Diagnosing enterovirus meningitis via blood transcriptomics: an alternative for lumbar puncture?

• Published in: Journal of Translational Medicine
• Main Authors: Esther Bartholomeus, Nicolas De Neuter, Annelies Lemay, Luc Pattyn, David Tuerlinckx, David Weynants, Koen Van Lede, Gerlant van Berlaer, Dominique Bulckaert, Tine Boiy, Ann Vander Auwera, Marc Raes, Dimitri Van der Linden, Helene Verhelst, Susanne Van Steijn, Tijl Jonckheer, Joke Dehoorne, Rik Joos, Hilde Jansens, Arvid Suls, Pierre Van Damme, Kris Laukens, Geert Mortier, Pieter Meysman, Benson Ogunjimi
• Format: Article
• Language: English
• Published: BMC 2019-08-01
• Subjects: Meningitis; Enterovirus; Bacterial meningitis; Differential gene expression
• Online Access: http://link.springer.com/article/10.1186/s12967-019-2037-6

Abstract Background Meningitis can be caused by several viruses and bacteria. Identifying the causative pathogen as quickly as possible is crucial to initiate the most optimal therapy, as acute bacterial meningitis is associated with a significant morbidity and mortality. Bacterial meningitis requires antibiotics, as opposed to enteroviral meningitis, which only requires supportive therapy. Clinical presentation is usually not sufficient to differentiate between viral and bacterial meningitis, thereby necessitating cerebrospinal fluid (CSF) analysis by PCR and/or time-consuming bacterial cultures. However, collecting CSF in children is not always feasible and a rather invasive procedure. Methods In 12 Belgian hospitals, we obtained acute blood samples from children with signs of meningitis (49 viral and 7 bacterial cases) (aged between 3 months and 16 years). After pathogen confirmation on CSF, the patient was asked to give a convalescent sample after recovery. 3′ mRNA sequencing was performed to determine differentially expressed genes (DEGs) to create a host transcriptomic profile. Results Enteroviral meningitis cases displayed the largest upregulated fold change enrichment in type I interferon production, response and signaling pathways. Patients with bacterial meningitis showed a significant upregulation of genes related to macrophage and neutrophil activation. We found several significantly DEGs between enteroviral and bacterial meningitis. Random forest classification showed that we were able to differentiate enteroviral from bacterial meningitis with an AUC of 0.982 on held-out samples. Conclusions Enteroviral meningitis has an innate immunity signature with type 1 interferons as key players. Our classifier, based on blood host transcriptomic profiles of different meningitis cases, is a possible strong alternative for diagnosing enteroviral meningitis.