Dataset Information


Gene expression profiling of differentiated HNECs stimulated by IL4, IL13, IFNalpha, IFNbeta, IFNgamma and controls

ABSTRACT: Background: In asthma, airway epithelium remodeling can already be detected during childhood, and epithelial cells are more susceptible to virus and oxidative stress. Their exact role in natural history and severity of children allergic respiratory disease remains however surprisingly unexplored. Aim: To analyze dysfunctions of epithelium in dust mite allergic respiratory disease (rhinitis ± asthma) in children. Methods: Expression profilings of nasal epithelial cells collected by brushing were performed on Affymetrix Hugene 1.0 ST arrays. All allergic patients were sensitized to dust mite. 19 patients had an isolated allergic rhinitis (AR). 14 patients had AR associated with asthma. Patients were compared to 12 controls, their severity and control being assessed according to NAEPP and ARIA criteria. Infections by respiratory viruses were excluded by real-time PCR measurements. Results: 61 probes were able to distinguish allergic rhinitis children from healthy controls. A majority of these probes was under the control of Th2 cytokines, as evidenced by parallel experiments performed on primary cultures of nasal epithelial cells. In uncontrolled asthmatic patients, we observed not only an enhanced expression of these Th2-responsive transcripts, but also a down-regulation of interferon-responsive genes. Conclusion: Our study identifies a Th2 driven epithelial phenotype common to all dust mite allergic children. Besides, it suggests that epithelium is involved in the severity of the disease. Expression profiles observed in uncontrolled asthmatic patients suggest that severity of asthma is linked at the same time to atopy and to impaired viral response. Differentiated HNECs gene expression profiling in context of Th2 and IFN cytokine stimulation Each condition was performed in triplicates: total of 21 samples


ORGANISM(S): Homo sapiens  

PROVIDER: E-GEOD-19182 | ExpressionAtlas | 2015-07-27

REPOSITORIES: ExpressionAtlas

Dataset's files

Action DRS
E-GEOD-19182-analysis-methods.tsv Tabular
E-GEOD-19182-atlasExperimentSummary.Rdata Rdata
E-GEOD-19182-configuration.xml Xml
E-GEOD-19182-percentile-ranks.tsv Tabular
E-GEOD-19182.condensed-sdrf.tsv Tabular
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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 su  ...[more]

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