International Journal of General Medicine (May 2024)
Exploring the Application of Metagenomic Next-Generation Sequencing in the Diagnosis of Unexplained Pulmonary Infection
Abstract
Sida Chen, Ling Wen, Jintao Ou, Yuting Lai, Yan Shen Department of Respiratory, Shenzhen Longgang Central Hospital, Shenzhen, Guangdong, 518000, People’s Republic of ChinaCorrespondence: Yan Shen, Shenzhen Longgang Central Hospital 6082 Longgang Boulevard (Longgang Section), Longgang District, Shenzhen, Guangdong, 518000, People’s Republic of China, Tel +86-0755-84806933-5901, Email [email protected]: Pulmonary infections are significant global health burdens, and conventional diagnostic methods (culture and polymerase chain reaction), are often limited by slow results and low sensitivity. Metagenomic next-generation sequencing (mNGS) offers a rapid, comprehensive alternative for identifying diverse pathogens, including rare and mixed infections. Thus, we assessed the diagnostic performance of mNGS in pulmonary infections, compared the findings with those of traditional pathogen detection methods, and explored its potential to enhance clinical diagnostics and patient care.Methods: We collected samples from 125 immunocompromised patients diagnosed with pulmonary infection at the Department of Respiratory Medicine of Shenzhen Longgang Central Hospital from March 2020 to July 2022. We compared the rate of pathogen positivity and pathogen distribution between conventional pathogen detection methods and mNGS using samples including sputum, blood, and bronchoalveolar lavage fluid.Results: Among the 125 cases of unexplained pulmonary infection, 82 (65.6%) and 40 (32.0%) tested positive for pathogens using mNGS and routine culture, respectively (P < 0.05). Both methods of pathogen detection were positive in 28 (22.4%) cases (complete match, 9; complete mismatch, 13; partial match, 6). However, 43.2% of cases only tested positive using mNGS, 9.4% only tested positive using routine tests, and 24.8% tested negative using both methods. A viral infection was present in 55.2% of cases. The detection rate of mycobacteria using mNGS (12.8%) was higher than that using conventional pathogen detection methods (5.6%).Conclusion: mNGS technology enhances pathogen detection in unexplained pulmonary infections, enabling targeted antimicrobial therapy and consequently helping to reduce broad-spectrum antibiotic use, aligning treatments more closely with the causative pathogens. Thus, mNGS offers significant clinical value by improving treatment efficacy and potentially reducing antibiotic resistance in pulmonary infection cases.Keywords: mNGS, Unexplained pulmonary infection, Pathogens, BALF
