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. This cross-sectional transcriptomics study consisted of 2 visits. At visit 1, asthma patients (n=12), and healthy atopic (n=6) and non-atopic (n=6) controls were screened for eligibility to participate according to the in- and exclusion criteria. Spirometry and a methacholine bronchoprovocation test were performed. At visit 2, FEV1 reversibility was measured and 4 endobronchial biopsies per subject were collected during a bronchoscopy. Airway smooth muscle was collected from the biopsies by laser capture microdissection and total RNA isolated. cDNA was prepared using the Ovation RNA-Seq System (NuGEN). RNA-Seq was performed using the GS FLX+ instrument (454/Roche). Sequence reads were mapped against the human genome (hg19; UCSC). Comparison of the numbers of reads per gene between asthma and healthy controls was based on the negative binomial distribution and carried out with the R package DESeq including correction for multiple testing.

Project description:Signalling pathways regulate all major cellular events in health and disease, including asthma development and progression. Complexity of human intracellular signalization can be explored using novel systemic approaches that exploit whole-transcriptome analysis. Cap-analysis-of-gene-expression (CAGE) is a method of choice for generating transcriptome libraries, as it interrogates only terminally capped mRNAs that have the highest probability to be translated into protein. In this study we for the first time systematically profiled differentially activated Intracellular Signalling Pathways (ISPs) in cultured primary human airway smooth muscle (ASM) cells from asthmatic (n=8) and non-asthmatic (n=6) subjects in a high-throughput assay, highlighting asthma-specific co-regulatory patterns. CAGE-libraries from primary human ASM cells were subject to massive parallel next generation sequencing, and a comprehensive analysis of ISP activation was performed using a recently developed technique OncoFinder. Analysis of 270 ISPs led to discovery of multiple pathways clearly distinguishing asthmatic from normal cells. In particular, we found 146 (p<0.05) and 103 (p<0.01) signalling pathways differentially active in asthmatic vs non-asthmatic samples. We identified seven clusters of coherently acting pathways functionally related to the disease. Pathways down-regulated in asthma mostly represented cell death-promoting pathways, whereas the up-regulated ones were mainly involved in cell growth and proliferation, inflammatory response and some specific reactions, including smooth muscle contraction and hypoxia - related signalization. Most of interactions uncovered in this study were not previously associated with asthma, suggesting that these results may be pivotal to development of novel therapeutic strategies that specifically address the ISP signature linked with asthma pathophysiology. Capped mRNA profiles of primary bronchial smooth muscle cells from 8 asthmatic and 6 healthy donors were generated by deep sequencing using Illumina HiSeq1500.

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.

Dataset Information

Expression data from asthamtic and healthy airway smooth muscle cells

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