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Published on: January 21, 2018
Nasal Airway Transcriptome Reflects Selected Asthma-Associated Gene Signatures in the Lower Airways
Hui Wen1,2, Tessa Kole1,2, Orestes A Carpaij1,2
1Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Background:
Transcriptomic analysis of bronchial brushes reveals asthma-associated gene signatures but is limited by the invasiveness of bronchoscopy. Based on the "united airways" hypothesis, we evaluated whether and to what extent nasal brushes reflect asthma-associated transcriptomic changes in the lower airways.
Methods:
In the ARMS study, we included 26 asthma patients and 28 healthy controls, all fully clinically characterized. Nasal and bronchial brushes were collected for RNA sequencing. We used edgeR and WGCNA to identify asthma-associated genes and modules in bronchial brushes. We assessed their expression patterns in ARMS nasal brushes and validated the findings in the independent ATLANTIS study (n = 427).
Results:
We identified 51 asthma-associated genes in the lower airways, of which 40 were up-regulated and 11 were down-regulated in asthma compared to healthy controls. Seven of the 40 up-regulated genes were also up-regulated in ARMS nasal brushes and validated in ATLANTIS: CLCA1, FETUB, CST1, NTRK2, CDH26, TPSAB1, and DHX35. WGCNA revealed two modules that were consistently elevated in asthma across bronchial and nasal brushes in ARMS and confirmed in ATLANTIS. One module represents IL-13 related inflammation, whereas the other represents mast cell activity.
Conclusion:
The asthma-associated gene signatures of the lower and upper airways show a limited but biologically coherent overlap, with seven genes and two gene modules consistently elevated in asthma. The shared gene signatures reflect two separate components of type 2 inflammation: IL-13 related inflammation and mast cell activity. Selected nasal gene signatures offer a non-invasive tool to identify asthma endotypes with distinct molecular mechanisms driving underlying disease biology.
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