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Metagenomic Next-generation Sequencing of Cerebrospinal Fluid for the Diagnosis of Central Nervous System Infections: A Multicentre Prospective Study

Authors :
Yihan Wu
Yueli Zou
Hongzhi Guan
Chunjuan Wang
Honglong Wu
Xiaohua Li
Yongjun Li
Weijun Chen
Changhong Ren
Ying Ge
Bin Peng
Siyuan Fan
Caiyun Liu
Shengnan Wang
Lei Liu
Jingping Shi
Hongfang Li
Liying Cui
Li Cui
Hui Bu
Gaoya Zhou
Shuo Feng
Haitao Ren
Jianzhao Zhang
Xiaodong Qiao
Yafang Hu
Wei Yue
Yushun Piao
Tianjia Guan
Shougang Guo
Xiaojuan Wang
Zheng Liu
Haishan Jiang
Yanhuan Zhao
Wei Li
Jiawei Wang
Weihe Zhang
Shiying Li
Weili Zhao
Lingzhi Qin
Jerome H. Chin
Publication Year :
2019
Publisher :
Cold Spring Harbor Laboratory, 2019.

Abstract

BackgroundInfectious encephalitis and meningitis are often treated empirically without identification of the causative pathogen. Metagenomic next-generation sequencing (mNGS) is a high throughput technology that enables the detection of pathogens independent of prior clinical or laboratory information.MethodsThe present study was a multicentre prospective evaluation of mNGS of cerebrospinal fluid (CSF) for the diagnosis of suspected central nervous system infections.ResultsA total of 276 patients were enrolled in this study between Jan 1, 2017 and Jan 1, 2018. Identification of an etiologic pathogen in CSF by mNGS was achieved in 101 patients (36.6%). mNGS detected 11 bacterial species, 7 viral species, 2 fungal species, and 2 parasitic species. The five leading positive detections were varicella-zoster virus (17), Mycobacterium tuberculosis (14), herpes simplex virus 1 (12), Epstein-Barr virus (12), and Cryptococcus neoformans (7). False positives occurred in 12 (4.3%) patients with bacterial infections known to be widespread in hospital environments. False negatives occurred in 16 (5.8%) patients and included bacterial, viral and fungal aetiologies.ConclusionsmNGS of CSF is a powerful diagnostic method to identify the pathogen for many central nervous system infections.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....335a5cef4b1f6af40140f049ad2efa26
Full Text :
https://doi.org/10.1101/658047