Boston University, Boston, MA
Copyright 2016, American College of Chest Physicians. All Rights Reserved.
SESSION TITLE: Novel Predictors of COPD Outcomes
SESSION TYPE: Original Investigation Slide
PRESENTED ON: Sunday, October 23, 2016 at 01:30 PM - 03:00 PM
PURPOSE: Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of death, and is characterized by variable but progressive lung function decline. The mechanisms underlying this progression are not well understood. Given our recent description of a bronchial airway gene expression signature associated with COPD and lung function impairment, we sought to determine whether airway gene expression profiling could be used to develop a prognostic signature that predicts rapid decline in lung function in individuals with COPD.
METHODS: We previously generated a dataset consisting of bronchial airway brushings from patients with COPD(n=87) measured on Affymetrix Human Gene 1.0 ST microarrays. From this dataset we selected the samples from 49 individuals who had at least one additional spirometry measurement performed >4 years subsequent to sample collection. Bronchial airway gene-patterns that at baseline were associated with subsequent decline in FEV1 were identified using a linear model with ANOVA controlling for relevant co-variates. Enriched pathways and biologic functions were identified using GATHER. GSEA was used to evaluate the relationship between gene-expression patterns significantly associated with lung function decline and the COPD signature, with a dataset of subjects with COPD treated with fluticasone, and a dataset that found gene expression changes correlated in lung damage.
RESULTS: A total of 268 genes were significantly associated with FEV1 decline among individuals with COPD (FDR<0.25). Genes whose expression associated with alterations in lung function were significantly enriched in immune response and ubiquitin cycle (p<0.05). The genes associated with lung function decline in COPD patients were also associated with an airway gene-expression signature of the presence or absence of COPD (GSEA-FDR<0.01), and enriched for genes that are reversed by fluticasone (GSEA-FDR<0.01).
CONCLUSIONS: We have identified an airway gene expression signature that is associated with future FEV1 decline in participants with COPD. This signature is significantly related to cross-sectional changes in airway gene expression associated with the presence of COPD, suggesting that signature can indicate lung damage from COPD. The signature of FEV1 decline is also reversed by inhaled fluticasone, suggesting that this signature is dynamic.
CLINICAL IMPLICATIONS: This airway gene expression signature of rapid lung function decline in individuals with COPD could be used to target high-risk individuals for trials of novel therapies to slow disease progression. This signature may also have utility as an intermediate biomarker of therapeutic efficacy, or predictor of COPD development.
DISCLOSURE: The following authors have nothing to disclose: Elizabeth Becker, Stephen Lam, Maarten van den Berge, Gang Liu, Xiaohui Zhang, Yuriy Alekseyev, Avrum Spira, Marc Lenburg, Katrina Steiling
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