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

Genome-Wide DNA Methylation Profiles Indicate CD8+ T Cell Hypermethylation in Multiple Sclerosis

Determine whether MS-specific DNA methylation profiles can be identified in whole blood or purified immune cells from untreated MS patients.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.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.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

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

<div><p>For multiple sclerosis, genome wide association studies and follow up studies have identified susceptibility single nucleotide polymorphisms located in or near <i>CLEC16A</i> at chromosome 16p13.13, encompassing among others <i>CIITA</i>, <i>DEXI</i> and <i>SOCS1</i> in addition to <i>CLEC16A</i>. 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 <i>CLEC16A</i> act as expression quantitative trait loci for <i>CLEC16A</i> itself in human pancreatic β-cells, for <i>DEXI</i> and <i>SOCS1</i> in thymic tissue samples, and for <i>DEXI</i> in monocytes and lymphoblastoid cell lines. Since T cells are major players in multiple sclerosis pathogenesis, we have performed expression analyses of the <i>CIITA-DEXI-CLEC16A-SOCS1</i> gene cluster in CD4+ and CD8+ T cells isolated from multiple sclerosis patients and healthy controls. We observed a higher expression of <i>SOCS1</i> and <i>CLEC16A</i> in CD4+ T cells in samples homozygous for the risk allele of <i>CLEC16A</i> rs12927355. Pair-wise linear regression analysis revealed high correlation in gene expression in peripheral T cells of <i>CIITA</i>, <i>DEXI</i>, <i>CLEC16A</i> and <i>SOCS1</i>. Our data imply a possible regulatory role for the multiple sclerosis-associated rs12927355 in <i>CLEC16A</i>.</p></div

The genotype of rs12927355 associates with increased expression of <i>CLEC16A</i> and <i>SOCS1</i> in CD4+T cells.

<p>The plots show gene expression of <i>CIITA</i>, <i>DEXI</i>, <i>CLEC16A</i> and <i>SOCS1</i> relative to <i>TBP</i> in CD4+ T cells (n = 50) from MS patients (n = 27) and HCs (n = 23). The samples were sorted according to <i>CLEC16A</i> genotype of two MS-associated SNPs (A) rs12927355 (risk allele = G): GG: n = 35, AG: n = 14 and AA: n = 1, and (B) rs4780346 (risk allele = A): AA: n = 4 and AG: n = 19, GG: n = 27. Mann-Whitney U-test was performed to compare the groups. Significant <i>P</i>-values are shown in the figure. The median value in each group is indicated as a horizontal line.</p

No difference in 16p13.13 T cell expression between MS patients and healthy controls.

<p>The plots show gene expression of <i>CIITA</i>, <i>DEXI</i>, <i>CLEC16A</i> and <i>SOCS1</i> relative to <i>TBP</i> in (A) CD4+ T cells (MS: n = 28; HC: n = 26) and (B) CD8+ T cells (MS n = 17; HC: n = 23). Mann-Whitney U-test was performed to compare the groups. The median value in each group is indicated as a horizontal line.</p

Characteristics of MS patients and controls.

<p>¹ At inclusion in this study.</p><p>Abbreviations: EDSS = expanded disability status scale, S.D. = standard deviation, N/A = not applicable.</p><p>Characteristics of MS patients and controls.</p

Top 40 results sorted by p-values from linear regression analysis models of DNA methylation in whole blood samples.

<p>¹Probe ID on 450K chip.</p><p>²Gene annotated to probe.</p><p>³p-value for specified probe in whole blood.</p><p>⁴Effect size of beta difference for specified probe. Positive values indicate hypomethylation of MS samples (i.e. controls DNA methylation higher than MS patients)</p><p>⁵Standard deviation for specified probe.</p><p>Formatting legend</p><p>“Bold probeID” Specific probe occurs in all three data top-40 (see Tables <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117403#pone.0117403.t002" target="_blank">2</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117403#pone.0117403.t003" target="_blank">3</a>)</p><p>“<i>Bold Italic Gene</i>” Gene occurs in all three data top-40 (see Tables <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117403#pone.0117403.t002" target="_blank">2</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117403#pone.0117403.t003" target="_blank">3</a>)</p><p>”Bold Effectsize” Hypermethylation of probe in MS patients</p><p>Results shown are restricted to methylation differences of at least 5% (absolute beta difference). Full lists are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117403#pone.0117403.s003" target="_blank">S1 Table</a>.</p><p>Top 40 results sorted by p-values from linear regression analysis models of DNA methylation in whole blood samples.</p

Pie charts of overall methylation levels for the three sample types.

<p><b>A</b>. Pie-charts of DNA hyper- and hypomethylation for all CpG sites with p-values less then or equal to 0.05. <b>B</b>. Pie-charts of DNA hyper- and hypomethylation for all CpG-sites with p-values above 0.05. Abbreviations: Hypo – hypomethylation, Hyper – hypermethylation, CD4 – CD4+ T cell data, CD8 – CD8+ T cell data, WB – whole blood data.</p

Characteristics of individual MS patients and summaries of patients and controls.

<p>¹Age category: 1 = 25–29, 2 = 30–34, 3 = 35–39, 4 = 40–44, 5 = 45–49, 6 = 60–64.</p><p>²At inclusion in this study.</p><p>³Oligoclonal bands present in cerebrospinal fluid taken at time of diagnosis.</p><p>⁴Contrast enhancing lesions on MRI.</p><p>Abbreviations: EDSS = Expanded Disability Status Scale, MSSS = Multiple Sclerosis Severity Score, OCB = oligoclonal bands, MRI = Magnetic Resonance Imaging, S.D. standard deviation</p><p>Characteristics of individual MS patients and summaries of patients and controls.</p

Principal component analyses.

<p>For samples in analyses a PCA was performed on overall methylation levels of CpG-sites that passed both quality controls and SNP filtering in (<b>A</b>) whole blood (Red), CD4+ T cells (Blue) and CD8+ T cells (Magenta) for all cases (squares) and controls (triangles). (<b>B</b>) PCA of DNA methylation data from whole blood only. (<b>C</b>) PCA of DNA methylation data from CD4+ T cells only. (<b>D</b>) PCA of DNA methylation data from CD8+ T cells only.</p