Transcriptomic profiling of inflammatory phenotypes of severe asthma using endobronchial biopsies
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE143303 | GEO | 2021/07/31
REPOSITORIES: GEO
Similar Datasets
Project description:Transcriptomic profiling of inflammatory phenotypes of severe asthma using endobronchial biopsies
| PRJNA599951 | ENA
Project description:This study identifies differentially expression genes in the sputum of people with eosinophilic, neutrophilic and paucigranulocytic asthma. A selection of markers identified using this microarray were further validated using qPCR on a wider sample set. Gene expression profiles were generated from induced sputum samples from 47 asthma patients and were grouped by the inflammatory phenotype assigned using sputum cell counts into neutrophilic asthma (n=12), eosinophilic asthma (n=17) and paucigranulocytic asthma (n=18). RNA was extracted, amplified and hybridised to Illumina Sentrix HumanRef-8 Version 2 Expression BeadChips, and genes that were differentially expressed between asthma inflammatory phenotypes were compared.
2014-03-25 | E-GEOD-45111 | biostudies-arrayexpress
Project description:Asthma is a complex, chronic respiratory disease with marked clinical and pathophysiological heterogeneity. Distinct inflammatory phenotypes of eosinophilic, mixed, neutrophilic and paucigranulocytic asthma are identified in patients, but most in vivo mouse models, studying asthma mechanisms, mimic only eosinophilic phenotype in humans. The detailed unbiased in vivo studies on molecular responses among different kinds of inflammation in asthma models are lacking. Therefore, we developed mouse models representing three different inflammatory phenotypes of airway inflammation, namely eosinophilic, mixed, and neutrophilic asthma via different methods of house dust mite sensitisation. We used microarrays to determine the global gene expression in the lungs of mice with eosinophilic, mixed and neutrophilic inflammatory phenotypes to uncover underlying differences in clinical presentation and to find novel molecular targets and pathways, which might reflect different molecular mechanisms of the disease. By whole genome transcriptome profiling, we found that airway tight junction (TJ) molecules, mucins and inflammasome-related genes are differentially expressed in distinct phenotypes of allergic airway inflammation. Next, detailed analysis of several molecules from these families by quantitative RT-PCR, western blot and confocal microscopy revealed that (i) Zo-1 and Cldn18 were downregulated in all phenotypes, while Cldn4 upregulation was characteristic for neutrophilic airway inflammation; (ii) mucins Clca1 (Gob5) and Muc5ac were upregulated in eosinophilic and even more in neutrophilic asthma, and (iii) upregulation of inflammasome-related molecules such as Nlrp3, Nlrc4, Casp-1 and IL-1b was characteristic for neutrophilic asthma. Finally, we showed that inflammasome/Th-17/neutrophilic axis cytokines, namely IL-1b and IL-17 impaired epithelial barrier function and increased mucins expressions in primary human bronchial epithelial cells from normal and asthmatic donors. Our findings suggest that differential expression of TJs, mucins and inflammasome-related molecules in distinct asthma phenotypes could be mechanistically linked and might further reflect the differences observed in the clinic.
2018-10-03 | GSE108417 | GEO
Project description: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.
2013-01-18 | E-GEOD-38994 | biostudies-arrayexpress
Project description: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.
2013-01-18 | GSE38994 | GEO
Project description:This project used a state-of-the-art, multi-omics approach to improve our understanding of the aetiopathogenesis of a highly prevalent, performance-limiting disorder of racehorses; mild to moderate equine asthma (MMEA). This advanced knowledge is a prerequisite to improving prophylactic, management and therapeutic options for this condition. Although a number of risk factors for MMEA have been identified, incomplete understanding of the precise aetiopathogenesis of this syndrome means that options for intervention are currently limited. This study aimed to apply a multi-omic approach, reveal key inflammatory pathways involved in inflammatory cell recruitment to the lower airways and highlight pathways specific to different MMEA inflammatory cell profiles (MMEA endotypes). Thus, we compared BALF cell gene and protein expression data from horses with normal bronchoalveolar lavage fluid (BALF) cytology (n = 8) with those isolated from horses with neutrophilic (n = 4), mastocytic (n = 8), mixed neutrophilic/mastocytic (n=4) and mixed eosinophilic/mastocytic (n=3) inflammation. Analyses on transcriptomic and proteomic data derived from BALF cells from horses with neutrophilic cytology showed enrichment in classical inflammatory pathways, while horses with mastocytic cytology showed enrichment in pathways involved in hypersensitivity reactions related to non-classical inflammation that could mimic a Th2 immune response. The mixed eosinophilic/mastocytic group also presented with a non-classical inflammatory profile while, the mixed neutrophilic/mastocytic group revealed profiles consistent with both neutrophilic inflammation and hypersensitivity. Our adopted multi-omics approach (both gene and protein expression) has enabled a more holistic assessment of the immunological status of the lower airways associated with the different cytological profiles of equine asthma.
2024-12-05 | GSE277308 | GEO
Project description:Severe asthma is a clinically and physiologically heterogeneous disease. Benralizumab is a monoclonal antibody which binds the alpha chain of the interleukin-5 receptor and used for severe eosinophilic asthma worldwide. However, not all eosinophilic asthma patients will benefit from benralizumab due to heterogeneity of this disease. Therefore, we performed comprehensive gene expression analysis of whole blood cells that examine severe asthma disease heterogeneity in response to benralizumab. This study is the first to perform comprehensive transcriptome analysis of whole blood cells to identify transcriptomic endotypes of severe asthma clusters that correlate with benralizumab response. The identified transcriptomic endotypes of severe asthma clusters are associated with gene signatures of eosinophils and neutrophilis.
2023-04-15 | GSE148725 | GEO
Project description:Airway epithelial barrier, mucins and inflammasome in distinct eosinophilic, neutrophilic and mixed inflammatory phenotypes of asthma
| PRJNA427213 | ENA
Project description:This study identifies differentially expression genes in the sputum of people with eosinophilic, neutrophilic and paucigranulocytic asthma. A selection of markers identified using this microarray were further validated using qPCR on a wider sample set.
2014-03-25 | GSE45111 | GEO
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.
2014-08-15 | E-GEOD-38003 | biostudies-arrayexpress