Impact of rituximab treatment regime on time to relapse in aquaporin-4 antibody positive neuromyelitis optica spectrum disorder.

BACKGROUND: Aquaporin-4 (AQP4) antibody associated neuromyelitis optica (NMOSD) requires long-term immunosuppression. Rituximab is increasingly used worldwide, however the optimal regime is not established. METHODS: We retrospectively examined different rituximab regimens in AQP4-NMOSD. Standard monotherapy (SM; 6 monthly infusions), SM plus oral steroids (SM+S), extended interval dosing (EID; guided by CD19 repopulation) and EID with oral steroids (EID+S) were compared. The primary outcome was time to first clinical relapse. Potential confounders including age, gender, number of previous relapses, and onset phenotype were included. RESULTS: 77 patients were included: 67 females, median onset age 35.6, median DSS at rituximab initiation 5.0. 39 were on SM+S, 20 SM, 6 EID, and 12 EID+S. 25/77 patients relapsed during a median follow-up of 44.0 months. No significant difference in time to first relapse was observed between any rituximab regimen. Pooled analyses to compare regimens that use standard monotherapy (SM and SM+S) against those that use extended interval dosing (EID and EID+S) showed no significant difference. Pooled analysis of regimens using steroids with those not using steroids also showed no significant difference. Adjusted Cox proportional hazard model revealed no significant difference between rituximab regimens or influence of demographic factors. 9 significant adverse events were recorded, 5 in the SM group and 4 in SM+S. CONCLUSIONS: This study provides some basis for further exploring EID as a viable option for long term treatment of AQP4-NMOSD. This may improve patient experience and consolidate use of hospital resources.

Age-specific effects of childhood body mass index on multiple sclerosis risk.

OBJECTIVE: Higher body mass index (BMI) during early life is thought to be a causal risk factor for multiple sclerosis (MS). We used longitudinal Mendelian randomisation (MR) to determine whether there is a critical window during which BMI influences MS risk. METHODS: Summary statistics for childhood BMI (n ~ 28,000 children) and for MS susceptibility were obtained from recent large genome-wide association studies (GWAS) (n = 14,802 MS, 26,703 controls). We generated exposure instruments for BMI during four non-overlapping age epochs (< 3 months, 3 months-1.5 years, 2-5 years, and 7-8 years) and performed MR using the inverse variance weighted method with standard sensitivity analyses. Multivariable MR was used to account for effects mediated via later-life BMI. RESULTS: For all age epochs other than birth, genetically determined higher BMI was associated with an increased liability to MS: Birth [Odds Ratio (OR) 0.81, 95% Confidence Interval (CI) 0.50-1.31, Number of Single-Nucleotide Polymorphisms (NSNPs) = 7, p = 0.39], Infancy (OR 1.18, 95% CI 1.04-1.33, NSNPs = 18, p = 0.01), Early childhood (OR 1.31, 95% CI 1.03-1.66, NSNPs = 4, p = 0.03), Later childhood (OR 1.34, 95% CI 1.08-1.66, NSNPs = 4, p = 0.01). Multivariable MR suggested that these effects may be mediated by effects on adult BMI. CONCLUSION: We provide evidence using MR that genetically determined higher BMI during early life is associated with increased MS risk. This effect may be driven by shared genetic architecture with later-life BMI.

Predicting Multiple Sclerosis: Challenges and Opportunities.

Determining effective means of preventing Multiple Sclerosis (MS) relies on testing preventive strategies in trial populations. However, because of the low incidence of MS, demonstrating that a preventive measure has benefit requires either very large trial populations or an enriched population with a higher disease incidence. Risk scores which incorporate genetic and environmental data could be used, in principle, to identify high-risk individuals for enrolment in preventive trials. Here we discuss the concepts of developing predictive scores for identifying individuals at high risk of MS. We discuss the empirical efforts to do so using real cohorts, and some of the challenges-both theoretical and practical-limiting this work. We argue that such scores could offer a means of risk stratification for preventive trial design, but are unlikely to ever constitute a clinically-helpful approach to predicting MS for an individual.