Why the study?
Early and accurate identification of pathogens is essential for improved outcomes in patients with viral encephalitis and/or viral meningitis.
Can metagenomic next-generation sequencing and proteomics analysis identify pathogens and diagnostic biomarkers in pediatric viral encephalitis and meningitis?
Can metagenomic next-generation sequencing and proteomics analysis identify pathogens and diagnostic biomarkers in pediatric viral encephalitis and meningitis?
mNGS and proteomics analysis can effectively identify viral pathogens and potential protein biomarkers in pediatric viral encephalitis and meningitis.
mNGS may improve pathogen detection in pediatric VE/VM; leaves open validation of proteomics biomarkers for HEV cases.
Introduction: Early and accurate identification of pathogens is essential for improved outcomes in patients with viral encephalitis (VE) and/or viral meningitis (VM). Methods: In our research, Metagenomic next-generation sequencing (mNGS) which can identify viral pathogens unbiasedly was performed on RNA and DNA to identify potential pathogens in cerebrospinal fluid (CSF) samples from 50 pediatric patients with suspected VEs and/or VMs. Then we performed proteomics analysis on the 14 HEV-positive CSF samples and another 12 CSF samples from health controls (HCs). A supervised partial least squaresdiscriminant analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA) model was performed using proteomics data. Results: Ten viruses in 48% patients were identified and the most common pathogen was human enterovirus (HEV) Echo18. 11 proteins overlapping between the top 20 DEPs in terms of P value and FC and the top 20 proteins in PLS-DA VIP lists were acquired. Discussion: Our result showed mNGS has certain advantages on pathogens identification in VE and VM and our research established a foundation to identify diagnosis biomarker candidates of HEV-positive meningitis based on MS-based proteomics analysis, which could also contribute toward investigating the HEV-specific host response patterns.
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Wang et al. (2023) studied this question.
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