DNA Methylation Changes Separate Allergic Patients from Healthy Controls and May Reflect Altered CD4⁺ T-Cell Population Structure
Artikel i vetenskaplig tidskrift, 2014

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 (Npatients = 8, Ncontrols = 8) and gene expression (Npatients = 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 (Npatients = 12, Ncontrols = 12), but not by gene expression (Npatients = 21, Ncontrols = 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 (Npatients = 35) and controls (Ncontrols = 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.

Pollen

Memory T cells

Gene expression

Microarrays

Methylation

Epigenetics

DNA methylation

T cells

Författare

C.E. Nestor

Universitetssjukhuset i Linkoping

Fredrik Barrenäs

Universitetssjukhuset i Linkoping

Hui Wang

Göteborgs universitet

A. Lentini

Universitetssjukhuset i Linkoping

H. Zhang

Universitetssjukhuset i Linkoping

Sören Bruhn

Universitetssjukhuset i Linkoping

Rebecka Jörnsten

Göteborgs universitet

Chalmers, Matematiska vetenskaper, matematisk statistik

M.A. Langston

University of Tennessee

G. Rogers

University of Tennessee

M. Gustafsson

Universitetssjukhuset i Linkoping

Mikael Benson

Universitetssjukhuset i Linkoping

PLoS Genetics

1553-7390 (ISSN) 1553-7404 (eISSN)

Vol. 10 1 e1004059

Ämneskategorier

Klinisk medicin

DOI

10.1371/journal.pgen.1004059