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Volume 73, Issue 2

Improving pulmonary infection diagnosis with metagenomic next-generation sequencing of bronchoalveolar lavage fluid No Access

Abstract

Inappropriate use of antibiotics and inadequate therapeutic regimens for early-stage pulmonary infections are major contributors to increased prevalence of complications and mortality. Moreover, due to the limitations in sensitivity of conventional testing, there is an urgent need for more diagnostically efficient methods for the detection and characterization of pathogens in pulmonary infections.

Metagenomic next-generation sequencing (mNGS) can contribute to the diagnosis and management of pulmonary infections.

This study aimed to evaluate the clinical application and value of mNGS in the diagnosis of clinically suspected pulmonary infections by comparing with conventional testing.

In this study, the diagnosis performance of mNGS was evaluated using bronchoalveolar lavage fluid (BALF) samples from 143 patients with suspected lung infections. First, we conducted a prospective study on 31 patients admitted to Yuebei People’s Hospital Affiliated to Shantou University Medical College to investigate the clinical value. Then a retrospective analysis was performed by including more patients (=112) to reduce the random error. Pathogens were detected by mNGS and conventional methods (culture and PCR). Then, the types and cases of detected pathogens, as well as the specificity and sensitivity, were compared between the two methods. We evaluated the performance of mNGS in detecting bacterial, fungal, viral and mixed infections in BALF. The effect of disease severity in pulmonary infections on the integrity of mNGS pathogen detection was also explored.

The mNGS provided an earlier and more comprehensive pathogen profile than conventional testing, which in turn prompted a change in clinical medication, which led to improvement in eight patients (8/31=25.81 %) in the presence of other serious comorbidities. In a retrospective analysis, mNGS was much more sensitive than conventional testing in the diagnosis of pulmonary infections (95.33 % vs. 55.56 %; <0.001), with a 39.77 % increase in sensitivity. The detection rate of mNGS for mixed infections was significantly higher than that of conventional testing methods for both common and severe pneumonia (48/67=71.64 % vs. 12/52=23.08 %, <0.001; 44/59=74.58 % vs. 11/59=18.64 %, <0.0001).

The sensitivity of mNGS in the diagnosis of pathogenic microorganisms in pulmonary infections far exceeds that of conventional culture tests. As a complementary method to conventional methods, mNGS can help improve the diagnosis of pulmonary infections. In addition, mNGS pathogen integrity detection rate was similar in common and severe pneumonia. We recommend the prompt use of mNGS when mixed or rare pathogen infections are suspected, especially in immunocompromised individuals and/or critically ill individuals.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): BALF , diagnostic and therapeutic applications , etiologic diagnosis , mNGS and pulmonary infection
Funding
This study was supported by the:
  • Research Project for Outstanding Scholar of Yuebei People's Hospital, Shantou University Medical College, China (Award RS202001)
    • Principle Award Recipient: ZhaoPingsen
  • Research Fund for Joint Laboratory for Digital and Precise Detection of Clinical Pathogens, Yuebei People's Hospital Affiliated to Shantou University Medical College, China (Award KEYANSHEN (2023) 01)
    • Principle Award Recipient: ZhaoPingsen
  • Shaoguan Engineering Research Center for Research and Development of Molecular and Cellular Technology in Rapid Diagnosis of Infectious Diseases and Cancer Program, China (Award 20221807)
    • Principle Award Recipient: ZhaoPingsen
  • Shaoguan Municipal Science and Technology Program, China (Award 220610154531525)
    • Principle Award Recipient: ZhaoPingsen
  • Shaoguan Municipal Science and Technology Program, China (Award 211102114530659)
    • Principle Award Recipient: ZhaoPingsen
  • Natural Science Foundation of Guangdong Province, China (Award 2021A1515012429)
    • Principle Award Recipient: ZhaoPingsen
© 2024 The Authors
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Improving pulmonary infection diagnosis with metagenomic next-generation sequencing of bronchoalveolar lavage fluid
J. Med. Microbiol. 73, 001808 (2024); https://doi.org/10.1099/jmm.0.001808
/content/journal/jmm/10.1099/jmm.0.001808
/content/journal/jmm/10.1099/jmm.0.001808
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