Dataset Information

SNP Health Association Resource (SHARe) Asthma Resource Project (SHARP)

ABSTRACT:

SNP Health Association Resource (SHARe) Asthma Resource project (SHARP) is conducting a genome-wide analysis in adults and children who have participated in National Heart, Lung, and Blood Institute's clinical research trials on asthma. This includes 1041 children with asthma who participated in the Childhood Asthma Management Program (CAMP), 994 children who participated in one or five clinical trials conducted by the Childhood Asthma Research and Education (CARE) network, and 701 adults who participated in one of six clinical trials conducted by the Asthma Clinical Research Network (ACRN).

There are three study types. The longitudinal clinical trials can be subsetted for population-based and/or case-control analyses. Each of the childhood asthma studies has a majority of children participating as part of a parent-child trio. The ACRN (adult) studies are probands alone. Control genotypes will be provided for case-control analyses.

PROVIDER: phs000166 | dbGaP |

SECONDARY ACCESSION(S): PRJNA75423PRJNA75421

REPOSITORIES: dbGaP

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Dataset's files

Source:

			Action	DRS
	phs000166.v1-Documents.zip	Other
	Study_Report.phs000166.SHARP.v1.p1.MULTI.pdf	Pdf
	manifest_phs000166.SHARP.v1.p1.c1.ARR.pdf	Pdf
	datadict_v2.xsl	Other
	phs000166.v1.pht000700.v1.CAMP_CData.data_dict_2008_12_15.xml	Xml

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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.

Project description:BACKGROUND: Evaluation of the airway transcriptome may reveal patterns of gene expression that are associated with clinical phenotypes of asthma. To define transcriptomic endotypes of asthma (TEA) we analyzed gene expression in induced sputum that correlate with phenotypes of disease. METHODS: Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation. RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower pre-bronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04), compared to the other TEA clusters. TEA cluster 2, the smallest cluster had the most subjects that were hospitalized for asthma (P = 0.04). Subjects in TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 x 10-06) and hospitalization (P = 0.01), respectively. CONCLUSIONS: Patterns of gene expression in the sputum and blood reveal TEA clusters that are associated with severe asthma phenotypes in children and adults. Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation.

Dataset Information

SNP Health Association Resource (SHARe) Asthma Resource Project (SHARP)

Dataset's files

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