Gene expression correlated with severe asthma characteristics reveals heterogeneous mechanisms of severe disease

Brian D. Modena, Eugene R. Bleecker, William W. Busse, Serpil C. Erzurum, Benjamin M. Gaston, Nizar N. Jarjour, Deborah A. Meyers, Jadranka Milosevic, John R. Tedrow, Wei Wu, Naftali Kaminski, Sally E. Wenzel

Research output: Contribution to journalArticlepeer-review

89 Scopus citations

Abstract

Rationale: Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals. Objectives: Identify networks of genes reflective of underlying biological processes that define SA. Methods: Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders. Measurements and Main Results: Weighted gene coexpression network analysis constructed 64 gene networkmodules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms.Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function weremarkedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12-21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA. Conclusions: In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes.

Original languageEnglish (US)
Pages (from-to)1449-1463
Number of pages15
JournalAmerican journal of respiratory and critical care medicine
Volume195
Issue number11
DOIs
StatePublished - Jun 1 2017
Externally publishedYes

Keywords

  • Bronchial epithelial cells
  • Gene expression
  • Mechanisms
  • Networks
  • Severe asthma

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine

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