Multiscale networks in multiple sclerosis.

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype.

Predicting disease severity in multiple sclerosis using multimodal data and machine learning.

BACKGROUND: Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. METHODS: We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre. RESULTS: We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high-accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts. CONCLUSION: Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening.

Immune cell subpopulations and serum neurofilament light chain are associated with increased risk of disease worsening in multiple sclerosis.

Changes is lymphocyte subpopulations in peripheral blood have been proposed as biomarkers for evaluation of disease activity in multiple sclerosis (MS). Serum neurofilament light chain (sNfL) is a biomarker reflecting neuro-axonal injury in MS that could be used to monitor disease activity, response to drugs and to prognosticate disease course. Here we show a moderate correlation between sNfL and lymphocyte cell subpopulations, and our data furthermore suggest that sNfL and specific immune cell subpopulations together could predict future disease worsening in MS.

Humoral immunity to SARS-CoV-2 mRNA vaccination in multiple sclerosis: the relevance of time since last rituximab infusion and first experience from sporadic revaccinations.

INTRODUCTION: The effect of disease-modifying therapies (DMT) on vaccine responses is largely unknown. Understanding the development of protective immunity is of paramount importance to fight the COVID-19 pandemic. OBJECTIVE: To characterise humoral immunity after mRNA-COVID-19 vaccination of people with multiple sclerosis (pwMS). METHODS: All pwMS in Norway fully vaccinated against SARS-CoV-2 were invited to a national screening study. Humoral immunity was assessed by measuring anti-SARS-CoV-2 SPIKE RBD IgG response 3-12 weeks after full vaccination, and compared with healthy subjects. RESULTS: 528 pwMS and 627 healthy subjects were included. Reduced humoral immunity (anti-SARS-CoV-2 IgG <70 arbitrary units) was present in 82% and 80% of all pwMS treated with fingolimod and rituximab, respectively, while patients treated with other DMT showed similar rates as healthy subjects and untreated pwMS. We found a significant correlation between time since the last rituximab dose and the development of humoral immunity. Revaccination in two seronegative patients induced a weak antibody response. CONCLUSIONS: Patients treated with fingolimod or rituximab should be informed about the risk of reduced humoral immunity and vaccinations should be timed carefully in rituximab patients. Our results identify the need for studies regarding the durability of vaccine responses, the role of cellular immunity and revaccinations.

Quantitative proteomics reveals protein dysregulation during T cell activation in multiple sclerosis patients compared to healthy controls.

BACKGROUND: Multiple sclerosis (MS) is an autoimmune, neurodegenerative disorder with a strong genetic component that acts in a complex interaction with environmental factors for disease development. CD4+ T cells are pivotal players in MS pathogenesis, where peripherally activated T cells migrate to the central nervous system leading to demyelination and axonal degeneration. Through a proteomic approach, we aim at identifying dysregulated pathways in activated T cells from MS patients as compared to healthy controls. METHODS: CD4+ T cells were purified from peripheral blood from MS patients and healthy controls by magnetic separation. Cells were left unstimulated or stimulated in vitro through the TCR and costimulatory CD28 receptor for 24 h prior to sampling. Electrospray liquid chromatography-tandem mass spectrometry was used to measure protein abundances. RESULTS: Upon T cell activation the abundance of 1801 proteins was changed. Among these proteins, we observed an enrichment of proteins expressed by MS-susceptibility genes. When comparing protein abundances in T cell samples from healthy controls and MS patients, 18 and 33 proteins were differentially expressed in unstimulated and stimulated CD4+ T cells, respectively. Moreover, 353 and 304 proteins were identified as proteins exclusively induced upon T cell activation in healthy controls and MS patients, respectively and dysregulation of the Nur77 pathway was observed only in samples from MS patients. CONCLUSIONS: Our study highlights the importance of CD4+ T cell activation for MS, as proteins that change in abundance upon T cell activation are enriched for proteins encoded by MS susceptibility genes. The results provide evidence for proteomic disturbances in T cell activation in MS, and pinpoint to dysregulation of the Nur77 pathway, a biological pathway known to limit aberrant effector T cell responses.

Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study.

BACKGROUND AND OBJECTIVES: Connectivity-based approaches incorporating the distribution and magnitude of the extended brain network aberrations caused by lesions may offer higher sensitivity for axonal damage in patients with multiple sclerosis (MS) than conventional lesion characteristics. Using individual brain disconnectome mapping, we tested the longitudinal associations between putative imaging-based brain network aberrations and levels of serum neurofilament light chain (NfL) as a neuroaxonal injury biomarker. METHODS: MS patients (n = 312, mean age 42.9 years, 71 % female) and healthy controls (HC) (n = 59, mean age 39.9 years, 78 % female) were prospectively enrolled at four European MS centres, and reassessed after two years (MS, n = 242; HC, n = 30). Post-processing of 3 Tesla (3 T) MRI data was performed at one centre using a harmonized pipeline, and disconnectome maps were calculated using BCBtoolkit based on individual lesion maps. Global disconnectivity (GD) was defined as the average disconnectome probability in each patient's white matter. Serum NfL concentrations were measured by single molecule array (Simoa). Robust linear mixed models (rLMM) with GD or T2-lesion volume (T2LV) as dependent variables, patient as a random factor, serum NfL, age, sex, timepoint for visit, diagnosis, treatment, and center as fixed factors were run. RESULTS: rLMM revealed significant associations between GD and serum NfL (t = 2.94, p = 0.003), age (t = 4.21, p = 2.5 × 10-5), and longitudinal changes in NfL (t = -2.29, p = 0.02), but not for sex (t = 0.63, p = 0.53) or treatments (t = 0.80-0.83, p = 0.41-0.42). Voxel-wise analyses revealed significant associations between dysconnectivity in cerebellar and brainstem regions and serum NfL (t = 7.03, p < 0.001). DISCUSSION: In our prospective multi-site MS cohort, rLMMs demonstrated that the extent of global and regional brain disconnectivity is sensitive to a systemic biomarker of axonal damage, serum NfL, in patients with MS. These findings provide a neuroaxonal correlate of advanced disconnectome mapping and provide a platform for further investigations of the functional and potential clinical relevance of brain disconnectome mapping in patients with brain disorders.

Serum neurofilament light chain concentration predicts disease worsening in multiple sclerosis.

BACKGROUND: Serum neurofilament light (sNfL) chain is a promising biomarker reflecting neuro-axonal injury in multiple sclerosis (MS). However, the ability of sNfL to predict outcomes in real-world MS cohorts requires further validation. OBJECTIVE: The aim of the study is to investigate the associations of sNfL concentration, magnetic resonance imaging (MRI) and retinal optical coherence tomography (OCT) markers with disease worsening in a longitudinal European multicentre MS cohort. METHODS: MS patients (n = 309) were prospectively enrolled at four centres and re-examined after 2 years (n = 226). NfL concentration was measured by single molecule array assay in serum. The patients' phenotypes were thoroughly characterized with clinical examination, retinal OCT and MRI brain scans. The primary outcome was disease worsening at median 2-year follow-up. RESULTS: Patients with high sNfL concentrations (⩾8 pg/mL) at baseline had increased risk of disease worsening at median 2-year follow-up (odds ratio (95% confidence interval) = 2.8 (1.5-5.3), p = 0.001). We found no significant associations of MRI or OCT measures at baseline with risk of disease worsening. CONCLUSION: Serum NfL concentration was the only factor associated with disease worsening, indicating that sNfL is a useful biomarker in MS that might be relevant in a clinical setting.

Exploring the role of the multiple sclerosis susceptibility gene CLEC16A in T cells.

C-type lectin-like domain family 16 member A (CLEC16A) is associated with autoimmune disorders, including multiple sclerosis (MS), but its functional relevance is not completely understood. CLEC16A is expressed in several immune cells, where it affects autophagic processes and receptor expression. Recently, we reported that the risk genotype of an MS-associated single nucleotide polymorphism in CLEC16A intron 19 is associated with higher expression of CLEC16A in CD4+ T cells. Here, we show that CLEC16A expression is induced in CD4+ T cells upon T cell activation. By the use of imaging flow cytometry and confocal microscopy, we demonstrate that CLEC16A is located in Rab4a-positive recycling endosomes in Jurkat TAg T cells. CLEC16A knock-down in Jurkat cells resulted in lower cell surface expression of the T cell receptor, however, this did not have a major impact on T cell activation response in vitro in Jurkat nor in human, primary CD4+ T cells.

Blood neurofilament light concentration at admittance: a potential prognostic marker in COVID-19.

OBJECTIVE: To test the hypotheses that blood biomarkers for nervous system injury, serum concentrations of neurofilament light chain protein (NfL) and glial fibrillary acidic protein (GFAp) can serve as biomarkers for disease severity in COVID-19 patients. METHODS: Forty-seven inpatients with confirmed COVID-19 had blood samples drawn on admission for assessing serum biomarkers of CNS injury by Single molecule array (Simoa), NfL and GFAp. Concentrations of NfL and GFAp were analyzed in relation to symptoms, clinical signs, inflammatory biomarkers and clinical outcomes. We used multivariate linear models to test for differences in biomarker concentrations in the subgroups, accounting for confounding effects. RESULTS: In total, 21% (n = 10) of the patients were admitted to an intensive care unit, and the overall mortality rate was 13% (n = 6). Non-survivors had higher serum concentrations of NfL (p < 0.001) upon admission than patients who were discharged alive both in adjusted analyses (p = 2.6 × 10-7) and unadjusted analyses (p = 0.001). The concentrations of NfL in non-survivors increased over repeated measurements; whereas, the concentrations in survivors were stable. The GFAp concentration was also significantly higher in non-survivors than survivors (p = 0.02). CONCLUSION: Increased concentrations of NfL and GFAp in COVID-19 patients on admission may indicate increased mortality risk. Measurement of blood biomarkers for nervous system injury can be useful to detect and monitor CNS injury in COVID-19.

Impact of treatment on cellular immunophenotype in MS: A cross-sectional study.

OBJECTIVE: To establish cytometry profiles associated with disease stages and immunotherapy in MS. METHODS: Demographic/clinical data and peripheral blood samples were collected from 227 patients with MS and 82 sex- and age-matched healthy controls (HCs) enrolled in a cross-sectional study at 4 European MS centers (Spain, Italy, Germany, and Norway). Flow cytometry of isolated peripheral blood mononuclear cells was performed in each center using specifically prepared antibody-cocktail Lyotubes; data analysis was centralized at the Genoa center. Differences in immune cell subsets were assessed between groups of untreated patients with relapsing-remitting or progressive MS (RRMS or PMS) and HCs and between groups of patients with RRMS taking 6 commonly used disease-modifying drugs. RESULTS: In untreated patients with MS, significantly higher frequencies of Th17 cells in the RRMS population compared with HC and lower frequencies of B-memory/B-regulatory cells as well as higher percentages of B-mature cells in patients with PMS compared with HCs emerged. Overall, the greatest deviation in immunophenotype in MS was observed by treatment rather than disease course, with the strongest impact found in fingolimod-treated patients. Fingolimod induced a decrease in total CD4+ T cells and in B-mature and B-memory cells and increases in CD4+ and CD8+ T-regulatory and B-regulatory cells. CONCLUSIONS: Our highly standardized, multisite cytomics data provide further understanding of treatment impact on MS immunophenotype and could pave the way toward monitoring immune cells to help clinical management of MS individuals.

No differential gene expression for CD4+ T cells of MS patients and healthy controls.

BACKGROUND: Multiple sclerosis-associated genetic variants indicate that the adaptive immune system plays an important role in the risk of developing multiple sclerosis. It is currently not well understood how these multiple sclerosis-associated genetic variants contribute to multiple sclerosis risk. CD4+ T cells are suggested to be involved in multiple sclerosis disease processes. OBJECTIVE: We aim to identify CD4+ T cell differential gene expression between multiple sclerosis patients and healthy controls in order to understand better the role of these cells in multiple sclerosis. METHODS: We applied RNA sequencing on CD4+ T cells from multiple sclerosis patients and healthy controls. RESULTS: We did not identify significantly differentially expressed genes in CD4+ T cells from multiple sclerosis patients. Furthermore, pathway analyses did not identify enrichment for specific pathways in multiple sclerosis. When we investigated genes near multiple sclerosis-associated genetic variants, we did not observe significant enrichment of differentially expressed genes. CONCLUSION: We conclude that CD4+ T cells from multiple sclerosis patients do not show significant differential gene expression. Therefore, gene expression studies of all circulating CD4+ T cells may not result in viable biomarkers. Gene expression studies of more specific subsets of CD4+ T cells remain justified to understand better which CD4+ T cell subsets contribute to multiple sclerosis pathology.

Quantitative proteomic analyses of CD4+ and CD8+ T cells reveal differentially expressed proteins in multiple sclerosis patients and healthy controls.

BACKGROUND: Multiple sclerosis (MS) is an autoimmune, neuroinflammatory disease, with an unclear etiology. However, T cells play a central role in the pathogenesis by crossing the blood-brain-barrier, leading to inflammation of the central nervous system and demyelination of the protective sheath surrounding the nerve fibers. MS has a complex inheritance pattern, and several studies indicate that gene interactions with environmental factors contribute to disease onset. METHODS: In the current study, we evaluated T cell dysregulation at the protein level using electrospray liquid chromatography-tandem mass spectrometry to get novel insights into immune-cell processes in MS. We have analyzed the proteomic profiles of CD4+ and CD8+ T cells purified from whole blood from 13 newly diagnosed, treatment-naive female patients with relapsing-remitting MS and 14 age- and sex-matched healthy controls. RESULTS: An overall higher protein abundance was observed in both CD4+ and CD8+ T cells from MS patients when compared to healthy controls. The differentially expressed proteins were enriched for T-cell specific activation pathways, especially CTLA4 and CD28 signaling in CD4+ T cells. When selectively analyzing proteins expressed from the genes most proximal to > 200 non-HLA MS susceptibility polymorphisms, we observed differential expression of eight proteins in T cells between MS patients and healthy controls, and there was a correlation between the genotype at three MS genetic risk loci and protein expressed from proximal genes. CONCLUSION: Our study provides evidence for proteomic differences in T cells from relapsing-remitting MS patients compared to healthy controls and also identifies dysregulation of proteins encoded from MS susceptibility genes.

Increased DNA methylation of SLFN12 in CD4+ and CD8+ T cells from multiple sclerosis patients.

DNA methylation is an epigenetic mark that is influenced by environmental factors and is associated with changes to gene expression and phenotypes. It may link environmental exposures to disease etiology or indicate important gene pathways involved in disease pathogenesis. We identified genomic regions that are differentially methylated in T cells of patients with relapsing remitting multiple sclerosis (MS) compared to healthy controls. DNA methylation was assessed at 450,000 genomic sites in CD4+ and CD8+ T cells purified from peripheral blood of 94 women with MS and 94 healthy women, and differentially methylated regions were identified using bumphunter. Differential DNA methylation was observed near four loci: MOG/ZFP57, HLA-DRB1, NINJ2/LOC100049716, and SLFN12. Increased methylation of the first exon of the SLFN12 gene was observed in both T cell subtypes and remained present after restricting analyses to samples from patients who had never been on treatment or had been off treatment for more than 2.5 years. Genes near the regions of differential methylation in T cells were assessed for differential expression in whole blood samples from a separate population of 1,329 women with MS and 97 healthy women. Gene expression of HLA-DRB1, NINJ2, and SLFN12 was observed to be decreased in whole blood in MS patients compared to controls. We conclude that T cells from MS patients display regions of differential DNA methylation compared to controls, and corresponding gene expression differences are observed in whole blood. Two of the genes that showed both methylation and expression differences, NINJ2 and SLFN12, have not previously been implicated in MS. SLFN12 is a particularly compelling target of further research, as this gene is known to be down-regulated during T cell activation and up-regulated by type I interferons (IFNs), which are used to treat MS.

Allelic imbalance of multiple sclerosis susceptibility genes IKZF3 and IQGAP1 in human peripheral blood.

BACKGROUND: Multiple sclerosis is a chronic inflammatory, demyelinating disease of the central nervous system. Recent genome-wide studies have revealed more than 110 single nucleotide polymorphisms as associated with susceptibility to multiple sclerosis, but their functional contribution to disease development is mostly unknown. RESULTS: Consistent allelic imbalance was observed for rs907091 in IKZF3 and rs11609 in IQGAP1, which are in strong linkage disequilibrium with the multiple sclerosis associated single nucleotide polymorphisms rs12946510 and rs8042861, respectively. Using multiple sclerosis patients and healthy controls heterozygous for rs907091 and rs11609, we showed that the multiple sclerosis risk alleles at IKZF3 and IQGAP1 are expressed at higher levels as compared to the protective allele. Furthermore, individuals homozygous for the multiple sclerosis risk allele at IQGAP1 had a significantly higher total expression of IQGAP1 compared to individuals homozygous for the protective allele. CONCLUSIONS: Our data indicate a possible regulatory role for the multiple sclerosis-associated IKZF3 and IQGAP1 variants. We suggest that such cis-acting mechanisms may contribute to the multiple sclerosis association of single nucleotide polymorphisms at IKZF3 and IQGAP1.

Persistent Low Toxoplasma IgG Avidity Is Common in Pregnancy: Experience from Antenatal Testing in Norway.

The parasite Toxoplasma gondii might harm the fetus if a woman is infected during pregnancy. IgG seroconversion and significant increase in IgG antibody amount in pregnancy indicates maternal infection. Presence of toxoplasma immunoglobulin M (IgM), immunoglobulin G (IgG) and low IgG avidity in a single serum sample indicates possible maternal infection, but positive toxoplasma IgM and low IgG avidity may persist for months and even years. We aimed to evaluate avidity development during pregnancy in a retrospective study. Serial blood samples from 176 pregnant women admitted to Oslo University Hospital 1993-2013 for amniocentesis because of suspected toxoplasma infection were included. Data were obtained from journals and laboratory records. The avidity method used was based on Platelia Toxo IgG assay. Mean maternal age at first serology was 29.9 years (SD 5.2, range 18-42). In 37 (21%) women only the avidity increased from low to high in < 3 months. In 139 (79%) the IgG avidity remained below the high threshold ≥ 3 months and within this group 74 (42%) women had stable low IgG avidity during the observation period. Median gestational age at first test was 10.6 weeks (range 4.6-28.7). Fetal infection was detected in four children, but none among children whose mother had stable low IgG avidity. The first antenatal toxoplasma serology should ideally be collected in early pregnancy and if stable values of toxoplasma IgM and low IgG-avidity are detected in a second sample after three to four weeks, the need for amniocentesis can be questioned.

Friedreich ataxia in Norway - an epidemiological, molecular and clinical study.

BACKGROUND: Friedreich ataxia is an autosomal recessive hereditary spinocerebellar disorder, characterized by progressive limb and gait ataxia due to proprioceptive loss, often complicated by cardiomyopathy, diabetes and skeletal deformities. Friedreich ataxia is the most common hereditary ataxia, with a reported prevalence of 1:20 000 - 1:50 000 in Central Europe. Previous reports from south Norway have found a prevalence varying from 1:100 000 - 1:1 350 000; no studies are previously done in the rest of the country. METHODS: In this cross-sectional study, Friedreich ataxia patients were identified through colleagues in neurological, pediatric and genetic departments, hospital archives searches, patients' associations, and National Centre for Rare Disorders. All included patients, carriers and controls were investigated clinically and molecularly with genotype characterization including size determination of GAA repeat expansions and frataxin measurements. 1376 healthy blood donors were tested for GAA repeat expansion for carrier frequency analysis. RESULTS: Twenty-nine Friedreich ataxia patients were identified in Norway, of which 23 were ethnic Norwegian, corresponding to a prevalence of 1:176 000 and 1:191 000, respectively. The highest prevalence was seen in the north. Carrier frequency of 1:196 (95 % CI = [1:752-1:112]) was found. Homozygous GAA repeat expansions in the FXN gene were found in 27/29, while two patients were compound heterozygous with c.467 T < C, L157P and the deletion (g.120032_122808del) including exon 5a. Two additional patients were heterozygous for GAA repeat expansions only. Significant differences in the level of frataxin were found between the included patients (N = 27), carriers (N = 37) and controls (N = 27). CONCLUSIONS: In this first thorough study of a complete national cohort of Friedreich ataxia patients, and first nation-wide study of Friedreich ataxia in Norway, the prevalence of Friedreich ataxia in Norway is lower than in Central Europe, but higher than in the last Norwegian report, and as expected from migration studies. A south-north prevalence gradient is present. Based on Hardy Weinberg's equilibrium, the carrier frequency of 1:196 is consistent with the observed prevalence. All genotypes, and typical and atypical phenotypes were present in the Norwegian population. The patients were phenotypically similar to European cohorts. Frataxin was useful in the diagnostic work-up of heterozygous symptomatic cases.

Multiple Sclerosis Risk Allele in CLEC16A Acts as an Expression Quantitative Trait Locus for CLEC16A and SOCS1 in CD4+ T Cells.

For multiple sclerosis, genome wide association studies and follow up studies have identified susceptibility single nucleotide polymorphisms located in or near CLEC16A at chromosome 16p13.13, encompassing among others CIITA, DEXI and SOCS1 in addition to CLEC16A. These genetic variants are located in intronic or intergenic regions and display strong linkage disequilibrium with each other, complicating the understanding of their functional contribution and the identification of the direct causal variant(s). Previous studies have shown that multiple sclerosis-associated risk variants in CLEC16A act as expression quantitative trait loci for CLEC16A itself in human pancreatic ß-cells, for DEXI and SOCS1 in thymic tissue samples, and for DEXI in monocytes and lymphoblastoid cell lines. Since T cells are major players in multiple sclerosis pathogenesis, we have performed expression analyses of the CIITA-DEXI-CLEC16A-SOCS1 gene cluster in CD4+ and CD8+ T cells isolated from multiple sclerosis patients and healthy controls. We observed a higher expression of SOCS1 and CLEC16A in CD4+ T cells in samples homozygous for the risk allele of CLEC16A rs12927355. Pair-wise linear regression analysis revealed high correlation in gene expression in peripheral T cells of CIITA, DEXI, CLEC16A and SOCS1. Our data imply a possible regulatory role for the multiple sclerosis-associated rs12927355 in CLEC16A.

Genome-wide DNA methylation profiles indicate CD8+ T cell hypermethylation in multiple sclerosis.

OBJECTIVE: Determine whether MS-specific DNA methylation profiles can be identified in whole blood or purified immune cells from untreated MS patients. METHODS: Whole blood, CD4+ and CD8+ T cell DNA from 16 female, treatment naïve MS patients and 14 matched controls was profiled using the HumanMethylation450K BeadChip. Genotype data were used to assess genetic homogeneity of our sample and to exclude potential SNP-induced DNA methylation measurement errors. RESULTS: As expected, significant differences between CD4+ T cells, CD8+ T cells and whole blood DNA methylation profiles were observed, regardless of disease status. Strong evidence for hypermethylation of CD8+ T cell, but not CD4+ T cell or whole blood DNA in MS patients compared to controls was observed. Genome-wide significant individual CpG-site DNA methylation differences were not identified. Furthermore, significant differences in gene DNA methylation of 148 established MS-associated risk genes were not observed. CONCLUSION: While genome-wide significant DNA methylation differences were not detected for individual CpG-sites, strong evidence for DNA hypermethylation of CD8+ T cells for MS patients was observed, indicating a role for DNA methylation in MS. Further, our results suggest that large DNA methylation differences for CpG-sites tested here do not contribute to MS susceptibility. In particular, large DNA methylation differences for CpG-sites within 148 established MS candidate genes tested in our study cannot explain missing heritability. Larger studies of homogenous MS patients and matched controls are warranted to further elucidate the impact of CD8+ T cell and more subtle DNA methylation changes in MS development and pathogenesis.

Retinoic acid enhances the levels of IL-10 in TLR-stimulated B cells from patients with relapsing-remitting multiple sclerosis.

We have explored the beneficial effects of retinoic acid (RA) on B cells from multiple sclerosis (MS) patients. When co-stimulated via the toll-like receptors (TLRs) TLR9 and RP105, MS B cells secreted less of the anti-inflammatory cytokine interleukin 10 (IL-10) compared to B cells from healthy controls. Importantly, RA enhanced the secretion of IL-10 by MS-derived B cells without affecting the levels of the pro-inflammatory cytokine TNF-α. RA revealed the same ability to induce IL-10 as did interferon-ß-1b (IFN-ß-1b), and B-cells from patients treated with glatiramer acetate or IFN-ß-1b still displayed the beneficial effects of RA on the IL-10/TNF-α ratio.

The kinase Itk and the adaptor TSAd change the specificity of the kinase Lck in T cells by promoting the phosphorylation of Tyr192.

The substrate specificity of Src family kinases (SFKs) is partly determined by their Src homology 2 (SH2) domains. Thus, transient alterations in the SH2 domain of SFKs might change their binding partners and affect intracellular signaling pathways. Lck is an SFK that is central to the initiation of T cell activation in response to ligand binding to the T cell receptor (TCR) and is also critical for later signaling processes. The kinase activity of Lck requires both the phosphorylation of an activating tyrosine residue and the dephosphorylation of an inhibitory tyrosine residue. We found that a third conserved tyrosine phosphorylation site (Tyr(192)) within the SH2 domain of Lck was required for proper T cell activation and formation of cell-cell conjugates between T cells and antigen-presenting cells. Through phosphopeptide arrays and biochemical assays, we identified several regulators of the actin cytoskeleton that preferentially bound to Lck phosphorylated at Tyr(192) compared to Lck that was not phosphorylated at this site. Two of these phosphorylation-dependent binding partners, the kinase Itk (interleukin-2-inducible Tec kinase) and the adaptor protein TSAd (T cell-specific adaptor), promoted the TCR-dependent phosphorylation of Lck at Tyr(192). Our data suggest that phosphorylation transiently alters SH2 domain specificity and provide a potential mechanism whereby SFKs may be rewired from one signaling program to another to enable appropriate cell activation.