Abstract
Acute exacerbation chronic obstructive pulmonary disease (AECOPD) has a high mortality rate. However, there is no efficiency biomarker for diagnosing AECOPD. The purpose of this study was to find biomarkers that can quickly and accurately diagnose AECOPD.45 normal controls (NC), 42 patients with stable COPD (SCOPD), and 66 patients with AECOPD were enrolled in our study. Serum exosomes were isolated by ultracentrifuge and verified by morphology and specific biomarkers. Fluorescent quantitation polymerase chain reaction (qRT-PCR) was used to detect the expression of micro RNAs (miRNAs), including miR-660-5p, miR-1258, miR-182-3p, miR-148a-3p, miR-27a-5p and miR-497-5p in serum exosomes and serum. Logistic regression and machine learning methods were used to constructed the diagnostic models of AECOPD. The levels of miR-1258 in the patients with AECOPD were higher than other groups (p < 0.001). The ability of exosomal miR-1258 (AUC = 0.851) to identify AECOPD from SCOPD was superior to other biomarkers, and the combination of exosomal miR-1258 and NLR can increase the AUC to 0.944, with a sensitivity of 81.82%, and specificity of 97.62%. The cross-validation of the models displayed that the logistic regression model based on exosomal miR-1258, NLR and neutrophil count had the best accuracy (0.880) in diagnosing AECOPD from SCOPD. The three most correlated biomarkers with serum exosome miR-1258 were neutrophil count (r = 0.57, p < 0.001), WBC (r = 0.50, p < 0.001) and serum miR-1258 (r = 0.33, p < 0.001). In conclusion, serum exosomal miR-1258 is associated with inflammation, and can be used as a valuable and reliable biomarker for the diagnosis of AECOPD, and the establishment of diagnostic model based on miR-1258, NLR and neutrophils count can help to improving the accuracy of AECOPD diagnosis.