Metagenomic next-generation sequencing for identifying pathogens in patients with rheumatic diseases and diffuse pulmonary lesions: A retrospective diagnostic study

• Published in: Frontiers in cellular and infection microbiology Vol. 12; p. 963611
• Main Authors: Jiang, Juan, Yang, Wei, Wu, Yanhao, Peng, Wenzhong, Zhang, Wenjuan, Pan, Pinhua, Hu, Chengping, Li, Yisha, Li, Yuanyuan
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 31-08-2022
• Subjects: Cellular and Infection Microbiology; diffuse pulmonary lesions; immunosuppressed population; metagenomic next-generation sequencing (mNGS); pulmonary infection; rheumatic diseases
• ISSN: 2235-2988; 2235-2988
• DOI: 10.3389/fcimb.2022.963611

Objective
Lung involvement is a major cause of morbidity and mortality in patients with rheumatic diseases. This study aimed to assess the application value of metagenomic next-generation sequencing (mNGS) for identifying pathogens in patients with rheumatic diseases and diffuse pulmonary lesions.
Methods
This retrospective study included patients who were diagnosed with rheumatic diseases and presenting diffuse pulmonary lesions on chest radiography in Xiangya Hospital from July 2018 to May 2022. Clinical characteristics were summarized, including demographics, symptoms, comorbidities, radiological and laboratory findings, and clinical outcomes. Pulmonary infection features of these patients were analyzed. Furthermore, diagnostic performance of mNGS and conventional methods (including smear microscopy, culture, polymerase chain reaction assay, and serum immunological test) in identifying pulmonary infections and causative pathogens were compared.
Results
A total of 98 patients were included, with a median age of 58.0 years old and a female proportion of 59.2%. Of these patients, 71.4% showed the evidence of pulmonary infections. Combining the results of mNGS and conventional methods, 129 infection events were detected, including 45 bacterial, 40 fungal and 44 viral infection events. Pulmonary mixed infections were observed in 38.8% of patients. The detection rates of mNGS for any pathogen (71.4% vs 40.8%,
P
< 0.001) and mixed pathogens (40.8% vs 12.2%,
P
< 0.001) were higher than that of conventional methods. Moreover, mNGS had a significantly higher sensitivity (97.1% vs. 57.1%,
P
< 0.001) than conventional methods in identifying pulmonary infections, while its specificity (92.9% vs. 96.4%,
P
= 0.553) were comparable to conventional methods. Antimicrobial and antirheumatic treatments were markedly modified based on mNGS results in patients with rheumatic diseases and diffuse pulmonary lesions.
Conclusions
For patients diagnosed with rheumatic diseases and presenting diffuse pulmonary lesions, mNGS is a powerful complement to conventional methods in pathogen identification due to its high efficiency and broad spectrum. Early application of mNGS can provide guidance for precision treatment, and may reduce mortality and avoid antibiotic abuse.