E-GEOD-75011
Ontology highlight
ABSTRACT:
DISEASE(S): Allergic Rhinitis,Normal,Asthma
PROVIDER: E-GEOD-75011 | ExpressionAtlas | 2019-05-14
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-75011-analysis-methods.tsv | Tabular | |||
| E-GEOD-75011-analytics.tsv | Tabular | |||
| E-GEOD-75011-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-75011-configuration.xml | Xml | |||
| E-GEOD-75011-g3_g1-mvaPlot.png | Other |
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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.
2014-08-15 | E-GEOD-38003 | biostudies-arrayexpress
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.
2014-08-15 | GSE38003 | 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: Damage to airway epithelium is followed by deposition of extracellular matrix (ECM) and migration of adjacent epithelial cells. We have shown that epithelial cells from asthmatic children fail to heal a wound in vitro. Objectives: To determine whether dysregulated ECM production by the epithelium plays a role in aberrant repair in asthma. Methods: Airway epithelial cells (AEC) from children with asthma (n=36), healthy atopic (n=23) and healthy non-atopic controls (n=53) were investigated by microarray, gene expression and silencing, transcript regulation analysis and ability to close mechanical wounds. Results: Wound repair of AEC from healthy and atopic children were not significantly different and were both faster than AEC from asthmatics. Microarray analysis revealed differential expression of multiple gene sets associated with repair and remodeling in asthmatic AEC. Fibronectin (FN) was the only ECM component whose expression was significantly lower in asthmatic AEC. Expression differences were verified by qPCR and ELISA, and reduced FN expression persisted in asthmatic cells over passage. Silencing of FN expression in non-asthmatic AEC inhibited wound repair, while addition of FN to asthmatic AEC restored reparative capacity. Asthmatic AEC failed to synthesize FN in response to wounding or cytokine/growth factor stimulation. Exposure to 5â, 2âdeoxyazacytidine had no effect on FN expression and subsequent analysis of the FN promoter did not show evidence of DNA methylation. Conclusions: These data show that the reduced capacity of asthmatic epithelial cells to secrete FN is an important contributor to the dysregulated AEC repair observed in these cells. 16 arrays, 2 experimental groups, asthma atopic, AA, and healthy non-atopic, HN.
2010-04-12 | E-GEOD-18965 | biostudies-arrayexpress
Project description:Obesity-associated asthma is recognized as a distinct entity with non-atopic T-helper 1 polarized systemic inflammation. DNA methylation is linked with T helper cell maturation and is associated with inflammatory patterns in asthma and obesity. However, it is unknown whether pathologic dysregulation of DNA methylation patterns occurs in obesity-associated asthma. Using HELP-tagging, we studied epigenome wide DNA methylation in peripheral blood mononuclear cells in 8 urban minority obese asthmatic pre-adolescent children and compared it to methylation in groups of 8 children with asthma alone, obesity alone and healthy controls. Ingenuity Pathway Analysis was used to identify biological pathways that were differentially targeted by methylation dysregulation. We found that obese asthmatics had distinct epigenome wide methylation patterns associated with decreased promoter methylation of a subset of genes, including RANTES, IL-12R and TBX21 and increased promoter methylation of CD23, a low affinity receptor for IgE and of TGFM-NM-2, inhibitor of Th cell activation. T cell signaling and macrophage activation were the two primary pathways that were selectively hypomethylated in obese asthmatics. These methylation patterns suggest that methylation is associated with non-atopic inflammation observed in obese asthmatic children compared to children with asthma alone and obesity alone. Our findings suggest a role of DNA methylation in the observed inflammatory patterns in pediatric obesity-associated asthma in minorities. 32 HpaII test
2014-04-14 | E-GEOD-43705 | 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:DNA methylation profiling of airway epithelial cells (AECs) and peripheral blood mononuclear cells (PBMCs) from normal, atopic and asthmatic subjects. The Illumina GoldenGate Methylation Cancer Panel I was used to obtain DNA methylation profiles across approximately 1505 CpGs in AECs and PBMCs. Samples included 7 healthy, 9 atopic, 4 atopic asthmatic and 5 non-atopic asthmatic subjects. Please note that only some of the samples are matched (i.e. AECs and PBMCs from the same individual) due to DNA quality or sample collection (i.e. only one sample (AEC or PBMC) was collected from the patient).
2012-05-09 | GSE37853 | GEO
Project description:DNA methylation profiling of airway epithelial cells (AECs) and peripheral blood mononuclear cells (PBMCs) from normal, atopic and asthmatic subjects. The Illumina GoldenGate Methylation Cancer Panel I was used to obtain DNA methylation profiles across approximately 1505 CpGs in AECs and PBMCs. Samples included 7 healthy, 9 atopic, 4 atopic asthmatic and 5 non-atopic asthmatic subjects. Please note that only some of the samples are matched (i.e. AECs and PBMCs from the same individual) due to DNA quality or sample collection (i.e. only one sample (AEC or PBMC) was collected from the patient). Bisulphite converted DNA from the 41 samples were hybridised to the Illumina GoldenGate Methylation Beadchip
2012-05-08 | E-GEOD-37853 | biostudies-arrayexpress
Project description:Background: Epigenetic marks, like asthma, are heritable. They are influenced by the environment, direct the maturation of T cellslymphocytes, and have been shown to enhance the development of allergic airways disease in mice. Thus, we hypothesized that epigenetic marks are associated with allergic asthma in inner-city children. Methods: We compared methylation patterns and gene expression in inner-city children with persistent atopic asthma versus healthy controls, using DNA and RNA from peripheral blood mononuclear cells (PBMCs) from inner city children aged 6-12 years with persistent atopic asthma children and healthy controls. Results were externally validated with the GABRIELA study population. Results: Comparing asthmatics (N=97) to controls (N=97), we identified 81 regions that were differentially methylated. Several immune genes were hypomethylated in asthmatics, including IL-13, RUNX3, and a number of specific genes relevant to natural killer cells (KIR2DL4, KIR2DL3, KIR3DL1, and KLRD1) and T cells lymphocytes (TIGIT). 14 differentially methylated regions (DMRs) were associated with the serum IgE concentration of IgE, including RUNX3. These results were internally and externally validated with a global methylation assessment using a different methodology in our inner-city cohort and an independent European cohort (GABRIELA). Hypo- and hypermethylated genes tended to be associated with increased and decreased gene expression, respectively (P<0.6x10-11 for asthma and ; P<0.01 for IgE). To further explore the relationship between methylation and gene expression, we created a matrix of genomic changes in methylation versus transcriptional changes (methyl eQTL) for asthma, and identified cis- and trans-regulated genes whose expression was related to asthma asthma-associated methylation marks. peripheral blood mononuclear cells (PBMCs) from 97 atopic asthmatic and 97 nonatopic nonasthmatic children
2015-02-02 | E-GEOD-40732 | biostudies-arrayexpress
Project description:Background: Epigenetic marks, like asthma, are heritable. They are influenced by the environment, direct the maturation of T cellslymphocytes, and have been shown to enhance the development of allergic airways disease in mice. Thus, we hypothesized that epigenetic marks are associated with allergic asthma in inner-city children. Methods: We compared methylation patterns and gene expression in inner-city children with persistent atopic asthma versus healthy controls, using DNA and RNA from peripheral blood mononuclear cells (PBMCs) from inner city children aged 6-12 years with persistent atopic asthma children and healthy controls. Results were externally validated with the GABRIELA study population. Results: Comparing asthmatics (N=97) to controls (N=97), we identified 81 regions that were differentially methylated. Several immune genes were hypomethylated in asthmatics, including IL-13, RUNX3, and a number of specific genes relevant to natural killer cells (KIR2DL4, KIR2DL3, KIR3DL1, and KLRD1) and T cells lymphocytes (TIGIT). 14 differentially methylated regions (DMRs) were associated with the serum IgE concentration of IgE, including RUNX3. These results were internally and externally validated with a global methylation assessment using a different methodology in our inner-city cohort and an independent European cohort (GABRIELA). Hypo- and hypermethylated genes tended to be associated with increased and decreased gene expression, respectively (P<0.6x10-11 for asthma and ; P<0.01 for IgE). To further explore the relationship between methylation and gene expression, we created a matrix of genomic changes in methylation versus transcriptional changes (methyl eQTL) for asthma, and identified cis- and trans-regulated genes whose expression was related to asthma asthma-associated methylation marks. peripheral blood mononuclear cells (PBMCs) from 97 atopic asthmatic and 97 nonatopic nonasthmatic children
2015-02-02 | E-GEOD-40576 | biostudies-arrayexpress