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Multiple sclerosis (MS) is an autoimmune inflammatory demyelinating central nervous system disorder that is more common in women, with onset often during reproductive years. The female:male sex ratio of MS rose in several regions over the last century, suggesting a possible sex by environmental interaction increasing MS risk in women. Since many with MS are in their childbearing years, family planning, including contraceptive and disease-modifying therapy (DMT) counselling, are important aspects of MS care in women. While some DMTs are likely harmful to the developing fetus, others can be used shortly before or until pregnancy is confirmed. Overall, pregnancy decreases risk of MS relapses, whereas relapse risk may increase postpartum, although pregnancy does not appear to be harmful for long-term prognosis of MS. However, ovarian aging may contribute to disability progression in women with MS. Here, we review sex effects across the lifespan in women with MS, including the effect of sex on MS susceptibility, effects of pregnancy on MS disease activity, and management strategies around pregnancy, including risks associated with DMT use before and during pregnancy, and while breastfeeding. We also review reproductive aging and sexual dysfunction in women with MS.

Background: The relationship between coronavirus disease 2019 (COVID-19) infection and multiple sclerosis (MS) relapse and disease progression remains unclear. Previous studies are limited by small sample sizes and most lack a propensity-matched control cohort. Objective: To evaluate the effect of COVID-19 infection on MS disease course with a large propensity-matched cohort. Design: This multi-centre cohort study analysed relapse and disability outcomes post-COVID-19 infection after balancing covariates using a propensity score matching method. The study period was from the 11th of September 2019 to the 16th of February 2023. The mean follow-up period was 1.7 years. Methods: Data were retrieved from the MSBase Registry. Propensity scores were obtained based on age, sex, disease duration, baseline Expanded Disability Status Scale (EDSS), MS course, relapses pre-baseline, disease-modifying therapy (DMT) class and country. Primary outcomes were time to first relapse, annualised relapse rate (ARR) and time to confirm EDSS progression. Secondary outcomes were time to EDSS of 3, 4 or 6. Sensitivity analyses with baseline DMT classes were performed. Results: The study included 2253 cases and 6441 controls. After matching, there were 2161 cases and an equal number of matched controls. Cases had a significantly higher ARR (ARR = 0.10 [95% CI 0.09–0.11]) compared to controls (ARR = 0.07 [95% CI 0.06–0.08]). Cases had a significantly greater hazard of time to first relapse compared to controls (hazard ratio (HR) = 1.54 [95% CI 1.29–1.84]). There was no association between COVID-19 infection and 24-week EDSS progression (HR = 1.18 [95% CI 0.92–1.52]), or time to EDSS of 3, 4 or 6. For patients on interferons and glatiramer acetate (BRACE), COVID-19 infection was associated with a greater hazard of time to first relapse (HR = 1.83 [95% CI 1.25–2.68]) and greater hazard of time to EDSS of 3 (HR = 2.04 [95% CI 1.06–3.90]) compared to patients on BRACE therapy without COVID-19 infection. Conclusion: COVID-19 infection was associated with a significantly increased MS relapse rate and a shorter time to first relapse. There was no effect on confirmed EDSS progression over the short term. These results support ongoing COVID-19 risk minimisation strategies to protect patients with MS. [ABSTRACT FROM AUTHOR]

Background: The International Multiple Sclerosis Genetics Consortium and MultipleMS Consortium recently reported a genetic variant associated with multiple sclerosis (MS) severity. However, it remains unclear if these variants remain associated with more robust, longitudinal measures of disease severity. Methods: We examined the top variant, rs10191329, from Harroud et al.'s study in 1813 relapse-onset MS patients from the MSBase Registry to assess association with longitudinal disease severity. Results: Our analysis revealed no significant association between rs10191329 genotype and longitudinal binary disease severity (p > 0.05). Conclusion: These findings highlight the complexity of genetic factors mediating long-term MS outcomes and the need for further research. [ABSTRACT FROM AUTHOR]

This letter responds to comments made by other researchers regarding a previous article on the genetics of multiple sclerosis severity. The authors disagree with the criticism of their power calculations and explain that their study was not a discovery project but rather aimed to validate the effect of a specific genetic variant. They also highlight differences between their study and others, including the use of a different cohort and a different definition of disease severity. The authors emphasize the complexity of the genetic association with MS progression and the need for further research using modern approaches. They conclude by inviting collaboration to replicate their findings using machine learning methodology. [Extracted from the article]

This document is an editorial published in Frontiers in Neurology titled "Aging in multiple sclerosis: from childhood to old age, in women and men." The editorial discusses various aspects of multiple sclerosis (MS) related to aging, including the impact of MS on different age groups, menopause, reproductive issues, treatment considerations, working ability, socio-economic burden, and frailty. The authors highlight the importance of timely diagnosis, the role of aging and sex hormones, and the use of magnetic resonance imaging (MRI) in understanding the aging process in MS. They also mention the influence of menopause on MS and the limited research on the incidence of cancer in MS and its treatment. The editorial concludes by suggesting further research topics that need consideration. [Extracted from the article]

Epigenetic mechanisms can regulate how DNA is expressed independently of sequence and are known to be associated with various diseases. Among those epigenetic mechanisms, DNA methylation (DNAm) is influenced by genotype and the environment, making it an important molecular interface for studying disease etiology and progression. In this study, we examined the whole blood DNA methylation profiles of a large group of people with (pw) multiple sclerosis (MS) compared to those of controls. We reveal that methylation differences in pwMS occur independently of known genetic risk loci and show that they more strongly differentiate disease (AUC = 0.85, 95% CI 0.82–0.89, p = 1.22 × 10−29) than known genetic risk loci (AUC = 0.72, 95% CI: 0.66–0.76, p = 9.07 × 10−17). We also show that methylation differences in MS occur predominantly in B cells and monocytes and indicate the involvement of cell-specific biological pathways. Overall, this study comprehensively characterizes the immune cell-specific epigenetic architecture of MS. [ABSTRACT FROM AUTHOR]

Multiple sclerosis is a leading cause of neurological disability in adults. Heterogeneity in multiple sclerosis clinical presentation has posed a major challenge for identifying genetic variants associated with disease outcomes. To overcome this challenge, we used prospectively ascertained clinical outcomes data from the largest international multiple sclerosis Registry, MSBase. We assembled a cohort of deeply phenotyped individuals of European ancestry with relapse-onset multiple sclerosis. We used unbiased genome-wide association study and machine learning approaches to assess the genetic contribution to longitudinally defined multiple sclerosis severity phenotypes in 1,813 individuals. Our primary analyses did not identify any genetic variants of moderate to large effect sizes that met genome-wide significance thresholds. The strongest signal was associated with rs7289446 (β=-0.4882, P = 2.73 × 10-7), intronic to SEZ6L on chromosome 22. However, we demonstrate that clinical outcomes in relapse-onset multiple sclerosis are associated with multiple genetic loci of small effect sizes. Using a machine learning approach incorporating over 62,000 variants together with clinical and demographic variables available at multiple sclerosis disease onset, we could predict severity with an area under the receiver operator curve of 0.84 (95% CI 0.79-0.88). Our machine learning algorithm achieved positive predictive value for outcome assignation of 80% and negative predictive value of 88%. This outperformed our machine learning algorithm that contained clinical and demographic variables alone (area under the receiver operator curve 0.54, 95% CI 0.48-0.60). Secondary, sex-stratified analyses identified two genetic loci that met genome-wide significance thresholds. One in females (rs10967273; βfemale =0.8289, P = 3.52 × 10-08), the other in males (rs698805; βmale = -1.5395, P = 4.35 × 10-08), providing some evidence for sex dimorphism in multiple sclerosis severity. Tissue enrichment and pathway analyses identified an overrepresentation of genes expressed in central nervous system compartments generally, and specifically in the cerebellum (P = 0.023). These involved mitochondrial function, synaptic plasticity, oligodendroglial biology, cellular senescence, calcium and g-protein receptor signalling pathways. We further identified six variants with strong evidence for regulating clinical outcomes, the strongest signal again intronic to SEZ6L (adjusted hazard ratio 0.72, P = 4.85 × 10-4). Here we report a milestone in our progress towards understanding the clinical heterogeneity of multiple sclerosis outcomes, implicating functionally distinct mechanisms to multiple sclerosis risk. Importantly, we demonstrate that machine learning using common single nucleotide variant clusters, together with clinical variables readily available at diagnosis can improve prognostic capabilities at diagnosis, and with further validation has the potential to translate to meaningful clinical practice change. [ABSTRACT FROM AUTHOR]