Asthma, a chronic respiratory disease affecting over 20 million Americans and 300 million people worldwide, results from the complex interaction of multiple genetic and environmental factors. Many studies have searched for individual genetic variants that contribute to asthma susceptibility, but a thorough understanding of the genetic basis of asthma has not been achieved. Our main hypothesis is that the genetic architecture underlying asthma susceptibility can be better understood by considering multiple genes and incorporating multiple sources of genomic data, including human asthma and mouse airways hyperresponsiveness (AHR) data. This hypothesis will be addressed via specific aims in which we will: (1) identify genetic variants that predispose humans to asthma and modulate human AHR by mapping regions associated with AHR in inbred strains of mice to human genome-wide association data, (2) use gene expression data, known protein-protein interactions, and known functional pathways to enhance the search for asthma and AHR genetic variants in humans, and (3) integrate individual human genetic variants to create a multivariate predictive model of asthma. Novel variants identified by Specific Aims 1 and 2 will be validated by replication in independent human populations of asthmatics. The predictive model created in Specific Aim 3 will be validated through replication and prediction in independent human populations of asthmatics. By completing the specific aims, we hope to make progress towards the development of a comprehensive model of the genetics of asthma, particularly of asthma characterized by increased airways responsiveness.

Public Health Relevance

By completing this proposal, we hope to identify genetic variants that modulate asthma risk. Identifying such variants could provide biological insights that may eventually lead to a better understanding of asthma. Additionally, we will create a predictive model of asthma, which could potentially lead to the development of a clinical prognostic test of who is at risk for developing asthma.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Transition Award (R00)
Project #
4R00HL105663-03
Application #
8724089
Study Section
Special Emphasis Panel (NSS)
Program Officer
Tigno, Xenia
Project Start
2013-09-01
Project End
2016-06-30
Budget Start
2013-09-01
Budget End
2014-06-30
Support Year
3
Fiscal Year
2013
Total Cost
$237,047
Indirect Cost
$102,711
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
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Greenblatt, Rebecca; Mansour, Omar; Zhao, Edward et al. (2017) Gender-specific determinants of asthma among U.S. adults. Asthma Res Pract 3:2
Himes, Blanca E; Ortega, Victor E (2017) Making progress toward understanding the genetic architecture of asthma in the most affected US ethnic group. Eur Respir J 49:
Kan, Mengyuan; Shumyatcher, Maya; Himes, Blanca E (2017) Using omics approaches to understand pulmonary diseases. Respir Res 18:149
Himes, Blanca E; Weitzman, Elissa R (2016) Innovations in health information technologies for chronic pulmonary diseases. Respir Res 17:38
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Koziol-White, Cynthia J; Jia, Yanlin; Baltus, Gretchen A et al. (2016) Inhibition of spleen tyrosine kinase attenuates IgE-mediated airway contraction and mediator release in human precision cut lung slices. Br J Pharmacol 173:3080-3087
Himes, Blanca E; Koziol-White, Cynthia; Johnson, Martin et al. (2015) Vitamin D Modulates Expression of the Airway Smooth Muscle Transcriptome in Fatal Asthma. PLoS One 10:e0134057
McGeachie, Michael J; Wu, Ann C; Tse, Sze Man et al. (2015) CTNNA3 and SEMA3D: Promising loci for asthma exacerbation identified through multiple genome-wide association studies. J Allergy Clin Immunol 136:1503-1510
Bunyavanich, Supinda; Schadt, Eric E; Himes, Blanca E et al. (2014) Integrated genome-wide association, coexpression network, and expression single nucleotide polymorphism analysis identifies novel pathway in allergic rhinitis. BMC Med Genomics 7:48

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