Assessment of Stx-1A gene polymorphism (rs1569061) in relation to the development of multiple sclerosis in Egyptian patients.

Multiple sclerosis (MS) is a multifactorial polygenic disease; results from autoimmune and neurodegenerative processes which lead to multifocal lesions of the central nervous system. Axonal degeneration was found to be prominent in the inflammation period of MS and contribute to the progression of disability. Soluble N-ethylmaleimide sensitive factor attachment receptor (SNARE) complex plays a vital role in the release of neurotransmitter by synaptic vesicle fusion. Stx-1A protein (Stx-1A), a major component of the SNARE complex, is widely expressed in brain tissue. This study intended to evaluate the prevalence of the Stx-1A gene polymorphism (rs1569061) in the Egyptian population with MS and to investigate its association with various clinical factors. This study included 65 adult Egyptian MS patients and 35 age- and sex-matched normal control subjects. Diagnosis of MS was made by an experienced neurologist according to revised McDonald criteria. All Patients underwent full history taking, included Age of onset of MS, disease duration, disease course and degree of disability according to the Expanded Disability Status Scale (EDSS) and family history of neurological diseases. Stx-1A gene polymorphism (rs1569061) genotyping was performed by TaqMan assay based quantitative real time (qPCR) and verified by sanger sequencer. Genotype and allele frequencies of (rs1569061) did not differ significantly between case and control groups. No difference was detected when comparing the genotype frequency and the allele frequency to different disease parameters. Discrepancy of the minor allele frequency (MAF) of Stx-1A gene (rs1569061) between different populations was noted. In conclusion, our study in Stx-1A gene polymorphism (rs1569061) and MS showed that no difference between the patient and control as regards gene frequency and allele frequency. Predicting no association between the studied polymorphism and MS in the Egyptian population. However, discrepancy between different population was noted as regards the MAF for Stx-1A gene (rs1569061).

Assessment of bidirectional relationships between multiple sclerosis and epilepsy: A two-sample Mendelian randomization study.

BACKGROUND AND OBJECTIVE: Epidemiological studies indicate that multiple sclerosis (MS) is associated with epilepsy. However, the causality and directionality of this association remain under-elucidated. This study aimed to reveal the causality between MS and epilepsy. METHODS: A two-sample Mendelian randomization (MR) analysis was performed by using summarized statistics derived from large genome-wide association studies of MS and epilepsy. We used the inverse variance weighted method as the primary approach, and then four other MR methods to bidirectionally evaluate the causality of the association between MS and epilepsy. Additional sensitivity analyses were performed to measure the robustness of the findings. RESULTS: Genetically predicted MS was positively correlated with developing all epilepsy [odds ratio (OR) = 1.027 (1.003-1.051), P  =  0.028] and generalized epilepsy [OR = 1.050 (1.008-1.094), P = 0.019]. In the reverse MR analysis, all epilepsy [OR = 1.310 (1.112-1.543), P = 0.001], generalized epilepsy [OR = 1.173 (1.010-1.363), P = 0.037], and focal epilepsy [OR = 1.264 (1.069-1.494), P  =  0.006] elevated the risk of developing MS. The result remained robust and congruous across all sensitivity analyses conducted. CONCLUSIONS: MS is potentially associated with a higher risk of developing epilepsy. Furthermore, epilepsy may be a causal determinant of MS risk. These findings may further the understanding of the interaction of the two conditions.

Genome-wide study of longitudinal brain imaging measures of multiple sclerosis progression across six clinical trials.

While the genetics of MS risk susceptibility are well-described, and recent progress has been made on the genetics of disease severity, the genetics of disease progression remain elusive. We therefore investigated the genetic determinants of MS progression on longitudinal brain MRI: change in brain volume (BV) and change in T2 lesion volume (T2LV), reflecting progressive tissue loss and increasing disease burden, respectively. We performed genome-wide association studies of change in BV (N = 3401) and change in T2LV (N = 3513) across six randomized clinical trials from Biogen and Roche/Genentech: ADVANCE, ASCEND, DECIDE, OPERA I & II, and ORATORIO. Analyses were adjusted for randomized treatment arm, age, sex, and ancestry. Results were pooled in a meta-analysis, and were evaluated for enrichment of MS risk variants. Variant colocalization and cell-specific expression analyses were performed using published cohorts. The strongest peaks were in PTPRD (rs77321193-C/A, p = 3.9 × 10-7) for BV change, and NEDD4L (rs11398377-GC/G, p = 9.3 × 10-8) for T2LV change. Evidence of colocalization was observed for NEDD4L, and both genes showed increased expression in neuronal and/or glial populations. No association between MS risk variants and MRI outcomes was observed. In this unique, precompetitive industry partnership, we report putative regions of interest in the neurodevelopmental gene PTPRD, and the ubiquitin ligase gene NEDD4L. These findings are distinct from known MS risk genetics, indicating an added role for genetic progression analyses and informing drug discovery.

Prioritization of risk genes in multiple sclerosis by a refined Bayesian framework followed by tissue-specificity and cell type feature assessment.

BACKGROUND: Multiple sclerosis (MS) is a debilitating immune-mediated disease of the central nervous system that affects over 2 million people worldwide, resulting in a heavy burden to families and entire communities. Understanding the genetic basis underlying MS could help decipher the pathogenesis and shed light on MS treatment. We refined a recently developed Bayesian framework, Integrative Risk Gene Selector (iRIGS), to prioritize risk genes associated with MS by integrating the summary statistics from the largest GWAS to date (n = 115,803), various genomic features, and gene-gene closeness. RESULTS: We identified 163 MS-associated prioritized risk genes (MS-PRGenes) through the Bayesian framework. We replicated 35 MS-PRGenes through two-sample Mendelian randomization (2SMR) approach by integrating data from GWAS and Genotype-Tissue Expression (GTEx) expression quantitative trait loci (eQTL) of 19 tissues. We demonstrated that MS-PRGenes had more substantial deleterious effects and disease risk. Moreover, single-cell enrichment analysis indicated MS-PRGenes were more enriched in activated macrophages and microglia macrophages than non-activated ones in control samples. Biological and drug enrichment analyses highlighted inflammatory signaling pathways. CONCLUSIONS: In summary, we predicted and validated a high-confidence MS risk gene set from diverse genomic, epigenomic, eQTL, single-cell, and drug data. The MS-PRGenes could further serve as a benchmark of MS GWAS risk genes for future validation or genetic studies.

A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis.

BACKGROUND: There exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules. RESULT: We assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omic integration of 20 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor-associated genes from several independent cohorts. Our benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS genes. The multi-omic case study using MS data revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module were differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10- 47) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS. CONCLUSIONS: We believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omic approaches for complex diseases.

Assessment of the genetic contribution to brain magnetic resonance imaging lesion load and atrophy measures in multiple sclerosis patients.

BACKGROUND AND PURPOSE: Multiple sclerosis (MS) susceptibility is influenced by genetics; however, little is known about genetic determinants of disease expression. We aimed at assessing genetic factors influencing quantitative neuroimaging measures in two cohorts of progressive MS (PMS) and relapsing-remitting MS (RRMS) patients. METHODS: Ninety-nine PMS and 214 RRMS patients underwent a 3-T brain magnetic resonance imaging (MRI) scan, with the measurement of five MRI metrics including T2 lesion volumes and measures of white matter, grey matter, deep grey matter, and hippocampal volumes. A candidate pathway strategy was adopted; gene set analysis was carried out to estimate cumulative contribution of genes to MRI phenotypes, adjusting for relevant confounders, followed by single nucleotide polymorphism (SNP) regression analysis. RESULTS: Seventeen Kyoto Encyclopedia of Genes and Genomes pathways and 42 Gene Ontology (GO) terms were tested. We additionally included in the analysis genes with enriched expression in brain cells. Gene set analysis revealed a differential pattern of association across the two cohorts, with processes related to sodium homeostasis being associated with grey matter volume in PMS (p = 0.002), whereas inflammatory-related GO terms such as adaptive immune response and regulation of inflammatory response appeared to be associated with T2 lesion volume in RRMS (p = 0.004 and p = 0.008, respectively). As for SNPs, the rs7104613T mapping to SPON1 gene was associated with reduced deep grey matter volume (ß = -0.731, p = 3.2*10-7 ) in PMS, whereas we found evidence of association between white matter volume and rs740948A mapping to SEMA3A gene (ß = 22.04, p = 5.5*10-6 ) in RRMS. CONCLUSIONS: Our data suggest a different pattern of associations between MRI metrics and functional processes across MS disease courses, suggesting different phenomena implicated in MS.

Race and ethnicity on MS presentation and disease course.

Multiple sclerosis (MS) has a strong racial and ethnic component and disproportionately affects whites of European background. Recent incidence reports suggest an increasing rate of MS among African Americans compared with whites. Despite this recent increase in MS in African Americans, Hispanics and Asians are significantly less likely to develop MS than whites of European ancestry. MS-specific mortality trends demonstrate distinctive disparities by race/ethnicity and age, suggesting that there is an unequal burden of disease. Inequalities in health along with differences in clinical characteristics that may be genetic, environmental, and social in origin may be contributing to disease variability and be suggestive of endophenotypes. The overarching goal of this review was to summarize the current understanding on the variability of disease that we observe in selected racial and ethnic populations: Hispanics and African Americans. Future challenges will be to unravel the genetic, environmental, and social determinants of the observed racial/ethnic disparities.

A quantitative neuropathological assessment of translocator protein expression in multiple sclerosis.

The 18 kDa translocator protein (TSPO) is increasingly used to study brain and spinal cord inflammation in degenerative diseases of the CNS such as multiple sclerosis. The enhanced TSPO PET signal that arises during disease is widely considered to reflect activated pathogenic microglia, although quantitative neuropathological data to support this interpretation have not been available. With the increasing interest in the role of chronic microglial activation in multiple sclerosis, characterising the cellular neuropathology associated with TSPO expression is of clear importance for understanding the cellular and pathological processes on which TSPO PET imaging is reporting. Here we have studied the cellular expression of TSPO and specific binding of two TSPO targeting radioligands (3H-PK11195 and 3H-PBR28) in tissue sections from 42 multiple sclerosis cases and 12 age-matched controls. Markers of homeostatic and reactive microglia, astrocytes, and lymphocytes were used to investigate the phenotypes of cells expressing TSPO. There was an approximate 20-fold increase in cells double positive for TSPO and HLA-DR in active lesions and in the rim of chronic active lesion, relative to normal appearing white matter. TSPO was uniformly expressed across myeloid cells irrespective of their phenotype, rather than being preferentially associated with pro-inflammatory microglia or macrophages. TSPO+ astrocytes were increased up to 7-fold compared to normal-appearing white matter across all lesion subtypes and accounted for 25% of the TSPO+ cells in these lesions. To relate TSPO protein expression to ligand binding, specific binding of the TSPO ligands 3H-PK11195 and 3H-PBR28 was determined in the same lesions. TSPO radioligand binding was increased up to seven times for 3H-PBR28 and up to two times for 3H-PK11195 in active lesions and the centre of chronic active lesions and a strong correlation was found between the radioligand binding signal for both tracers and the number of TSPO+ cells across all of the tissues examined. In summary, in multiple sclerosis, TSPO expression arises from microglia of different phenotypes, rather than being restricted to microglia which express classical pro-inflammatory markers. While the majority of cells expressing TSPO in active lesions or chronic active rims are microglia/macrophages, our findings also emphasize the significant contribution of activated astrocytes, as well as smaller contributions from endothelial cells. These observations establish a quantitative framework for interpretation of TSPO in multiple sclerosis and highlight the need for neuropathological characterization of TSPO expression for the interpretation of TSPO PET in other neurodegenerative disorders.

Landscape of MS patient cohorts and registries: Recommendations for maximizing impact.

BACKGROUND: There is a growing number of cohorts and registries collecting phenotypic and genotypic data from groups of multiple sclerosis patients. Improved awareness and better coordination of these efforts is needed. OBJECTIVE: The purpose of this report is to provide a global landscape of the major longitudinal MS patient data collection efforts and share recommendations for increasing their impact. METHODS: A workshop that included over 50 MS research and clinical experts from both academia and industry was convened to evaluate how current and future MS cohorts could be better used to provide answers to urgent questions about progressive MS. RESULTS: The landscape analysis revealed a significant number of largely uncoordinated parallel studies. Strategic oversight and direction is needed to streamline and leverage existing and future efforts. A number of recommendations for enhancing these efforts were developed. CONCLUSIONS: Better coordination, increased leverage of evolving technology, cohort designs that focus on the most important unanswered questions, improved access, and more sustained funding will be needed to close the gaps in our understanding of progressive MS and accelerate the development of effective therapies.

Assessment of Early Evidence of Multiple Sclerosis in a Prospective Study of Asymptomatic High-Risk Family Members.

Importance: Subclinical inflammatory demyelination and neurodegeneration often precede symptom onset in multiple sclerosis (MS). Objective: To investigate the prevalence of brain magnetic resonance imaging (MRI) and subclinical abnormalities among asymptomatic individuals at risk for MS. Design, Setting, and Participants: The Genes and Environment in Multiple Sclerosis (GEMS) project is a prospective cohort study of first-degree relatives of people with MS. Each participant's risk for MS was assessed using a weighted score (Genetic and Environmental Risk Score for Multiple Sclerosis Susceptibility [GERSMS]) comprising an individual's genetic burden and environmental exposures. The study dates were August 2012 to July 2015. Main Outcomes and Measures: Participants in the top and bottom 10% of the risk distribution underwent standard and quantitative neurological examination, including disability status, visual, cognitive, motor, and sensory testing, as well as qualitative and quantitative neuroimaging with 3-T brain MRI and optical coherence tomography. Results: This study included 100 participants at risk for MS, with 41 at higher risk (40 women [98%]) and 59 at lower risk (25 women [42%]), at a mean (SD) age of 35.1 (8.7) years. Given the unequal sex distribution between the 2 groups, the analyses were restricted to women (n = 65). When considering all measured outcomes, higher-risk women differed from lower-risk women (P = .01 by omnibus test). Detailed testing with a vibration sensitivity testing device in a subgroup of 47 women showed that higher-risk women exhibited significantly poorer vibration perception in the distal lower extremities (P = .008, adjusting for age, height, and testing date). Furthermore, 5 of 65 women (8%) (4 at higher risk and 1 at lower risk) met the primary neuroimaging outcome of having T2-weighted hyperintense brain lesions consistent with the 2010 McDonald MRI criteria for dissemination in space. A subset of participants harbor many different neuroimaging features associated with MS, including perivenous T2-weighted hyperintense lesions and focal leptomeningeal enhancement, consistent with the hypothesis that these individuals are at higher risk of developing clinical symptoms of MS than the general population. Conclusions and Relevance: Higher-risk asymptomatic family members of patients with MS are more likely to have early subclinical manifestations of MS. These findings underscore the importance of early detection in high-risk individuals. Trial Registration: clinicaltrials.gov Identifier: NCT01353547.

Network Modeling of Crohn's Disease Incidence.

BACKGROUND: Numerous genetic and environmental risk factors play a role in human complex genetic disorders (CGD). However, their complex interplay remains to be modelled and explained in terms of disease mechanisms. METHODS AND FINDINGS: Crohn's Disease (CD) was modeled as a modular network of patho-physiological functions, each summarizing multiple gene-gene and gene-environment interactions. The disease resulted from one or few specific combinations of module functional states. Network aging dynamics was able to reproduce age-specific CD incidence curves as well as their variations over the past century in Western countries. Within the model, we translated the odds ratios (OR) associated to at-risk alleles in terms of disease propensities of the functional modules. Finally, the model was successfully applied to other CGD including ulcerative colitis, ankylosing spondylitis, multiple sclerosis and schizophrenia. CONCLUSION: Modeling disease incidence may help to understand disease causative chains, to delineate the potential of personalized medicine, and to monitor epidemiological changes in CGD.

A Preliminary Comparative Assessment of the Role of CD8+ T Cells in Chronic Fatigue Syndrome/Myalgic Encephalomyelitis and Multiple Sclerosis.

Background. CD8+ T cells have putative roles in the regulation of adaptive immune responses during infection. The purpose of this paper is to compare the status of CD8+ T cells in Multiple Sclerosis (MS) and Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (CFS/ME). Methods. This preliminary investigation comprised 23 CFS/ME patients, 11 untreated MS patients, and 30 nonfatigued controls. Whole blood samples were collected from participants, stained with monoclonal antibodies, and analysed on the flow cytometer. Using the following CD markers, CD27 and CD45RA (CD45 exon isoform 4), CD8+ T cells were divided into naïve, central memory (CM), effector memory CD45RA- (EM), and effector memory CD45RA+ (EMRA) cells. Results. Surface expressions of BTLA, CD127, and CD49/CD29 were increased on subsets of CD8+ T cells from MS patients. In the CFS/ME patients CD127 was significantly decreased on all subsets of CD8+ T cells in comparison to the nonfatigued controls. PSGL-1 was significantly reduced in the CFS/ME patients in comparison to the nonfatigued controls. Conclusions. The results suggest significant deficits in the expression of receptors and adhesion molecules on subsets of CD8+ T cells in both MS and CFS/ME patients. These deficits reported may contribute to the pathogenesis of these diseases. However, larger sample size is warranted to confirm and support these encouraging preliminary findings.

Testing for association in case-control genome-wide association studies with shared controls.

The statistical analysis of genome-wide association studies (GWASs) with multiple diseases and shared controls (SCs) is discussed. The usual method for analyzing data from these studies is to compare each individual disease with either the SCs or the pooled controls which include other diseases. We observed that applying individual association tests can be problematic because these tests may suffer from power loss in detecting significant associations between diseases and single-nucleotide polymorphism or copy number variant. We propose here a two-stage procedure wherein we first apply an overall chi-square test for multiple diseases with SCs; if the overall test is rejected, then individual tests using the chi-square partition method will be applied to each disease against SCs. A real GWAS data set with SCs and a Monte Carlo simulation study are used to demonstrate that the proposed method is more effective and preferable than other existing methods for analyzing data from GWASs with multiple diseases and SCs.

Assessment of microRNA-related SNP effects in the 3' untranslated region of the IL22RA2 risk locus in multiple sclerosis.

Recent large-scale association studies have identified over 100 MS risk loci. One of these MS risk variants is single-nucleotide polymorphism (SNP) rs17066096, located ~14 kb downstream of IL22RA2. IL22RA2 represents a compelling MS candidate gene due to the role of IL-22 in autoimmunity; however, rs17066096 does not map into any known functional element. We assessed whether rs17066096 or a nearby proxy SNP may exert pathogenic effects by affecting microRNA-to-mRNA binding and thus IL22RA2 expression using comprehensive in silico predictions, in vitro reporter assays, and genotyping experiments in 6,722 individuals. In silico screening identified two predicted microRNA binding sites in the 3'UTR of IL22RA2 (for hsa-miR-2278 and hsa-miR-411-5p) encompassing a SNP (rs28366) in moderate linkage disequilibrium with rs17066096 (r (2) = 0.4). The binding of both microRNAs to the IL22RA2 3'UTR was confirmed in vitro, but their binding affinities were not significantly affected by rs28366. Association analyses revealed significant association of rs17066096 and MS risk in our independent German dataset (odds ratio = 1.15, P = 3.48 × 10(-4)), but did not indicate rs28366 to be the cause of this signal. While our study provides independent validation of the association between rs17066096 and MS risk, this signal does not appear to be caused by sequence variants affecting microRNA function.

MCPerm: a Monte Carlo permutation method for accurately correcting the multiple testing in a meta-analysis of genetic association studies.

Traditional permutation (TradPerm) tests are usually considered the gold standard for multiple testing corrections. However, they can be difficult to complete for the meta-analyses of genetic association studies based on multiple single nucleotide polymorphism loci as they depend on individual-level genotype and phenotype data to perform random shuffles, which are not easy to obtain. Most meta-analyses have therefore been performed using summary statistics from previously published studies. To carry out a permutation using only genotype counts without changing the size of the TradPerm P-value, we developed a Monte Carlo permutation (MCPerm) method. First, for each study included in the meta-analysis, we used a two-step hypergeometric distribution to generate a random number of genotypes in cases and controls. We then carried out a meta-analysis using these random genotype data. Finally, we obtained the corrected permutation P-value of the meta-analysis by repeating the entire process N times. We used five real datasets and five simulation datasets to evaluate the MCPerm method and our results showed the following: (1) MCPerm requires only the summary statistics of the genotype, without the need for individual-level data; (2) Genotype counts generated by our two-step hypergeometric distributions had the same distributions as genotype counts generated by shuffling; (3) MCPerm had almost exactly the same permutation P-values as TradPerm (r = 0.999; P<2.2e-16); (4) The calculation speed of MCPerm is much faster than that of TradPerm. In summary, MCPerm appears to be a viable alternative to TradPerm, and we have developed it as a freely available R package at CRAN: http://cran.r-project.org/web/packages/MCPerm/index.html.

Incidence of multiple sclerosis in multiple racial and ethnic groups.

OBJECTIVE: To determine whether the incidence of multiple sclerosis (MS) varies by race/ethnicity in a multiethnic, population-based cohort. METHODS: We conducted a retrospective cohort study of more than 9 million person-years of observation from the multiethnic, community-dwelling members of Kaiser Permanente Southern California health plan from January 1, 2008 to December 31, 2010. Incidence of MS and risk ratios comparing incidence rates between racial/ethnic groups were calculated using Poisson regression. RESULTS: We identified 496 patients newly diagnosed with MS who met McDonald criteria. The average age at diagnosis was 41.6 years (range 8.6-78.3 years) and 70.2% were women. The female preponderance was more pronounced among black (79.3%) than white, Hispanic, and Asian individuals with MS (67.8%, 68.1%, and 69.2%, respectively; p = 0.03). The incidence of MS was higher in blacks (10.2, 95% confidence interval [CI] 8.4-12.4; p < 0.0001) and lower in Hispanics (2.9, 95% CI 2.4-3.5; p < 0.0001) and Asians (1.4, 95% CI 0.7-2.4; p < 0.0001) than whites (6.9, 95% CI 6.1-7.8). Black women had a higher risk of MS (risk ratio 1.59, 95% CI 1.27-1.99; p = 0.0005) whereas black men had a similar risk of MS (risk ratio 1.04, 95% CI = 0.67-1.57) compared with whites. CONCLUSIONS: Our findings do not support the widely accepted assertion that blacks have a lower risk of MS than whites. A possible explanation for our findings is that people with darker skin tones have lower vitamin D levels and thereby an increased risk of MS, but this would not explain why Hispanics and Asians have a lower risk of MS than whites or why the higher risk of MS among blacks was found only among women.

Genomic regions associated with multiple sclerosis are active in B cells.

More than 50 genomic regions have now been shown to influence the risk of multiple sclerosis (MS). However, the mechanisms of action, and the cell types in which these associated variants act at the molecular level remain largely unknown. This is especially true for associated regions containing no known genes. Given the evidence for a role for B cells in MS, we hypothesized that MS associated genomic regions co-localized with regions which are functionally active in B cells. We used publicly available data on 1) MS associated regions and single nucleotide polymorphisms (SNPs) and 2) chromatin profiling in B cells as well as three additional cell types thought to be unrelated to MS (hepatocytes, fibroblasts and keratinocytes). Genomic intervals and SNPs were tested for overlap using the Genomic Hyperbrowser. We found that MS associated regions are significantly enriched in strong enhancer, active promoter and strong transcribed regions (p = 0.00005) and that this overlap is significantly higher in B cells than control cells. In addition, MS associated SNPs also land in active promoter (p = 0.00005) and enhancer regions more than expected by chance (strong enhancer p = 0.0006; weak enhancer p = 0.00005). These results confirm the important role of the immune system and specifically B cells in MS and suggest that MS risk variants exert a gene regulatory role. Previous studies assessing MS risk variants in T cells may be missing important effects in B cells. Similar analyses in other immunological cell types relevant to MS and functional studies are necessary to fully elucidate how genes contribute to MS pathogenesis.

Assessment of evidence for a protective role of vitamin D in multiple sclerosis.

Evidence for a role of vitamin D insufficiency in determining risk in Multiple Sclerosis (MS) is supported by studies in both pediatric- and adult-onset patients. The potential role of vitamin D in modulating MS disease activity is an area of active clinical trials research, and the possibility of primary disease prevention with vitamin D supplementation in early life is an emerging concept. With Sir Austin Bradford Hill's criteria as a framework, the present review assesses the evidence for a causal relationship between vitamin D insufficiency and the pathobiology of MS, and discusses rationale for future clinical trials with vitamin D.