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 characterized by an irreversible obstruction to airflow and affects 14.8 million people in the United States alone. Treatment options are currently limited to therapies that variably manage disease symptoms without permanently reversing airflow obstruction. The lack of disease-modifying therapies for COPD could be explained in part by our current lack of understanding the multitude of molecular mechanisms underlying the pathobiology of COPD. Our prior studies have identified a 98-gene expression signature of COPD and disease severity using airway epithelial brushings, but also significant variation in the expression of this signature among individuals with COPD. We therefore sought to explore this molecular heterogeneity by applying an unsupervised learning approach to sub-classify patients with COPD.