| Title | Clinical Utility of In-house Metagenomic Next-generation Sequencing for the Diagnosis of Lower Respiratory Tract Infections and Analysis of the Host Immune Response |
| Authors | Chen, Hongbin Yin, Yuyao Gao, Hua Guo, Yifan Dong, Zhao Wang, Xiaojuan Zhang, Yawei Yang, Shuo Peng, Qiusheng Liu, Yudong Wang, Hui |
| Affiliation | Peking Univ Peoples Hosp, Dept Clin Lab, Beijing 100044, Peoples R China |
| Keywords | COMMUNITY-ACQUIRED PNEUMONIA VENTILATOR-ASSOCIATED PNEUMONIA MYCOBACTERIUM-TUBERCULOSIS PRACTICE GUIDELINES DISEASES SOCIETY THORACIC SOCIETY T-CELLS ADULTS IDENTIFICATION LYMPHOCYTES |
| Issue Date | 15-Nov-2020 |
| Publisher | CLINICAL INFECTIOUS DISEASES |
| Abstract | Background. Only few pathogens that cause lower respiratory tract infections (LRTIs) can be identified due to limitations of traditional microbiological methods and the complexity of the oropharyngeal normal flora. Metagenomic next-generation sequencing (mNGS) has the potential to solve this problem. Methods. This prospective observational study sequentially enrolled 93 patients with LRTI and 69 patients without LRTI who visited Peking University People's Hospital in 2019. Pathogens in bronchoalveolar lavage fluid (BALF) specimens were detected using mNGS (DNA and RNA) and traditional microbiological assays. Human transcriptomes were compared between LRTI and non-LRTI, bacterial and viral LRTI, and tuberculosis and nontuberculosis groups. Results. Among 93 patients with LRTI, 20%, 35%, and 65% of cases were detected as definite or probable pathogens by culture, all microbiological tests, and mNGS, respectively. Our in-house BALF mNGS platform had an approximately 2-working-day turnaround time and detected more viruses and fungi than the other methods. Taking the composite reference standard as a gold standard, it had a sensitivity of 66.7%, specificity of 75.4%, positive-predictive value of 78.5%, and negative-predictive value of 62.7%. LRTI-, viral LRTI-, and tuberculosis-related differentially expressed genes were respectively related to immunity responses to infection, viral transcription and response to interferon-gamma pathways, and perforin 1 and T-cell receptor B variable 9. Conclusions. Metagenomic DNA and RNA-seq can identify a wide range of LRTI pathogens, with improved sensitivity for viruses and fungi. Our in-host platform is likely feasible in the clinic. Host transcriptome data are expected to be useful for the diagnosis of LRTIs. |
| URI | http://hdl.handle.net/20.500.11897/621921 |
| ISSN | 1058-4838 |
| DOI | 10.1093/cid/ciaa1516 |
| Indexed | SCI(E) |
| Appears in Collections: | 人民医院 |
