Abstract
Background: Encephalitis is an inflammatory condition of the brain associated with long-term neurologic sequelae and even death in children. Although viruses are often implicated, an etiology is not identified in the majority of cases. Metagenomics-based next-generation sequencing (mNGS) is a high-throughput sequencing technique that can enhance the detection of novel or low-frequency pathogens. Methods: Hospitalized immunocompetent children aged 6 months to 18 years with encephalitis of unidentified etiology were eligible for enrollment. Demographic, historical, and clinical information was obtained, and residual blood and cerebrospinal fluid (CSF) samples were subjected to mNGS. Pathogens were identified by querying the sequence data against the NCBI GenBank database. Results: Twenty children were enrolled prospectively between 2013 and 2017. mNGS of CSF identified 7 nonhuman nucleic acid sequences of significant frequency in 6 patients, including that of Mycoplasma bovis, parvovirus B19, Neisseria meningitidis, and Balamuthia mandrillaris. mNGS also detected Cladophialophora species, tobacco mosaic virus, and human bocavirus, which were presumed to be contaminants or nonpathogenic organisms. One patient was found to have positive serology results for California encephalitis virus, but mNGS did not detect it. Patients for whom mNGS identified a diagnosis had a significantly higher CSF white blood cell count, a higher CSF protein concentration, and a lower CSF glucose level than patients for whom mNGS did not identify a diagnosis. Conclusion: We describe here the results of a prospective cohort analysis to evaluate mNGS as a diagnostic tool for children with unexplained encephalitis. Although mNGS detected multiple nonpathogenic organisms, it also identified multiple pathogens successfully and was most useful in patients with a CSF abnormality.