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Am J Respir Crit Care Med. 2017 Jun 1;195(11):1449-1463. doi: 10.1164/rccm.201607-1407OC.

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease.

Author information

1
1 Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh Asthma Institute at UPMC, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
2
2 Scripps Translational Science Institute, The Scripps Research Institute, La Jolla, California.
3
3 Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina.
4
4 Division of Allergy, Pulmonary, and Critical Care Medicine, University of Wisconsin, Madison, Wisconsin.
5
5 Department of Pathobiology, Lerner Research Institute, The Cleveland Clinic Foundation, Cleveland, Ohio.
6
6 Division of Pediatric Pulmonary, Allergy and Immunology, Case Western Reserve University, Cleveland, Ohio.
7
7 Rainbow Babies and Children's Hospital, Cleveland, Ohio.
8
8 Lane Center for Computational Biology School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania; and.
9
9 Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut.

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 network modules, 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 were markedly 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.

KEYWORDS:

bronchial epithelial cells; gene expression; mechanisms; networks; severe asthma

Comment in

PMID:
27984699
PMCID:
PMC5470748
DOI:
10.1164/rccm.201607-1407OC
[Indexed for MEDLINE]
Free PMC Article

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