Background: Asthma and atopy share common characteristics including type 2 helper-T-cell-mediated inflammation. However, only asthma is associated with variable airways obstruction. The complex cellular and molecular pathways distinguishing asthma and atopy can now be captured by transcriptomic analysis (RNA-Seq). We hypothesized that the transcriptomic profile of airway smooth muscle (ASM) distinguishes atopic asthma from atopic healthy controls. First, we compared the ASM transcriptomic profiles of endobronchial biopsies between glucocorticoid-free, atopic asthma patients, and atopic and nonatopic healthy controls. Second, we investigated the association between ASM transcriptomic profiles and airway function.
Methods: Twelve asthma patients and 12 control subjects (six atopic, six nonatopic) underwent bronchoscopy. RNA of laser-dissected ASM from 96 bronchial biopsy specimens was sequenced with Roche GS FLX. Gene networks were identified using Ingenuity Pathway Analysis. RNA-Seq reads were assumed to follow a negative binomial distribution. With the current sample size, the estimated false discovery rate was approximately 1%.
Results: One hundred and seventy four ASM genes were differentially expressed between asthma patients and atopic controls, 108 between asthma patients and nonatopic controls, and 135 between atopic and nonatopic controls. A set of eight genes discriminated asthma patients from nonasthmatic controls, irrespective of atopy. Four of these genes (RPTOR, VANGL1, FAM129A, LEPREL1) were associated with airway hyper-responsiveness (P < 0.05).
Conclusion: Airway smooth muscle from asthma patients can be distinguished from that of atopic and nonatopic control subjects by a specific gene expression profile, which is associated with airway hyper-responsiveness.
Keywords: RNA-Seq; airway smooth muscle; asthma; gene expression analysis; transcriptomics.
© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.