Investigating the comorbidity of COPD and tuberculosis, a computational study

Area of Science:

• Pulmonary Medicine
• Immunology
• Computational Biology

Background:

• Chronic obstructive pulmonary disease (COPD) significantly increases susceptibility to tuberculosis (TB).
• COPD patients exhibit a higher risk of developing active TB and increased mortality compared to the general population.
• Understanding the interplay between COPD and TB is crucial for managing comorbid conditions.

Purpose of the Study:

• To investigate the comorbidity effects of COPD on tuberculosis disease and granuloma formation using a multi-scale model.
• To analyze how COPD influences the containment or dissemination of *Mycobacterium tuberculosis* (Mtb).
• To examine disease outcomes in smoking and non-smoking COPD populations with TB.

Main Methods:

• Developed a multi-scale computational model integrating pathophysiological and immunopathological aspects of COPD and TB.
• Incorporated agent-based models (ABM) for cellular immune response.
• Integrated physiological, systems biology, and metabolic models to simulate Mtb infection dynamics in COPD patients.

Main Results:

• The model simulates key drivers of disease outcomes: clearance, granuloma-based containment, and disseminated disease.
• Differential disease progression pathways were investigated for COPD patients with and without smoking history.
• The study provides insights into the mechanisms underlying increased TB susceptibility and severity in COPD.

Conclusions:

• COPD significantly alters the host-pathogen dynamics of tuberculosis, increasing the risk of active disease and mortality.
• The multi-scale model offers a framework for exploring therapeutic strategies targeting COPD-TB comorbidity.
• Further research is needed to validate model predictions and translate findings into clinical practice.