Gene Expression in Relation to Exhaled Nitric Oxide Identifies Novel Asthma Phenotypes with Unique Biomolecular Pathways

Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma...

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Veröffentlicht in:American journal of respiratory and critical care medicine Jg. 190; H. 12; S. 1363 - 1372
Hauptverfasser: Modena, Brian D., Tedrow, John R., Milosevic, Jadranka, Bleecker, Eugene R., Meyers, Deborah A., Wu, Wei, Bar-Joseph, Ziv, Erzurum, Serpil C., Gaston, Benjamin M., Busse, William W., Jarjour, Nizar N., Kaminski, Naftali, Wenzel, Sally E.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States American Thoracic Society 15.12.2014
Schlagworte:
Adult
Asthma - genetics
Asthma - metabolism
Biomarkers
Bronchi - cytology
Bronchi - metabolism
Case-Control Studies
Female
Gene Expression - genetics
Humans
Male
Middle Aged
Multigene Family - genetics
Nitric Oxide - metabolism
Oligonucleotide Array Sequence Analysis
Original
Phenotype
Real-Time Polymerase Chain Reaction
exhaled nitric oxide
severe asthma
clustering
ISSN:1073-449X, 1535-4970, 1535-4970
Online-Zugang:Volltext
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Zusammenfassung:Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma studies. To link gene expression patterns to clinical asthma phenotypes. We used a microarray platform to analyze bronchial airway epithelial cell gene expression in relation to the asthma biomarker fractional exhaled nitric oxide (FeNO) in 155 subjects with asthma and healthy control subjects from the Severe Asthma Research Program (SARP). We first identified a diverse set of 549 genes whose expression correlated with FeNO. We used k-means to cluster the patient samples according to the expression of these genes, identifying five asthma clusters/phenotypes with distinct clinical, physiological, cellular, and gene transcription characteristics-termed "subject clusters" (SCs). To then investigate differences in gene expression between SCs, a total of 1,384 genes were identified that highly differentiated the SCs at an unadjusted P value < 10(-6). Hierarchical clustering of these 1,384 genes identified nine gene clusters or "biclusters," whose coexpression suggested biological characteristics unique to each SC. Although genes related to type 2 inflammation were present, novel pathways, including those related to neuronal function, WNT pathways, and actin cytoskeleton, were noted. These findings show that bronchial epithelial cell gene expression, as related to the asthma biomarker FeNO, can identify distinct asthma phenotypes, while also suggesting the presence of underlying novel gene pathways relevant to these phenotypes.
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ISSN:1073-449X
1535-4970
1535-4970
DOI:10.1164/rccm.201406-1099OC