Evaluation of Salivary Biomarkers and Spirometry for Diagnosing COPD in Non-Smokers and Smokers of Polish Origin.
Magdalena Rudzinska-RadeckaBartłomiej BańcerowskiRobert MarczyńskiDebjita MukherjeeTomasz SikoraKarolina MorawskaAgnieszka MielczarekMarcin MoździerskiBogdan HajdukBeata U KotowiczPublished in: Biomedicines (2024)
Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory condition with global implications. Accurate and timely diagnosis is critical; however, traditional diagnostic methods (based on spirometry) show limitations, prompting the search for predictive biomarkers and modern diagnostic techniques. This study explored the validation of COPD-related biomarkers (C-reactive protein, procalcitonin, neutrophil elastase, and alpha-1 antitrypsin) in saliva. A diverse cohort, including healthy non-smokers, healthy smokers, and COPD patients of Polish origin, underwent spirometry and marker analysis. The data correlated with clinical factors, revealing noteworthy relations. Firstly, salivary biomarker levels were compared with serum concentrations, demonstrating notable positive or negative correlations, depending on the factor. Further analysis within healthy individuals revealed associations between biomarker levels, spirometry, and clinical characteristics such as age, sex, and BMI. Next, COPD patients exhibited an enhanced concentration of biomarkers compared to healthy groups. Finally, the study introduced a breathing assessment survey, unveiling significant associations between self-perceived breathing and spirometric and tested parameters. Outcomes emphasized the relevance of subjective experiences in COPD research. In conclusion, this research underscored the potential of salivary biomarkers as diagnostic tools for COPD, offering a non-invasive and accessible alternative to traditional methods. The findings paved the way for improved modern diagnostic approaches.
Keyphrases
- chronic obstructive pulmonary disease
- lung function
- cystic fibrosis
- air pollution
- end stage renal disease
- smoking cessation
- ejection fraction
- chronic kidney disease
- prognostic factors
- depressive symptoms
- electronic health record
- big data
- metabolic syndrome
- body mass index
- skeletal muscle
- single cell
- adipose tissue
- social support
- artificial intelligence