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.publishedVersio

Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations

A meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 x 10(-7), 4.3 x 10(-9)) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain.publishedVersio

Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesA meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 x 10(-7), 4.3 x 10(-9)) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain.Swedish Research Council Knut and Alice Wallenberg Foundation AFA Foundation Swedish Brain Foundatio

DNA methylation data in MS immune cells and whole blood

These are raw data of DNA methylation obtained on the Illumina 450K humanmethylation chip. The samples are either MS patients (MS) or healthy controls (K). Beta values after BMIQ normalisation are provided

Assessing the Power of Exome Chips

Genotyping chips for rare and low-frequent variants have recently gained popularity with the introduction of exome chips, but the utility of these chips remains unclear. These chips were designed using exome sequencing data from mainly American-European individuals, enriched for a narrow set of common diseases. In addition, it is well-known that the statistical power of detecting associations with rare and low-frequent variants is much lower compared to studies exclusively involving common variants. We developed a simulation program adaptable to any exome chip design to empirically evaluate the power of the exome chips. We implemented the main properties of the Illumina HumanExome BeadChip array. The simulated data sets were used to assess the power of exome chip based studies for varying effect sizes and causal variant scenarios. We applied two widely-used statistical approaches for rare and low-frequency variants, which collapse the variants into genetic regions or genes. Under optimal conditions, we found that a sample size between 20,000 to 30,000 individuals were needed in order to detect modest effect sizes (0.5% 1%) with 80% power. For small effect sizes (PAR <0.5%), 60,000–100,000 individuals were needed in the presence of non-causal variants. In conclusion, we found that at least tens of thousands of individuals are necessary to detect modest effects under optimal conditions. In addition, when using rare variant chips on cohorts or diseases they were not originally designed for, the identification of associated variants or genes will be even more challenging

Global DNA methylation changes in treated and untreated MS patients measured over time

Multiple sclerosis (MS) is an autoimmune, neurological disease. We investigated genome-wide DNA methylation profiles of CD4+ and CD8+ T cells from MS patients and healthy controls at baseline and a follow-up visit. Patients were all treatment-naïve at baseline, and either on treatment or remained untreated at the follow-up visit. MS patients show more changes in their T cell DNA methylation profiles as compared to healthy controls over time, with the most pronounced differences observed in the untreated MS patients. These findings underline the potential of DNA methylation as biomarkers in MS

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

SVM-based tool to detect patients with multiple sclerosis using a commercial EMG sensor

Multiple sclerosis (MS) is a major auto-immune disease that is the leading cause of non-traumatic impairment of the central nervous system (CNS) in young adults. Successful treatment of MS patients depends on accurate tools for both the MS diagnosis and the disability progression. In current and upcoming studies the authors aim to explore the capabilities of applying a commercial electromyographic and inertial sensor (MYO Armband by Thalmic Labs Inc.), coupled with a multichannel signal processing tool, to standard neurological examination of MS progression. In this pilot study we formulate a two-class “healthy control” - “having MS” classification problem. A dataset of electromyographic signals and inertial sensor measurements from 71 individuals (31 MS patients and 40 healthy controls) was acquired during standard neurological examination routine. Temporal and spectral features of the signals were extracted in order to train and validate a classification model. Finally, a Support Vector Machine classifier was obtained giving AUROC = 0.94, 95% CI = [0.88, 0.99]. We propose a set of signal descriptors that correlate with objective components of the neurological examination. The proposed signal acquisition and processing technique, being easy to integrate into the traditional neurological exam, may have high potential for aiding in quantifying MS progression

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. CD4þ T cells are suggested to be involved in multiple sclerosis disease processes. Objective: We aim to identify CD4þ 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 CD4þ T cells from multiple sclerosis patients and healthy controls. Results: We did not identify significantly differentially expressed genes in CD4þ 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 CD4þ T cells from multiple sclerosis patients do not show significant differential gene expression. Therefore, gene expression studies of all circulating CD4þ T cells may not result in viable biomarkers. Gene expression studies of more specific subsets of CD4þ T cells remain justified to understand better which CD4þ T cell subsets contribute to multiple sclerosis pathology