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Expression data from severe asthmatics, mild asthmatics and healthy controls

ABSTRACT: Background: Around 5% of children with asthma suffer from chronic symptoms and/or severe exacerbations despite extensive treatment. The causes of severe therapy-resistant childhood asthma are poorly understood. Objectives: To define global patterns of gene expression in severe therapy-resistant vs. controlled asthma and healthy controls. Methods: Children with severe, therapy-resistant (SA, n=20) and controlled asthma (CA, n=20) were identified from a Swedish nation-wide study including extensive clinical and immunological characterisation. In addition, healthy controls were recruited (Ctrl, n=19). White blood cells were isolated and the global transcriptome profile was characterised using the Affymetrix Human Gene ST 1.0 chip. Results: 1378 genes were differentially expressed in one or several of the CA vs. Ctrl, SA vs. CA or SA vs. Ctrl contrasts. A large number could uniquely differentiate the SA group from the CA (n=351 genes) and Ctrl (n=315) groups, whereas fewer genes differentiated the CA from the Ctrl group (n=149). Several non-coding RNAs were found up-regulated in SA compared to CA or Ctrl. Three significantly enriched KEGG pathways were represented; bitter taste transduction, TAS2Rs (up-regulated mostly in SA), natural killer cell mediated cytotoxicity (up-regulated in CA) and N-Glycan biosynthesis (down-regulated in SA). An unsupervised hierarchical clustering of the 1378 genes could crudely separate the SA, CA and Ctrl individuals. Conclusion: Our data indicate a separation in gene expression patterns between children with severe, therapy-resistant asthma and controlled persistent asthma, and suggest novel pathways characterizing the severe therapy-resistant asthma phenotype.

ORGANISM(S): Homo sapiens

PROVIDER: GSE27011 | GEO | 2011/12/01

SECONDARY ACCESSION(S): PRJNA137597

REPOSITORIES: GEO

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Project description:Background: Around 5% of children with asthma suffer from chronic symptoms and/or severe exacerbations despite extensive treatment. The causes of severe therapy-resistant childhood asthma are poorly understood. Objectives: To define global patterns of gene expression in severe therapy-resistant vs. controlled asthma and healthy controls. Methods: Children with severe, therapy-resistant (SA, n=20) and controlled asthma (CA, n=20) were identified from a Swedish nation-wide study including extensive clinical and immunological characterisation. In addition, healthy controls were recruited (Ctrl, n=19). White blood cells were isolated and the global transcriptome profile was characterised using the Affymetrix Human Gene ST 1.0 chip. Results: 1378 genes were differentially expressed in one or several of the CA vs. Ctrl, SA vs. CA or SA vs. Ctrl contrasts. A large number could uniquely differentiate the SA group from the CA (n=351 genes) and Ctrl (n=315) groups, whereas fewer genes differentiated the CA from the Ctrl group (n=149). Several non-coding RNAs were found up-regulated in SA compared to CA or Ctrl. Three significantly enriched KEGG pathways were represented; bitter taste transduction, TAS2Rs (up-regulated mostly in SA), natural killer cell mediated cytotoxicity (up-regulated in CA) and N-Glycan biosynthesis (down-regulated in SA). An unsupervised hierarchical clustering of the 1378 genes could crudely separate the SA, CA and Ctrl individuals. Conclusion: Our data indicate a separation in gene expression patterns between children with severe, therapy-resistant asthma and controlled persistent asthma, and suggest novel pathways characterizing the severe therapy-resistant asthma phenotype. The transcriptomes of 59 subjects were assayed on the Affymetrix Human Gene ST 1.0 expression array. All samples passed pre-hybridisation quality control. After pre-processing and quality control of the post-hybridised arrays, five samples were regarded as outliers and removed (ctrl 510, MA 248, SA 141, SA 261, SA 41). The remaining sample set of 17 severe asthmatics (SA), 19 mild asthmatics (MA) and 18 controls (ctrl) were used for down-stream analysis.

Project description:Asthma is an inflammatory disease of the airways characterised by episodic airway obstruction resulting in cough, episodic shortness of breath. It is, and is clinically and physiologically heterogeneous. It is estimated that around 300 million people worldwide have the diseaseare diagnosed with asthma, including up to 20% of children (Asher et al, 2006), with 5–10% of these children believed to have severe or difficult-to-treat asthma. Asthma has often been classified in terms of severity and based on clinical diagnostic criteria, but it is now apparent that the heterogeneity that exists at the physiological level is also a feature of the underlying pathological mechanisms (Lotvall et al, 2011). The aim of this study was to identify blood transcriptomics profiles for children diagnosed with asthma or wheeze, and establish whether these profiles suggested endotypes or mechanisms that could underlie disease, or be related to disease severity, in these children. Importantly, given that children are currently treated with the same medicines as adults, we also aimed to compare profiles of children to those of adults with asthma to help determine whether efforts should be directed to the development of medicines targeting pathways and mechanisms that may be unique to children. To this end, we used gene transcriptome data generated from blood samples from adults and children from the U-BIOPRED consortium to ask how similar or different the differential gene expression profiles were between groups of adults and pre-school or school-aged children with severe or mild-moderate asthma (or wheeze for the pre-school aged children) using current definitions. The Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project was set up as a public-private partnership within the framework of the Innovative Medicines Initiative (IMI), engaging academia, the pharmaceutical industry and patient groups. The goal of this investigation was to identify transcript fingerprints in whole blood that characterize patients with severe asthma and to determine whether subgroups of severe asthmatics can be identified.

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Expression data from severe asthmatics, mild asthmatics and healthy controls

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