Chronic Bronchitis, COPD, Emphysema, Smoking
Conditions
Brief summary
COPD is a significant health problem worldwide. It affects more than 10% of patients over the age of 40. According to the World Health Organization, it is the third most common cause of death among adults in the world, and the number of patients is continuously growing. Hence, all measures aimed at a better understanding of COPD pathogenesis, the course of the disease, and limitations in treatment efficacy seem critically important. Since 2008 our team has provided a substantial output in understanding the pathophysiology of airway inflammation in obstructive lung diseases. In our studies, we systematically evaluated selected cytokines concentrations in different respiratory samples to determine their mutual relations and to determine the role of cytokines in airway inflammation more precisely. However, there is still a large gap in our understanding of COPD. It is hypothesized that in COPD pathogenesis, additional factors, like genetics, autoimmune processes or deviated microbiota are involved. Each of the mentioned factors leads to a different type of immune response with a different effect on the airways. We believe that using more advanced laboratory methods (i.e. metabolomics and airway microbiome analysis) alongside the well-established ones (i.e. cellular and cytokine composition) will allow for an adequate characterization of inflammation. The study will include 50 COPD subjects and 50 smokers without COPD and 20 control subjects (never smokers) who meet the inclusion and exclusion criteria (Table 1) and give an informed written consent to participate in the study. All study participants will undergo the following procedures: peripheral blood sample collection, chest HRCT imaging (without contrast), lung function assessment (spirometry with a bronchial obstruction reversibility test, bodyplethismography, diffusion lung capacity for carbon monoxide (DLCO), sputum induction with sterile hypertonic saline (NaCl).
Interventions
None listed
Sponsors
Medical University of Warsaw
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
40 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* age ⩾ 40 years, * written informed history of smoking ⩾ 10 pack-years * COPD diagnosis (post- bronchodilator FEV1/FVC \< LLN) * stable COPD (min. 3 months)
Exclusion criteria
* history of asthma or current lung disease (exception: solitary nodules), respiratory failure * use of inhaled or oral steroids in the 3 months prior to the study, * infection of the respiratory tract or exacerbation in the 3 months prior the study * uncontrolled comorbidities such as: systemic connective tissue diseases, malignancy, uncontrolled cardiovascular diseases, chronic paranasal sinusitis, * contraindications to sputum induction
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Development of a Risk Calculator for COPD Severity and Phenotyping Using Feature Selection and Enrichment Analysis | Up to 6 months after sample collection | In this study, we will use the Boruta algorithm for feature selection and perform enrichment analysis to identify overrepresented biological pathways. Based on these results, we will develop and validate a calculator that generates a risk score for the disease and predicts the likelihood of severe progression. This calculator will serve as an outcome measure, providing an integrated tool to assess patient status and guide clinical decisions. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Secondary Outcome Measure 1: Identification of Omics Biomarkers Associated with CT Imaging Changes in COPD | Up to 6 months after sample collection | We will apply the Boruta algorithm to proteomic, metabolomic, and cytokine data to identify molecules significantly associated with CT imaging findings (e.g., wall thickening and emphysema). Additionally, we will explore the relationships between inflammatory cytokines, specific metabolites, proteins, and immune cell populations (assessed in induced sputum) to elucidate mechanistic links between systemic inflammation and structural lung alterations. |
| Secondary Outcome Measure 2: Assessment of Host-Environment Interactions via Microbiome Analysis | Up to 6 months after sample collection | We will perform microbiome profiling of the airway and integrate these data with proteomic, metabolomic, cytokine, and immune cell information from induced sputum using the Boruta algorithm. This analysis will assess host-environment interactions by identifying biomarkers that connect microbial composition with inflammatory profiles and CT imaging changes, thereby enhancing our understanding of the interplay between host factors and environmental influences in COPD. |
Countries
Poland
Outcome results
None listed