Viral central nervous system (CNS) infections have been associated with substantial morbidity and mortality depending on the causative pathogen. Confirming the diagnosis can be difficult in patients suspected of a CNS infection because the differential diagnosis is broad. A substantial proportion of patients who are initially suspected of a CNS infection turns out to have a different diagnosis, including inflammatory diseases, epilepsy or stroke. In patients with a clinical diagnosis of a viral CNS infection, no causative virus can be identified in 35- 42%. As part of routine diagnostics for CNS infections, a selection of viruses is tested using quantitative PCR (qPCR), currently the gold standard for the majority of the most common viruses causing CNS infection. The limitation of common diagnostic qPCR techniques is that they only target specific viruses and therefore other viruses are missed. Therefore, alternative diagnostic assays, which allow detection of a broader range of viruses, are desirable, yet currently not routinely available. Viral metagenomics has emerged as promising method to detect viruses hypothesis-free. In theory, it should be able to detect all viruses, including unknown viruses, also in samples with low viral loads. Virus discovery cDNA-amplified fragment length polymorphism (cDNA-AFLP) next generation sequencing (VIDISCA-NGS) is one of these methods. VIDISCA-NGS uses restriction enzyme digestion to generate the library for NGS, which has the advantage that a relatively low sequence depth is needed and thereby increases the number of samples that can be processed and drastically reduces costs and runtime per sample. Multiple viruses have been discovered with VIDISCA-NGS, including one in cerebrospinal fluid (CSF). We have previously optimised this method for CSF and analysed its performance from a viral perspective on a selection of CSF samples with a known viral load. In the current study we examined the diagnostic accuracy of VIDISCA-NGS on a cohort of patients with suspected CNS infections.

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Immunotherapy: Open Access
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