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J Allergy Clin Immunol. 2018 Apr;141(4):1280-1290. doi: 10.1016/j.jaci.2017.06.037. Epub 2017 Jul 26.

Pathway discovery using transcriptomic profiles in adult-onset severe asthma.

Author information

1
Respiratory Medicine, Academic Medical Centre, Amsterdam, The Netherlands. Electronic address: p.w.hekking@amc.uva.nl.
2
Janssen Research and Development, Johnson & Johnson, Spring House, Pa.
3
Data Science Institute, Imperial College, London, United Kingdom.
4
European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France.
5
Respiratory Medicine, Academic Medical Centre, Amsterdam, The Netherlands.
6
Acclarogen, Cambridge, United Kingdom.
7
Discovery Medicine, GlaxoSmithKline, Brentford, United Kingdom.
8
Respiratory Research Unit, University of Nottingham, Nottingham, United Kingdom.
9
Centre for Respiratory Medicine and Allergy, Institute of Inflammation and Repair, University of Manchester and University Hospital of South Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom.
10
Areteva, Nottingham, United Kingdom.
11
NIHR Southampton Centre for Biomedical Research, University of Southampton, Southampton, United Kingdom.
12
National Heart & Lung Institute, Imperial College, London, United Kingdom.

Abstract

BACKGROUND:

Adult-onset severe asthma is characterized by highly symptomatic disease despite high-intensity asthma treatments. Understanding of the underlying pathways of this heterogeneous disease is needed for the development of targeted treatments. Gene set variation analysis is a statistical technique used to identify gene profiles in heterogeneous samples.

OBJECTIVE:

We sought to identify gene profiles associated with adult-onset severe asthma.

METHODS:

This was a cross-sectional, observational study in which adult patients with adult-onset of asthma (defined as starting at age ≥18 years) as compared with childhood-onset severe asthma (<18 years) were selected from the U-BIOPRED cohort. Gene expression was assessed on the total RNA of induced sputum (n = 83), nasal brushings (n = 41), and endobronchial brushings (n = 65) and biopsies (n = 47) (Affymetrix HT HG-U133+ PM). Gene set variation analysis was used to identify differentially enriched predefined gene signatures of leukocyte lineage, inflammatory and induced lung injury pathways.

RESULTS:

Significant differentially enriched gene signatures in patients with adult-onset as compared with childhood-onset severe asthma were identified in nasal brushings (5 signatures), sputum (3 signatures), and endobronchial brushings (6 signatures). Signatures associated with eosinophilic airway inflammation, mast cells, and group 3 innate lymphoid cells were more enriched in adult-onset severe asthma, whereas signatures associated with induced lung injury were less enriched in adult-onset severe asthma.

CONCLUSIONS:

Adult-onset severe asthma is characterized by inflammatory pathways involving eosinophils, mast cells, and group 3 innate lymphoid cells. These pathways could represent useful targets for the treatment of adult-onset severe asthma.

KEYWORDS:

Adult-onset asthma; ILC3; eosinophils; gene set variation analysis; mast cells; mechanisms; phenotyping; severe asthma; transcriptomics

PMID:
28756296
DOI:
10.1016/j.jaci.2017.06.037
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