Sputum gene expression signature of 6 biomarkers discriminates asthma inflammatory phenotypes

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• 作者：Katherine J. Baines ; PhD^a ; ^b ; ^{katherine.baines@newcastle.edu.au" class="auth_mail} ; Jodie L. Simpson ; PhD^a ; ^b ; Lisa G. Wood ; PhD^a ; ^b ; Rodney J. Scott ; PhD^c ; Naomi L. Fibbens ; DipPathTech^a ; ^b ; Heather Powell ; MMedSci^a ; ^b ; Douglas C. Cowan ; PhD^d ; D. Robin Taylor ; DSc^d ; Jan O. Cowan^d ; Peter G. Gibson ; MBBS^a ; ^b
• 关键词：Asthma ; inflammatory phenotypes ; gene expression ; induced sputum ; neutrophils ; eosinophils
• 刊名：Journal of Allergy and Clinical Immunology
• 出版年：April, 2014
• 年：2014
• 卷：133
• 期：4
• 页码：997-1007
• 全文大小：1238 K

文摘

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Background

Airway inflammation is associated with asthma exacerbation risk, treatment response, and disease mechanisms.

Objective

This study aimed to identify and validate a sputum gene expression signature that discriminates asthma inflammatory phenotypes.

Methods

An asthma phenotype biomarker discovery study generated gene expression profiles from induced sputum of 47聽asthmatic patients. A聽clinical validation study (n聽= 59 asthmatic patients) confirmed differential expression of key genes. A聽6-gene signature was identified and evaluated for reproducibility (n聽= 30 asthmatic patients and n聽= 20 control subjects) and prediction of inhaled corticosteroid (ICS) response (n聽= 71 asthmatic patients). Receiver operating characteristic curves were calculated, and area under the curve (AUC) values were reported.

Results

From 277 differentially expressed genes between asthma inflammatory phenotypes, we identified 23 genes that showed highly significant differential expression in both the discovery and validation populations. A聽signature of 6 genes, including Charcot-Leydon crystal protein (CLC); carboxypeptidase A3 (CPA3); deoxyribonuclease I-like 3聽(DNASE1L3); IL-1尾 (IL1B); alkaline phosphatase, tissue-nonspecific isozyme (ALPL); and chemokine (C-X-C motif) receptor 2 (CXCR2), was reproducible and could significantly (P聽< .0001) discriminate eosinophilic asthma from other phenotypes, including patients with noneosinophilic asthma (AUC, 89.6%), paucigranulocytic asthma (AUC, 92.6%), or neutrophilic asthma (AUC, 91.4%) and healthy control subjects (AUC, 97.6%), as well as discriminating patients with neutrophilic asthma from those with paucigranulocytic asthma聽(AUC, 85.7%) and healthy control subjects (AUC, 90.8). The 6-gene signature predicted ICS response (>12% change in FEV₁; AUC, 91.5%). ICS treatment reduced the expression of CLC, CPA3, and DNASE1L3 in patients with eosinophilic asthma.

Conclusions

A sputum gene expression signature of 6 biomarkers reproducibly and significantly discriminates inflammatory phenotypes of asthma and predicts ICS treatment response. This signature has the potential to become a useful diagnostic tool to assist in the clinical diagnosis and management of asthma.