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Difei Academic | Application of mNGS in the diagnosis and treatment of patients with suspected lower respiratory tract infection

Views: 0     Author: Diffei Medical     Publish Time: 2024-05-11      Origin: 迪飞医学

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In January 2024, Diffei Medical took the lead and teamed up with the respiratory department teams of Nanjing Drum Tower Hospital, Eastern Theater General Hospital and Jiangsu Provincial Hospital of Integrated Traditional Chinese and Western Medicine to publish a report in the journalInfection(IF=7.5)A multi-center research paper was published.The article included a total of 205 clinical samples from 201 patients with suspected lower respiratory tract infections, and performed metagenomic next-generation sequencing (mNGS) and conventional etiology tests (Conventional microbiology tests (CMTs)) at the same time.Guide CMTs-negative patients to adjust treatment plans based on mNGS results and evaluate their treatment effects.The study aims to explore the application potential of mNGS in diagnosing suspected lower respiratory tract infections and guiding treatment decisions to prove the feasibility of mNGS in actual clinical scenarios.

Research Background

Lower respiratory tract infections (LRTIs) affect the trachea, bronchi and lung tissue and are one of the leading infectious causes of death in all ages, especially in children under 5 years old.LRTIs can be caused by a variety of pathogens, including bacteria, fungi, and viruses, and their potential epidemiology covers diseases such as pneumonia, influenza, bronchitis, and bronchiolitis.

In the early stages of LRTIs, clinicians often give empirical treatment with antibiotics, which may lead to patients developing resistance due to frequent use of broad-spectrum antibiotics.Therefore, understanding the complexity of the respiratory microbiome is crucial for early diagnosis and timely adjustment of treatment in patients with lower respiratory tract infections.

Research methods

The study finally included 201 patients with suspected lower respiratory tract infections, and a total of 205 clinical samples were tested for both mNGS and CMTs, including 180 alveolar lavage fluids, 10 peripheral blood, 6 pleural effusions, 3 sputum, 3 Lung biopsy tissue in 2 cases, pus in 2 cases, and cerebrospinal fluid in 1 case.The detection of CMTs includes methods such as culture, G test, GM test, and acid-fast staining.For the evaluation of patients' treatment effects, clinicians evaluated the patients' clinical responses based on the standards of the 'Chinese Adult Community-Acquired Pneumonia Diagnosis and Treatment Guidelines' and finally divided them into four categories: effective treatment, stable condition, treatment failure, and failure to follow up. .

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Figure 1 Research flow chart

Research result

mNGSExtensive identification of lower respiratory tract infection pathogens

All 205 samples were analyzed using mNGS results and compared with CMTs results to evaluate the pathogen detection effect of mNGS in LRTIs.Among all samples, the positive detection rate of mNGS was significantly higher than that of CMTs (93.9% vs 36.1%, P<0.001).Compared with CMTs results, mNGS showed a sensitivity of 93.5% (95% CI: 85.5-97.9%) across all clinical samples, with a sensitivity of 95.4% for alveolar lavage fluid and 100 for blood. %, and the sensitivity to pleural effusion is 50%.Across all clinical samples, the overall specificity of mNGS was 9.4% (95% CI: 4.9-15.8%) and the accuracy was 41.0% (95% CI: 34.2-48.0%) (Figure 2B).

When comparing mNGS and CMTs to identify pathogens, the results showed that mNGS detected clear pathogens in 23 cases (12.2%) and possible pathogens in 138 cases (73.4%).Approximately 14.4% of clinical samples identified pathogens by mNGS that were considered unlikely.Furthermore, 33.2% of samples were diagnosed as single species infections by mNGS, whereas CMTs detected single species in only 2.4% of samples (Fig. 2D).

When comparing the consistency of the number of species detected by CMTs and mNGS, the results showed that 14.6% of the samples were of a single species in both methods, while there were only 2 cases (1.0%) of samples with multiple species detected at the same time, and there were 2 negative samples. 11 cases (5.4%).

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Figure 2 Diagnostic performance of mNGS for LRTIs-infecting pathogens

mNGSGuide CMTs-negative patients to make medication adjustments and their impact on patient prognosis

Tracking the treatment strategies of 114 patients with negative CMTs and positive mNGS, we found that 92 (80.7%) of them were treated based on mNGS results, while the remaining 22 patients were treated with empirical antibiotics unrelated to mNGS results (Figure 3).

Among patients whose treatment strategy was adjusted based on mNGS results, 33.7% (31/92) patients received upgraded treatment, 31.5% (29/92) patients received de-escalated treatment, and 34.8% (32/92) patients maintained the original level of treatment. treat.It is worth mentioning that 68.5% (63/92) of patients received effective treatment guided by mNGS results, and 25.0% (23/92) of patients had stable conditions after treatment.Only 6 patients failed to achieve the expected treatment effect, which was reflected in worsening of clinical symptoms or disease progression.

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Figure 3 Treatment strategies adopted for CMTs-negative and mNGS-positive patients (N = 114)

Microbial distribution of LRTI in cancer patients and clinical outcomes of mNGS-guided therapy

In a subgroup analysis of cancer patients,The findings revealed clear differences in microbial composition and diversity between cancer patients and non-cancer patients.In non-cancer patients, the relative abundance of Prevotella melanogaster, Streptococcus infantis, Prevotella jejuni, Pseudomonas tanneri, and Micromonas parvum was significantly higher than that in cancer patients.In contrast, the types of microorganisms detected in cancer patients are limited, with only Leuconostoc pseudomembranosus, Mycobacterium fortuitum, Lactobacillus gasseri, Escherichia coli, Aspergillus niger, and papillomavirus among others. cancer was detected in the population.also,A significantly higher proportion of specific fungi and viruses were detected in cancer patients, including Candida albicans, Aspergillus fumigatus, Pneumocystis jiroveci, Epstein-Barr virus, human herpesvirus, and human cytomegalovirus (Figure 4C).

Among 39 cancer patients, 31 patients had discordant CMTs and mNGS results.Among them, 27 patients adjusted their treatment according to the mNGS test results, and the other 4 patients showed symptoms consistent with the diagnosis of CMTs.Among these patients, 41.9% received escalation of treatment, 9.7% received deescalation, and 48.4% had no change in antibiotic treatment level.It is worth noting that 41.9% of patients showed effective treatment effects, and 35.5% of patients maintained stable condition (Figures 4D and 4E).These results confirm the potential of mNGS in optimizing personalized medicine, especially when the results of CMTs are inconclusive or the results of CMTs and mNGS are inconsistent.

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Figure 4 Microbial identification and mNGS-guided medication adjustment in cancer patients

in conclusion

mNGSThe technology has great application value in detecting pathogenic microorganisms in lower respiratory tract infections.It has the advantages of not relying on prediction and short turnaround time, and its detection sensitivity is less affected by antibacterial drugs.These properties enable mNGS to become an important supplementary tool in clinical diagnosis and treatment decision-making for suspected lower respiratory tract infections, providing clinicians with more accurate pathogenic information, thereby helping to formulate more precise treatment strategies.


Lv T, Zhao Q, Liu J, Wang S, Wu W, Miao L, Zhan P, Chen X, Huang M, Ye M, Ou Q, Zhang Y. Utilizing metagenomic next-generation sequencing for pathogen detection and diagnosis in lower respiratory tract tract infections in real-world clinical practice. Infection. 2024 Feb 18. doi: 10.1007/s15010-024-02185-1. Epub ahead of print. PMID: 38368306.

Compiler: Xue Leng Review: Lily, Jia typesetting: Lin

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