Background

Commensal gut microbes are known to affect host immune function and may be modifiable. Recent work suggests gut microbiota composition contributes to onset of MS; however, little is known about its contribution to MS disease activity.

Objectives

Estimate the association between gut microbiota and subsequent disease activity among individuals with pediatric-onset MS (pedMS) from the U.S. Network of Pediatric MS Centers.

Methods

Stool samples were collected from cases (MS symptom onset <18 years) and profiled using 16S rRNA sequencing of the V4 region. Amplicon sequence variants (ASVs) were identified using the Divisive Amplicon Denoising Algorithm-2 (DADA2). ASVs present in <20% of samples were removed. ASV clusters (modules) were identified using weighted genetic correlation network analysis (WGCNA) and sparCC transformation of ASV abundance. Cox proportional hazard recurrent event models were used to examine the relationship between individual ASVs and then ASV clusters, adjusted for age, sex, and disease modifying therapy (DMT) use.

Results

Of 53 pedMS cases, 72% were girls. At stool sample collection, the mean age was 15.5 years (SD: 2.7) and disease duration was 1.1 years (SD: 1.0). Less than half (45%) had one relapse and 30% had >1 relapse over the subsequent mean follow-up of 2.5 years (SD:1.3). Over this time, 91% used a DMT. Among 270 individual ASVs included in the analyses, 20 were nominally significant (p<0.05), e.g. the presence of Blautia stercoris was associated with higher relapse risk (hazard ratio [HR]=2.50; 95% confidence interval [CI]=1.43, 4.37). WGCNA identified 6 ASV modules. Higher values of one module’s eigengene was significantly (false discovery rate q<0.2) associated with higher relapse risk (HR=1.23, 95% CI=1.02, 1.50). Four ASVs nominally associated with higher relapse risk were in this module. These included Blautia massiliensis, Dorea longicatena, Coprococcus comes, and an unknown species in genus Subdoligranulum.

Conclusions

We found that a high relative abundance of a gut microbiota species within the Blautia genus, and its interconnected variants, was associated with a higher relapse risk in pedMS cases. While our study represents the largest of its kind in MS, findings need to be replicated. However, Blautia stercoris has been linked to disease activity in other immune-mediated diseases such as systemic lupus erythematosus.

Background

We previously reported a relationship between air pollutants and increased risk of pediatric MS (ped-MS). Environmental risk factor research in ped-MS offers the advantage of shorter duration between exposure and disease onset. Ozone, an air pollutant, is a major global health hazard thought to have a role in MS pathoetiology. Identifying gene-environment interactions advances the understanding of biological processes at play in MS susceptibility.

Objectives

We sought to examine the interaction between ozone pollution and DRB1*15 status as the main genetic variant associated with MS susceptibility.

Methods

Cases and controls enrolled in the Environmental and Genetic Risk Factors for Pediatric MS study of the US Network of Pediatric MS Centers were analysed. County-level modeled ozone data were acquired from the CDC’s Environmental Tracking Network air pollution database. Participants were assigned ozone values based on county of residence. Values were categorized into tertiles based on healthy controls. The association between ozone tertiles and having MS were assessed by logistic regression. Interaction between tertiles of ozone level and presence of DRB1*15 alleles on odds of ped-MS was evaluated. Models were adjusted for sex, race, ethnicity, age, second-hand smoke exposure, and mother’s education. Additive interaction was estimated using relative risk due to interaction (RERI) and attributable proportion of disease were calculated.

Results

355 ped-MS cases and 565 controls contributed to the analyses. Ozone levels were associated with MS with an odds ratio (OR) of 2.35 (95%CI 1.57–3.51) and 2.21 (95%CI 1.48–3.32) in the upper two tertiles, respectively, compared with the lowest tertile. DRB1 status was also independently associated with MS (OR 1.99; 95%CI 1.43–2.78). There was a significant additive interaction between ozone and DRB1, with a RERI of 2.74 (95%CI 0.50–4.98) and 2.43 (95%CI 0.36–4.5) in the upper two tertiles, respectively. Approximately 60% of the ped-MS risk in those with HLA-DRB1*15 haplotype and high ozone exposure was attributable to the interaction between these risk factors.

Conclusions

Our data revealed additive interaction between higher exposure to ozone and DRB1 alleles on ped-MS susceptibility. Further evaluation of additional genetic variants that might play a role in ozone-induced ped-MS is underway to provide mechanistic insight.

Background

Serum neurofilament light chain (sNfL) reflects neuro-axonal damage and may qualify as a biomarker of suboptimal response to disease modifying therapy (DMT).

Objectives

To investigate the predictive value of sNfL in clinically isolated syndrome (CIS) and relapsing-remitting (RR) MS patients with established DMT for future MS disease activity in the Swiss MS Cohort Study.

Methods

All patients were on DMT for at least 3 months. sNfL was measured 6 or 12-monthly with the NF-light^®assay. The association between sNfL and age was modeled using a generalized additive model for location scale and shape. Z-scores (sNfLz) were derived thereof, reflecting the deviation of a patient sNfL value from the mean value of same age healthy controls (n=8865 samples). We used univariable mixed logistic regression models to investigate the association between sNfLz and the occurrence of clinical events (relapses, EDSS worsening [≥1.5 steps if EDSS 0; ≥1.0 if 1.0-5.5 or ≥0.5 if >5.5] in the following year in all patients, and in those fulfilling NEDA-3 criteria (no relapses, EDSS worsening, contrast enhancing or new/enlarging T2 lesions in brain MRI, based on previous year). We combined sNfLz with clinical and MRI measures of MS disease activity in the previous year (EDA-3) in a multivariable mixed logistic regression model for predicting clinical events in the following year.

Results

sNfL was measured in 1062 patients with 5192 longitudinal samples (median age 39.7 yrs; EDSS 2.0; 4.1% CIS, 95.9% RRMS; median follow-up 5 yrs). sNfLz predicted clinical events in the following year (OR 1.21 [95%CI 1.11-1.36], p<0.001, n=4624). This effect increased in magnitude with increasing sNfLz (sNfLz >1: OR 1.41 [95%CI 1.15-1.73], p=0.001; >1.5: OR 1.80 [95%CI 1.43-2.28], p<0.001; >2: OR 2.33 [95%CI 1.74-3.14], p<0.001). Similar results were found for the prediction of future new/enlarging T2 lesions and brain volume loss. In the multivariable model, new/enlarging T2 lesions (OR 1.88 [95%CI 1.13-3.12], p=0.016) and sNfLz>1.5 (OR 2.18 [95%CI 1.21-3.90], p=0.009) predicted future clinical events (n=853), while previous EDSS worsening, previous relapses and current contrast enhancement did not. In NEDA-3 patients, change of sNfLz (per standard deviation) was associated with a 37% increased risk of clinical events in the subsequent year (OR 1.37 [95%CI 1.04-1.78], p=0.025, n=587).

Conclusions

Our data support the value of sNfL levels, beyond the NEDA3 concept, for treatment monitoring in MS clinical practice.

Abstract

Following upon the discoveries that specific bacteria in the gut may modulate the onset of experimental autoimmune encephalomyelitis, an animal model for MS, the human gut microbiome has been investigated in the human disease. Data in MS have been mostly generated from small to moderate size studies using stool samples from patients with relatively long disease duration and often receiving disease-modifying therapies that can affect microbial communities. A consistent finding across these studies is that the alpha and beta diversity of gut microbial communities appears overall similar in MS patients and controls, i.e. the overall bacterial composition is not dramatically different. In contrast, increased or decreased abundance of specific microbes has been reported in cases compared to controls, with some current research emphasis on bacterial cluster differences. While a few of these differences are consistent across studies, many are not, possibly due to variability in geographical region of origin, diet, comorbidities, use of MS drugs and age of the patients. Immune changes in relation to gut microbial alterations have been reported in MS compared to controls. Very few publications have addressed so far the association between the gut microbiome characteristics and the risk of relapse or disability progression. A critical focus of current research is to unravel the changes in metabolic function resulting from alterations in microbial communities (i.e. the dysregulation of specific metabolic pathways due to variations in the presence or abundance of specific bacteria). Ongoing pilot trials of probiotic supplementation or microbiome transplant will determine the feasibility of these interventions and allow the design of future studies to attempt disease modification.

Background

Metagenomic sequencing reveals the functional potential of the gut microbiome, and may explain how the gut microbiome influences pediatric-onset multiple sclerosis (MS) risk.

Objectives

To examine the gut microbiome functional potential by metagenomic analysis of stool samples from pediatric MS cases and controls using a case-control design.

Methods

Persons ≤21 years old enrolled in the Canadian Pediatric Demyelinating Disease Network who provided a stool sample and were not exposed to antibiotics or corticosteroids 30 days prior were included for study. All MS cases met McDonald criteria, had symptom onset <18 years of age and had either no prior disease-modifying drug (DMD) exposure or were exposed to beta-interferon or glatiramer acetate only. Twenty MS cases were matched to 20 non-affected controls by sex, age (± 3 years), stool consistency (Bristol Stool Scale, BSS) and, when possible, by race. Shotgun metagenomic reads were generated using the Illumina NextSeq platform and assembled using MEGAHIT. Metabolic pathway analysis was used to compare the gut microbiome between cases and controls, as well as cases by DMD status (DMD naïve vs DMD exposed MS cases vs controls). Gene ontology classifications were used to assess α-diversity and differential abundance analyses (based on the negative binomial distribution) reported as age-adjusted log-fold change (LFC) in relative abundance, 95% confidence intervals (CI), and false discovery rate adjusted p-values.

Results

The MS cases were aged 13.6 mean years at symptom onset. On average, MS cases and controls were 16.1 and 15.4 years old at the time of stool collection and 80% of each group were girls. MS cases and controls were similar for body mass index (median: 22.8 and 21.0, respectively), stool consistency (BSS types 1-2: n=4, types 3-5: n=16, for both MS and controls) and race (Caucasian: 11 and 9, respectively). Eight MS cases were DMD naïve. Richness of gene ontology classifications did not differ by disease status or DMD status (all p>0.4). However, differential analysis of metabolic pathways indicated that the relative abundance of tryptophan degradation (via the kynurenine pathway; LFC 13; 95%CI: 8–19; p<0.0005) and cresol degradation (LFC 19; 95%CI: 13–25; p<0.0001) pathways were enriched for MS cases vs controls. Differences by DMD status were also observed, e.g., choline biosynthesis was enriched in DMD exposed vs naïve MS cases (LFC 21; 95%CI: 12–29; p<0.0001).

Conclusions

We observed differences in the functional potential of the gut microbiome of young individuals with MS relative to controls at various metabolic pathways, including enrichment of pathways related to tryptophan and metabolism of industrial chemicals. DMD exposure affected findings, with enrichment of pathways involved in promoting CNS remyelination (e.g., choline).

Background

Methylphenidate, modafinil, and amantadine are commonly prescribed medications for alleviating fatigue in multiple sclerosis (MS); however, the evidence supporting their efficacy is sparse and conflicting.

Objectives

Our goal was to compare the efficacy of these three medications against each other and placebo in patients with MS-related fatigue.

Methods

In this randomized, double-blind, placebo-controlled, four-sequence, four-period crossover trial, patients with MS fatigue received twice-daily oral amantadine, modafinil, methylphenidate, or placebo, each given for up to six weeks. The primary outcome measure was the Modified Fatigue Impact Scale (MFIS) measured while taking the highest tolerated dose. Secondary outcomes included measures of sleepiness, adverse events, and the maximal tolerated dose of each medication.

Results

A total of 141 patients were enrolled and randomly assigned to one of four medication administration sequences. Data from 136 participants were available for the intent-to-treat analysis of the primary outcome. The estimated mean values of MFIS total scores at baseline and the maximal tolerated dose were as follows: 51.3 at baseline, 40.7 with placebo, 41.2 with amantadine, 39.0 with modafinil, and 38.7 with methylphenidate (P=0.20 for the overall medication effect). As compared to placebo (30.6%), higher proportions of participants reported adverse events while taking amantadine (38.6%), modafinil (40.0%), and methylphenidate (39.5%).

Conclusions

Amantadine, modafinil, and methylphenidate were not superior to placebo in improving MS-related fatigue and caused more frequent adverse events. The results of this study do not support an indiscriminate use of amantadine, modafinil, and methylphenidate for the treatment of fatigue in MS. (ClinicalTrials.gov number, NCT03185065.)

Abstract

Following upon the discoveries that specific bacteria in the gut may modulate the onset of experimental autoimmune encephalomyelitis, an animal model for MS, the human gut microbiome has been investigated in the human disease. Data in MS have been mostly generated from small to moderate size studies using stool samples from patients with relatively long disease duration and often receiving disease-modifying therapies that can affect microbial communities. A consistent finding across these studies is that the alpha and beta diversity of gut microbial communities appears overall similar in MS patients and controls, i.e. the overall bacterial composition is not dramatically different. In contrast, increased or decreased abundance of specific microbes has been reported in cases compared to controls, with some current research emphasis on bacterial cluster differences. While a few of these differences are consistent across studies, many are not, possibly due to variability in geographical region of origin, diet, comorbidities, use of MS drugs and age of the patients. Immune changes in relation to gut microbial alterations have been reported in MS compared to controls. Very few publications have addressed so far the association between the gut microbiome characteristics and the risk of relapse or disability progression. A critical focus of current research is to unravel the changes in metabolic function resulting from alterations in microbial communities (i.e. the dysregulation of specific metabolic pathways due to variations in the presence or abundance of specific bacteria). Ongoing pilot trials of probiotic supplementation or microbiome transplant will determine the feasibility of these interventions and allow the design of future studies to attempt disease modification.

Abstract

Following upon the discoveries that specific bacteria in the gut may modulate the onset of experimental autoimmune encephalomyelitis, an animal model for MS, the human gut microbiome has been investigated in the human disease. Data in MS have been mostly generated from small to moderate size studies using stool samples from patients with relatively long disease duration and often receiving disease-modifying therapies that can affect microbial communities. A consistent finding across these studies is that the alpha and beta diversity of gut microbial communities appears overall similar in MS patients and controls, i.e. the overall bacterial composition is not dramatically different. In contrast, increased or decreased abundance of specific microbes has been reported in cases compared to controls, with some current research emphasis on bacterial cluster differences. While a few of these differences are consistent across studies, many are not, possibly due to variability in geographical region of origin, diet, comorbidities, use of MS drugs and age of the patients. Immune changes in relation to gut microbial alterations have been reported in MS compared to controls. Very few publications have addressed so far the association between the gut microbiome characteristics and the risk of relapse or disability progression. A critical focus of current research is to unravel the changes in metabolic function resulting from alterations in microbial communities (i.e. the dysregulation of specific metabolic pathways due to variations in the presence or abundance of specific bacteria). Ongoing pilot trials of probiotic supplementation or microbiome transplant will determine the feasibility of these interventions and allow the design of future studies to attempt disease modification.

Background

COVID-19, the disease caused by SARS CoV2, causes severe respiratory disease, and rarely multisystem inflammatory syndrome, in some pediatric patients. Little is known about the disease course among patients with pediatric-onset multiple sclerosis.

Objectives

To describe the demographic and clinical characteristics of a subgroup of pediatric-onset multiple sclerosis (POMS) patients infected with SARS CoV2.

Methods

The Network of Pediatric Multiple Sclerosis Centers (NPMSC), a consortium of 10 US pediatric multiple sclerosis (MS) centers contributes clinical information about POMS patients and demyelinating disorders to a centralized database, the Pediatric Demyelinating Disease Database (PeMSDD), to facilitate research for this rare disorder. In addition to collecting clinical data on clinical course, comorbidities, disease modifying therapy use, and functional status, the NPMSC developed a screening questionnaire to administer to patients during standard of care visits to further evaluate their COVID- 19 status. Additionally POMS patients with confirmed or highly suspected COVID-19, will be assessed for risk factors including smoking use, recent glucocorticoid use, comorbidities; clinical presentation, including symptoms, radiological and laboratory data; COVID-19 treatments and outcomes. POMS patients will also complete the COViMS (COVID-19 Infections in MS & Related Diseases) database, a joint effort of the US National MS Society and the Consortium of MS Centers to capture information on outcomes of people with MS and other central nervous system (CNS) demyelinating diseases (Neuromyelitis Optica Spectrum Disease, or MOG antibody disease) who have developed COVID-19. Together with data collected from the PeMSDD, we will present comprehensive data on the POMS patient experience with COVID-19 and compare it to POMS patients without known or suspected COVID-19.

Results

Data collection continues. Results available by the meeting due date will describe the demographics, risk factors, treatments and outcomes of POMS with COVID-19.

Conclusions

Conclusions will be drawn pending results of data analysis. We anticipate reporting on demographic data, risk factors, outcomes and any associations with disease modifying therapy.

Background

Intrathecal IgM synthesis was reported to be associated with higher clinical disease activity and severity. We found an association also with earlier use of high efficacy treatments in relapsing MS (RMS).

Objectives

To explore whether patients with intrathecal IgM synthesis show a) higher serum neurofilament light chain levels (sNfL) as a reflection of neuronal damage, or b) signs of increased disease severity in cerebral MRI, in patients with RMS followed in the Swiss MS Cohort Study.

Methods

487 patients were categorized by presence of oligoclonal IgG bands (OCGB) and intrathecally produced IgG/M:

1) OCGB-/IgG-/IgM- (reference [ref]);

2) OCGB+/IgG-/IgM-;

3) OCGB+/IgG+/IgM- and

4) OCGB+/IgG+/IgM+.

sNfL was measured (at baseline and every 6- or 12 months) with the NF-light^® assay. Age-dependent sNfL z-scores (sNfLz) were modelled in 8865 healthy control samples to reflect the deviation of a patient sNfL value compared to mean values observed in same age healthy controls. Yearly T2 lesion number and occurrence of new/enlarging T2 lesions were automatically assessed in cerebral MRIs and checked manually. Contrast enhancing lesions (CEL) were manually quantified. Linear or negative binomial mixed models were used to investigate the associations between the four CSF Ig patterns and longitudinal sNfLz and MRI measures, adjusted for DMT and other covariates.

Results

IgM+ patients had higher sNfLz vs reference (estimate 0.50 [CI 0.12, 0.89], p=0.011), whereas those with only OCGB+ (0.11 [-0.28, 0.50], p=0.582) or with OCGB+/IgG+ (0.20 [-0.16, 0.56], p=0.270) did not (n=2970 observations). This was confirmed when analyzing only untreated patients adjusting for T2 and CEL numbers (1.16 [0.47, 1.86], p<0.01 vs 0.58 [-0.11, 1.27], p=0.1022 vs 0.51 [-0.11, 1.13], p=0.108 vs ref, respectively) (n=234).

IgM+ patients had 2.28-fold more T2 lesions ([1.51, 3.44], p<0.01) vs ref; for patients with only OCGB+ (1.61 [1.07, 2.43], p=0.0237) or OCGB+/IgG+ (1.58 [CI 1.08, 2.32], p=0.0179) (n=1580) this association was weaker.

IgM+ was associated with a 2.47-fold risk for new/enlarging T2 lesions on yearly follow-up MRIs vs ref (2.47 [1.28, 4.78], p<0.01) but not the two other patient groups (1.84 [CI 0.93; 3.65], p=0.0799 and 1.61 [CI 0.87; 2.95], p=0.1280) (n=861).

Conclusions

Intrathecal IgM synthesis was consistently associated with quantitative measures of neuro-axonal injury and disease severity in RMS. Our findings strongly support the clinical utiliy of this biomarker.

Background

In relapsing MS, blood NfL has emerged as a promising biomarker of disease activity and worsening. The ability of serum NfL (sNfL) to detect relapse-independent disability progression is less well established.

Objectives

We investigated whether patients followed in the Swiss Multiple Sclerosis Cohort (SMSC) without any relapses during follow-up, had higher sNfL levels when experiencing confirmed disability progression independent of relapses (PIRA) as compared to stable patients. Secondly, we explored whether baseline (BL) sNfL could predict PIRA.

Methods

BL and 6- or 12-monthly follow-up sNfL were measured by Simoa NF-light^® assay in 4608 samples from 806 relapse-free MS patients and 8865 serum samples from 4133 healthy controls (median age 45 yrs). Age-dependent sNfL z-scores (sNfLz) were modeled in healthy controls using a generalised additive model for location scale and shape to reflect the deviation of a patient sNfL value from the mean value of same age healthy controls. PIRA was defined as an EDSS increase of ≥1.5 steps if baseline EDSS 0, ≥1.0 if 1.0-5.5, or ≥0.5 if >5.5, confirmed after ≥6 months. We used mixed effects models to investigate the association between PIRA, clinical parameters, disease modifying treatment, and log(sNfL) as dependent variable at each sampling. The predictive value of BL sNfLz was investigated by uni- and multivariable Cox proportional hazards models.

Results

806 (4608 samples) of 1399 patients in the SMSC did not experience relapses during a median follow-up of 4.7 years (57.6%; BL: 715 RRMS, 43 SPMS, 48 PPMS; median age 42 yrs; samples/patient: 5; EDSS 2.0). PIRA occurred in 153/806 (19.0%). In a multivariable model, sNfL was positively associated with age (1.7%/year [95%CI 1.5;2.0], p<0.001) and EDSS at BL (7.6%/step, [5.8;9.6], p<0.001), whereas it was decreased when sampled during monoclonal antibody therapy (-10.8%, [-14.7;-6.6], p<0.001) or oral MS treatments (-10.4%, [-14.1;-6.5%], p<0.001) as compared to untreated timepoints. Importantly, patients experiencing PIRA had 11.6% higher sNfL levels, compared with stable patients (4.5;19.2, p=0.001). The hazard of future PIRA increased by 23.5% (8.3;40.8, p=0.002) per 1 standard deviation higher BL sNfLz. This finding was confirmed after adjusting for age, EDSS score and treatment at BL (27.8%, [11.5;46.5], p<0.001; sNfLz > 2: 2.5-fold risk [95%CI 1.7-3.9], p<0.001 for PIRA event vs. sNfLz < 2).

Conclusions

Our data support the value of sNfL to capture and predict neuro-axonal injury leading to disability progression independent from relapses.

Background

Serum neurofilament light chain (sNfL) levels reflect neuroaxonal damage and relate to disease activity in MS. sNfL may qualify as well as a biomarker of suboptimal treatment response to disease modifying therapies (DMT). Establishment of age-dependent reference ranges in healthy controls is a prerequisite for developing this biomarker for clinical use.

Objectives

To compare on-treatment sNfL levels with values from a healthy control cohort and to investigate the effect of DMTs on sNfL levels in patients from the Swiss MS Cohort Study.

Methods

sNfL was measured (at baseline and every 6- or 12 months) with the NF-light® assay. Age-dependent sNfL z-scores (sNfLz) were modeled in healthy controls using a generalized additive model for location scale and shape to reflect the deviation of a patient sNfL value from the mean value of same age healthy controls. Linear mixed models were used to investigate the associations between clinical characteristics, DMT and longitudinal sNfLz. Interaction terms and splines were used to model sNfLz and for comparison log(NfL), and their dynamics under treatment.

Results

sNfL was measured in 1368 patients with 7550 longitudinal samples (baseline: median age: 41.9 yrs; 5.4% CIS, 83.2% RRMS, 5.6% SPMS, 5.8% PPMS; median EDSS: 2.0; median follow-up: 4.6 yrs) and 4133 healthy controls with 8865 samples (median age: 44.8 yrs). In the multivariable model, sNfLz increased with EDSS (0.131/step, [95% CI 0.101;0.161]), recent (<120 days) relapse (0.739 [0.643;0.835]) decreased with age (-0.014/year [-0.02;-0.009]), and time on DMT (-0.040/year [-0.054;-0.027]); sNfLz were lower when sampled while on more effective DMT (oral versus platform injectables: -0.229 [-0.344;-0.144]; monoclonal antibodies (mAB) versus platform injectables: -0.349 [-0.475;-0.224]), (p<0.001 for all associations). sNfLz were inversely associated with the hierarchy in efficacy of mAB over orals and orals over platform therapies with regard to slope and extent of decrease (interaction between time under DMT and DMT class: p<0.001). sNfLz, but not log(NfL) showed normalization of sNfL levels by mAB to healthy control levels.

Conclusions

The dynamic change of sNfLz on DMT reflects closely their relative clinical efficacy and is more meaningful than log(sNfL) by excluding age as a confounding factor. Use of sNfLz based on a large normative database as an age-independent sNfL measure improves the accuracy of the sNfL signal and hence their clinical utility.

Background

Studies examining the role of the microbiota in multiple sclerosis (MS) often focus on the gut bacteria; few have considered a potential role of gut mycobiota. Methods for evaluating gut mycobiota are lacking and require systematic evaluation of sequencing protocols, reference databases, and bioinformatics pipelines to properly investigate possible gut mycobiome influences on MS.

Objectives

We set out to evaluate the performance of different sequencing conditions and analytical approaches for characterizing the gut mycobiome in a cohort of healthy individuals and cases with monophasic acquired demyelinating syndrome (mono ADS) or pediatric-onset MS.

Methods

We first assessed a mock-community control pool of known, staggered quantities of 19 defined fungal organisms. We then assessed 201 stool samples obtained from our cohort of 52 healthy individuals, 49 individuals with mono ADS, and 46 participants with pediatric-onset MS. The fungal internal transcribed spacer (ITS) 2 region was sequenced using the Illumina® MiSeq platform. Varying concentrations of PhiX Control v3 Library spike-in were tested to address low-complexity amplicon sequencing. Generated sequences were characterized by the UNITE database—a curated collection of eukaryotic ITS sequences—in conjunction with three distinct fungal sequence analysis pipelines: LotuS, mothur, and PIPITS.

Results

Taxa identified in our mock-community differed across sequencing conditions but were similar between technical replicates. LotuS correctly classified 7 taxa at species-level, 7 taxa at genus-level, whereas 5 remained unclassified. Mothur correctly identified 5 species-level taxa, 11 genus-level taxa, whereas 3 remained unclassified. Lastly, PIPITS correctly identified only 3 species-level taxa, 12 genus-level, while 4 remained unclassified. We successfully generated sequence data for 112 of 147 (76%) individuals (70 females; 42 males). The mean age at stool sample collection was 17.3 (SD 5.1) years. Of the tested sequencing conditions, a spike-in of 50% PhiX produced the highest-quality reads.

Conclusions

The LotuS pipeline best identified fungal taxa in our mock-community, with optimal resolution to species level. Sequencing read quality was optimal when 50% PhiX was used for sequencing ITS2 amplicon libraries of stool samples. Establishment of this validated sequencing pipeline, confirmed using a mock-community with known fungal identities, will aid characterization of gut mycobiomes for our cohort of individuals with/without pediatric-onset MS.

Background

The gut microbiota may influence multiple sclerosis (MS) onset. Pediatric MS offers the opportunity to examine pathological processes close to risk acquisition.

Objectives

To examine the gut microbiota from stool samples of persons with pediatric onset MS, or monophasic acquired demyelinating syndromes (ADS) and unaffected controls in a case-control study.

Methods

Persons ≤21 years old with symptom onset <18 years of age with either MS (McDonald criteria) or ADS were eligible, as were unaffected controls with no known neurological or immune-mediated condition (migraine, asthma/allergies were permissible) were enrolled via the Canadian Pediatric Demyelinating Disease Network. Stools were collected between Nov/2015–Mar/2018, shipped on ice, and stored at -80°C. The 16S ribosomal RNA gene (V4 region) was amplified from extracted DNA and sequenced via the Illumina MiSeq platform. Amplicon sequence variants were used to compare the gut microbiota by disease status (MS/ADS/controls). The MS cases were also compared by disease-modifying drug (DMD) status (exposed/naïve). Negative binomial regression was used for genus-level analyses, with rate ratios adjusted (aRR) for age and sex.

Results

Of the 32/41/36 included MS/ADS/control participants, 24/23/21 were girls, averaging age 16.5/13.8/15.1 years at stool sample, respectively. The MS/ADS cases were 14.0/6.9 years at symptom onset. The 3 groups (MS/ADS/controls) were relatively similar for: body mass index (median: 22.8/19.7/19.9), presence of constipation (number of participants with a Bristol Stool Scale score of 1 or 2=8/9/7) and diet (% caloric intake for fat (median)=34/35/34 and for fibre (median)=9/10/11 g/day). Nine MS cases (28%) were DMD naïve. Gut microbiota diversity (alpha and beta) did not differ by disease (MS/ADS/controls), or DMD status (all p>0.1), while taxa-level findings did. For example, relative abundance of the Proteobacteria, Sutterella was depleted for MS cases vs controls and MS vs ADS cases (aRR:0.13;95%CI:0.03–0.59 and 0.21;95%CI:0.05–0.98), but did not differ for the ADS cases vs controls or by DMD status for the MS cases (all p>0.1). Several of the butyrate-producing genera within the Clostridia class (Firmicutes phylum) —Ruminococcaceae UCG−003, Lachnospiraceae UCG−008 and UCG−004—exhibited similar patterns.

Conclusions

Gut microbiota diversity was similar for individuals with pediatric MS relative to either monophasic ADS or unaffected controls. However, at the taxa-level, differences were observed which differentiated the MS cases from the monophasic ADS cases and controls.

Background

Myelin oligodendrocyte glycoprotein (MOG) antibodies (ab) are detected in approximately 1/3 of children with demyelinating disease at onset; presentations commonly overlap with optic neuritis, neuromyelitis optica spectrum disorder (NMOSD) or acute disseminated encephalomyelitis. Serum MOG-ab titers have unclear relevance to disease course, and optimal treatment strategy is unknown.

Objectives

We aimed to characterize children with CNS demyelinating disorders who tested positive for MOG-ab. We also aimed to evaluate the relevance of serum MOG-ab titers for diagnosis, risk and severity of subsequent demyelinating events. Finally, we aimed to evaluate treatment strategies for MOG-ab positive children.

Methods

This retrospective study evaluated children with demyelinating disorders with onset before 18 years of age seen at the University of California, San Francisco who tested positive for MOG-ab (tested by live cell-based fluorescent activated cell sorting assay at Mayo Clinic) between October 2006-June 2020. Demographic information, clinical presentation at onset, MRI, CSF, brain biopsy, and treatment data were collected by chart review.

Results

Sixty children were included (mean onset age 8.2 years; 53% female; 72% white; 40% Hispanic or Latino). The most common clinical localization at onset included optic nerve (ON) (53%) and/or brainstem/cerebellum (42%). 83% of initial events were severe. Median EDSS assessed within 6 months of onset was 1.5 (range 0-4). 81% of initial brain MRIs had T2 bright lesions and 61% had gadolinium-enhancing lesions; T2 bright lesions were most commonly seen in subcortical areas (50%) and/or brainstem/cerebellum (33%). Oligoclonal bands were positive in 17% of initial CSF. 57% had initial serum MOG-ab titers ≥1:100 (median time from onset to first titer 15.4 months). Titers ≥1:320 were only observed within 2 months of an event (disease onset or relapse). While 38% had no relapses (mean follow-up 1.42 years), those who did had a median of 2 relapses (mean follow-up 3.83 years). The most commonly used treatments were interferon beta (28%) and rituximab (27%). Brain biopsy was performed in 2 patients and showed overt demyelination and prominent infiltration of monocyte lineage and polymorphonuclear cells.

Conclusions

The most common clinical onset localizations in MOG-ab positive children were ON and brainstem/cerebellum. Higher MOG-ab titers were only observed close to a clinical event.

Background

Neuromyelitis optica spectrum disorder (NMOSD) is a rare autoimmune condition which can led to significant disability. Approximately 4% of the NMOSD cases are pediatric onset. At present, there are limited studies that aim at guiding physicians in their treatment choices for NMOSD in children.

Objectives

To evaluate the effect of different disease modifying therapies (DMT) with respect to attack prevention in children with NMOSD.

Methods

Cohort study that included 12 clinical centers participating in the US Network of Pediatric MS Centers. Cases were validated for NMOSD diagnostic criteria and classified via serostatus as AQP4+, MOG+, or double-seronegative (DS). Clinical data, including demographics, attack details, type of initial DMT (rituximab, mycophenolate mofetil, azathioprine, IVIg) and neurological visit data were extracted from charts, centrally collected in a database, and analyzed. Treatment response in the three serostatus subgroups was evaluated. Effect of DMTs on annualized relapse rate (ARR) was assessed by negative binomial regression.

Results

111 pediatric patients with NMOSD were identified: 80 AQP4+, 10 MOG+, 14 double seronegative (DS), and 7 with unknown serostatus (94 females and 17 males; 48 white, 47 African American, 13 other races). Mean follow-up duration was 1.9 years (SD±2.2). About 6% of patients were treatment-naive. First-line DMTs varied by serostatus: in the AQP4+ subgroup 42% used rituximab, 16% mycophenolate mofetil, 16% azathioprine, and 8% IVIg. Among MOG+ patients, 13% received rituximab, 13% azathioprine, 13% mycophenolate, and 38% IVIg. Within the DS group, rituximab was used in 21% of cases, azathioprine in 7%, mycophenolate in 21%, and IVIg in 21%. In the unknown serogroup, 33% received rituximab, 17% azathioprine, 0% mycophenolate, and 33% IVIg. The ARR calculated in all the serogroups was 0.25 (95% CI 0.13-0.46) for rituximab, 0.73 (95% CI 0.27-2.00) for azathioprine, 0.40 (95% CI 0.18-0.89) for mycophenolate, and 0.56 (95% CI 0.26-1.20) for IVIg. In the AQP4+ subgroup, the patients started on rituximab showed an ARR of 0.25 (95% CI 0.13-0.48), those on azathioprine an ARR of 0.76 (95% CI 0.24-2.39), those on mycophenolate an ARR 0.43 (95% CI 0.17-1.07), and those on IVIg an ARR of 0.63 (95% CI 0.26-1.55).

Conclusions

This retrospective study showed that rituximab is associated with a lowered annual relapse rate in pediatric NMOSD and in particular in the AQP4+ subgroup.