Dataset Information

Genome Wide Association for Asthma and Lung Function

ABSTRACT:

The SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic (STAMPEED) asthma project includes subjects with asthma and controls from the Chicago Asthma Genetics Study (CAG), NHLBI multicenter Severe Asthma Research Program (SARP) and NHLBI Collaborative Studies on the Genetics of Asthma CSGA (Wake Forest). All studies included European American and African American children and adults with asthma ranging from mild to severe and adult controls. CAG participants were collected at the University of Chicago. SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al, Am J Respir Crit Care Med, 2010, PMID: 19892860). CSGA cases and controls collected by the Wake Forest investigators were also included. Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. Genotyping was performed on the Illumina 1Mv1 platform, with individual genotypes called using clustering algorithms as implemented in the BeadStudio software by Illumina. The total number of markers following standard QC was 1,025,129. Imputation was performed using the HapMap phase 2, release 21 SNPs using MACH with the phased HapMap CEU and YRI haplotypes as a reference. Case/control association tests for asthma status were performed using logistic regression in R (http://CRAN.R-project.org/) on genotype dosages, and adjusting for the first principal component from EIGENSTRAT.

PROVIDER: phs000355.v1.p1 | EGA |

REPOSITORIES: EGA

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Publications

Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.

Torgerson Dara G DG Ampleford Elizabeth J EJ Chiu Grace Y GY Gauderman W James WJ Gignoux Christopher R CR Graves Penelope E PE Himes Blanca E BE Levin Albert M AM Mathias Rasika A RA Hancock Dana B DB Baurley James W JW Eng Celeste C Stern Debra A DA Celedón Juan C JC Rafaels Nicholas N Capurso Daniel D Conti David V DV Roth Lindsey A LA Soto-Quiros Manuel M Togias Alkis A Li Xingnan X Myers Rachel A RA Romieu Isabelle I Van Den Berg David J DJ Hu Donglei D Hansel Nadia N NN Hernandez Ryan D RD Israel Elliott E Salam Muhammad T MT Galanter Joshua J Avila Pedro C PC Avila Lydiana L Rodriquez-Santana Jose R JR Chapela Rocio R Rodriguez-Cintron William W Diette Gregory B GB Adkinson N Franklin NF Abel Rebekah A RA Ross Kevin D KD Shi Min M Faruque Mezbah U MU Dunston Georgia M GM Watson Harold R HR Mantese Vito J VJ Ezurum Serpil C SC Liang Liming L Ruczinski Ingo I Ford Jean G JG Huntsman Scott S Chung Kian Fan KF Vora Hita H Li Xia X Calhoun William J WJ Castro Mario M Sienra-Monge Juan J JJ del Rio-Navarro Blanca B Deichmann Klaus A KA Heinzmann Andrea A Wenzel Sally E SE Busse William W WW Gern James E JE Lemanske Robert F RF Beaty Terri H TH Bleecker Eugene R ER Raby Benjamin A BA Meyers Deborah A DA London Stephanie J SJ Gilliland Frank D FD Burchard Esteban G EG Martinez Fernando D FD Weiss Scott T ST Williams L Keoki LK Barnes Kathleen C KC Ober Carole C Nicolae Dan L DL

Nature genetics 20110731 9

Asthma is a common disease with a complex risk architecture including both genetic and environmental factors. We performed a meta-analysis of North American genome-wide association studies of asthma in 5,416 individuals with asthma (cases) including individuals of European American, African American or African Caribbean, and Latino ancestry, with replication in an additional 12,649 individuals from the same ethnic groups. We identified five susceptibility loci. Four were at previously reported l ...[more]

PMID: 21804549

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Project description:The EVE Asthma Genetics Consortium comprises U.S. investigators who have conducted genome-wide association studies (GWAS) of asthma; the main objective is to combine results of individual studies to increase the overall power to identify loci for asthma and asthma-associated traits. The consortium includes investigators at 9 U.S. institutions with GWAS results for >10,000 individuals representing European American, African American, African Caribbean, U.S. Hispanic, and Mexican populations and includes the following studies: <ul> <li>The Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE)</li> <li>The Genetic Research on Asthma in the African Diaspora (GRAAD) Study</li> <li>The Genetics of Asthma in Latino Americans (GALA 1) Study</li> <li>The Childhood Asthma Management Program (CAMP)</li> <li>The Childhood Asthma Research and Education (CARE) Network</li> <li>The Children's Health Study (CHS)</li> <li>Mexico City Childhood Asthma Study (MCCAS)</li> <li>The Chicago Asthma Genetics Study (CAG)*</li> <li>The National Heart, Lung, and Blood Institute Collaborative Studies of the Genetics of Asthma (CSGA)*</li> <li>The Severe Asthma Research Program (SARP)*</li> </ul> (*CAG, CSGA, and SARP are part of the NHLBI-supported SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic Data (STAMPEED) consortium.) For the GWAS, we developed a common set of >1 million genotyped and imputed SNPs from the EVE Asthma Genetics Consortium to be tested for association with asthma and associated phenotypes in all samples and combined p-values for a grand meta-analysis for asthma gene discovery. A subset of 296 individuals representing African American, European American, and Latino ancestry were selected for whole genome sequencing. The broad goals of this project were to characterize the genetic architecture of asthma and associated quantitative phenotypes (e.g., lung function, total serum IgE) in ethnically diverse populations from the U.S., Mexico, Puerto Rico, and Barbados.

Project description:The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The exome sequencing asthma project includes 200 African-Americans with asthma from the NHLBI multicenter Severe Asthma Research Program (SARP). SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al., Am J Respir Crit Care Med, 2010. PMID: <a href="http://www.ncbi.nlm.nih.gov/pubmed/19892860" target="_blank">19892860</a>). Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. All subjects were carefully characterized using the standardized SARP protocol which included spirometry (medication withheld), maximum bronchodilator reversibility, hyper-responsiveness to methacholine (not performed in subjects with low baseline FEV1), skin-tests to common allergens, questionnaires on health care utilization and medication use and sputum, lung imaging and bronchoscopy in a subset. In addition GWAS data are available (<a href="./study.cgi?study_id=phs000355">phs000355</a>, Illumina platform).

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.

Dataset Information

Genome Wide Association for Asthma and Lung Function

Publications

Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.

Similar Datasets

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