Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

From bedside to bench: how existing therapies inform the relationship between Epstein-Barr virus and multiple sclerosis

Therapy for relapsing-remitting multiple sclerosis (MS) has advanced dramatically despite incomplete understanding of the cause of the condition. Current treatment involves inducing broad effects on immune cell populations with consequent off-target side effects, and no treatment can completely prevent disability progression. Further therapeutic advancement will require a better understanding of the pathobiology of MS. Interest in the role of Epstein-Barr virus (EBV) in multiple sclerosis has intensified based on strong epidemiological evidence of an association between EBV seroprevalence and MS. Hypotheses proposed to explain the biological relationship between EBV and MS include molecular mimicry, EBV immortalised autoreactive B cells and infection of glial cells by EBV. Examining the interaction between EBV and immunotherapies that have demonstrated efficacy in MS offers clues to the validity of these hypotheses. The efficacy of B cell depleting therapies could be consistent with a hypothesis that EBV-infected B cells drive MS; however, loss of T cell control of B cells does not exacerbate MS. A number of MS therapies invoke change in EBV-specific T cell populations, but pathogenic EBV-specific T cells with cross-reactivity to CNS antigen have not been identified. Immune reconstitution therapies induce EBV viraemia and expansion of EBV-specific T cell clones, but this does not correlate with relapse. Much remains unknown regarding the role of EBV in MS pathogenesis. We discuss future translational research that could fill important knowledge gaps.

A multiple sclerosis-protective coding variant reveals an essential role for HDAC7 in regulatory T cells

Genome-wide association studies identifying hundreds of susceptibility loci for autoimmune diseases indicate that genes active in immune cells predominantly mediate risk. However, identification and functional characterization of causal variants remain challenging. Here, we focused on the immunomodulatory role of a protective variant of histone deacetylase 7 (HDAC7). This variant (rs148755202, HDAC7.p.R166H) was identified in a study of low-frequency coding variation in multiple sclerosis (MS). Through transcriptomic analyses, we demonstrate that wild-type HDAC7 regulates genes essential for the function of Foxp3⁺ regulatory T cells (T_regs), an immunosuppressive subset of CD4 T cells that is generally dysfunctional in patients with MS. Moreover, T_reg-specific conditional hemizygous deletion of HDAC7 increased the severity of experimental autoimmune encephalitis (EAE), a mouse model of neuroinflammation. In contrast, T_regs transduced with the protective HDAC7 R166H variant exhibited higher suppressive capacity in an in vitro functional assay, mirroring phenotypes previously observed in patient samples. In vivo modeling of the human HDAC7 R166H variant by generation of a knock-in mouse model bearing an orthologous R150H substitution demonstrated decreased EAE severity linked to transcriptomic alterations of brain-infiltrating T_regs, as assessed by single-cell RNA sequencing. Our data suggest that dysregulation of epigenetic modifiers, a distinct molecular class associated with disease risk, may influence disease onset. Last, our approach provides a template for the translation of genetic susceptibility loci to detailed functional characterization, using in vitro and in vivo modeling.

Impact of Body Mass Index on the Age of Relapsing-Remitting Multiple Sclerosis Onset: A Retrospective Study

A BACKROUND: Multiple sclerosis (MS) is a complex chronic disease of the central nervous system (CNS). Body mass index (BMI), a component of metabolic syndrome (MetS), is considered among the risk factors for MS. However, its role in MS remains ambiguous. OBJECTIVE: To examine the impact of BMI on the age of onset in patients with relapsing-remitting MS (RRMS) in a Greek cohort. METHODS: Data from 821 Greek patients with RRMS were collected. The BMI values were considered as quartiles. Comparisons for the demographic characteristics between the quartiles were made by Pearson’s chi-square test for the categorical variables and by ANOVA for the continuous variables. An overall p-value was calculated corresponding to trend for association. In case of significant association, further post-hoc analysis was performed in order to identify differences in demographic characteristics between specific BMI quartiles groups. Linear regression analyses were used to assess the relationship between BMI and age at onset of MS. RESULTS: Comparisons of participant characteristics by quartiles of BMI revealed that participants with the highest BMI had an older age of disease onset. Results from linear regression analysis showed that with each increase of 1 BMI unit, the age of RRMS onset increases by 0.255 (95% CI 0.136 to 0.374) years, p < 0.001. CONCLUSIONS: Patients with higher BMI, as a parameter of MetS, exhibit increased age of RRMS onset. Our results may present an alternative personalized approach for diagnosis, prognosis, and/or prevention of RRMS.

Genetic and gene expression signatures in multiple sclerosis

Multiple sclerosis (MS) exhibits a well-documented increased incidence in individuals with respective family history, that is, is a heritable disease. In the last decade, genome-wide association studies have enabled the agnostic interrogation of the whole genome at a large scale. To date, over 200 genetic associations have been described at the strict level of genome-wide significance. Our current understanding of MS genetics can explain up to half of the disease's heritability, raising the important question of whether this is enough information to leverage toward improving diagnosis in MS. Parallel advancements in technologies that allow the characterization of the full transcriptome down to the single-cell level have enabled the generation of an unprecedented wealth of information. Transcriptional changes of putative causal cells could be utilized to identify early signs of disease onset. These recent findings in genetics and genomics, coupled with new technologies and deeply phenotyped cohorts, have the potential to improve the diagnosis of MS.