The immune cell transcriptome is modulated by vitamin D3 supplementation in people with a first demyelinating event participating in a randomized placebo-controlled trial.

Vitamin D deficiency is a risk factor for developing multiple sclerosis. The PrevANZ trial was conducted to determine if vitamin D3 supplementation can prevent recurrent disease activity in people with a first demyelinating event. As a sub-study of this trial, we investigated the effect of supplementation on peripheral immune cell gene expression. Participants were randomized to 1000, 5000 or 10,000 international units daily of vitamin D3 or placebo. Peripheral blood was collected at baseline and 12 weeks and sent for ribonucleic acid sequencing. Datasets from 55 participants were included. Gene expression was modulated by high dose supplementation. Antigen presentation and viral response pathways were upregulated. Oxidative phosphorylation and immune signaling pathways, including tumor necrosis factor-alpha and interleukin-17 signaling, were downregulated. Overall, vitamin D3 supplementation for 12 weeks modulated the peripheral immune cell transcriptome with induction of anti-inflammatory gene expression profiles. Our results support a dose-dependent effect of vitamin D3 supplementation on immune gene expression.

No evidence for association between rs10191329 severity locus and longitudinal disease severity in 1813 relapse-onset multiple sclerosis patients from the MSBase registry.

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.

DNA Methylation Signatures of Multiple Sclerosis Occur Independently of Known Genetic Risk and Are Primarily Attributed to B Cells and Monocytes.

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.

Evaluation of Cell-Specific Epigenetic Age Acceleration in People With Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: In multiple sclerosis (MS), accelerated aging of the immune system (immunosenescence) may be associated with disease onset or drive progression. DNA methylation (DNAm) is an epigenetic factor that varies among lymphocyte subtypes, and cell-specific DNAm is associated with MS. DNAm varies across the life span and can be used to accurately estimate biological age acceleration, which has been linked to a range of morbidities. The objective of this study was to test for cell-specific epigenetic age acceleration (EAA) in people with MS. METHODS: This was a case-control study of EAA using existing DNAm data from several independent previously published studies. Data were included if .idat files from Illumina 450K or EPIC arrays were available for both a case with MS and an age-matched and sex-matched control, from the same study. Multifactor statistical modeling was performed to assess the primary outcome of EAA. We explored the relationship of EAA and MS, including interaction terms to identify immune cell-specific effects. Cell-sorted DNA methylation data from 3 independent datasets were used to validate findings. RESULTS: We used whole blood DNA methylation data from 583 cases with MS and 643 non-MS controls to calculate EAA using the GrimAge algorithm. The MS group exhibited an increased EAA compared with controls (approximately 9 mths, 95% CI 3.6-14.4), p = 0.001). Statistical deconvolution showed that EAA is associated with MS in a B cell-dependent manner (ß int = 1.7, 95% CI 0.3-2.8), p = 0.002), irrespective of B-cell proportions. Validation analysis using 3 independent datasets enriched for B cells showed an EAA increase of 5.1 years in cases with MS compared with that in controls (95% CI 2.8-7.4, p = 5.5 × 10-5). By comparison, there was no EAA difference in MS in a T cell-enriched dataset. We found that EAA was attributed to the DNAm surrogates for Beta-2-microglobulin (difference = 47,546, 95% CI 10,067-85,026; p = 7.2 × 10-5), and smoking pack-years (difference = 8.1, 95% CI 1.9-14.2, p = 0.002). DISCUSSION: This study provides compelling evidence that B cells exhibit marked EAA in MS and supports the hypothesis that premature B-cell immune senescence plays a role in MS. Future MS studies should focus on age-related molecular mechanisms in B cells.

Conceiving complexity: Biological mechanisms underpinning the lasting effect of pregnancy on multiple sclerosis outcomes.

Multiple sclerosis (MS) is an autoimmune, demyelinating disease with the highest incidence in women of childbearing age. The effect of pregnancy on disease activity and progression is a primary concern for women with MS and their clinical teams. It is well established that inflammatory disease activity is naturally suppressed during pregnancy, followed by an increase postpartum. However, the long-term effect of pregnancy on disease progression is less understood. Having had a pregnancy before MS onset has been associated with an older age at first demyelinating event, an average delay of 3.4 years. After MS onset, there is conflicting evidence about the impact of pregnancy on long-term outcomes. The study with the longest follow-up to date showed that pregnancy was associated with a 0.36-point lower disability score after 10-years of disease in 1830 women. Understanding the biological mechanism by which pregnancy induces long-term beneficial effects on MS outcomes could provide mechanistic insights into the elusive determinants of secondary progression. Here, we review potential biological processes underlying this effect, including evidence that acute sex hormone exposure induces lasting changes to neurobiological and DNA methylation patterns, and how sustained methylation changes in immune cells can alter immune composition and function long-term.

Interferon beta treatment is a potent and targeted epigenetic modifier in multiple sclerosis.

Introduction: Multiple Sclerosis (MS) has a complex pathophysiology that involves genetic and environmental factors. DNA methylation (DNAm) is one epigenetic mechanism that can reversibly modulate gene expression. Cell specific DNAm changes have been associated with MS, and some MS therapies such as dimethyl fumarate can influence DNAm. Interferon Beta (IFNß), was one of the first disease modifying therapies in multiple sclerosis (MS). However, how IFNß reduces disease burden in MS is not fully understood and little is known about the precise effect of IFNß treatment on methylation. Methods: The objective of this study was to determine the changes in DNAm associated with INFß use, using methylation arrays and statistical deconvolutions on two separate datasets (total ntreated = 64, nuntreated = 285). Results: We show that IFNß treatment in people with MS modifies the methylation profile of interferon response genes in a strong, targeted, and reproducible manner. Using these identified methylation differences, we constructed a methylation treatment score (MTS) that is an accurate discriminator between untreated and treated patients (Area under the curve = 0.83). This MTS is time-sensitive and in consistent with previously identified IFNß treatment therapeutic lag. This suggests that methylation changes are required for treatment efficacy. Overrepresentation analysis found that IFNß treatment recruits the endogenous anti-viral molecular machinery. Finally, statistical deconvolution revealed that dendritic cells and regulatory CD4+ T cells were most affected by IFNß induced methylation changes. Discussion: In conclusion, our study shows that IFNß treatment is a potent and targeted epigenetic modifier in multiple sclerosis.

Parity is associated with long-term differences in DNA methylation at genes related to neural plasticity in multiple sclerosis.

BACKGROUND: Pregnancy in women with multiple sclerosis (wwMS) is associated with a reduction of long-term disability progression. The mechanism that drives this effect is unknown, but converging evidence suggests a role for epigenetic mechanisms altering immune and/or central nervous system function. In this study, we aimed to identify whole blood and immune cell-specific DNA methylation patterns associated with parity in relapse-onset MS. RESULTS: We investigated the association between whole blood and immune cell-type-specific genome-wide methylation patterns and parity in 192 women with relapse-onset MS, matched for age and disease severity. The median time from last pregnancy to blood collection was 16.7 years (range = 1.5-44.4 years). We identified 2965 differentially methylated positions in whole blood, 68.5% of which were hypermethylated in parous women; together with two differentially methylated regions on Chromosomes 17 and 19 which mapped to TMC8 and ZNF577, respectively. Our findings validated 22 DMPs and 366 differentially methylated genes from existing literature on epigenetic changes associated with parity in wwMS. Differentially methylated genes in whole blood were enriched in neuronal structure and growth-related pathways. Immune cell-type-specific analysis using cell-type proportion estimates from statistical deconvolution of whole blood revealed further differential methylation in T cells specifically (four in CD4+ and eight in CD8+ T cells). We further identified reduced methylation age acceleration in parous women, demonstrating slower biological aging compared to nulligravida women. CONCLUSION: Differential methylation at genes related to neural plasticity offers a potential molecular mechanism driving the long-term effect of pregnancy on MS outcomes. Our results point to a potential 'CNS signature' of methylation in peripheral immune cells, as previously described in relation to MS progression, induced by parity. As the first epigenome-wide association study of parity in wwMS reported, validation studies are needed to confirm our findings.

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.

Whole-blood methylation signatures are associated with and accurately classify multiple sclerosis disease severity.

BACKGROUND: The variation in multiple sclerosis (MS) disease severity is incompletely explained by genetics, suggesting genetic and environmental interactions are involved. Moreover, the lack of prognostic biomarkers makes it difficult for clinicians to optimise care. DNA methylation is one epigenetic mechanism by which gene-environment interactions can be assessed. Here, we aimed to identify DNA methylation patterns associated with mild and severe relapse-onset MS (RMS) and to test the utility of methylation as a predictive biomarker. METHODS: We conducted an epigenome-wide association study between 235 females with mild (n = 119) or severe (n = 116) with RMS. Methylation was measured with the Illumina methylationEPIC array and analysed using logistic regression. To generate hypotheses about the functional consequence of differential methylation, we conducted gene set enrichment analysis using ToppGene. We compared the accuracy of three machine learning models in classifying disease severity: (1) clinical data available at baseline (age at onset and first symptoms) built using elastic net (EN) regression, (2) methylation data using EN regression and (3) a weighted methylation risk score of differentially methylated positions (DMPs) from the main analysis using logistic regression. We used a conservative 70:30 test:train split for classification modelling. A false discovery rate threshold of 0.05 was used to assess statistical significance. RESULTS: Females with mild or severe RMS had 1472 DMPs in whole blood (839 hypermethylated, 633 hypomethylated in the severe group). Differential methylation was enriched in genes related to neuronal cellular compartments and processes, and B-cell receptor signalling. Whole-blood methylation levels at 1708 correlated CpG sites classified disease severity more accurately (machine learning model 2, AUC = 0.91) than clinical data (model 1, AUC = 0.74) or the wMRS (model 3, AUC = 0.77). Of the 1708 selected CpGs, 100 overlapped with DMPs from the main analysis at the gene level. These overlapping genes were enriched in neuron projection and dendrite extension, lending support to our finding that neuronal processes, rather than immune processes, are implicated in disease severity. CONCLUSION: RMS disease severity is associated with whole-blood methylation at genes related to neuronal structure and function. Moreover, correlated whole-blood methylation patterns can assign disease severity in females with RMS more accurately than clinical data available at diagnosis.

Epigenome-wide association studies: current knowledge, strategies and recommendations.

The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.

Patient Preferences for Time and Location of Infusible Therapies in Multiple Sclerosis and Neuroimmunologic Disorders.

BACKGROUND: People with multiple sclerosis and neuroimmunologic disorders (herein referred to as patients) are increasingly treated with infusible monoclonal antibodies. This rise in demand has placed increased loads on current infusion services and mandates careful strategic planning. This study examined patient preferences for the timing and location of infusions and their association with demographic and disease variables to facilitate patient-focused strategic planning. METHODS: Ninety-one patients receiving an infusible therapy at an infusion service during March 2019 were asked to complete a questionnaire exploring eight domains, including preferences for time of infusions and location of infusion centers. Potential access to home-based treatment was included as an option. Unstructured (free-text) feedback on current service was also obtained. RESULTS: Eighty-three patients completed the survey (mean age, 42 years; 75% women). Infusions were predominantly natalizumab (66%) and ocrelizumab (25%). Of these patients, 71% were engaged in some form of work or study, and 83% of this group had to arrange time off from work or study to attend treatment. Seventy percent of patients would prefer their infusion before noon, and 60% would consider home-based infusions. Most used a car as their transport to the infusion service. CONCLUSIONS: These results suggest that patients are more likely to prefer infusible treatment in the morning and are open to home-based infusions. This study provides information for health services to target service delivery at peak preference times and consider alternate ways of delivering infusible treatments.

The Pharmacogenetics of Rituximab: Potential Implications for Anti-CD20 Therapies in Multiple Sclerosis.

There are a broad range of disease-modifying therapies (DMTs) available in relapsing-remitting multiple sclerosis (RRMS), but limited biomarkers exist to personalise DMT choice. All DMTs, including monoclonal antibodies such as rituximab and ocrelizumab, are effective in preventing relapses and preserving neurological function in MS. However, each agent harbours its own risk of therapeutic failure or adverse events. Pharmacogenetics, the study of the effects of genetic variation on therapeutic response or adverse events, could improve the precision of DMT selection. Pharmacogenetic studies of rituximab in MS patients are lacking, but pharmacogenetic markers in other rituximab-treated autoimmune conditions have been identified. This review will outline the wider implications of pharmacogenetics and the mechanisms of anti-CD20 agents in MS. We explore the non-MS rituximab literature to characterise pharmacogenetic variants that could be of prognostic relevance in those receiving rituximab, ocrelizumab or other monoclonal antibodies for MS.