Predicting treatable traits for long-acting bronchodilators in patients with stable COPD

Jieun Kang,1,* Ki Tae Kim,2,* Ji-Hyun Lee,3 Eun Kyung Kim,3 Tae-Hyung Kim,4 Kwang Ha Yoo,5 Jae Seung Lee,1 Woo Jin Kim,6 Ju Han Kim,2 Yeon-Mok Oh1 1Department of Pulmonology and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 2Seoul National University Biomedical Informatics and Systems Biomedical Informatics Research Center, Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, 3Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, 4Division of Pulmonology, Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, 5Department of Internal Medicine, Konkuk University Hospital, Konkuk University School of Medicine, Seoul, 6Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, South Korea *These authors contributed equally to this work Purpose: There is currently no measure to predict a treatability of long-acting β-2 agonist (LABA) or long-acting muscarinic antagonist (LAMA) in patients with chronic obstructive pulmonary disease (COPD). We aimed to build prediction models for the treatment response to these bronchodilators, in order to determine the most responsive medication for patients with COPD.Methods: We performed a prospective open-label crossover study, in which each long-acting bronchodilator was given in a random order to 65 patients with stable COPD for 4 weeks, with a 4-week washout period in between. We analyzed 14 baseline clinical traits, expression profiles of 31,426 gene transcripts, and damaged-gene scores of 6,464 genes acquired from leukocytes. The gene expression profiles were measured by RNA microarray and the damaged-gene scores were obtained after DNA exome sequencing. Linear regression analyses were performed to build prediction models after using factor and correlation analyses.Results: Using a prediction model for a LABA, traits found associated with the treatment response were post-bronchodilator forced expiratory volume in 1 second, bronchodilator reversibility (BDR) to salbutamol, expression of three genes (CLN8, PCSK5, and SKP2), and damage scores of four genes (EPG5, FNBP4, SCN10A, and SPTBN5) (R2=0.512, p