Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Next-Generation Transcriptome Sequencing (RNA-Seq) of Human Endobronchial Biopsies: Asthma vs Controls

ABSTRACT: Rationale: The cellular and molecular pathways in asthma are highly complex. Increased understanding can be obtained by unbiased transcriptomic analysis (RNA-Seq). Hypothesis and Aims: We hypothesized that the transcriptomic profile of whole human endobronchial biopsies differs between patients with asthma and controls. First, we investigated the feasibility to obtain RNA from whole endobronchial biopsies suitable for RNA-Seq. Second, we examined the difference in transcriptomic profiles between asthma and controls. Methods: This cross-sectional study compared 4 steroid-free atopic asthma patients and 5 healthy non-atopic 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 Poisson distribution. At the current sample size the estimated false discovery rate was 4%. Results: Yield of isolated RNA was 900-9,300ng. We identified 10,167 and 11,006 unique genes for asthma and controls, respectively. Forty-six genes were differentially expressed between asthma and controls, including pendrin, periostin, and BCL2. Ten gene networks involved in cellular morphology, movement, and development had an IPA network score ≥2. Conclusion:RNA isolated from whole human endobronchial biopsies is suitable for RNA-Seq, showing different transcriptomic profiles between asthma and controls. Novel and confirmative genes were found to be linked to asthma. These results indicate that biological processes in the airways of asthma patients are differently regulated compared to healthy controls, which may be relevant for the pathogenesis and treatment of the disease. This cross-sectional transcriptomics study consisted of 2 visits. At visit 1, atopic asthma patients (n=4), and healthy non-atopic controls (n=5) 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. Total RNA from whole endobronchial biopsies was collected. 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 Poisson distribution.

ORGANISM(S): Homo sapiens

SUBMITTER: Ching Yong Yick

PROVIDER: E-GEOD-38994 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Transcriptome sequencing (RNA-Seq) of human endobronchial biopsies: asthma versus controls.

Yick Ching Yong CY Zwinderman Aeilko H AH Kunst Peter W PW Grünberg Katrien K Mauad Thais T Dijkhuis Annemiek A Bel Elisabeth H EH Baas Frank F Lutter René R Sterk Peter J PJ

The European respiratory journal 20130111 3

The cellular and molecular pathways in asthma are highly complex. Increased understanding can be obtained by unbiased transcriptomic analysis (RNA-Seq). We hypothesised that the transcriptomic profile of whole human endobronchial biopsies differs between asthma patients and controls. First, we investigated the feasibility of obtaining RNA from whole endobronchial biopsies suitable for RNA-Seq. Secondly, we examined the difference in transcriptomic profiles between asthma and controls. This cross ...[more]

PMID: 23314903

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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:Rationale: Steroids are the mainstay of asthma therapy. However, it is unclear whether the benefits of steroids in asthma are merely based on anti-inflammatory properties. Steroids may also alter gene expression of airway smooth muscle (ASM). Hypothesis and Aims: We hypothesized that the transcriptomic profile of the ASM layer in endobronchial biopsies of atopic asthma patients changes by oral steroid therapy. First, we examined the change in ASM transcriptomic profile in endobronchial biopsies after 14 days of oral steroid therapy. Second, we investigated the association between changes in ASM transcriptomic profile and airway function. Methods: 12 atopic steroid-free asthma patients were included in this double-blind intervention study. Endobronchial biopsies were taken before and after 14 days of oral prednisolon (n=6) or placebo (n=6). RNA of laser-dissected ASM was sequenced (RNA-Seq) using the GS FLX+ System (454/Roche). Gene networks were identified using Ingenuity Pathway Analysis. RNA-Seq reads were assumed to follow a negative binomial distribution. At the current sample size the estimated false discovery rate was approximately 3%. Results: 15 genes were significantly changed by 14 days of oral prednisolon. 2 of these genes (FAM129A, SYNPO2) were associated with the methacholine PC20 (r=0.637, p=0.035; r=0.662, p=0.027). Pathway analysis revealed 3 gene networks that were associated with cellular functions including cellular growth, proliferation, and development. Conclusion: Oral prednisolon changes the gene expression profile of the ASM layer in asthma. This indicates that steroids also exert effects on the transcriptomic level of ASM in addition to their anti-inflammatory properties, which can promote improved airway function. The current randomized, double-blind, parallel, placebo-controlled intervention study comprised 4 visits. At visit 1, asthma patients were screened according to the in- and exclusion criteria prior to enrollment. Additionally, spirometry and methacholine bronchoprovocation test were performed. At visit 2, FEV1 reversibility was measured and endobronchial biopsies were collected during a bronchoscopy. Asthma patients were then prescribed oral prednisolon at a dose of 0.5 mg/kg per day or placebo for 14 consecutive days. The dosage and dosing scheme was based on international recommendations for the treatment of acute exacerbations [1]. On the 11th day after visit 2, the patients visited the lung function laboratory for spirometry and methacholine bronchoprovocation test. Finally, at visit 4 (15th day after visit 2) FEV1 reversibility was measured and endobronchial biopsies were collected by 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 the prednisolon and placebo study group was carried out with the R package DESeq.

Dataset Information

Next-Generation Transcriptome Sequencing (RNA-Seq) of Human Endobronchial Biopsies: Asthma vs Controls

Publications

Transcriptome sequencing (RNA-Seq) of human endobronchial biopsies: asthma versus controls.

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