Not all roads lead to the immune system: the genetic basis of multiple sclerosis severity.

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 1813 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 (ß = -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; ßfemale = 0.8289, P = 3.52 × 10-8), the other in males (rs698805; ßmale = -1.5395, P = 4.35 × 10-8), providing some evidence for sex dimorphism in multiple sclerosis severity. Tissue enrichment and pathway analyses identified an overrepresentation of genes expressed in CNS 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.

Multiple Sclerosis and Microbiome.

The composition of microbiota and the gut-brain axis is increasingly considered a factor in the development of various pathological conditions. The etiology of multiple sclerosis (MS), a chronic autoimmune disease affecting the CNS, is complex and interactions within the gut-brain axis may be relevant in the development and the course of MS. In this article, we focus on the relationship between gut microbiota and the pathophysiology of MS. We review the contribution of germ-free mouse studies to our understanding of MS pathology and its implications for treatment strategies to modulate the microbiome in MS. This summary highlights the need for a better understanding of the role of the microbiota in patients' responses to disease-modifying drugs in MS and disease activity overall.

To be or not to be vaccinated: The risk of MS or NMOSD relapse after COVID-19 vaccination and infection.

BACKGROUND: COVID-19 vaccination and infection are speculated to increase the activity of immune-mediated diseases, including multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). The aim of this study was to evaluate a short-term risk of relapse after COVID-19 vaccination and COVID-19 infection in patients with these demyelinating disorders of the central nervous system and to determine disease exacerbation risk factors. METHODS: Data in this retrospective, observational cohort study was collected via the Czech nationwide registry ReMuS from March 1, 2020, to October 30, 2021. We compared the proportion of patients with at least one clinical relapse in the 90 days following vaccination or infection to the 90-day intervals during the year before. For the evaluation of the risk factors of relapse, a comparison between groups with and without relapses after COVID-19 vaccination or infection was made. RESULTS: We identified 1661 vaccinated (90.11% BNT162b2) patients with MS without a history of COVID-19 and 495 unvaccinated patients with MS who experienced COVID-19. A mild increase in the proportion of patients with at least one clinical relapse (-360 to -270 days: 4.46%; -270 to -180: 4.27%; -180 to -90: 3.85%; -90 to 0: 3.79% vs. 0 to +90 days: 5.30%) after vaccination in patients with MS was observed, as well as a rise in the proportion of patients with at least one clinical relapse after COVID-19. Lower age was associated with MS relapse after vaccination or infection. Although there were only 17 vaccinated and eight post-COVID-19 patients with NMOSD, the results were broadly consistent with those of patients with MS. CONCLUSION: There is a mild increase in the relapse incidence after the COVID-19 vaccination. The risks, however, need to be balanced against the risks of COVID-19 itself, also leading to the rise in relapse rate and particularly to morbidity and mortality.