ArticleFrontiers in cellular and infection microbiology2022
Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing.
Article in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 16 citations in OpenAlex.
- Human infection with pseudorabies virus: review of evidence, risk assessment, and future directions.Journal of virology · 2026Review
- Clinical efficacy of plasma cell-free DNA metagenomic next-generation sequencing in diagnosing bloodstream infections.BMC infectious diseases · 2026Article
- Recent advances in diagnostic technologies for postoperative central nervous system infections: a review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Review
- Advances in molecular epidemiology and detection methods of pseudorabies virus.Discover nano · 2025Review
- Exploring the Spectrum of Microbiota in Central Nervous System Infections Through Metagenomic Next-Generation Sequencing.Infection and drug resistance · 2025Article
- Diagnostic Performance of Clinical Metagenomic Next-Generation Sequencing for Suspected Central Nervous System Infections in a Municipal Hospital: A Retrospective Study in China.Infection and drug resistance · 2025Article
- Solving the diagnostic dilemma in bone infections: metagenomic next generation sequencing enhances pathogen identification accuracy.Frontiers in medicine · 2025Article
- Diagnostic performance and clinical utility of metagenomic next-generation sequencing in suspected central nervous system infections: a prospective comparative study.Frontiers in cellular and infection microbiology · 2025Article
- Impact of metagenomic sequencing on clinical outcomes in patients with suspected central nervous system infections: a retrospective case-control study.Frontiers in cellular and infection microbiology · 2025Article
- Utility of next-generation sequencing for the etiological diagnosis ofInfectious medicine · 2024Article
- Clinical application and evaluation of metagenomic next-generation sequencing in pathogen detection for suspected central nervous system infections.Scientific reports · 2024Article
- Hepatitis E virus and Klebsiella pneumoniae co-infection detected by metagenomics next-generation sequencing in a patient with central nervous system and bloodstream Infection: a case report.BMC infectious diseases · 2024Article
- Microbiomes Detected by Bronchoalveolar Lavage Fluid Metagenomic Next-Generation Sequencing among HIV-Infected and Uninfected Patients with Pulmonary Infection.Microbiology spectrum · 2023Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Community-acquired central nervous system infections (CA-CNS infections) have the characteristics of acute onset and rapid progression, and are associated with high levels of morbidity and mortality worldwide. However, there have been only limited studies on the etiology of this infections. Here, metagenomic next-generation sequencing (mNGS), a comprehensive diagnosis method, facilitated us to better understand the etiology of CA-CNS infections. Methods: We conducted a single-center retrospective study between September 2018 and July 2021 in which 606 cerebrospinal fluid (CSF) samples were collected from suspected CNS infectious patients for mNGS testing, and all positive samples were included in this analysis. Results: After the exclusion criteria, a total of 131 mNGS-positive samples were finally enrolled. Bacterial, viral, fungal, parasitic, specific pathogen and mixed infections were accounted for 32.82% (43/131), 13.74% (18/131), 0.76% (1/131), 2.29% (3/131) and 6.87% (9/131), respectively. A total of 41 different pathogens were identified, including 16 bacteria, 12 viruses, 10 fungi, and 1 parasite and 3 specific pathogens. The most frequent infecting pathogens are Conclusion: In this study, mNGS identified a wide variety of pathogens of CA-CNS infections and many of which could not be detected by conventional methods. Our data provide a better understanding of the etiology of CA-CNS infections and show that mNGS represents a comparative screening of CSF in an unbiased manner for a broad range of human pathogens.
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