Despite differences in the underlying pathogenic mechanisms of asthma, the fundamental processes that drive lung biology are present across most, if not all, injury and repair responses. However, a major challenge is the identification of common patterns present in these conditions. Currently, asthma phenotypes have been defined in limited terms and imprecise clinical paradigms that rely on features such as allergic history, age of onset, lung function, and symptoms of severity. These studies, including the Severe Asthma Research Program (SARP) characterization of asthma clusters, have been useful, but are driven by differences in demographic and physiologic variables, measures that are distal to many biologic aspects of the disease.4 In contrast to these approaches, integrative functional genomics has the potential to define asthma endophenotypes at a level reflective of true endophenotypes that are mechanistically important to the pathogenesis of asthma. To this end, our multidisciplinary research team has developed a molecular phenotyping protocol to evaluate transcriptomic asthma endophenotypes using genome-wide gene expression measured in the sputum and circulation of asthmatics and has identified 3 transcriptional endophenotypes of asthma (sputum TEA clusters). TEA cluster 1 has a low level of airway inflammation and the most reversible airway obstruction; TEA cluster 2 has a moderate amount of airway inflammation, reversible airflow obstruction, and high sputum IL-13 levels (Th2 cluster); and TEA cluster 3 has the highest level of airway inflammation, the least reversible airway obstruction (remodeled cluster), and high levels of sputum YKL-40 (a chitinase-like-protein we have shown to be associated with remodeling and severe asthma). In addition, using matched blood gene expression data from this cohort, we developed a predictive model using 69 genes that can determine an individual's sputum TEA cluster assignment with 85% accuracy. Taken together, these data demonstrate that transcriptomically-derived asthma endophenotypes are associated with airway inflammation, physiologic remodeling, and immunophenotype-associated cytokines. In this application, integrative functional genomics will be used to evaluate the stability of the TEA cluster model. A second independent cohort of asthma subjects will be studied longitudinally, and the innate and adaptive immune system responses associated with the TEA clusters will be determined. The generalizability of TEA clusters to other lung diseases will be evaluated to identify the fundamental expression networks associated with the TEA clusters. Ultimately, these studies will improve our understanding of asthma heterogeneity at the molecular level at the site of disease, and identify patients with similar modulation of gene networks. The results will generate new molecular diagnoses of asthma endophenotypes that can be used to sub-classify patients for pathogenetic and therapeutic studies using blood and sputum gene expression and identify novel targets for candidate gene studies.

Public Health Relevance

Using an integrative functional genomics method to identify subgroups of patients, we will evaluate gene expression in sputum from asthmatics. These studies will improve our understanding of the molecular diversity of asthma and will identify patients with similar gene networks. The results will generate new molecular diagnoses of asthma that can then be used to sub-classify patients for future research and therapeutic studies.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL118346-03
Application #
8849497
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Noel, Patricia
Project Start
2013-08-15
Project End
2016-05-31
Budget Start
2015-06-01
Budget End
2016-05-31
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Yale University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
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Yan, Xiting; Liang, Anqi; Gomez, Jose et al. (2017) A novel pathway-based distance score enhances assessment of disease heterogeneity in gene expression. BMC Bioinformatics 18:309
Yao, Yi; Welp, Tobias; Liu, Qing et al. (2017) Multiparameter Single Cell Profiling of Airway Inflammatory Cells. Cytometry B Clin Cytom 92:12-20
Gomez, Jose L; Yan, Xiting; Holm, Carole T et al. (2017) Characterisation of asthma subgroups associated with circulating YKL-40 levels. Eur Respir J 50:
Nezgovorova, Vera; Liu, Qing; Hu, Bugu et al. (2016) Sputum Gene Expression of IL-13 Receptor ?2 Chain Correlates with Airflow Obstruction and Helper T-Cell Type 2 Inflammation in Asthma. Ann Am Thorac Soc 13 Suppl 1:S96-7
Yan, Xiting; Chu, Jen-Hwa; Gomez, Jose et al. (2016) Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma. Ann Am Thorac Soc 13 Suppl 1:S104-5
Yan, Xiting; Chu, Jen-Hwa; Gomez, Jose et al. (2015) Noninvasive analysis of the sputum transcriptome discriminates clinical phenotypes of asthma. Am J Respir Crit Care Med 191:1116-25
Ahangari, Farida; Sood, Akshay; Ma, Bing et al. (2015) Chitinase 3-like-1 regulates both visceral fat accumulation and asthma-like Th2 inflammation. Am J Respir Crit Care Med 191:746-57
Levy, Bruce D; Noel, Patricia J; Freemer, Michelle M et al. (2015) Future Research Directions in Asthma. An NHLBI Working Group Report. Am J Respir Crit Care Med 192:1366-72
Gomez, Jose L; Crisafi, Gina M; Holm, Carole T et al. (2015) Genetic variation in chitinase 3-like 1 (CHI3L1) contributes to asthma severity and airway expression of YKL-40. J Allergy Clin Immunol 136:51-58.e10

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