate-adjusted analysis of the matched set, patients with SPMS who were treated with rituximab had a significantly lower EDSS score during a mean (SD) follow-up of 3.5 (2.7) years (mean difference, -0.52; 95% CI, -0.79 to -0.26; P < .001). Time to confirmed disability progression was significantly delayed in the rituximab-treated group (hazard ratio, 0.49; 95% CI, 0.26-0.93; P = .03).

Conclusions and Relevance

In this study, patients with SPMS treated with rituximab had a significantly lower EDSS score for up to 10 years of follow-up and a significantly delayed confirmed progression compared with matched controls, suggesting that B-cell depletion by rituximab may be therapeutically beneficial in these patients. A prospective randomized clinical trial with a better level of evidence is needed to confirm the efficacy of rituximab in such patients.

Brain MRI Predicts Worsening Multiple Sclerosis Disability over 5 Years in the SUMMIT Study

BACKGROUND AND PURPOSE

Brain MRI-derived lesions and atrophy are related to multiple sclerosis (MS) disability. In the Serially Unified Multicenter MS Investigation (SUMMIT), from Brigham and Women's Hospital (BWH) and University of California, San Francisco (UCSF), we assessed whether MRI methodologic heterogeneity may limit the ability to pool multisite data sets to assess 5-year clinical-MRI associations.

METHODS

Patients with relapsing-remitting (RR) MS (n = 100 from each site) underwent baseline brain MRI and baseline and 5-year clinical evaluations. Patients were matched on sex (74 women each), age, disease duration, and Expanded Disability Status Scale (EDSS) score. MRI was performed with differences between sites in both acquisition (field strength, voxel size, pulse sequences), and postprocessing pipeline to assess brain parenchymal fraction (BPF) and T2 lesion volume (T2LV).

RESULTS

The UCSF cohort showed higher correlation than the BWH cohort between T2LV and disease duration. UCSF showed a higher inverse correlation between BPF and age than BWH. UCSF showed a higher inverse correlation than BWH between BPF and 5-year EDSS score. Both cohorts showed inverse correlations between BPF and T2LV, with no between-site difference. The pooled but not individual cohort data showed a link between a lower baseline BPF and the subsequent 5-year worsening in disability in addition to other stronger relationships in the data.

CONCLUSIONS

MRI acquisition and processing differences may result in some degree of heterogeneity in assessing brain lesion and atrophy measures in patients with MS. Pooling of data across sites is beneficial to correct for potential biases in individual data sets.

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.

Silent progression in disease activity-free relapsing multiple sclerosis

Objective

Rates of worsening and evolution to secondary progressive multiple sclerosis (MS) may be substantially lower in actively treated patients compared to natural history studies from the pretreatment era. Nonetheless, in our recently reported prospective cohort, more than half of patients with relapsing MS accumulated significant new disability by the 10th year of follow‐up. Notably, “no evidence of disease activity” at 2 years did not predict long‐term stability. Here, we determined to what extent clinical relapses and radiographic evidence of disease activity contribute to long‐term disability accumulation.

Methods

Disability progression was defined as an increase in Expanded Disability Status Scale (EDSS) of 1.5, 1.0, or 0.5 (or greater) from baseline EDSS = 0, 1.0–5.0, and 5.5 or higher, respectively, assessed from baseline to year 5 (±1 year) and sustained to year 10 (±1 year). Longitudinal analysis of relative brain volume loss used a linear mixed model with sex, age, disease duration, and HLA‐DRB1*15:01 as covariates.

Results

Relapses were associated with a transient increase in disability over 1‐year intervals (p = 0.012) but not with confirmed disability progression (p = 0.551). Relative brain volume declined at a greater rate among individuals with disability progression compared to those who remained stable (p < 0.05).

Interpretation

Long‐term worsening is common in relapsing MS patients, is largely independent of relapse activity, and is associated with accelerated brain atrophy. We propose the term silent progression to describe the insidious disability that accrues in many patients who satisfy traditional criteria for relapsing–remitting MS. Ann Neurol 2019;85:653–666

Why monkeys do not get multiple sclerosis (spontaneously): An evolutionary approach

The goal of this review is to apply an evolutionary lens to understanding the origins of multiple sclerosis (MS), integrating three broad observations. First, only humans are known to develop MS spontaneously. Second, humans have evolved large brains, with characteristically large amounts of metabolically costly myelin. This myelin is generated over long periods of neurologic development—and peak MS onset coincides with the end of myelination. Third, over the past century there has been a disproportionate increase in the rate of MS in young women of childbearing age, paralleling increasing westernization and urbanization, indicating sexually specific susceptibility in response to changing exposures. From these three observations about MS, a life history approach leads us to hypothesize that MS arises in humans from disruption of the normal homeostatic mechanisms of myelin production and maintenance, during our uniquely long myelination period. This review will highlight under-explored areas of homeostasis in brain development, that are likely to shed new light on the origins of MS and to raise further questions about the interactions between our ancestral genes and modern environments.