Clinical Application of Metagenomic Next-Generation Sequencing in the diagnosis of severe pneumonia pathogens

Ying Zhang¹Caitao Dong²Raojuan Huang³Jingdi Chen⁴Handong Zou⁵Yang Liu⁶Mengmeng GUO³Hang Gao⁵Quan Ke⁵Wei Wu^5*

• ¹Department of Vascular Surgery, Renmin Hospital of Wuhan University, Wuhan, China
• ²Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
• ³First Clinical College of Wuhan University, Wuhan University, Wuhan, China
• ⁴Department of orthopedics, The Airborne Military Hospital, Wuhan, China
• ⁵Department of Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, China
• ⁶Department of Critical Care Medicine, Xianfeng county people's hospital, En shi, China

Background: Severe pneumonia is a significant cause of mortality among ICU patients. Metagenomic next-generation sequencing (mNGS) is an advanced, comprehensive, unbiased diagnostic tool for pathogen identification in infectious diseases. This study aimed to evaluate the clinical efficacy of mNGS for diagnosing severe pneumonia. Methods: This study retrospectively analyzed 323 patients with suspected severe pneumonia admitted to the intensive care unit (ICU) of Wuhan University Renmin Hospital between January 2022 and December 2023. Bronchoalveolar lavage fluid (BALF) samples were collected from all 323 patients, and blood samples were obtained from 80 patients. Both mNGS and conventional microbial testing (CMT) were performed on the collected BALF and blood samples to analyze the pathogen spectrum. The diagnostic performance of mNGS and CMT was systematically evaluated and compared. Results: The overall positivity rate of mNGS was significantly greater than that of CMT (93.5% vs. 55.7%, p < 0.001). mNGS demonstrated significantly greater sensitivity than did CMT (94.74% vs. 57.24%, p < 0.001) but lower specificity (26.32% vs. 68.42%, p < 0.01). mNGS identified 36 bacterial species, 14 fungal species, 7 viral species, and 1 Chlamydia species, whereas CMT detected 21 bacterial species and 9 fungal species. According to the pathogen spectrum, Klebsiella pneumoniae, Acinetobacter baumannii, and Candida albicans were the predominant pathogens associated with severe pneumonia. The detection rate of mixed infections was significantly higher with mNGS than with CMT (62.8% vs. 18.3%, p < 0.001). Conclusions: Compared with CMT methods, mNGS has significant advantages in pathogen detection for severe pneumonia. Owing to its broad detection range and high sensitivity, mNGS serves as a valuable complementary approach to traditional culture-based methods.