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Abstract 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

Abstract Bullous cutaneous reactions can be caused by many factors, including vaccines.1 However, among all cutaneous reactions following coronavirus disease 2019 (COVID‐19) mRNA vaccines, bullous reactions are rare. Here, we describe two patients with delayed generalised bullous cutaneous reactions 7 days after receiving Moderna (Spikevax®) and Pfizer–BioNTech (Comirnaty®) COVID‐19 vaccination, respectively.

Abstract Myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD) is an autoimmune demyelinating condition that affects children differently than adults. We performed a literature review to assess the presentation and clinical course of pediatric MOGAD. The most common initial phenotype is acute disseminated encephalomyelitis, especially among children younger than five years, followed by optic neuritis (ON) and/or transverse myelitis. Approximately one‐quarter of children with MOGAD have at least one relapse that typically occurs within three years of disease onset and often includes ON, even if ON was not present at onset. Clinical risk factors for a relapsing course have not been elucidated.

Abstract Objective To identify features of the gut microbiome associated with multiple sclerosis activity over time. Methods We used 16S ribosomal RNA sequencing from stool of 55 recently diagnosed pediatric‐onset multiple sclerosis patients. Microbiome features included the abundance of individual microbes and networks identified from weighted genetic correlation network analyses. Prentice‐Williams‐Peterson Cox proportional hazards models estimated the associations between features and three disease activity outcomes: clinical relapses and both new/enlarging T2 lesions and new gadolinium‐enhancing lesions on brain MRI. Analyses were adjusted for age, sex, and disease‐modifying therapies. Results Participants were followed, on average, 2.1 years. Five microbes were nominally associated with all three disease activity outcomes after multiple testing correction. These included butyrate producers Odoribacter (relapse hazard ratio = 0.46, 95% confidence interval: 0.24, 0.88) and Butyricicoccus (relapse hazard ratio = 0.49, 95% confidence interval: 0.28, 0.88). Two networks of co‐occurring gut microbes were significantly associated with a higher hazard of both MRI outcomes (gadolinium‐enhancing lesion hazard ratios (95% confidence intervals) for Modules 32 and 33 were 1.29 (1.08, 1.54) and 1.42 (1.18, 1.71), respectively; T2 lesion hazard ratios (95% confidence intervals) for Modules 32 and 33 were 1.34 (1.15, 1.56) and 1.41 (1.21, 1.64), respectively). Metagenomic predictions of these networks demonstrated enrichment for amino acid biosynthesis pathways. Interpretation Both individual and networks of gut microbes were associated with longitudinal multiple sclerosis activity. Known functions and metagenomic predictions of these microbes suggest the important role of butyrate and amino acid biosynthesis pathways. This provides strong support for future development of personalized microbiome interventions to modify multiple sclerosis disease activity.

Abstract Objective No relapse risk prediction tool is currently available to guide treatment selection for multiple sclerosis (MS). Leveraging electronic health record (EHR) data readily available at the point of care, we developed a clinical tool for predicting MS relapse risk. Methods Using data from a clinic‐based research registry and linked EHR system between 2006 and 2016, we developed models predicting relapse events from the registry in a training set (n = 1435) and tested the model performance in an independent validation set of MS patients (n = 186). This iterative process identified prior 1‐year relapse history as a key predictor of future relapse but ascertaining relapse history through the labor‐intensive chart review is impractical. We pursued two‐stage algorithm development: (1) L1‐regularized logistic regression (LASSO) to phenotype past 1‐year relapse status from contemporaneous EHR data, (2) LASSO to predict future 1‐year relapse risk using imputed prior 1‐year relapse status and other algorithm‐selected features. Results The final model, comprising age, disease duration, and imputed prior 1‐year relapse history, achieved a predictive AUC and F score of 0.707 and 0.307, respectively. The performance was significantly better than the baseline model (age, sex, race/ethnicity, and disease duration) and noninferior to a model containing actual prior 1‐year relapse history. The predicted risk probability declined with disease duration and age. Conclusion Our novel machine‐learning algorithm predicts 1‐year MS relapse with accuracy comparable to other clinical prediction tools and has applicability at the point of care. This EHR‐based two‐stage approach of outcome prediction may have application to neurological disease beyond MS.

Abstract Objective Serum neurofilament light (sNfL) is a promising new biomarker in multiple sclerosis (MS). We explored the relationship between sNfL and health outcomes and resource use in MS patients. Methods MS patients with serum samples and health‐outcome measurements collected longitudinally between 2011 and 2016 were analyzed. sNfL values were evaluated across age and gender. Data were analyzed using correlation with log‐transformed sNfL values. Results A total of 304 MS patients with a mean age of 32.9 years, average EDSS of 1.6 (SD = 1.5) and baseline sNfL of 8.8 (range 1.23–78.3) pg/mL were studied. Baseline sNFL values increased with age and were higher in females. Baseline sNfL correlated with baseline Multiple Sclerosis Quality of Life physical composite (mean = 49.4 (9.1), P = 0.035) and baseline EDSS (P = 0.002). Other PRO measures at baseline did not show a significant relationship with baseline sNfL. Average of baseline and follow‐up sNfL correlated with MSQoL physical‐role limitations (mean = 48.9 (10.8), P = 0.043) and social‐functioning (mean = 52.3 (7), P = 0.034) at 24‐month follow‐up. We found a trend for numerically higher sNfL levels in nonpersistent patients compared to those who were persistent to treatment (11.13 vs. 8.53 pg/mL, P = 0.093) measured as average of baseline and 24‐month values. Baseline NfL was associated with number of intravenous steroid infusions (mean = 0.2; SD = 3.0, P = 0.013), whereas the average of baseline and 12 months NfL values related to inpatient stays at 12 months (mean = 0.2; SD = 3.0 P = 0.053). Conclusion Serum NfL is a patient‐centric biomarker that correlated with MS patient health‐outcomes and healthcare utilization measures in a real‐world cohort.

Abstract Objective Multiple sclerosis (MS) is an autoimmune demyelinating disorder, which is characterized by relapses and remissions. Serum neurofilament light chain (sNfL) is an emerging biomarker of disease activity but its clinical use is still limited. In this study, we aim to characterize the temporal association between sNfL and new clinical relapses and new gadolinium‐enhancing (Gd+) lesions. Methods Annual sNfL levels were measured with a single‐molecule array (SIMOA) assay in 94 patients with MS enrolled in the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women’s Hospital (CLIMB) study. We used a multivariable linear mixed‐effects model to test the temporal association of sNfL with clinical relapses and/or new Gd+ lesions. We adjusted this model for age, disease duration, sex, and disease‐modifying therapies (DMTs) use. Results In the 3 months after a Gd+ lesion, we observed an average 35% elevation in sNfL (P

Abstract Objective Onset of multiple sclerosis (MS) occurs in childhood for approximately 5% of cases (pediatric MS, or ped‐MS). Epigenetic influences are strongly implicated in MS pathogenesis in adults, including the contribution from microRNAs (miRNAs), small noncoding RNAs that affect gene expression by binding target gene mRNAs. Few studies have specifically examined miRNAs in ped‐MS, but individuals developing MS at an early age may carry a relatively high burden of genetic risk factors, and miRNA dysregulation may therefore play a larger role in the development of ped‐MS than in adult‐onset MS. This study aimed to look for evidence of miRNA involvement in ped‐MS pathogenesis. Methods GWAS results from 486 ped‐MS cases and 1362 controls from the U.S. Pediatric MS Network and Kaiser Permanente Northern California membership were investigated for miRNA‐specific signals. First, enrichment of miRNA‐target gene network signals was evaluated using MIGWAS software. Second, SNPs in miRNA genes and in target gene binding sites (miR−SNPs) were tested for association with ped‐MS, and pathway analysis was performed on associated target genes. Results MIGWAS analysis showed that miRNA‐target gene signals were enriched in GWAS (P = 0.038) and identified 39 candidate biomarker miRNA‐target gene pairs, including immune and neuronal signaling genes. The miR‐SNP analysis implicated dysregulation of miRNA binding to target genes in five pathways, mainly involved in immune signaling. Interpretation Evidence from GWAS suggests that miRNAs play a role in ped‐MS pathogenesis by affecting immune signaling and other pathways. Candidate biomarker miRNA‐target gene pairs should be further studied for diagnostic, prognostic, and/or therapeutic utility.