ADVANCING RESPIRATORY HEALTH IN ATHLETES: APPLYING METAGENOMICS NEXT-GENERATION SEQUENCING FOR DETECTING PULMONARY FUNGAL DISEASES IN TUBERCULOSIS

Abstract

Objective: To evaluate the effectiveness of Metagenomics Next-Generation Sequencing (MNGS) in diagnosing tuberculosis and associated fungal infections, which can significantly impact respiratory health and performance in athletes. Methods: The study reviewed clinical data from 60 tuberculosis patients with concurrent fungal infections, collecting samples via alveolar lavage fluid (BALF) and traditional pathogen tests from blood or BALF. We compared MNGS results to those from traditional diagnostic methods to ascertain the enhanced diagnostic value of MNGS in detecting tuberculosis-fungal coinfections. Results: Among the patients (40% male, 60% female, mean age 46.7 ± 16.9 years), MNGS identified tuberculosis and fungal pathogens with significantly higher sensitivity than traditional methods (P <0.05). Specifically, detection rates for tuberculosis were 28% (smear), 48% (culture), 63% (TB-DNA), 68% (TB-RNA), and 80% (MNGS). For fungal infections, the positive rates were 25% (culture), 28% (G-test), 22% (GM-test), 17% (cryptococcal capsule antigens), and 72% (MNGS). The majority of detected pathogens were Candida albicans, Cryptococcus neoformans, and Aspergillus fumigatus. Conclusion: MNGS significantly outperforms traditional diagnostic methods in identifying Mycobacterium tuberculosis complex (MTBC) and fungal pathogens, improving the diagnostic accuracy for tuberculosis with fungal coinfections. For athletes, timely and precise diagnosis of such infections is critical to managing treatment plans and minimizing downtime due to illness, thereby supporting optimal respiratory health and maintaining peak performance levels. Combining MNGS with traditional diagnostic approaches offers a robust method for diagnosing complex infections in athletes, ensuring better health management and quicker return to training and competition.