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The Major Histocompatibility Complex (MHC) makes the largest genetic contribution to multiple sclerosis (MS) susceptibility, with 32 independent effects across the region explaining 20% of the heritability in European populations. Variation is high across populations with allele frequency differences and population-specific risk alleles identified. We sought to identify MHC-specific MS susceptibility variants and assess the effect of ancestral risk modification within 2652 Latinx and Hispanic individuals as well as 2435 Black and African American individuals. We have identified several novel susceptibility alleles which are rare in European populations including HLA-B*53:01, and we have utilized the differing linkage disequilibrium patterns inherent to these populations to identify an independent role for HLA-DRB1*15:01 and HLA-DQB1*06:02 on MS risk. We found a decrease in Native American ancestry in MS cases vs controls across the MHC, peaking near the previously identified MICB locus with a decrease of ~5.5% in Hispanics and ~0.4% in African Americans. We have identified several susceptibility variants, including within the MICB gene region, which show global ancestry risk modification and indicate ancestral differences which may be due in part to correlated environmental factors. We have also identified several susceptibility variants for which MS risk is modified by local ancestry and indicate true ancestral genetic differences; including HLA-DQB1*06:02 for which MS risk for European allele carriers is almost two times the risk for African allele carriers. These results validate the importance of investigating MS susceptibility at an ancestral level and offer insight into the epidemiology of MS phenotypic diversity.

ObjectiveThis study was undertaken to determine whether the vertical parasagittal approach or the lateral peri-insular/peri-Sylvian approach to hemispheric surgery is the superior technique in achieving long-term seizure freedom.MethodsWe conducted a post hoc subgroup analysis of the HOPS (Hemispheric Surgery Outcome Prediction Scale) study, an international, multicenter, retrospective cohort study that identified predictors of seizure freedom through logistic regression modeling. Only patients undergoing vertical parasagittal, lateral peri-insular/peri-Sylvian, or lateral trans-Sylvian hemispherotomy were included in this post hoc analysis. Differences in seizure freedom rates were assessed using a time-to-event method and calculated using the Kaplan-Meier survival method.ResultsData for 672 participants across 23 centers were collected on the specific hemispherotomy approach. Of these, 72 (10.7%) underwent vertical parasagittal hemispherotomy and 600 (89.3%) underwent lateral peri-insular/peri-Sylvian or trans-Sylvian hemispherotomy. Seizure freedom was obtained in 62.4% (95% confidence interval [CI] = 53.5%-70.2%) of the entire cohort at 10-year follow-up. Seizure freedom was 88.8% (95% CI = 78.9%-94.3%) at 1-year follow-up and persisted at 85.5% (95% CI = 74.7%-92.0%) across 5- and 10-year follow-up in the vertical subgroup. In contrast, seizure freedom decreased from 89.2% (95% CI = 86.3%-91.5%) at 1-year to 72.1% (95% CI = 66.9%-76.7%) at 5-year to 57.2% (95% CI = 46.6%-66.4%) at 10-year follow-up for the lateral subgroup. Log-rank test found that vertical hemispherotomy was associated with durable seizure-free progression compared to the lateral approach (p = .01). Patients undergoing the lateral hemispherotomy technique had a shorter time-to-seizure recurrence (hazard ratio = 2.56, 95% CI = 1.08-6.04, p = .03) and increased seizure recurrence odds (odds ratio = 3.67, 95% CI = 1.05-12.86, p = .04) compared to those undergoing the vertical hemispherotomy technique.SignificanceThis pilot study demonstrated more durable seizure freedom of the vertical technique compared to lateral hemispherotomy techniques. Further studies, such as prospective expertise-based observational studies or a randomized clinical trial, are required to determine whether a vertical approach to hemispheric surgery provides superior long-term seizure outcomes.

Using a targeted transcriptomics approach, we have analyzed resected brain tissue from a cohort of 53 pediatric epilepsy surgery cases, and have found that there is a spectrum of involvement of both the innate and adaptive immune systems as evidenced by the differential expression of immune-specific genes in the affected brain tissue. The specimens with the highest expression of immune-specific genes were from two Rasmussen encephalitis cases, which is known to be a neuro-immunological disease, but also from tuberous sclerosis complex (TSC), focal cortical dysplasia, and hemimegalencephaly surgery cases. We obtained T cell receptor (TCR) Vβ chain sequence data from brain tissue and blood from patients with the highest levels of T cell transcripts. The clonality indices and the frequency of the top 50 Vβ clonotypes indicated that T cells in the brain were clonally restricted. The top 50 Vβ clonotypes comprised both public and private (patient specific) clonotypes, and the TCR Vβ chain third complementarity region (CDR3) of the most abundant public Vβ clonotype in each brain sample was strikingly similar to a CDR3 that recognizes an immunodominant epitope in either human cytomegalovirus or Epstein Barr virus, or influenza virus A. We found that the frequency of 14 of the top 50 brain Vβ clonotypes from a TSC surgery case had significantly increased in brain tissue removed to control recurrent seizures 11 months after the first surgery. Conversely, we found that the frequency in the blood of 18 of the top 50 brain clonotypes from a second TSC patient, who was seizure free, had significantly decreased 5 months after surgery indicating that T cell clones found in the brain had contracted in the periphery after removal of the brain area associated with seizure activity and inflammation. However, the frequency of a public and a private clonotype significantly increased in the brain after seizures recurred and the patient underwent a second surgery. Combined single cell gene expression and TCR sequencing of brain-infiltrating leukocytes from the second surgery showed that the two clones were CD8 effector T cells, indicating that they are likely to be pathologically relevant.

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. 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). 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. 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. 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.

Background and purposeBrain 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.MethodsPatients 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).ResultsThe 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.ConclusionsMRI 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.

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.

Objective: Glial fibrillary acidic protein (GFAP) is expressed in astrocytes and may be a useful marker of non‐active progressive multiple sclerosis (MS). We evaluate serum GFAP (sGFAP) in a large cohort of MS patients to determine if it predicts progression independent of relapse activity (PIRA), future gait aid, and conversion to secondary progressive disease (SPMS). Methods: Adults with clinically isolated syndrome or any subtype of MS who were listed in the Brigham MS Center Research Database and had at least one sGFAP result were included. All clinic visits following first sample were analyzed for PIRA, future gait aid, and conversion to SPMS. Future cognitive dysfunction and fatigue were evaluated as secondary outcomes. Results: In total, 741 patients were included (average age: 42.3, average disease duration: 3.7 years, median EDSS: 2, and median follow‐up duration: 10.0 years). Of 643 patients (86.8%) without progressive disease at baseline, 15.9% developed SPMS. Among all 741, 50.5% had PIRA and 18.6% developed a gait aid requirement. sGFAP level predicted PIRA, future gait aid, and conversion to SPMS in univariable models (p < 0.001, <0.001, and 0.002). sGFAP remained predictive for PIRA and future gait aid in multivariable models in those younger than 50 (p = 0.048, 0.003). Change in sGFAP level over time was not predictive. There was no association between sGFAP and future fatigue or cognitive dysfunction. Interpretation: sGFAP helps to predict PIRA, future gait aid, and conversion to SPMS in a large cohort of MS patients. Our data suggest that baseline levels may be more useful than the change over time. [ABSTRACT FROM AUTHOR]

BackgroundThere is a pressing need for robust longitudinal cohort studies in the modern treatment era of multiple sclerosis.ObjectiveBuild a multiple sclerosis (MS) cohort repository to capture the variability of disability accumulation, as well as provide the depth of characterization (clinical, radiologic, genetic, biospecimens) required to adequately model and ultimately predict a patient's course.MethodsSerially Unified Multicenter Multiple Sclerosis Investigation (SUMMIT) is an international multi-center, prospectively enrolled cohort with over a decade of comprehensive follow-up on more than 1000 patients from two large North American academic MS Centers (Brigham and Women's Hospital (Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB; BWH)) and University of California, San Francisco (Expression/genomics, Proteomics, Imaging, and Clinical (EPIC))). It is bringing online more than 2500 patients from additional international MS Centers (Basel (Universitätsspital Basel (UHB)), VU University Medical Center MS Center Amsterdam (MSCA), Multiple Sclerosis Center of Catalonia-Vall d'Hebron Hospital (Barcelona clinically isolated syndrome (CIS) cohort), and American University of Beirut Medical Center (AUBMC-Multiple Sclerosis Interdisciplinary Research (AMIR)).Results and conclusionWe provide evidence for harmonization of two of the initial cohorts in terms of the characterization of demographics, disease, and treatment-related variables; demonstrate several proof-of-principle analyses examining genetic and radiologic predictors of disease progression; and discuss the steps involved in expanding SUMMIT into a repository accessible to the broader scientific community.

ObjectiveTo identify circulating microRNAs (miRNAs) linked to disease, disease stage, and disability in MS across cohorts.MethodsSamples were obtained from the Comprehensive Longitudinal Investigation of Multiple Sclerosis (CLIMB, Boston, MA), EPIC (San Francisco, CA), AMIR (Beirut, Lebanon) as part of the SUMMIT consortium, and Stockholm Prospective Assessment of Multiple Sclerosis (Stockholm, Sweden) cohorts. Serum miRNA expression was measured using locked nucleic acid-based quantitative PCR. Four groups were compared: (1) MS vs healthy control (HC), (2) relapsing-remitting (RR) vs HC, (3) secondary progressive (SP) vs HC, and (4) RR vs SP. A Wilcoxon rank-sum test was used for the comparisons. The association between each miRNA and the Expanded Disability Status Scale (EDSS) score was assessed using the Spearman correlation coefficient. For each comparison, the p values were corrected for multiple comparisons using the approach of Benjamini and Hochberg to control the false discovery rate.ResultsIn the CLIMB cohort, 5 miRNAs (hsa-miR-484, hsa-miR-140-5p, hsa-miR-320a, hsa-miR-486-5p, and hsa-miR-320c) showed a significant difference between patients with MS and healthy individuals; among these, miR-484 remained significant after accounting for multiple comparisons (p = 0.01). When comparing RRMS with HCs, hsa-miR-484 showed a significant difference (p = 0.004) between the groups after accounting for multiple group comparisons. When SP and HC were compared, 6 miRNAs (hsa-miR-484, hsa-miR-140-5p, hsa-miR-142-5p, hsa-miR-320a, hsa-miR-320b, and hsa-miR-320c) remained significantly different after accounting for multiple comparisons. Disability correlation analysis with miRNA provided 4 miRNAs (hsa-miR-320a, hsa-miR-337-3p, hsa-miR-199a-5p, and hsa-miR-142-5p) that correlated with the EDSS during the internal reproducibility phase. Among these, hsa-miR-337-3p was the most statistically significant miRNA that negatively correlated with the EDSS in three of the MS cohorts tested.ConclusionsThese findings further confirm the use of circulating serum miRNAs as biomarkers to diagnose and monitor disease status in MS.Classification of evidenceThis study provides Class III evidence that levels of circulating miRNAs identify patients with MS.

ObjectiveTo investigate the relationship between brain volume and disability worsening over ≥3 years in the natural history of primary progressive multiple sclerosis using data from the placebo group of the INFORMS trial (n = 487; clinicaltrials.gov NCT00731692).MethodsMagnetic resonance imaging scans were collected annually. Brain volume loss was determined using SIENA. Patients were stratified by baseline normalized brain volume after adjusting for demographic and disease-burden covariates.ResultsBaseline normalized brain volume was predictive of disability worsening: Risk of 3-month confirmed disability progression was reduced by 36% for high versus low baseline normalized brain volume (Cox's model hazard ratio 0.64, P = 0.0339; log-rank test: P = 0.0297). Moreover, on-study brain volume loss was significantly associated with disability worsening (P = 0.012) and was evident in patients with or without new lesions or relapses. Brain volume loss depended significantly on baseline T2 lesion volume (P