COPD Exacerbation Biomarkers Validated Using Multiple Reaction Monitoring Mass Spectrometry

• Published in: PloS one Vol. 11; no. 8; p. e0161129
• Main Authors: Leung, Janice M., Chen, Virginia, Hollander, Zsuzsanna, Dai, Darlene, Tebbutt, Scott J., Aaron, Shawn D., Vandemheen, Kathy L., Rennard, Stephen I., FitzGerald, J. Mark, Woodruff, Prescott G., Lazarus, Stephen C., Connett, John E., Coxson, Harvey O., Miller, Bruce, Borchers, Christoph, McManus, Bruce M., Ng, Raymond T., Sin, Don D.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 15.08.2016; Public Library of Science (PLoS)
• Subjects: Acute Disease; Aged; Analysis; Apolipoproteins; Biology and Life Sciences; Biomarkers; Biomarkers - blood; Chronic obstructive lung disease; Chronic obstructive pulmonary disease; Clinical trials; Convalescence; Critical care; Dyspnea; Female; Heart attacks; Hospitals; Humans; Identification methods; Lipoproteins; Lung diseases; Male; Mass Spectrometry; Mass spectroscopy; Medicine; Medicine and Health Sciences; Middle Aged; Monitoring; Morbidity; Mortality; Obstructive lung disease; Patients; Protein folding; Proteins; Proteomics; Pulmonary Disease, Chronic Obstructive - blood; R&D; Regression analysis; Regression models; Research & development; Risk factors; Rodents; Scientific imaging; Sleep; Spectroscopy; Statistical analysis; Statistical methods
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0161129

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) result in considerable morbidity and mortality. However, there are no objective biomarkers to diagnose AECOPD. We used multiple reaction monitoring mass spectrometry to quantify 129 distinct proteins in plasma samples from patients with COPD. This analytical approach was first performed in a biomarker cohort of patients hospitalized with AECOPD (Cohort A, n = 72). Proteins differentially expressed between AECOPD and convalescent states were chosen using a false discovery rate <0.01 and fold change >1.2. Protein selection and classifier building were performed using an elastic net logistic regression model. The performance of the biomarker panel was then tested in two independent AECOPD cohorts (Cohort B, n = 37, and Cohort C, n = 109) using leave-pair-out cross-validation methods. Five proteins were identified distinguishing AECOPD and convalescent states in Cohort A. Biomarker scores derived from this model were significantly higher during AECOPD than in the convalescent state in the discovery cohort (p<0.001). The receiver operating characteristic cross-validation area under the curve (CV-AUC) statistic was 0.73 in Cohort A, while in the replication cohorts the CV-AUC was 0.77 for Cohort B and 0.79 for Cohort C. A panel of five biomarkers shows promise in distinguishing AECOPD from convalescence and may provide the basis for a clinical blood test to diagnose AECOPD. Further validation in larger cohorts is necessary for future clinical translation.