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Increased numbers of IL-7 receptor molecules on CD4+CD25-CD107a+ T-cells in patients with autoimmune diseases affecting the central nervous system.

Vudattu NK, Kuhlmann-Berenzon S, Khademi M, Seyfert V, Olsson T, Maeurer MJ - PLoS ONE (2009)

Bottom Line: We did not observe differences in the relative percentage of IL-7R-positive immune cells in PBMCs.In contrast, we identified significant differences in IL-7 density, measured on a single cell level, in 2/59 variables: increased numbers of CD127 molecules on TCRalphabeta+CD4+CD25 (intermed) T-cells and on TCRalphabeta+CD4+CD25-CD107a+ T-cells (mean: 28376 Il-7R binding sites on cells from HD, 48515 in patients with RRMS, 38195 in patients with SPMS and 33692 IL-7 receptor binding sites on cells from patients with OND).These data show that immunophenotyping represents a powerful tool to differentiate healthy individuals from individuals suffering from neurological diseases and that the number of IL-7 receptor molecules on differentiated TCRalphabeta+CD4+CD25-CD107a+ T-cells, but not the percentage of IL-7R-positive cells, segregates healthy individuals from patients with neurological disorders.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institutet, Stockholm, Sweden.

ABSTRACT

Background: High content immune profiling in peripheral blood may reflect immune aberrations associated with inflammation in multiple sclerosis (MS) and other autoimmune diseases affecting the central nervous system.

Methods and findings: Peripheral blood mononuclear cells from 46 patients with multiple sclerosis (MS), 9 patients diagnosed with relapsing remitting MS (RRMS), 13 with secondary progressive multiple sclerosis (SPMS), 9 with other neurological diseases (OND) and well as 15 healthy donors (HD) were analyzed by 12 color flow cytometry (TCRalphabeta, TCRgammadelta, CD4, CD8alpha, CD8beta, CD45RA, CCR7, CD27, CD28, CD107a, CD127, CD14) in a cross-sectional study to identify variables significantly different between controls (HD) and patients (OND, RRMS, SPMS). We analyzed 187 individual immune cell subsets (percentages) and the density of the IL-7 receptor alpha chain (CD127) on 59 individual immune phenotypes using a monoclonal anti-IL-7R antibody (clone R34.34) coupled to a single APC molecule in combination with an APC-bead array. A non-parametric analysis of variance (Kruskal-Wallis test) was conducted in order to test for differences among the groups in each of the variables. To correct for the multiplicity problem, the FDR correction was applied on the p-values. We identified 19 variables for immune cell subsets (percentages) which allowed to segregate healthy individuals and individuals with CNS disorders. We did not observe differences in the relative percentage of IL-7R-positive immune cells in PBMCs. In contrast, we identified significant differences in IL-7 density, measured on a single cell level, in 2/59 variables: increased numbers of CD127 molecules on TCRalphabeta+CD4+CD25 (intermed) T-cells and on TCRalphabeta+CD4+CD25-CD107a+ T-cells (mean: 28376 Il-7R binding sites on cells from HD, 48515 in patients with RRMS, 38195 in patients with SPMS and 33692 IL-7 receptor binding sites on cells from patients with OND).

Conclusion: These data show that immunophenotyping represents a powerful tool to differentiate healthy individuals from individuals suffering from neurological diseases and that the number of IL-7 receptor molecules on differentiated TCRalphabeta+CD4+CD25-CD107a+ T-cells, but not the percentage of IL-7R-positive cells, segregates healthy individuals from patients with neurological disorders.

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Visualization of differences in immune cell frequencies using heatmaps.After quality data extraction and statistical analysis (Kruskal-Wallis test, see material and methods), p-values were obtained and a cutoff of 0.05 was applied to obtain a subset of significant variables. The final analysis included a principal component analysis (PCA) to study the correlation between the variables, and cluster analysis to see the connection between variables and groups of patients. Lighter colors (white) represent higher standardized values and darker represent lower standardized values (red) summarizing cellular immune phenotypes (percentages of immune cell subsets). The individual 45 (a healthy blood donor is included in the analysis). This individual showed aberrant immune markers in PBMCs.
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pone-0006534-g002: Visualization of differences in immune cell frequencies using heatmaps.After quality data extraction and statistical analysis (Kruskal-Wallis test, see material and methods), p-values were obtained and a cutoff of 0.05 was applied to obtain a subset of significant variables. The final analysis included a principal component analysis (PCA) to study the correlation between the variables, and cluster analysis to see the connection between variables and groups of patients. Lighter colors (white) represent higher standardized values and darker represent lower standardized values (red) summarizing cellular immune phenotypes (percentages of immune cell subsets). The individual 45 (a healthy blood donor is included in the analysis). This individual showed aberrant immune markers in PBMCs.

Mentions: Analysis of PBMCs obtained from individual number 45, a healthy donor, showed a very different pattern of immune cell subsets as compared to the rest of the individuals. The statistical testing and multiplicity correction were therefore run in two different variants: including (Figure 2) and excluding individual number 45 (Figure 3) from the statistical analysis. The significant 19 variables are listed with the corresponding p-values in heatmaps, each color represents a defined percentage of the target immune cell population in lymphocytes. It is evident that all phenotypic variables (percentages of immune cell subsets) are slightly different in each individual. In general, clustering the 19 different variables showed that phenotypic markers, defined by flow cytometry, allow to segregate healthy individuals from individuals with neurological diseases. This exercise also confirmed the results that individual # 45 (a healthy blood donor) exhibited a different phenotypic pattern in PBMCs (Figures 2 and 3), clinically very well defined populations are crucial for the identification of markers which allow to identify an individual as ‘healthy’ or suffering from a (inflammatory, neurological) disease. The heatmap analysis also indicated that certain immunophenotype subgroups discern between HD and OND groups and patients with MS (RRMS and SPMS). In general, two groups were formed: healthy donors on one side, and OND, RRMS, and SPMS on the other. Differences could be identified in the relative percentages of Treg cells, including CD3+CD4+/CD25high+/Foxp3+/CD27+CD28+ T-cells; increased percentages could also be identified in TCRγδ+/CD45RA−CCR7+ T-cells, in TCRαβ+/CD8αα+/CD45RA−CCR7+ T-cells as well as in the TCRαβ+/CD8αα+/CD45RA+CCR7+/CD27−CD28+ T-cell subset.


Increased numbers of IL-7 receptor molecules on CD4+CD25-CD107a+ T-cells in patients with autoimmune diseases affecting the central nervous system.

Vudattu NK, Kuhlmann-Berenzon S, Khademi M, Seyfert V, Olsson T, Maeurer MJ - PLoS ONE (2009)

Visualization of differences in immune cell frequencies using heatmaps.After quality data extraction and statistical analysis (Kruskal-Wallis test, see material and methods), p-values were obtained and a cutoff of 0.05 was applied to obtain a subset of significant variables. The final analysis included a principal component analysis (PCA) to study the correlation between the variables, and cluster analysis to see the connection between variables and groups of patients. Lighter colors (white) represent higher standardized values and darker represent lower standardized values (red) summarizing cellular immune phenotypes (percentages of immune cell subsets). The individual 45 (a healthy blood donor is included in the analysis). This individual showed aberrant immune markers in PBMCs.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2717329&req=5

pone-0006534-g002: Visualization of differences in immune cell frequencies using heatmaps.After quality data extraction and statistical analysis (Kruskal-Wallis test, see material and methods), p-values were obtained and a cutoff of 0.05 was applied to obtain a subset of significant variables. The final analysis included a principal component analysis (PCA) to study the correlation between the variables, and cluster analysis to see the connection between variables and groups of patients. Lighter colors (white) represent higher standardized values and darker represent lower standardized values (red) summarizing cellular immune phenotypes (percentages of immune cell subsets). The individual 45 (a healthy blood donor is included in the analysis). This individual showed aberrant immune markers in PBMCs.
Mentions: Analysis of PBMCs obtained from individual number 45, a healthy donor, showed a very different pattern of immune cell subsets as compared to the rest of the individuals. The statistical testing and multiplicity correction were therefore run in two different variants: including (Figure 2) and excluding individual number 45 (Figure 3) from the statistical analysis. The significant 19 variables are listed with the corresponding p-values in heatmaps, each color represents a defined percentage of the target immune cell population in lymphocytes. It is evident that all phenotypic variables (percentages of immune cell subsets) are slightly different in each individual. In general, clustering the 19 different variables showed that phenotypic markers, defined by flow cytometry, allow to segregate healthy individuals from individuals with neurological diseases. This exercise also confirmed the results that individual # 45 (a healthy blood donor) exhibited a different phenotypic pattern in PBMCs (Figures 2 and 3), clinically very well defined populations are crucial for the identification of markers which allow to identify an individual as ‘healthy’ or suffering from a (inflammatory, neurological) disease. The heatmap analysis also indicated that certain immunophenotype subgroups discern between HD and OND groups and patients with MS (RRMS and SPMS). In general, two groups were formed: healthy donors on one side, and OND, RRMS, and SPMS on the other. Differences could be identified in the relative percentages of Treg cells, including CD3+CD4+/CD25high+/Foxp3+/CD27+CD28+ T-cells; increased percentages could also be identified in TCRγδ+/CD45RA−CCR7+ T-cells, in TCRαβ+/CD8αα+/CD45RA−CCR7+ T-cells as well as in the TCRαβ+/CD8αα+/CD45RA+CCR7+/CD27−CD28+ T-cell subset.

Bottom Line: We did not observe differences in the relative percentage of IL-7R-positive immune cells in PBMCs.In contrast, we identified significant differences in IL-7 density, measured on a single cell level, in 2/59 variables: increased numbers of CD127 molecules on TCRalphabeta+CD4+CD25 (intermed) T-cells and on TCRalphabeta+CD4+CD25-CD107a+ T-cells (mean: 28376 Il-7R binding sites on cells from HD, 48515 in patients with RRMS, 38195 in patients with SPMS and 33692 IL-7 receptor binding sites on cells from patients with OND).These data show that immunophenotyping represents a powerful tool to differentiate healthy individuals from individuals suffering from neurological diseases and that the number of IL-7 receptor molecules on differentiated TCRalphabeta+CD4+CD25-CD107a+ T-cells, but not the percentage of IL-7R-positive cells, segregates healthy individuals from patients with neurological disorders.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institutet, Stockholm, Sweden.

ABSTRACT

Background: High content immune profiling in peripheral blood may reflect immune aberrations associated with inflammation in multiple sclerosis (MS) and other autoimmune diseases affecting the central nervous system.

Methods and findings: Peripheral blood mononuclear cells from 46 patients with multiple sclerosis (MS), 9 patients diagnosed with relapsing remitting MS (RRMS), 13 with secondary progressive multiple sclerosis (SPMS), 9 with other neurological diseases (OND) and well as 15 healthy donors (HD) were analyzed by 12 color flow cytometry (TCRalphabeta, TCRgammadelta, CD4, CD8alpha, CD8beta, CD45RA, CCR7, CD27, CD28, CD107a, CD127, CD14) in a cross-sectional study to identify variables significantly different between controls (HD) and patients (OND, RRMS, SPMS). We analyzed 187 individual immune cell subsets (percentages) and the density of the IL-7 receptor alpha chain (CD127) on 59 individual immune phenotypes using a monoclonal anti-IL-7R antibody (clone R34.34) coupled to a single APC molecule in combination with an APC-bead array. A non-parametric analysis of variance (Kruskal-Wallis test) was conducted in order to test for differences among the groups in each of the variables. To correct for the multiplicity problem, the FDR correction was applied on the p-values. We identified 19 variables for immune cell subsets (percentages) which allowed to segregate healthy individuals and individuals with CNS disorders. We did not observe differences in the relative percentage of IL-7R-positive immune cells in PBMCs. In contrast, we identified significant differences in IL-7 density, measured on a single cell level, in 2/59 variables: increased numbers of CD127 molecules on TCRalphabeta+CD4+CD25 (intermed) T-cells and on TCRalphabeta+CD4+CD25-CD107a+ T-cells (mean: 28376 Il-7R binding sites on cells from HD, 48515 in patients with RRMS, 38195 in patients with SPMS and 33692 IL-7 receptor binding sites on cells from patients with OND).

Conclusion: These data show that immunophenotyping represents a powerful tool to differentiate healthy individuals from individuals suffering from neurological diseases and that the number of IL-7 receptor molecules on differentiated TCRalphabeta+CD4+CD25-CD107a+ T-cells, but not the percentage of IL-7R-positive cells, segregates healthy individuals from patients with neurological disorders.

Show MeSH
Related in: MedlinePlus