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, N controls = 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. Author Summary T-cells, a type of white blood cell, are an important part of the immune-system in humans. T-cells allow us to adapt our immune-response to the various infectious agents we encounter during life. However, T-cells can also cause disease when they target the body’s own cells, e.g. Psoriasis, or when they react to a harmless particle or ‘antigen’, i.e. allergy. Much evidence supports an environmental, or ‘epigenetic’, component to allergy. Surprisingly, although allergy is viewed as a T-cell disease with an epigenetic component, no studies have identified epigenetic differences between healthy individuals and allergic individuals. Using a state-of-the-art genome-wide approach, we found that we could clearly and robustly separate allergic patients from healthy controls. It is often assumed that these changes reflect changes in DNA methylation in a given type of cell; however such differences can also result from different mixtures of T-cell subtypes in the samples. Indeed, we found that allergic patients had different proportions of T-cell sub-types compared to healthy controls. These changes in T-cell proportions may explain the difference in DNA methylation profile we observed between patients and controls. Our study is the first successful molecular classification of allergy using CD4 + T cells.
【초록키워드】 Stratification, Inflammatory diseases, Structure, Gene Expression, T cells, T-cells, Microarrays, CD4, heterogeneity, immune, Population, memory, DNA, epigenomics, White blood cell, cells, humans, Patient, Control, phenotype, allergy, PBMC, DNA methylation, molecular, T-cell, etiology, SAR, Illumina, disease, change, Epigenetic, mechanism, Methylation, Evidence, PBMCs, Gene expression profiles, allergic rhinitis, psoriasis, infectious agents, life, Seasonal allergic rhinitis, blood cell, allergen, infectious agent, Support, profile, healthy control, healthy individuals, Author, alteration, proportions, allergic, separation, healthy controls, gene expression profile, subtype, in vitro model, seasonal, approach, controls, highlight, compared, found, different, proportion, changes in, individuals, purified, explain, healthy individual, Separate, Altered, assumed,