RNA sequencing of peripheral blood mononuclear cells isolated from Korean patients with asthma
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE226825 | GEO | 2023/03/08
REPOSITORIES: GEO
Similar Datasets
Project description:Asthma is a very frequent airway disease that affects 6 to 20% of the population. Severe asthma, represents 3 to 5% of all asthmatic patients and is histologically characterized by an increased bronchial smooth muscle (BSM) mass and clinically by viral exacerbations. Functionally, BSM remodeling had a poor prognostic value in asthma, since higher BSM mass was associated with lower lung function and increased exacerbation rate. However, the role of BSM as a potential actor of asthma exacerbation has only been sparsely suggested. Thus, we hypothesis that asthmatic BSM cell metabolism is modified compare to that of non-asthmatic and that could be a potential target to reduce asthmatic BSM cell proliferation and remodeling in asthma.
2021-06-10 | PXD015566 | Pride
Project description:Background: Most asthmatic patients have high serum levels of IgE directed against common environmental allergens such as house dust mite, animal danders and moulds. However the presence of specific IgE against individual allergens alone does not account for asthma. Many individuals are atopic but not asthmatic. Precise knowledge of the serum IgE specificity repertoire in asthmatic and non-asthmatic patients would substantially help in understanding the pathogenesis of the disease and at the same time facilitate the treatment and the implementation of preventive measures. Methods: We developed a microarray immunoassay containing 103 common allergens to study the IgE reactivity profiles of 485 asthmatic and 342 non-asthmatic individuals from families whose members had a documented history of asthma and atopy. The results were analyzed using k-means clustering to investigate whether IgE reactivity profiles correlated with asthma, disease severity and age of onset as well as with other atopic conditions such as rhinitis, conjunctivitis and eczema. We trained an artificial neural network (ANN) using the serum reactivity data to identify individuals as asthmatic and non-asthmatic. Results: Individual sera showed clear differences in the number and the combinations of allergens recognized as well as in the level of specific IgE. While the presence of specific IgE against single allergens correlated poorly with the pathological conditions examined k-means clustering analysis unraveled that a particular profile was significantly associated with asthma (p <1E-8). An ANN-based algorithm, calibrated with the profile reactivity data correctly classified as asthmatic or non-asthmatic 78% of the individual examined. Conclusions: Our analysis demonstrates that asthma may be a higher-order phenomenon related to patterns of response and not attributable to single antibody reactions. This information sheds new light on the risk of developing the disease and can be readily utilized in combination with an ANN-based tool to distinguish asthmatic and non-asthmatic individuals on the basis of their serum reactivity profile. The study consisted of a total of 872 sera samples: 485 individuals were diagnosed with asthma, 342 were classified as non asthmatic, a remaining 45 were classified as unconfirmed asthma diagnosis. The serum IgE reactivity profiles were analyzed against 103 allergens representative of 11 distinct allergen classes. Quantification of bound IgE: The fluorescence signal was acquired using ProScanArray Express™ version 3.0 software. PMC reading values of individual spots were corrected against the internal negative control to identify signals above background. Duplicate measurements of individual allergens were utilized. The signal collected from the allergens was interpolated with an external calibration curve to obtain the IU/ml value (see supplementary file GSE20020_IU_ml values.txt), and translated into a Class Score by plotting the data in a standard reactivity scale (see Sample data tables). Class Score values: (CLASS 0 (less than 0.35 IU/ml); CLASS 1 (0.35-0.7 IU/ml); CLASS 2 (0.71-3.5 IU/ml); CLASS 3 (3.51-17.5 IU/ml); CLASS 4 (17.51-50 IU/ml); CLASS 5 (50.01-100 IU/ml).
2012-01-03 | E-GEOD-20020 | biostudies-arrayexpress
Project description:We report the application of RNA sequencing technology for high-throughput profiling of gene expression responses to human rhinovirus infection at 24 hours in air-liquid interface human airway epithelial cell cultures derived from 6 asthmatic and 6 non-asthmatic donors. RNA-seq analysis identified sets of genes associated with asthma specific viral responses. These genes are related to inflammatory pathways, epithelial remodeling and cilium assembly and function, including those described previously (e.g. CCL5, CXCL10 and CX3CL1), and novel ones that were identified for the first time in this study (e.g. CCRL1, CDHR3). We concluded that air liquid interface cultured human airway epithelial cells challenged with live HRV are a useful in vitro model for the study of rhinovirus induced asthma exacerbation, given that our findings are consistent with clinical data sets. Furthermore, our data suggest that abnormal airway epithelial structure and inflammatory signaling are important contributors to viral induced asthma exacerbation. Differentiated air-liquid interface cultured human airway epithelial cell mRNA profiles from 6 asthmatic and 6 non-asthmatic donors after 24 hour treatment with either HRV or vehicle control were generated by deep sequencing, using Illumina HiSeq 2000.
2015-03-01 | E-GEOD-61141 | biostudies-arrayexpress
Project description:Background: Most asthmatic patients have high serum levels of IgE directed against common environmental allergens such as house dust mite, animal danders and moulds. However the presence of specific IgE against individual allergens alone does not account for asthma. Many individuals are atopic but not asthmatic. Precise knowledge of the serum IgE specificity repertoire in asthmatic and non-asthmatic patients would substantially help in understanding the pathogenesis of the disease and at the same time facilitate the treatment and the implementation of preventive measures. Methods: We developed a microarray immunoassay containing 103 common allergens to study the IgE reactivity profiles of 485 asthmatic and 342 non-asthmatic individuals from families whose members had a documented history of asthma and atopy. The results were analyzed using k-means clustering to investigate whether IgE reactivity profiles correlated with asthma, disease severity and age of onset as well as with other atopic conditions such as rhinitis, conjunctivitis and eczema. We trained an artificial neural network (ANN) using the serum reactivity data to identify individuals as asthmatic and non-asthmatic. Results: Individual sera showed clear differences in the number and the combinations of allergens recognized as well as in the level of specific IgE. While the presence of specific IgE against single allergens correlated poorly with the pathological conditions examined k-means clustering analysis unraveled that a particular profile was significantly associated with asthma (p <1E-8). An ANN-based algorithm, calibrated with the profile reactivity data correctly classified as asthmatic or non-asthmatic 78% of the individual examined. Conclusions: Our analysis demonstrates that asthma may be a higher-order phenomenon related to patterns of response and not attributable to single antibody reactions. This information sheds new light on the risk of developing the disease and can be readily utilized in combination with an ANN-based tool to distinguish asthmatic and non-asthmatic individuals on the basis of their serum reactivity profile.
2012-01-03 | GSE20020 | GEO
Project description:Asthma is a very frequent airway disease that affects 6 to 20% of the population. Severe asthma, represents 3 to 5% of all asthmatic patients and is histologically characterized by an increased bronchial smooth muscle (BSM) mass and clinically by viral exacerbations. Functionally, BSM remodeling had a poor prognostic value in asthma, since higher BSM mass was associated with lower lung function and increased exacerbation rate. However, the role of BSM as a potential actor of asthma exacerbation has only been sparsely suggested. We thus hypothesis that asthmatic BSM cells could act on bronchial epithelium and modified its response to rhinovirus infection.
2023-05-02 | PXD015604 | Pride
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.
2016-02-17 | E-GEOD-63744 | 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
Project description:Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long non-coding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor SNPs demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (FDR correction<0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability (RCP)>0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis.
2021-11-04 | GSE186922 | GEO
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.
2016-02-17 | GSE63744 | GEO