Alex Poole1, Cydney Urbanek1, Celeste Eng2, Jeoffrey Schageman3, Sean Jacobson4, Brian P O'Connor5, Joshua M Galanter6, Christopher R Gignoux6, Lindsey A Roth2, Rajesh Kumar7, Sharon Lutz4, Andrew H Liu8, Tasha E Fingerlin4, Robert A Setterquist3, Esteban G Burchard6, Jose Rodriguez-Santana9, Max A Seibold10. 1. Integrated Center for Genes, Environment, and Health, National Jewish Health, Denver, Colo. 2. Department of Medicine, University of California-San Francisco, San Francisco, Calif. 3. Research and Development, Life Technologies, Austin, Tex. 4. Departments of Epidemiology and Biostatistics, Colorado School of Public Health, Aurora, Colo. 5. Integrated Center for Genes, Environment, and Health, National Jewish Health, Denver, Colo; Integrated Department of Immunology, National Jewish Health and the University of Colorado-Denver, Denver, Colo. 6. Department of Medicine, University of California-San Francisco, San Francisco, Calif; Department of Bioengineering and Therapeutic Sciences, University of California-San Francisco, San Francisco, Calif. 7. Ann and Robert H. Lurie Children's Hospital of Chicago and the Feinberg School of Medicine, Northwestern University, Chicago, Ill. 8. Department of Pediatrics, National Jewish Health, Denver, Colo. 9. Centro de Neumologia Pediatrica, San Juan, Puerto Rico. 10. Integrated Center for Genes, Environment, and Health, National Jewish Health, Denver, Colo; Department of Pediatrics, National Jewish Health, Denver, Colo; Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado-Denver, Denver, Colo. Electronic address: seiboldm@njhealth.org.
Abstract
BACKGROUND: Bronchial airway expression profiling has identified inflammatory subphenotypes of asthma, but the invasiveness of this technique has limited its application to childhood asthma. OBJECTIVES: We sought to determine whether the nasal transcriptome can proxy expression changes in the lung airway transcriptome in asthmatic patients. We also sought to determine whether the nasal transcriptome can distinguish subphenotypes of asthma. METHODS: Whole-transcriptome RNA sequencing was performed on nasal airway brushings from 10 control subjects and 10 asthmatic subjects, which were compared with established bronchial and small-airway transcriptomes. Targeted RNA sequencing nasal expression analysis was used to profile 105 genes in 50 asthmatic subjects and 50 control subjects for differential expression and clustering analyses. RESULTS: We found 90.2% overlap in expressed genes and strong correlation in gene expression (ρ = .87) between the nasal and bronchial transcriptomes. Previously observed asthmatic bronchial differential expression was strongly correlated with asthmatic nasal differential expression (ρ = 0.77, P = 5.6 × 10(-9)). Clustering analysis identified TH2-high and TH2-low subjects differentiated by expression of 70 genes, including IL13, IL5, periostin (POSTN), calcium-activated chloride channel regulator 1 (CLCA1), and serpin peptidase inhibitor, clade B (SERPINB2). TH2-high subjects were more likely to have atopy (odds ratio, 10.3; P = 3.5 × 10(-6)), atopic asthma (odds ratio, 32.6; P = 6.9 × 10(-7)), high blood eosinophil counts (odds ratio, 9.1; P = 2.6 × 10(-6)), and rhinitis (odds ratio, 8.3; P = 4.1 × 10(-6)) compared with TH2-low subjects. Nasal IL13 expression levels were 3.9-fold higher in asthmatic participants who experienced an asthma exacerbation in the past year (P = .01). Several differentially expressed nasal genes were specific to asthma and independent of atopic status. CONCLUSION: Nasal airway gene expression profiles largely recapitulate expression profiles in the lung airways. Nasal expression profiling can be used to identify subjects with IL13-driven asthma and a TH2-skewed systemic immune response.
BACKGROUND: Bronchial airway expression profiling has identified inflammatory subphenotypes of asthma, but the invasiveness of this technique has limited its application to childhood asthma. OBJECTIVES: We sought to determine whether the nasal transcriptome can proxy expression changes in the lung airway transcriptome in asthmatic patients. We also sought to determine whether the nasal transcriptome can distinguish subphenotypes of asthma. METHODS: Whole-transcriptome RNA sequencing was performed on nasal airway brushings from 10 control subjects and 10 asthmatic subjects, which were compared with established bronchial and small-airway transcriptomes. Targeted RNA sequencing nasal expression analysis was used to profile 105 genes in 50 asthmatic subjects and 50 control subjects for differential expression and clustering analyses. RESULTS: We found 90.2% overlap in expressed genes and strong correlation in gene expression (ρ = .87) between the nasal and bronchial transcriptomes. Previously observed asthmatic bronchial differential expression was strongly correlated with asthmatic nasal differential expression (ρ = 0.77, P = 5.6 × 10(-9)). Clustering analysis identified TH2-high and TH2-low subjects differentiated by expression of 70 genes, including IL13, IL5, periostin (POSTN), calcium-activated chloride channel regulator 1 (CLCA1), and serpin peptidase inhibitor, clade B (SERPINB2). TH2-high subjects were more likely to have atopy (odds ratio, 10.3; P = 3.5 × 10(-6)), atopic asthma (odds ratio, 32.6; P = 6.9 × 10(-7)), high blood eosinophil counts (odds ratio, 9.1; P = 2.6 × 10(-6)), and rhinitis (odds ratio, 8.3; P = 4.1 × 10(-6)) compared with TH2-low subjects. Nasal IL13 expression levels were 3.9-fold higher in asthmatic participants who experienced an asthma exacerbation in the past year (P = .01). Several differentially expressed nasal genes were specific to asthma and independent of atopic status. CONCLUSION: Nasal airway gene expression profiles largely recapitulate expression profiles in the lung airways. Nasal expression profiling can be used to identify subjects with IL13-driven asthma and a TH2-skewed systemic immune response.
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