Pathway discovery using transcriptomic profiles in adult-onset severe asthma

Hekking, Pieter-Paul; Loza, Matt J.; Pavlidis, Stelios; de Meulder, Bertrand; Lefaudeux, Diane; Baribaud, Fred; Auffray, Charles; Wagener, Ariane H.; Brinkman, Paul; Lutter, Rene; Bansal, Aruna T.; Sousa, Ana R.; Bates, Steve A.; Pandis, Yannis; Fleming, Louise J.; Shaw, Dominique E.; Fowler, Stephen J.; Guo, Y.; Meiser, Andrea; Sun, Kai; Corfield, Julie; Howarth, Peter H.; Bel, Elisabeth H.; Adcock, Ian M.; Chung, Kian Fan; Djukanovic, Ratko; Sterk, Peter J.

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 (

• Journal Article Type: Article
• Acceptance Date: Jun 21, 2017
• Online Publication Date: Jul 26, 2017
• Publication Date: 2018-04
• Deposit Date: May 17, 2018
• Journal: Journal of Allergy and Clinical Immunology
• Print ISSN: 0091-6749
• Electronic ISSN: 0091-6749
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 141
• Issue: 4
• Pages: 1280-1290
• DOI: https://doi.org/10.1016/j.jaci.2017.06.037
• Keywords: Adult-onset asthma, severe asthma, gene set variation; analysis, phenotyping, transcriptomics, mechanisms, eosinophils, mast cells, ILC3
• Public URL: https://nottingham-repository.worktribe.com/output/929621
• Publisher URL: https://www.jacionline.org/article/S0091-6749(17)31195-8/abstract