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Dissecting childhood asthma with nasal transcriptomics distinguishes subphenotypes of disease - 01/03/14

Doi : 10.1016/j.jaci.2013.11.025 
Alex Poole, MS a, Cydney Urbanek, BS a, Celeste Eng, BS b, Jeoffrey Schageman, BS c, Sean Jacobson, MS d, Brian P. O'Connor, PhD a, e, Joshua M. Galanter, MD b, f, Christopher R. Gignoux, PhD b, f, Lindsey A. Roth, MA b, Rajesh Kumar, MD g, Sharon Lutz, PhD d, Andrew H. Liu, MD h, Tasha E. Fingerlin, PhD d, Robert A. Setterquist, PhD c, Esteban G. Burchard, MD b, f, Jose Rodriguez-Santana, MD i, Max A. Seibold, PhD a, h, j,
a Integrated Center for Genes, Environment, and Health, National Jewish Health, Denver, Colo 
h Department of Pediatrics, National Jewish Health, Denver, Colo 
b Department of Medicine, University of California–San Francisco, San Francisco, Calif 
f Department of Bioengineering and Therapeutic Sciences, University of California–San Francisco, San Francisco, Calif 
c Research and Development, Life Technologies, Austin, Tex 
d Departments of Epidemiology and Biostatistics, Colorado School of Public Health, Aurora, Colo 
e Integrated Department of Immunology, National Jewish Health and the University of Colorado-Denver, Denver, Colo 
g Ann and Robert H. Lurie Children's Hospital of Chicago and the Feinberg School of Medicine, Northwestern University, Chicago, Ill 
i Centro de Neumologia Pediatrica, San Juan, Puerto Rico 
j Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado-Denver, Denver, Colo 

Corresponding author: Max A. Seibold, PhD, Department of Pediatrics, Integrated Center for Genes, Environment, and Health, National Jewish Health, 1400 Jackson St, Denver, CO 80238.

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.

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Key words : Nasal airway epithelium, transcriptome, TH2, asthma, bronchial airway epithelium

Abbreviations used : CLCA1, CPA3, FPKM, GALA II, GWAS, KRT5, MUC5B, OSM, POSTN, RNA-seq, SERPINB2, ZPBP2


Plan


 Supported in part by a UCSF Dissertation Year Fellowship and National Institutes of Health (NIH) training grant T32 GM007175 (to C.R.G.); the NIH (ES015794, AI077439, AI079139, AI061774, HL088133, HL078885, HL104608, HL079055, CA113710, and DK064695), the Sandler Foundation, the American Asthma Foundation, and the National Institute on Minority Health and Health Disparities of the National Institutes of Health (P60MD006902; to E.G.B.); and the Colorado Career Development in Genetics and Genomics of Lung Diseases (K12HL090147) and In-kind research support for AmpliSeq assays (sequencing was received from Life Technologies; to M.A.S.).
 Disclosure of potential conflict of interest: C. Eng has received research support from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institutes of Health (NIH). J. M. Galanter has received research support from the NHLBI and NIH. C. R. Gignoux has received research support from the NIH and the American Asthma Foundation and has stock/stock options in 23andMe. R. Kumar has received research support from the NIH. E. G. Burchard has received research support from the NHLBI and NIH. M. A. Seibold has received research support from the Colorado Career NIH Development in Genetics and Genomics of Lung Diseases (K12HL090147), Life Technologies, and Pfizer; served as an advisory board member for Genentech; and has patents planned, pending, or issued from MUC5B Genetic Variant in Pulmonary Fibrosis. The rest of the authors declare that they have no relevant conflicts of interest.


© 2014  American Academy of Allergy, Asthma & Immunology. Publié par Elsevier Masson SAS. Tous droits réservés.
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