Dataset Information

Application of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infectious Pathogens From Bronchoalveolar Lavage Samples.

ABSTRACT:

Background

Metagenomic next-generation sequencing (mNGS) is a powerful method for pathogen detection. In this study, we assessed the value of mNGS for bronchoalveolar lavage (BAL) samples in the diagnosis of pulmonary infections.

Methods

From February 2018 to April 2019, BAL samples were collected from 235 patients with suspected pulmonary infections. mNGS and microbial culture were performed to evaluate the effectiveness of mNGS in pulmonary infection diagnosis.

Results

We employed mNGS to evaluate the alpha diversity, results suggesting that patients with confirmed pathogens had a lower microbial diversity index compared to that of patients with uncertain pathogens. For the patients admitted to the respiratory intensive care unit (RICU) or on a ventilator, they experienced a lower diversity index than that of the patients in the general ward or not on a ventilator. In addition, mNGS of BAL had a diagnostic sensitivity of 88.89% and a specificity of 14.86% in pulmonary infection, with 21.16% positive predictive value (PPV) and 83.87% negative predictive value (NPV). When rare pathogens were excluded, the sensitivity of mNGS decreased to 73.33%, and the specificity increased to 41.71%. For patients in the simple pulmonary infection group and the immunocompromised group, the main infection types were bacterial infection (58.33%) and mixed-infection (43.18%). Furthermore, mNGS had an advantage over culture in describing polymicrobial ecosystem, demonstrating the microbial distribution and the dominant strains of the respiratory tract in patients with different underlying diseases.

Conclusions

The study indicated that mNGS of BAL samples could provide more accurate diagnostic information in pulmonary infections and demonstrate the changes of respiratory microbiome in different underlying diseases. This method might play an important role in the clinical use of antimicrobial agents in the future.

SUBMITTER: Chen Y

PROVIDER: S-EPMC7991794 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Metagenomic next-generation sequencing (mNGS) has been gradually applied to clinical practice due to its unbiased characteristics of pathogen detection. However, its diagnostic performance and clinical value in suspected pulmonary infection need to be evaluated. We systematically reviewed the clinical data of 246 patients with suspected pulmonary infection from 4 medical institutions between January 2019 and September 2021. The diagnostic performances of mNGS and conventional testing (CT) were systematically analyzed based on bronchoalveolar lavage fluid (BALF). The impacts of mNGS and CT on diagnosis modification and treatment adjustment were also assessed. The positive rates of mNGS and CT were 47.97% and 23.17%, respectively. The sensitivity of mNGS was significantly higher than that of CT (53.49% versus 23.26%, P < 0.01), especially for infections of Mycobacterium tuberculosis (67.86% versus 17.86%, P < 0.01), atypical pathogens (100.00% versus 7.14%, P < 0.01), viruses (92.31% versus 7.69%, P < 0.01), and fungi (78.57% versus 39.29%, P < 0.01). The specificity of mNGS was superior to that of CT, with no statistical difference (90.32% versus 77.42%, P = 0.167). The positive predictive value (PPV) and negative predictive value (NPV) of mNGS were 97.46% and 21.88%, respectively. Diagnosis modification and treatment adjustment were conducted in 32 (32/246, 13.01%) and 23 (23/246, 9.35%) cases, respectively, according to mNGS results only. mNGS significantly improved the diagnosis of suspected pulmonary infection, especially infections of M. tuberculosis, atypical pathogens, viruses, and fungi, and it demonstrated the pathogen distribution of pulmonary infections. It is expected to be a promising microbiological detection and diagnostic method in clinical practice. IMPORTANCE Pulmonary infection is a heterogeneous and complex infectious disease with high morbidity and mortality worldwide. In clinical practice, a considerable proportion of the etiology of pulmonary infection is unclear, microbiological diagnosis being challenging. Metagenomic next-generation sequencing detects all nucleic acids in a sample in an unbiased manner, revealing the microbial community environment and organisms and improving the microbiological detection and diagnosis of infectious diseases in clinical settings. This study is the first multicenter, large-scale retrospective study based entirely on BALF for pathogen detection by mNGS, and it demonstrated the superior performance of mNGS for microbiological detection and diagnosis of suspected pulmonary infection, especially in infections of Mycobacterium tuberculosis, atypical pathogens, viruses, and fungi. It also demonstrated the pathogen distribution of pulmonary infections in the real world, guiding targeted treatment and improving clinical management and prognoses.

Project description:BackgroundLower respiratory tract infections (LRTI)are known to be diagnosed late or inaccurately. This has fueled the unscrupulous use of antibiotics, as they are often used empirically and clinically, leading to antibiotic abuse and multidrug resistance in patients. Metagenomic next-generation sequencing (mNGS), now widely used in clinical studies, could be a potential intervention to revolutionize microbiology by rapidly identifying unknown species.MethodsThis review and meta-analysis were conducted on eligible studies with respect to metagenomic sequencing on clinical LRTI diagnostics up to May 01, 2022. QUADAS-2 was employed to assess the methodological bias as well as applicability. After that, a meta-analysis was conducted to analyze the accuracy of mNGS, compared with the composite reference standard (CRS), among the enrolled studies.ResultsThis work collected 1248 samples in 13/21 qualified articles to factor in the accuracy of the diagnostic test. Typically, methods like molecular testing, culture, composite measures, and clinical decision-making were adopted as the reference criteria. With regard to Bronchoalveolar Lavage Samples, their sensitivity was 89% (82-93%) while their specificity was 90% (66-98%), with obvious heterogeneities in these two factors as demonstrated by different studies. The summary receiver operating characteristic (SROC) curve was plotted for mNGS as a function of LRTI, and the area under the curve (AUC) was 0.94. A Funnel plot with a p-value greater than 0.05 indicated the absence of publication bias. Positive and negative likelihood ratios (PLR and NLR) were >10 and > 0.1, respectively. In this pre-test probability-post-probability-likelihood ratio relationship graph, the values were Prior prob (%) = 20, Post-prob-Pos (%) = 77 and Post-prob-Neg (%) = 4.ConclusionThe AUC value of SROC suggested a high accuracy of mNGS in diagnosis, with no publication bias and high reliability. The application of mNGS exhibits notable diagnostic efficacy in discerning pathogens present in bronchoalveolar lavage fluid (BALF) among patients afflicted with LRTI. However, mNGS is more meaningful for the definitive diagnosis of the disease rather than the exclusion of the disease. This post-test probability is significantly higher than the pre-test probability.

Project description:Objectives The aim of this study was to evaluate the diagnostic value of bronchoalveolar lavage fluid (BALF) metagenomic next-generation sequencing (mNGS) versus conventional microbiological tests (CMTs) for pediatric pneumonia. Methods This retrospective observational study enrolled 103 children who were diagnosed with pneumonia and hospitalized at Hubei Maternity and Child Health Care Hospital between 15 October 2020 and 15 February 2022. The pneumonia diagnosis was based on clinical manifestations, lung imaging, and microbiological tests. Pathogens in the lower respiratory tract were detected using CMTs and BALF mNGS (of DNA and RNA). The diagnostic performance of BALF mNGS was compared with that of CMTs. Results In 96 patients, pathogens were identified by microbiological tests. The overall pathogen detection rate of mNGS was significantly higher than that of CMTs (91.3% vs. 59.2%, p = 0.000). The diagnostic performance of mNGS varied for different pathogens; however, its sensitivity and accuracy for diagnosing bacterial and viral infections were both higher than those of CMTs (p = 0.000). For the diagnosis of fungi, the sensitivity of mNGS (87.5%) was higher than that of CMTs (25%); however, its specificity and accuracy were lower than those of CMTs (p < 0.01). For the diagnosis of Mycoplasma pneumoniae, the specificity (98.8%) and accuracy (88.3%) of mNGS were high; however, its sensitivity (42.1%) was significantly lower than that of CMTs (100%) (p = 0.001). In 96 patients with definite pathogens, 52 cases (50.5%) were infected with a single pathogen, while 44 cases (42.7%) had polymicrobial infections. Virus–bacteria and virus–virus co-infections were the most common. Staphylococcus aureus, Haemophilus influenzae, rhinovirus, cytomegalovirus, parainfluenza virus, and fungi were more likely to be associated with polymicrobial infections. Conclusions BALF mNGS improved the detection rate of pediatric pneumonia, especially in mixed infections. The diagnostic performance of BALF mNGS varies according to pathogen type. mNGS can be used to supplement CMTs. A combination of mNGS and CMTs may be the best diagnostic strategy.