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      Metagenomics next-generation sequencing for the diagnosis of central nervous system infection: A systematic review and meta-analysis

      systematic-review

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          Abstract

          Objective

          It is widely acknowledged that central nervous system (CNS) infection is a serious infectious disease accompanied by various complications. However, the accuracy of current detection methods is limited, leading to delayed diagnosis and treatment. In recent years, metagenomic next-generation sequencing (mNGS) has been increasingly adopted to improve the diagnostic yield. The present study sought to evaluate the value of mNGS in CNS infection diagnosis.

          Methods

          Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2022 guidelines, we searched relevant articles published in seven databases, including PubMed, Web of Science, and Cochrane Library, published from January 2014 to January 2022. High-quality articles related to mNGS applications in the CNS infection diagnosis were included. The comparison between mNGS and the gold standard of CNS infection, such as culture, PCR or serology, and microscopy, was conducted to obtain true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values, which were extracted for sensitivity and specificity calculation.

          Results

          A total of 272 related studies were retrieved and strictly selected according to the inclusion and exclusion criteria. Finally, 12 studies were included for meta-analysis and the pooled sensitivity was 77% (95% CI: 70–82%, I 2 = 39.69%) and specificity was 96% (95% CI: 93–98%, I 2 = 72.07%). Although no significant heterogeneity in sensitivity was observed, a sub-group analysis was conducted based on the pathogen, region, age, and sample pretreatment method to ascertain potential confounders. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for CNS infection was 0.91 (95% CI: 0.88–0.93). Besides, Deek's Funnel Plot Asymmetry Test indicated no publication bias in the included studies ( Figure 3, p > 0.05).

          Conclusion

          Overall, mNGS exhibits good sensitivity and specificity for diagnosing CNS infection and diagnostic performance during clinical application by assisting in identifying the pathogen. However, the efficacy remains inconsistent, warranting subsequent studies for further performance improvement during its clinical application.

          Study registration number

          INPLASY202120002

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          Most cited references47

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          QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

          In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.
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            Clinical metagenomics

            Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health.
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              Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection

              Nearly all infectious agents contain DNA or RNA genomes, making sequencing an attractive approach for pathogen detection. The cost of high-throughput or next-generation sequencing has been reduced by several orders of magnitude since its advent in 2004, and it has emerged as an enabling technological platform for the detection and taxonomic characterization of microorganisms in clinical samples from patients. This review focuses on the application of untargeted metagenomic next-generation sequencing to the clinical diagnosis of infectious diseases, particularly in areas in which conventional diagnostic approaches have limitations. The review covers ( a) next-generation sequencing technologies and common platforms, ( b) next-generation sequencing assay workflows in the clinical microbiology laboratory, ( c) bioinformatics analysis of metagenomic next-generation sequencing data, ( d) validation and use of metagenomic next-generation sequencing for diagnosing infectious diseases, and ( e) significant case reports and studies in this area. Next-generation sequencing is a new technology that has the promise to enhance our ability to diagnose, interrogate, and track infectious diseases.
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                20 September 2022
                2022
                : 13
                : 989280
                Affiliations
                [1] 1Department of Neurosurgery, Xiangya Hospital, Central South University , Changsha, China
                [2] 2Xiangya School of Medicine, Central South University , Changsha, China
                [3] 3National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University , Changsha, China
                Author notes

                Edited by: Félix Javier Jiménez-Jiménez, Hospital Universitario del Sureste, Spain

                Reviewed by: Juan Carlos Garcia-Monco, Basurto Hospital, Spain; Konstantinos I. Tsamis, University of Ioannina, Greece

                *Correspondence: Yu Zeng zengyu@ 123456csu.edu.cn

                This article was submitted to Neurogenetics, a section of the journal Frontiers in Neurology

                †These authors have contributed equally to this work and share first authorship

                Article
                10.3389/fneur.2022.989280
                9530978
                36203993
                eaf5af92-20fd-4db1-b087-e94031aadee5
                Copyright © 2022 Qu, Chen, Ouyang, Huang, Liu, Yan, Lu, Zeng and Liu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 July 2022
                : 29 August 2022
                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 47, Pages: 11, Words: 5897
                Funding
                Funded by: Natural Science Foundation of Hunan Province, doi 10.13039/501100004735;
                Award ID: 2019JJ50961
                Funded by: China Postdoctoral Science Foundation, doi 10.13039/501100002858;
                Award ID: 2018M643006
                Categories
                Neurology
                Systematic Review

                Neurology
                metagenomic next-generation sequencing,central nervous system,infection,diagnosis,meta-analysis

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