Distinct epithelial gene expression phenotypes in childhood respiratory allergy
L Giovannini-Chami, B Marcet… - European …, 2012 - Eur Respiratory Soc
European Respiratory Journal, 2012•Eur Respiratory Soc
Epithelial cell contribution to the natural history of childhood allergic respiratory disease
remains poorly understood. Our aims were to identify epithelial pathways that are
dysregulated in different phenotypes of respiratory allergy. We established gene expression
signatures of nasal brushings from children with dust mite-allergic rhinitis, associated or not
associated with controlled or uncontrolled asthma. Supervised learning and unsupervised
clustering were used to predict the different subgroups of patients and define altered …
remains poorly understood. Our aims were to identify epithelial pathways that are
dysregulated in different phenotypes of respiratory allergy. We established gene expression
signatures of nasal brushings from children with dust mite-allergic rhinitis, associated or not
associated with controlled or uncontrolled asthma. Supervised learning and unsupervised
clustering were used to predict the different subgroups of patients and define altered …
Epithelial cell contribution to the natural history of childhood allergic respiratory disease remains poorly understood. Our aims were to identify epithelial pathways that are dysregulated in different phenotypes of respiratory allergy.
We established gene expression signatures of nasal brushings from children with dust mite-allergic rhinitis, associated or not associated with controlled or uncontrolled asthma. Supervised learning and unsupervised clustering were used to predict the different subgroups of patients and define altered signalling pathways. These profiles were compared with those of primary cultures of human nasal epithelial cells stimulated with either interleukin (IL)-4, IL-13, interferon (IFN)-α, IFN-β or IFN-γ, or during in vitro differentiation.
A supervised method discriminated children with allergic rhinitis from healthy controls (prediction accuracy 91%), based on 61 transcripts, including 21 T-helper cell (Th) type 2-responsive genes. This method was then applied to predict children with controlled or uncontrolled asthma (prediction accuracy 75%), based on 41 transcripts: nine of them, which were down-regulated in uncontrolled asthma, are directly linked to IFN. This group also included GSDML, which is genetically associated with asthma.
Our data revealed a Th2-driven epithelial phenotype common to all children with dust mite allergic rhinitis. It highlights the influence of epithelially expressed molecules on the control of asthma, in association with atopy and impaired viral response.
European Respiratory Society