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J Clin Invest. 2018 Nov 1. pii: 121087. doi: 10.1172/JCI121087. [Epub ahead of print]

An airway epithelial IL-17A response signature identifies a steroid-unresponsive COPD patient subgroup.

Abstract

BACKGROUND:

Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous smoking-related disease characterized by airway obstruction and inflammation. This inflammation may persist even after smoking cessation and responds variably to corticosteroids. Personalizing treatment to biologically similar "molecular phenotypes" may improve therapeutic efficacy in COPD. IL-17A is involved in neutrophilic inflammation and corticosteroid resistance, and thus may be particularly important in a COPD molecular phenotype.

METHODS:

We generated a gene expression signature of IL-17A response in bronchial airway epithelial brushings ("BAE") from smokers with and without COPD (n = 238), and validated it using data from two randomized trials of IL-17 blockade in psoriasis. This IL-17 signature was related to clinical and pathologic characteristics in two additional human studies of COPD: (1) SPIROMICS (n = 47), which included former and current smokers with COPD, and (2) GLUCOLD (n = 79), in which COPD participants were randomized to placebo or corticosteroids.

RESULTS:

The IL-17 signature was associated with an inflammatory profile characteristic of an IL-17 response, including increased airway neutrophils and macrophages. In SPIROMICS the signature was associated with increased airway obstruction and functional small airway disease on quantitative chest CT. In GLUCOLD the signature was associated with decreased response to corticosteroids, irrespective of airway eosinophilic or Type 2 inflammation.

CONCLUSION:

These data suggest that a gene signature of IL-17 airway epithelial response distinguishes a biologically, radiographically, and clinically distinct COPD subgroup that may benefit from personalized therapy.

TRIAL REGISTRATION:

ClinicalTrials.gov NCT01969344.

FUNDING:

Primary support from NIH/NHLBI. For others see below.

KEYWORDS:

Adaptive immunity; Bioinformatics; COPD; Immunology; Pulmonology

PMID:
30383540
DOI:
10.1172/JCI121087
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