DNA methylation changes separate allergic patients from healthy controls and may reflect altered CD4+ T-cell population structure.

Altered DNA methylation patterns in CD4(+) T-cells indicate the importance of epigenetic mechanisms in inflammatory diseases. However, the identification of these alterations is complicated by the heterogeneity of most inflammatory diseases. Seasonal allergic rhinitis (SAR) is an optimal disease model for the study of DNA methylation because of its well-defined phenotype and etiology. We generated genome-wide DNA methylation (N(patients) = 8, N(controls) = 8) and gene expression (N(patients) = 9, Ncontrols = 10) profiles of CD4(+) T-cells from SAR patients and healthy controls using Illumina's HumanMethylation450 and HT-12 microarrays, respectively. DNA methylation profiles clearly and robustly distinguished SAR patients from controls, during and outside the pollen season. In agreement with previously published studies, gene expression profiles of the same samples failed to separate patients and controls. Separation by methylation (N(patients) = 12, N(controls) = 12), but not by gene expression (N(patients) = 21, N(controls) = 21) was also observed in an in vitro model system in which purified PBMCs from patients and healthy controls were challenged with allergen. We observed changes in the proportions of memory T-cell populations between patients (N(patients) = 35) and controls (N(controls) = 12), which could explain the observed difference in DNA methylation. Our data highlight the potential of epigenomics in the stratification of immune disease and represents the first successful molecular classification of SAR using CD4(+) T cells.

Dysregulation of complement system and CD4+ T cell activation pathways implicated in allergic response.

Allergy is a complex disease that is likely to involve dysregulated CD4+ T cell activation. Here we propose a novel methodology to gain insight into how coordinated behaviour emerges between disease-dysregulated pathways in response to pathophysiological stimuli. Using peripheral blood mononuclear cells of allergic rhinitis patients and controls cultured with and without pollen allergens, we integrate CD4+ T cell gene expression from microarray data and genetic markers of allergic sensitisation from GWAS data at the pathway level using enrichment analysis; implicating the complement system in both cellular and systemic response to pollen allergens. We delineate a novel disease network linking T cell activation to the complement system that is significantly enriched for genes exhibiting correlated gene expression and protein-protein interactions, suggesting a tight biological coordination that is dysregulated in the disease state in response to pollen allergen but not to diluent. This novel disease network has high predictive power for the gene and protein expression of the Th2 cytokine profile (IL-4, IL-5, IL-10, IL-13) and of the Th2 master regulator (GATA3), suggesting its involvement in the early stages of CD4+ T cell differentiation. Dissection of the complement system gene expression identifies 7 genes specifically associated with atopic response to pollen, including C1QR1, CFD, CFP, ITGB2, ITGAX and confirms the role of C3AR1 and C5AR1. Two of these genes (ITGB2 and C3AR1) are also implicated in the network linking complement system to T cell activation, which comprises 6 differentially expressed genes. C3AR1 is also significantly associated with allergic sensitisation in GWAS data.