Simultaneous statistical inference for epigenetic data

Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology

Simultaneous statistical inference for epigenetic data

Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology

Simultaneous statistical inference for epigenetic data

Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology

Simultaneous Statistical Inference for Epigenetic Data

Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology

Statins increase the frequency of circulating CD4+ FOXP3+ regulatory T cells in healthy individuals

RESUMEN: Las estatinas se han demostrado para modular el número y la función supresora de células T CD4 + FOXP3 (Treg) en condiciones inflamatorias. Sin embargo, no está bien establecido si estatinas también podría afectar Treg en ausencia de inflamación. Para abordar esta cuestión, dieciocho sujetos masculinos normocolesterolémicos fueron tratados con lovastatina o atorvastatina al día durante 45 días. La frecuencia y el fenotipo de circulación Treg se evaluaron en los días 0, 7, 30, y 45. Los niveles de ARNm de FOXP3, IDO, TGF-β, e IL-10 se midieron en las células T CD4 +. Se encontró que tanto los que aumenta significativamente los niveles de ARNm y de frecuencia de Treg FOXP3 en el día 30. En el día 45, los números de Treg volvieron a los valores basales; Sin embargo, el TGF-β y los niveles de ARNm de FOXP3 se mantuvo alta, acompañada por el aumento de los porcentajes de CTLA-4 y GITR que expresan Treg. Treg expresión de Ki-67 se redujo tras el tratamiento con estatinas. la frecuencia de Treg correlacionó positivamente con los niveles plasmáticos de colesterol de lipoproteínas de alta densidad (HDL-C), lo que sugiere un papel para el HDL-C en la homeostasis de Treg. Por lo tanto, las estatinas parecen tener efectos inmunomoduladores inflamación independiente. Por lo tanto, el aumento de la frecuencia de Treg células probablemente contribuye a inmunomoduladores efecto de las estatinas, incluso en individuos sanos.ABSTRACT: Statins have been shown to modulate the number and the suppressive function of CD4+FOXP3+ T cells (Treg) in inflammatory conditions. However, it is not well established whether statin could also affect Treg in absence of inflammation. To address this question, eighteen normocholesterolemic male subjects were treated with lovastatin or atorvastatin daily for 45 days. The frequency and phenotype of circulating Treg were evaluated at days 0, 7, 30, and 45. mRNA levels of FOXP3, IDO, TGF-β, and IL-10 were measured in CD4+ T cells. We found that both statins significantly increased Treg frequency and FOXP3 mRNA levels at day 30. At day 45, Treg numbers returned to baseline values; however, TGF-β and FOXP3 mRNA levels remained high, accompanied by increased percentages of CTLA-4- and GITR-expressing Treg. Treg Ki-67 expression was decreased upon statin treatment. Treg frequency positively correlated with plasma levels of high-density lipoprotein cholesterol (HDL-c), suggesting a role for HDL-c in Treg homeostasis. Therefore, statins appear to have inflammation-independent immune-modulatory effects. Thus, the increase in Treg cells frequency likely contributes to immunomodulatory effect of statins, even in healthy individual

Regulatory T-Cells and Associated Pathways in Metastatic Renal Cell Carcinoma (mRCC) Patients Undergoing DC-Vaccination and Cytokine-Therapy

Purpose: To evaluate CD4+CD25+FOXP3+ T regulatory cells (TREG) and associated immune-regulatory pathways in peripheral blood lymphocytes (PBL) of metastatic renal cell carcinoma (mRCC) patients and healthy volunteers. We subsequently investigated the effects of immunotherapy on circulating TREG combining an extensive phenotype examination, DNA methylation analysis and global transcriptome analysis. Design: Eighteen patients with mRCC and twelve volunteers (controls) were available for analysis. TREG phenotype was examined using flow cytometry (FCM). TREG were also quantified by analyzing the epigenetic status of the FOXP3 locus using methylation specific PCR. As a third approach, RNA of the PBL was hybridized to Affymetrix GeneChip Human Gene 1.0 ST Arrays and the gene signatures were explored using pathway analysis. Results We observed higher numbers of TREG in pre-treatment PBL of mRCC patients compared to controls. A significant increase in TREG was detected in all mRCC patients after the two cycles of immunotherapy. The expansion of TREG was significantly higher in non-responders than in responding patients. Methylation specific PCR confirmed the FCM data and circumvented the variability and subjectivity of the FCM method. Gene Set Enrichment Analysis (GSEA) of the microarray data showed significant enrichment of FOXP3 target genes, CTLA-4 and TGF-ß associated pathways in the patient cohort. Conclusion: Immune monitoring of the peripheral blood and tumor tissue is important for a wide range of diseases and treatment strategies. Adoption of methodology for quantifying TREG with the least variability and subjectivity will enhance the ability to compare and interpret findings across studies

Risk factors for Epstein–Barr virus reactivation after renal transplantation: Results of a large, multi‐centre study

Epstein-Barr virus (EBV) reactivation is a very common and potentially lethal complication of renal transplantation. However, its risk factors and effects on transplant outcome are not well known. Here, we have analysed a large, multi-centre cohort (N = 512) in which 18.4% of the patients experienced EBV reactivation during the first post-transplant year. The patients were characterized pre-transplant and two weeks post-transplant by a multi-level biomarker panel. EBV reactivation was episodic for most patients, only 12 patients showed prolonged viraemia for over four months. Pre-transplant EBV shedding and male sex were associated with significantly increased incidence of post-transplant EBV reactivation. Importantly, we also identified a significant association of post-transplant EBV with acute rejection and with decreased haemoglobin levels. No further severe complications associated with EBV, either episodic or chronic, could be detected. Our data suggest that despite relatively frequent EBV reactivation, it had no association with serious complications during the first post-transplantation year. EBV shedding prior to transplantation could be employed as biomarkers for personalized immunosuppressive therapy. In summary, our results support the employed immunosuppressive regimes as relatively safe with regard to EBV. However, long-term studies are paramount to support these conclusions

Epigenetic Control of the foxp3 Locus in Regulatory T Cells

Compelling evidence suggests that the transcription factor Foxp3 acts as a master switch governing the development and function of CD4(+) regulatory T cells (Tregs). However, whether transcriptional control of Foxp3 expression itself contributes to the development of a stable Treg lineage has thus far not been investigated. We here identified an evolutionarily conserved region within the foxp3 locus upstream of exon-1 possessing transcriptional activity. Bisulphite sequencing and chromatin immunoprecipitation revealed complete demethylation of CpG motifs as well as histone modifications within the conserved region in ex vivo isolated Foxp3(+)CD25(+)CD4(+) Tregs, but not in naïve CD25(−)CD4(+) T cells. Partial DNA demethylation is already found within developing Foxp3(+) thymocytes; however, Tregs induced by TGF-β in vitro display only incomplete demethylation despite high Foxp3 expression. In contrast to natural Tregs, these TGF-β–induced Foxp3(+) Tregs lose both Foxp3 expression and suppressive activity upon restimulation in the absence of TGF-β. Our data suggest that expression of Foxp3 must be stabilized by epigenetic modification to allow the development of a permanent suppressor cell lineage, a finding of significant importance for therapeutic applications involving induction or transfer of Tregs and for the understanding of long-term cell lineage decisions

Regulatory T-Cells and Associated Pathways in Metastatic Renal Cell Carcinoma (mRCC) Patients Undergoing DC-Vaccination and Cytokine-Therapy

To evaluate CD4(+)CD25(+)FOXP3(+) T regulatory cells (T(REG)) and associated immune-regulatory pathways in peripheral blood lymphocytes (PBL) of metastatic renal cell carcinoma (mRCC) patients and healthy volunteers. We subsequently investigated the effects of immunotherapy on circulating T(REG) combining an extensive phenotype examination, DNA methylation analysis and global transcriptome analysis