The association of elevated circulating endocan levels with lung function decline in COPD patients

A narrative review on lung injury: mechanisms, biomarkers, and monitoring

Lung injury is closely associated with the heterogeneity, severity, mortality, and prognosis of various respiratory diseases. Effective monitoring of lung injury is crucial for the optimal management and improved outcomes of patients with lung diseases. This review describes acute and chronic respiratory diseases characterized by significant lung injury and current clinical tools for assessing lung health. Furthermore, we summarized the mechanisms of lung cell death observed in these diseases and highlighted recently identified biomarkers in the plasma indicative of injury to specific cell types and scaffold structure in the lung. Last, we propose an artificial intelligence-driven lung injury monitoring model to assess disease severity, and predict mortality and prognosis, aiming to achieve precision and personalized medicine.

Identifying miRNA Modules and Related Pathways of Chronic Obstructive Pulmonary Disease Associated Emphysema by Weighted Gene Co-Expression Network Analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a heterogeneous chronic inflammatory disease characterized by progressive airflow limitation that causes high morbidity and mortality. MicroRNA, a short-chain noncoding RNA, regulates gene expression at the transcriptional level. microRNA modules with a role in the pathogenesis of COPD may serve as COPD biomarkers.

METHODS

We downloaded the GSE33336 microarray data set from the Gene Expression Omnibus (GEO) database, the data are derived from 29 lung samples of patients with emphysema undergoing curative resection for lung cancer. We used weighted gene co-expression network analysis (WGCNA) to construct co-expression modules and detect trait-related microRNA modules. We used the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to predict the biological function of the interest modules, and we screened out candidate hub microRNAs based on their module membership (MM) value and top proteins on the results of the protein-protein interaction (PPI) network.

RESULTS

Three microRNA modules (royal blue, light yellow and grey60) were highly associated with COPD. Axon guidance, proteoglycans in cancer and mitogen-activated protein kinases (MAPK) signaling pathway were common pathways in these three modules. Keratin18 (KRT18) was the top protein in our study. miR-452, miR-149, miR-133a, miR-181a and miR-421 in hub microRNAs may play a role in COPD.

CONCLUSION

These findings provide evidence for the role of miRNAs in COPD and identify biomarker candidates.

Endocan as a potential biomarker of disease severity and exacerbations in COPD

INTRODUCTION

Endocan is a proteoglycan that is regarded as a novel marker of endothelial dysfunction. Endothelial dysfunction in pulmonary vascular bed is known to play an important role for the pathogenesis of COPD.

OBJECTIVE

This study aimed to determine serum endocan levels in patients with stable COPD and acute exacerbation of COPD (AECOPD) and to test the relationship between serum endocan levels and exacerbations.

METHODS

This study enrolled a total of 55 COPD patients, 24 of which had AECOPD and 31 had stable COPD. All patients' basic demographic and clinical data were recorded and blood samples were collected.

RESULTS

Serum endocan levels were significantly higher in the AECOPD group compared to the stable COPD and control groups (for both p < 0.001) and stable COPD group had higher levels than the control group (p < 0.005). Additionally, serum endocan levels were negatively correlated with FVC, FEV1, partial oxygen pressure and oxygen saturation (r = -0.30, p = 0.03; r = -0.34, p = 0.01; r = -0.34, p = 0.01 and r = -0.36, p = 0.007 respectively), and positively correlated with disease duration and systolic pulmonary artery pressure (r = 0.47, p < 0.001; r = 0.31, p = 0.02 respectively). A cut-off value of 434.29 pg/ml for endocan predicted exacerbation with a sensitivity of 79% and a specificity of 84% (AUC: 0.778, 95% Cl 0.648-0.909; p < 0.001). Logistic regression analysis revealed that increased endocan levels was independent predictor of COPD exacerbation (OR = 9.32, 95%CI, 1.64-52.95; p = 0.01).

CONCLUSION

Endocan may be a novel biomarker for detection of endothelial dysfunction and prediction of exacerbations in patients with COPD.