A Proteomics-Based Analysis of Blood Biomarkers for the Diagnosis of COPD Acute Exacerbation

Abstract

Purpose: The identification of blood biomarkers to diagnose acute exacerbation of chronic obstructive pulmonary disease (AECOPD) will have clinical utility. Here, we used a proteomics-based approach to identify biomarkers capable of identifying AECOPD.

Patients and Methods: This prospective, single-center pilot study enrolled 12 patients who came to Asan Medical Center (South Korea) via the outpatient clinic or emergency department with symptoms of AECOPD and were follow-up in the outpatient clinic during convalescence between 2015 and 2017. Paired blood samples collected from each patient during the treatment naive AECOPD and convalescence stages were analyzed. A sequential window acquisition of all theoretical fragmentation spectra-mass spectrometry (SWATH-MS)-based proteome analysis was performed and a subset of the data were verified by ELISA.

Results: The SWATH-MS analysis identified 226 plasma proteins across all samples examined. The median coefficient of variation for triplicate technical replicates of each sample was 1.13 +/- 1.38%, indicating high precision of the technique. Fold-change and paired t-test analyses revealed that 14 proteins were present at higher levels in the AECOPD samples than in the convalescence samples. A gene ontology analysis revealed that these proteins are involved in the acute-phase response. A total of 15 proteins were present at higher levels during the recovery (convalescence) stage than during the acute exacerbation phase, and gene ontology analysis revealed that these proteins are related to lipid metabolism and transport. Verification of the SWATH-MS data was performed using ELISAs for three proteins that were up-regulated in AECOPD, namely, LBP, ORM2, and SERPINA3. Among them, SERPINA3 (p = 0.005) was up-regulated significantly in AECOPD compared with the convalescence state.

Conclusion: Potential plasma biomarkers of AECOPD were discovered using the SWATH-MS proteomics method, and functional molecular associations were investigated. SERPINA3 could be a promising diagnostic biomarker for the early identification and tracking of AECOPD.