ABSTRACTS in the management of subjects with asthma from the young to the very old. In the future, it will be important to develop strategies to prevent the development of asthma and, in children with the disease, to maximize the appropriate use of, and adherence to, the available medications before considering more expensive alternatives. To do this, we will need to standardize and harmonize medical care, while improving communication and setting up systems of collaboration. If executed effectively, this effort should have a marked impact on reducing the prevalence of asthma in the future and the consequent burden of asthma on society. Author disclosures are available with the text of this article at www.atsjournals.org. (Received in original form June 29, 2015; accepted in final form July 14, 2015 ) Correspondence and requests for reprints should be addressed to Stanley J. Szefler, M.D., Pediatric Asthma Research Program, the Breathing Institute, Children’s Hospital Colorado, 13123 East 16th Avenue, Box 395, Aurora, CO 80045. E-mail: [email protected] Ann Am Thorac Soc Vol 13, Supplement 1, pp S103–S104, Mar 2016 Copyright © 2016 by the American Thoracic Society Internet address: www.atsjournals.org
understand the contributions of genetic variation to asthma and other diseases. Author disclosures are available with the text of this abstract at www.atsjournals.org. (Received in original form August 13, 2015; accepted in final form August 19, 2015 ) Supported by National Institutes of Health grant R01HL124285 (to D.J.E.). Correspondence and requests for reprints should be addressed to David J. Erle, M.D., University of California, San Francisco, UCSF Box 2922, San Francisco, CA 94143. E-mail: [email protected] Ann Am Thorac Soc Vol 13, Supplement 1, p S104, Mar 2016 Copyright © 2016 by the American Thoracic Society Internet address: www.atsjournals.org
Reference 1 Zhao W, Pollack JL, Blagev DP, Zaitlen N, McManus MT, Erle DJ. Massively parallel functional annotation of 39 untranslated regions. Nat Biotechnol 2014;32:387–391.
Massively Parallel Identification of Regulatory Variants in Asthma
Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma
Anne Biton, Dara Torgerson, Olivier Letonqueze, Wenxue Zhao, Noah Zaitlen, and David J. Erle
Xiting Yan1, Jen-Hwa Chu2, Jose Gomez1, Maria Koenigs1, Carole Holm1, Xiaoxuan He1, Mario F. Perez1, Hongyu Zhao1, Shrikant Mane1, Fernando D. Martinez3, Carole Ober4, Dan L. Nicolae4, Kathleen C. Barnes5, Stephanie J. London6, Frank Gilliland7, Scott T. Weiss2, Benjamin A. Raby2, Lauren Cohn1, and Geoffrey L. Chupp1
University of California, San Francisco, San Francisco, California
Genetic association studies have identified hundreds of genetic variants associated with asthma and other common diseases. However, identification of causal variants underlying these associations is complicated by linkage disequilibrium as well as the fact that most associations are found in noncoding regions. To address these issues, we recently developed a novel massively parallel experimental assay for measuring activity of one major class of regulatory sequences, the mRNA 39 untranslated region (UTR) (1). This functional annotation of sequences from three-prime UTRs (fast-UTR) assay detected the effects of a diverse set of known and novel 39 UTR cis-regulatory elements on mRNA levels, mRNA stability, and protein production. Furthermore, fast-UTR was able to directly measure functional effects of large sets of sequence variants and was suitable for use in multiple cell types. To help understand the importance of 39 UTR sequence variation in asthma, we designed a fast-UTR library representing more than 200,000 39 UTR variants. These variants include (1) all common 39 UTR variants in all protein-coding genes, and (2) selected rare variants identified by whole genome sequencing in the Consortium on Asthma among Africanancestry Populations in the Americas (CAAPA) study. We are testing the activity of these sequences in three cell types that are important for asthma pathogenesis: airway epithelial cells, CD41 T cells, and airway smooth muscle cells. This project will demonstrate how massively parallel assay technology can be harnessed to identify functional variants and help
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1 Yale School of Medicine, New Haven, Connecticut; 2Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts; 3University of Arizona, Tucson, Arizona; 4University of Chicago, Chicago, Illinois; 5The Johns Hopkins University School of Medicine, Baltimore, Maryland; 6National Institutes of Health, Research Triangle Park, North Carolina; and 7University of Southern California Keck School of Medicine, Los Angeles, California
Introduction: It is increasingly recognized that asthma is a heterogeneous disease. Therefore, it is possible that analysis of gene expression in the airway will reveal clinically meaningful transcriptional endotypes of asthma (TEA clusters). Methods: We measured whole transcriptome gene expression profiles in the sputum and whole blood of 100 individuals with asthma and 12 control subjects using the Affymetrix HuGene ST 1.0 gene arrays. Unsupervised clustering was conducted using pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG). This identified three TEA clusters that were correlated with clinical, physiologic, and inflammatory characteristics of the disease. TEA cluster 1 is a cluster of patients with asthma with a significantly higher rate of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) than the other two TEA clusters. TEA cluster 2 has a higher rate of hospitalization for asthma (P = 0.04) and is AnnalsATS Volume 13 Supplement 1 | March 2016
understand the contributions of genetic variation to asthma and other diseases. Author disclosures are available with the text of this abstract at www.atsjournals.org. (Received in original form August 13, 2015; accepted in final form August 19, 2015 ) Supported by National Institutes of Health grant R01HL124285 (to D.J.E.). Correspondence and requests for reprints should be addressed to David J. Erle, M.D., University of California, San Francisco, UCSF Box 2922, San Francisco, CA 94143. E-mail: [email protected] Ann Am Thorac Soc Vol 13, Supplement 1, p S104, Mar 2016 Copyright © 2016 by the American Thoracic Society Internet address: www.atsjournals.org
Reference 1 Zhao W, Pollack JL, Blagev DP, Zaitlen N, McManus MT, Erle DJ. Massively parallel functional annotation of 39 untranslated regions. Nat Biotechnol 2014;32:387–391.
Massively Parallel Identification of Regulatory Variants in Asthma
Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma
Anne Biton, Dara Torgerson, Olivier Letonqueze, Wenxue Zhao, Noah Zaitlen, and David J. Erle
Xiting Yan1, Jen-Hwa Chu2, Jose Gomez1, Maria Koenigs1, Carole Holm1, Xiaoxuan He1, Mario F. Perez1, Hongyu Zhao1, Shrikant Mane1, Fernando D. Martinez3, Carole Ober4, Dan L. Nicolae4, Kathleen C. Barnes5, Stephanie J. London6, Frank Gilliland7, Scott T. Weiss2, Benjamin A. Raby2, Lauren Cohn1, and Geoffrey L. Chupp1
University of California, San Francisco, San Francisco, California
Genetic association studies have identified hundreds of genetic variants associated with asthma and other common diseases. However, identification of causal variants underlying these associations is complicated by linkage disequilibrium as well as the fact that most associations are found in noncoding regions. To address these issues, we recently developed a novel massively parallel experimental assay for measuring activity of one major class of regulatory sequences, the mRNA 39 untranslated region (UTR) (1). This functional annotation of sequences from three-prime UTRs (fast-UTR) assay detected the effects of a diverse set of known and novel 39 UTR cis-regulatory elements on mRNA levels, mRNA stability, and protein production. Furthermore, fast-UTR was able to directly measure functional effects of large sets of sequence variants and was suitable for use in multiple cell types. To help understand the importance of 39 UTR sequence variation in asthma, we designed a fast-UTR library representing more than 200,000 39 UTR variants. These variants include (1) all common 39 UTR variants in all protein-coding genes, and (2) selected rare variants identified by whole genome sequencing in the Consortium on Asthma among Africanancestry Populations in the Americas (CAAPA) study. We are testing the activity of these sequences in three cell types that are important for asthma pathogenesis: airway epithelial cells, CD41 T cells, and airway smooth muscle cells. This project will demonstrate how massively parallel assay technology can be harnessed to identify functional variants and help
S104
1 Yale School of Medicine, New Haven, Connecticut; 2Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts; 3University of Arizona, Tucson, Arizona; 4University of Chicago, Chicago, Illinois; 5The Johns Hopkins University School of Medicine, Baltimore, Maryland; 6National Institutes of Health, Research Triangle Park, North Carolina; and 7University of Southern California Keck School of Medicine, Los Angeles, California
Introduction: It is increasingly recognized that asthma is a heterogeneous disease. Therefore, it is possible that analysis of gene expression in the airway will reveal clinically meaningful transcriptional endotypes of asthma (TEA clusters). Methods: We measured whole transcriptome gene expression profiles in the sputum and whole blood of 100 individuals with asthma and 12 control subjects using the Affymetrix HuGene ST 1.0 gene arrays. Unsupervised clustering was conducted using pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG). This identified three TEA clusters that were correlated with clinical, physiologic, and inflammatory characteristics of the disease. TEA cluster 1 is a cluster of patients with asthma with a significantly higher rate of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) than the other two TEA clusters. TEA cluster 2 has a higher rate of hospitalization for asthma (P = 0.04) and is AnnalsATS Volume 13 Supplement 1 | March 2016
