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. 2022 Jun 15;23(1):156.
doi: 10.1186/s12931-022-02070-1.

Proteome analysis of urinary biomarkers in a cigarette smoke-induced COPD rat model

Weiwei Qin  1   2 , He Huang  2 , Yuting Dai  1 , Wei Han  3 , Youhe Gao  4
Affiliations

Proteome analysis of urinary biomarkers in a cigarette smoke-induced COPD rat model

Weiwei Qin et al. Respir Res. .

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory airway disease caused by inhalation of cigarette smoke (CS) and other harmful gases and particles.

Methods: This study aimed to explore potential urinary biomarkers for CS-induced COPD based on LC-MS/MS analysis.

Results: A total of 340 urinary proteins were identified, of which 79 were significantly changed (30, 31, and 37 at week 2, 4 and 8, respectively). GO annotation of the differential urinary proteins revealed that acute-phase response, response to organic cyclic compounds, complement activation classical pathway, and response to lead ion were significantly enriched at week 2 and 4. Another four processes were only enriched at week 8, namely response to oxidative stress, positive regulation of cell proliferation, thyroid hormone generation, and positive regulation of apoptotic process. The PPI network indicated that these differential proteins were biologically connected in CS-exposed rats. Of the 79 differential proteins in CS-exposed rats, 56 had human orthologs. Seven proteins that had changed at week 2 and 4 when there were no changes of pulmonary function and pathological morphology were verified as potential biomarkers for early screening of CS-induced COPD by proteomic analysis. Another six proteins that changed at week 8 when obvious airflow obstruction was detected were verified as potential biomarkers for prognostic assessment of CS-induced COPD.

Conclusions: These results reveal that the urinary proteome could sensitively reflect pathological changes in CS-exposed rats, and provide valuable clues for exploring COPD biomarkers.

Keywords: Biomarker; COPD; Cigarette smoking; LC–MS/MS; Rat model; Urinary proteome.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Clinical characterization of the cigarette smoke-induced COPD rat model. a Body weight changes in the CS-induced COPD rat model (n = 12, *p < 0.01); b Pulmonary function in rats (n = 10, *p < 0.01); d HE staining of alveolar tissue at an original magnification 200 × ; d AB-PAS staining for mucus expression in the epithelium of the bronchus at an original magnification 200 ×
Fig. 2
Fig. 2
The Venn diagram of the differential urinary proteins at week 2, 4 and 8 in cigarette smoking-induced COPD rat model
Fig. 3
Fig. 3
GO enrichment analysis of the differential urinary proteins at week 2, 4 and 8 in cigarette smoke-induced COPD rat model
Fig. 4
Fig. 4
STRING PPI network analysis of the differential urinary proteins in cigarette smoke-induced COPD rat model. The number of nodes is 68, the average node degree is 4.29, and the average local clustering coefficient is 0.491 (p-value < 1.0e–16)
See this image and copyright information in PMC

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Supplementary concepts