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ImportanceCerebrospinal fluid (CSF) cytologic testing and flow cytometry are insensitive for diagnosing neoplasms of the central nervous system (CNS). Such clinical phenotypes can mimic infectious and autoimmune causes of meningoencephalitis.ObjectiveTo ascertain whether CSF metagenomic next-generation sequencing (mNGS) can identify aneuploidy, a hallmark of malignant neoplasms, in difficult-to-diagnose cases of CNS malignant neoplasm.Design, setting, and participantsTwo case-control studies were performed at the University of California, San Francisco (UCSF). The first study used CSF specimens collected at the UCSF Clinical Laboratories between July 1, 2017, and December 31, 2019, and evaluated test performance in specimens from patients with a CNS malignant neoplasm (positive controls) or without (negative controls). The results were compared with those from CSF cytologic testing and/or flow cytometry. The second study evaluated patients who were enrolled in an ongoing prospective study between April 1, 2014, and July 31, 2019, with presentations that were suggestive of neuroinflammatory disease but who were ultimately diagnosed with a CNS malignant neoplasm. Cases of individuals whose tumors could have been detected earlier without additional invasive testing are discussed.Main outcomes and measuresThe primary outcome measures were the sensitivity and specificity of aneuploidy detection by CSF mNGS. Secondary subset analyses included a comparison of CSF and tumor tissue chromosomal abnormalities and the identification of neuroimaging characteristics that were associated with test performance.ResultsAcross both studies, 130 participants were included (median [interquartile range] age, 57.5 [43.3-68.0] years; 72 men [55.4%]). The test performance study used 125 residual laboratory CSF specimens from 47 patients with a CNS malignant neoplasm and 56 patients with other neurological diseases. The neuroinflammatory disease study enrolled 12 patients and 17 matched control participants. The sensitivity of the CSF mNGS assay was 75% (95% CI, 63%-85%), and the specificity was 100% (95% CI, 96%-100%). Aneuploidy was detected in 64% (95% CI, 41%-83%) of the patients in the test performance study with nondiagnostic cytologic testing and/or flow cytometry, and in 55% (95% CI, 23%-83%) of patients in the neuroinflammatory disease study who were ultimately diagnosed with a CNS malignant neoplasm. Of the patients in whom aneuploidy was detected, 38 (90.5%) had multiple copy number variations with tumor fractions ranging from 31% to 49%.Conclusions and relevanceThis case-control study showed that CSF mNGS, which has low specimen volume requirements, does not require the preservation of cell integrity, and was orginally developed to diagnose neurologic infections, can also detect genetic evidence of a CNS malignant neoplasm in patients in whom CSF cytologic testing and/or flow cytometry yielded negative results with a low risk of false-positive results.

ImportanceIdentifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed.ObjectiveTo present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious.Design, setting, and participantsIn this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis.Main outcomes and measuresPathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results.ResultsThe 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm.Conclusions and relevanceDiverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.

Importance:Powassan virus is a rare but increasingly recognized cause of severe neurological disease. Objective:To highlight the diagnostic challenges and neuropathological findings in a fatal case of Powassan encephalitis caused by deer tick virus (lineage II) in a patient with follicular lymphoma receiving rituximab, with nonspecific anti-GAD65 antibodies, who was initially seen with fever and orchiepididymitis. Design, Setting, and Participants:Comparison of clinical, radiological, histological, and laboratory findings, including immunohistochemistry, real-time polymerase chain reaction, antibody detection, and unbiased sequencing assays, in a single case report (first seen in December 2016) at an academic medical center. Exposure:Infection with Powassan virus. Main Outcomes and Measures:Results of individual assays compared retrospectively. Results:In a 63-year-old man with fatal Powassan encephalitis, serum and cerebrospinal fluid IgM antibodies were not detected via standard methods, likely because of rituximab exposure. Neuropathological findings were extensive, including diffuse leptomeningeal and parenchymal lymphohistiocytic infiltration, microglial proliferation, marked neuronal loss, and white matter microinfarctions most severely involving the cerebellum, thalamus, and basal ganglia. Diagnosis was made after death by 3 independent methods, including demonstration of Powassan virus antigen in brain biopsy and autopsy tissue, detection of viral RNA in serum and cerebrospinal fluid by targeted real-time polymerase chain reaction, and detection of viral RNA in cerebrospinal fluid by unbiased sequencing. Extensive testing for other etiologies yielded negative results, including mumps virus owing to prodromal orchiepididymitis. Low-titer anti-GAD65 antibodies identified in serum, suggestive of limbic encephalitis, were not detected in cerebrospinal fluid. Conclusions and Relevance:Owing to the rarity of Powassan encephalitis, a high degree of suspicion is required to make the diagnosis, particularly in an immunocompromised patient, in whom antibody-based assays may be falsely negative. Unbiased sequencing assays have the potential to detect uncommon infectious agents and may prove useful in similar scenarios.