Clinical Evaluation of an Improved Metagenomic Next-Generation Sequencing Test for the Diagnosis of Bloodstream Infections.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) of plasma cell-free DNA has emerged as a promising diagnostic technology for bloodstream infections. However, a major limitation of current mNGS assays is the high rate of false-positive results due to contamination. METHODS: We made novel us...

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Publicado en:Clinical Chemistry Vol. 67; no. 8; pp. 1133 - 1144
Autores principales: Chendi Jing, Hongbin Chen, Yong Liang, Ying Zhong, Qi Wang, Lifeng Li, Shijun Sun, Yifan Guo, Ruobing Wang, Zhi Jiang, Hui Wang
Formato: Journal Article
Publicado: Oxford University Press / USA Aug2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2021
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      pub: Oxford University Press / USA
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        atl: Clinical Evaluation of an Improved Metagenomic Next-Generation Sequencing Test for the Diagnosis of Bloodstream Infections.
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        au:
          Chendi Jing
          Hongbin Chen
          Yong Liang
          Ying Zhong
          Qi Wang
          Lifeng Li
          Shijun Sun
          Yifan Guo
          Ruobing Wang
          Zhi Jiang
          Hui Wang
        affil: Department of Clinical Laboratory, Peking University People's Hospital, Beijing, China
      sug:
      ab: BACKGROUND: Metagenomic next-generation sequencing (mNGS) of plasma cell-free DNA has emerged as a promising diagnostic technology for bloodstream infections. However, a major limitation of current mNGS assays is the high rate of false-positive results due to contamination. METHODS: We made novel use of 3 control groups--external negative controls under long-term surveillance, blood samples with a negative result in conventional tests, and a group of healthy people--that were combined and dedicated to distinguishing contaminants arising from specimen collection, sample processing, and human normal flora. We also proposed novel markers to filter out false-positive interspecies calls. This workflow was applied retrospectively to 209 clinical plasma samples from patients with suspected bloodstream infections. Every pathogen identified by the mNGS test was reviewed to assess the diagnostic performance of the workflow. RESULTS: Our mNGS workflow showed clinical sensitivity of 87.1%, clinical specificity of 80.2%, positive predictive value of 77.9%, and negative predictive value of 88.6% compared with the composite reference standard. Notably, mNGS showed great improvement in clinical specificity compared with the current test while keeping clinical sensitivity at a high level. CONCLUSION: The mNGS workflow with multiple control groups dedicated to distinguishing nonpathogen microbes from real causal pathogens has reducing falsepositive results. This contribution, with its optimization of workflow and careful use of controls, can help mNGS become a powerful tool for identifying the pathogens responsible for bloodstream infections.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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