Project description:We performed genome-wide profiling of miRNA expression in the airway epithelial compartment in asthma to identify miRNA pathways associated with epithelial abnormalities using miRNA microarrays and real-time PCR. We also sought to identify the effect of inhaled corticosteroids (ICS) on airway epithelial miRNA expression Samples were obtained from airway epithelial cells by bronchoscopic brushing from three groups of subjects: Healthy Controls ( N=12), Steroid Naïve Asthma (N=16), Steroid-requiring Asthma (N=19).
Project description:Airway epithelial brushings were obtained for microarray analysis by research bronchoscopy in 62 subjects with mild-to-moderate asthma not on inhaled steroids and 43 healthy controls. Asthma subjects were stratified into 2 subgroups, Th2 high and Th2 low asthma, based on their expression of a three-gene signature of Type 2 inflammation: POSTN, SERPINB2, and CLCA1. Gene expression comparisons were made between: 1. asthmatics and healthy controls, and 2. Th2 high asthma and Th2 Low asthma/Healthy controls. The gene expression alterations most associated with asthma were then used in gene set enrichment analyses and gene signature development to compare this asthma dataset to COPD gene expression datasets.
Project description:Airway epithelial brushings were obtained for microarray analysis by research bronchoscopy in 62 subjects with mild-to-moderate asthma not on inhaled steroids and 43 healthy controls. Asthma subjects were stratified into 2 subgroups, Th2 high and Th2 low asthma, based on their expression of a three-gene signature of Type 2 inflammation: POSTN, SERPINB2, and CLCA1.
Project description:Molecular profiling studies in asthma cohorts have identified a Th2-driven asthma subtype, characterized by elevated lower airway expression of POSTN, CLCA1 and SERPINB2. To assess upper airway gene expression as a potential biomarker for lower airway Th2 inflammation, we assayed upper airway (nasal) and lower airway (bronchial) epithelial gene expression, serum total IgE, blood eosinophils and serum periostin in a cohort of 54 allergic asthmatics and 30 matched healthy controls. 23 of 51 asthmatics in our cohort were classified as âTh2 highâ based on lower airway Th2 gene signature expression. Consistent with this classification, âTh2 highâ subjects displayed elevated total IgE and blood eosinophil levels relative to âTh2 lowâ subjects. Upper airway Th2 signature expression was significantly correlated with lower airway Th2 signature expression (r=0.44), with similar strength of association as serum total IgE and blood eosinophils, known biomarkers of Th2 inflammation. In an unbiased genome-wide scan, we identified 8 upper airway genes more strongly correlated with lower airway Th2 gene signature expression (r=0.58), including Eotaxin-3 (CCL26), Galectin-10 (CLC) and Cathepsin-C (CTSC). Asthmatics classified as âTh2 highâ using this 8-gene signature show similar serum total IgE and blood eosinophil levels as âTh2 highâ asthmatics classified using lower airway Th2 gene signature expression. We have identified an 8-gene upper airway signature correlated with lower airway Th2 inflammation, which may be used as a diagnostic biomarker for Th2-driven asthma. Upper airway (nasal) and lower airway (bronchial) epithelial brushings obtained from a cohort of 54 allergic asthmatics and 30 matched healthy controls were profiled by gene expression by microarray. Subjects were assayed for gene expression, serum total IgE, blood eosinophils and serum periostin.
Project description:Rhinovirus infections are the most common cause of asthma exacerbations. The complex responses by the airway epithelium to rhinovirus can be captured by gene expression profiling. We hypothesized that the upper and lower airway epithelium exhibit differential responses to double-stranded RNA (dsRNA), and that this is modulated by the presence of asthma and allergic rhinitis. Identification of dsRNA-induced gene expression profiles by microarray of primary nasal and bronchial epithelial cells from the same individuals and examining the impact of allergic rhinitis with and without concomitant allergic asthma on expression profiles. 17 subjects were included in a cross-sectional study (6 allergic asthma and allergic rhinitis; 5 allergic rhinitis; 6 healthy controls). RNA was extracted from isolated and cultured epithelial cells that were stimulated with Poly(I:C) for 24 hours from bronchial brushes and nasal biopsies, and analyzed by microarray (Affymetrix U133+ PM Genechip Array).
Project description:Rationale: Asthma and atopy shares common features including Th2-inflammation. However, impairment of airway function seems to be absent in atopy. Increased understanding of the complex cellular and molecular pathways defining the similarities and differences between asthma and atopy may be achieved by transcriptomic analysis (RNA-Seq). Hypothesis and Aims: As the airway smooth muscle (ASM) layer plays an important role in airway function, we hypothesized that the transcriptomic profile of the ASM layer in endobronchial biopsies is different between atopic asthma patients and atopic healthy controls. First, we examined the differences in transcriptomic profiles of the ASM layer in endobronchial biopsies between atopic mild, steroid-free asthma patients, and atopic and non-atopic healthy controls. Second, we investigated the association between the transcriptomic profiles of the ASM layer and airway function. Methods: This cross-sectional study included 12 steroid-free atopic asthma patients, 6 atopic, and 6 non-atopic healthy controls. RNA of ASM from 4 endobronchial biopsies per subject was isolated and sequenced (GS FLX+, 454/Roche). Ingenuity Pathway Analysis was used to identify gene networks. Comparison of the numbers of reads per gene in asthma and controls was based on the negative binomial distribution. At the current sample size the estimated false discovery rate was approximately 1%. Results: Yield of isolated RNA was 30-821ng. We identified 174 differentially expressed genes between asthma and atopic controls, 108 between asthma and non-atopic controls, and 135 between atopic and non-atopic controls. A set of 8 genes was identified, which seems to define asthma patients from non-asthmatic controls regardless of atopy. Four of these genes were significantly associated with airway hyperresponsiveness. Conclusion: A difference in transcriptomic profile of the airway smooth muscle layer in asthma patients compared to atopic and non-atopic healthy controls may lead to a different regulation of inflammatory pathways and of airway smooth muscle function and development resulting in impaired airway function.