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ObjectivePrimary progressive multiple sclerosis (PPMS) causes accumulation of neurological disability from disease onset without clinical attacks typical of relapsing multiple sclerosis (RMS). However, whether genetic variation influences the disease course remains unclear. We aimed to determine whether mutations causative of neurological disorders that share features with multiple sclerosis (MS) contribute to risk for developing PPMS.MethodsWe examined whole-genome sequencing (WGS) data from 38 PPMS and 81 healthy subjects of European ancestry. We selected pathogenic variants exclusively found in PPMS patients that cause monogenic neurological disorders and performed two rounds of replication genotyping in 746 PPMS, 3,049 RMS, and 1,000 healthy subjects. To refine our findings, we examined the burden of rare, potentially pathogenic mutations in 41 genes that cause hereditary spastic paraplegias (HSPs) in PPMS (n = 314), secondary progressive multiple sclerosis (SPMS; n = 587), RMS (n = 2,248), and healthy subjects (n = 987) genotyped using the MS replication chip.ResultsWGS and replication studies identified three pathogenic variants in PPMS patients that cause neurological disorders sharing features with MS: KIF5A p.Ala361Val in spastic paraplegia 10; MLC1 p.Pro92Ser in megalencephalic leukodystrophy with subcortical cysts, and REEP1 c.606 + 43G>T in Spastic Paraplegia 31. Moreover, we detected a significant enrichment of HSP-related mutations in PPMS patients compared to controls (risk ratio [RR] = 1.95; 95% confidence interval [CI], 1.27-2.98; p = 0.002), as well as in SPMS patients compared to controls (RR = 1.57; 95% CI, 1.18-2.10; p = 0.002). Importantly, this enrichment was not detected in RMS.InterpretationThis study provides evidence to support the hypothesis that rare Mendelian genetic variants contribute to the risk for developing progressive forms of MS. Ann Neurol 2018;83:51-63.

Low serum levels of 25-hydroxyvitamin D [25(OH)D] and low sunlight exposure are known risk factors for the development of multiple sclerosis. Add-on vitamin D supplementation trials in established multiple sclerosis have been inconclusive. The effects of vitamin D supplementation to prevent multiple sclerosis is unknown. We aimed to test the hypothesis that oral vitamin D3 supplementation in high-risk clinically isolated syndrome (abnormal MRI, at least three T2 brain and/or spinal cord lesions), delays time to conversion to definite multiple sclerosis, that the therapeutic effect is dose-dependent, and that all doses are safe and well tolerated. We conducted a double-blind trial in Australia and New Zealand. Eligible participants were randomized 1:1:1:1 to placebo, 1000, 5000 or 10 000 international units (IU) of oral vitamin D3 daily within each study centre (n = 23) and followed for up to 48 weeks. Between 2013 and 2021, we enrolled 204 participants. Brain MRI scans were performed at baseline, 24 and 48 weeks. The main study outcome was conversion to clinically definite multiple sclerosis based on the 2010 McDonald criteria defined as either a clinical relapse or new brain MRI T2 lesion development. We included 199 cases in the intention-to-treat analysis based on assigned dose. Of these, 116 converted to multiple sclerosis by 48 weeks (58%). Compared to placebo, the hazard ratios (95% confidence interval) for conversion were 1000 IU 0.87 (0.50, 1.50); 5000 IU 1.37 (0.82, 2.29); and 10 000 IU 1.28 (0.76, 2.14). In an adjusted model including age, sex, latitude, study centre and baseline symptom number, clinically isolated syndrome onset site, presence of infratentorial lesions and use of steroids, the hazard ratios (versus placebo) were 1000 IU 0.80 (0.45, 1.44); 5000 IU 1.36 (0.78, 2.38); and 10 000 IU 1.07 (0.62, 1.85). Vitamin D3 supplementation was safe and well tolerated. We did not demonstrate reduction in multiple sclerosis disease activity by vitamin D3 supplementation after a high-risk clinically isolated syndrome. [ABSTRACT FROM AUTHOR]

It is unknown whether the currently known risk factors of multiple sclerosis reflect the etiology of progressive-onset multiple sclerosis (POMS) as observational studies rarely included analysis by type of onset. We designed a case–control study to examine associations between environmental factors and POMS and compared effect sizes to relapse-onset MS (ROMS), which will offer insights into the etiology of POMS and potentially contribute to prevention and intervention practice. This study utilizes data from the Primary Progressive Multiple Sclerosis (PPMS) Study and the Australian Multi-center Study of Environment and Immune Function (the AusImmune Study). This report outlines the conduct of the PPMS Study, whether the POMS sample is representative, and the planned analysis methods. The study includes 155 POMS, 204 ROMS, and 558 controls. The distributions of the POMS were largely similar to Australian POMS patients in the MSBase Study, with 54.8% female, 85.8% POMS born before 1970, mean age of onset of 41.44 ± 8.38 years old, and 67.1% living between 28.9 and 39.4° S. The POMS were representative of the Australian POMS population. There are some differences between POMS and ROMS/controls (mean age at interview: POMS 55 years vs. controls 40 years; sex: POMS 53% female vs. controls 78% female; location of residence: 14.3% of POMS at a latitude ≤ 28.9°S vs. 32.8% in controls), which will be taken into account in the analysis. We discuss the methodological issues considered in the study design, including prevalence-incidence bias, cohort effects, interview bias and recall bias, and present strategies to account for it. Associations between exposures of interest and POMS/ROMS will be presented in subsequent publications. [ABSTRACT FROM AUTHOR]

Background and purpose: The validity, reliability, and longitudinal performance of the Patient‐Determined Disease Steps (PDDS) scale is unknown in people with multiple sclerosis (MS) with mild to moderate disability. We aimed to examine the psychometric properties and longitudinal performance of the PDDS. Methods: We included relapsing–remitting MS patients with an Expanded Disability Status Scale (EDSS) score of less than 4. Validity and test–retest reliability was examined. Longitudinal data were analysed with mixed‐effect modelling and Cohen's kappa for concordance in confirmed disability progression (CDP). Results: We recruited a total of 1093 participants, of whom 904 had complete baseline data. The baseline correlation between PDDS and EDSS was weak (ρ = 0.45, p < 0.001). PDDS had stronger correlations with patient‐reported outcomes (PROs). Conversely, EDSS had stronger correlations with age, disease duration, Kurtzke's functional systems and processing speed test. PDDS test–retest reliability was good to excellent (concordance correlation coefficient = 0.73–0.89). Longitudinally, PDDS was associated with EDSS, age and depression. A higher EDSS score was associated with greater PDSS progression. The magnitude of these associations was small. There was no concordance in CDP as assessed by PDDS and EDSS. Conclusion: The PDDS has greater correlation with other PROs but less correlation with other MS‐related outcome measures compared to the EDSS. There was little correlation between PDDS and EDSS longitudinally. Our findings suggest that the PDDS scale is not interchangeable with the EDSS. [ABSTRACT FROM AUTHOR]

Background and purpose: Understanding predictors of changes in employment status among people living with multiple sclerosis (MS) can assist health care providers to develop appropriate work retention/rehabilitation programs. We aimed to model longitudinal transitions of employment status in MS and estimate the probabilities of retaining employment status or losing or gaining employment over time in individuals with a first clinical diagnosis of central nervous system demyelination (FCD). Methods: This prospective cohort study comprised adults (aged 18–59 years) diagnosed with FCD (n = 237) who were followed for more than 11 years. At each review, participants were assigned to one of three states: unemployed, part‐time, or full‐time employed. A Markov multistate model was used to examine the rate of state‐to‐state transitions. Results: At the time of FCD, participants with full‐time employment had an 89% chance of being in the same state over a 1‐year period, but this decreased to 42% over the 10‐year follow‐up period. For unemployed participants, there was a 92% likelihood of remaining unemployed after 1 year, but this probability decreased to 53% over 10 years. Females, those who progressed to clinically definite MS, those with a higher relapse count, and those with a greater level of disability were at increased risk of transitioning to a deteriorated employment state. In addition, those who experienced clinically significant fatigue over the follow‐up period were less likely to gain employment after being unemployed. Conclusions: In our FCD cohort, we found a considerable rate of employment transition during the early years post‐diagnosis. Over more than a decade of follow‐up post‐FCD, we found that females and individuals with a greater disability and a higher relapse count are at higher risk of losing employment. [ABSTRACT FROM AUTHOR]

Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.

Background and purpose: Epstein–Barr virus (EBV) is implicated in multiple sclerosis (MS) risk; evidence for other herpesviruses is inconsistent. Here, we test blood markers of infection with human herpesvirus 6 (HHV‐6), varicella zoster virus (VZV), and cytomegalovirus (CMV) as risk factors for a first clinical diagnosis of central nervous system demyelination (FCD) in the context of markers of EBV infection. Methods: In the Ausimmune case–control study, cases had an FCD, and population controls were matched on age, sex, and study region. We quantified HHV‐6‐ and VZV‐DNA load in whole blood and HHV‐6, VZV, and CMV antibodies in serum. Conditional logistic regression tested associations with FCD risk, adjusting for Epstein–Barr nuclear antigen (EBNA) IgG, EBV‐DNA load, and other covariates. Results: In 204 FCD cases and 215 matched controls, only HHV‐6‐DNA load (positive vs. negative) was associated with FCD risk (adjusted odds ratio = 2.20, 95% confidence interval = 1.08–4.46, p = 0.03). Only EBNA IgG and HHV‐6‐DNA positivity were retained in a predictive model of FCD risk; the combination had a stronger association than either alone. CMV‐specific IgG concentration modified the association between an MS risk‐related human leucocyte antigen gene and FCD risk. Six cases and one control had very high HHV‐6‐DNA load (>1.0 × 106 copies/mL). Conclusions: HHV‐6‐DNA positivity and high load (possibly due to inherited HHV‐6 chromosomal integration) were associated with increased FCD risk, particularly in association with markers of EBV infection. With growing interest in prevention/management of MS through EBV‐related pathways, there should be additional consideration of the role of HHV‐6 infection. [ABSTRACT FROM AUTHOR]

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]

Background: Consumption of ultra-processed foods (UPFs) has been linked to risk of chronic diseases, with scant evidence in relation to multiple sclerosis (MS). Methods: We tested associations between UPF consumption and likelihood of a first clinical diagnosis of central nervous system demyelination (FCD) (267 cases, 508 controls), a common precursor to MS. We used data from the 2003–2006 Ausimmune Study and logistic regression with full propensity score matching for age, sex, region of residence, education, smoking history, body mass index, physical activity, history of infectious mononucleosis, dietary misreporting, and total energy intake. Results: Higher UPF consumption was statistically significantly associated with an increased likelihood of FCD (adjusted odds ratio = 1.08; 95% confidence interval = 1.0,1.15; p = 0.039), representing an 8% increase in likelihood of FCD per one energy-adjusted serving/day of UPFs. Conclusion: Higher intakes of UPF were associated with increased likelihood of FCD in this Australian cohort. Nutrition education and awareness of healthy eating patterns may benefit those at high risk of FCD. [ABSTRACT FROM AUTHOR]