201. Chronic Meningitis Investigated via Metagenomic Next-Generation Sequencing.
- Author
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Wilson, Michael R, Wilson, Michael R, O'Donovan, Brian D, Gelfand, Jeffrey M, Sample, Hannah A, Chow, Felicia C, Betjemann, John P, Shah, Maulik P, Richie, Megan B, Gorman, Mark P, Hajj-Ali, Rula A, Calabrese, Leonard H, Zorn, Kelsey C, Chow, Eric D, Greenlee, John E, Blum, Jonathan H, Green, Gary, Khan, Lillian M, Banerji, Debarko, Langelier, Charles, Bryson-Cahn, Chloe, Harrington, Whitney, Lingappa, Jairam R, Shanbhag, Niraj M, Green, Ari J, Brew, Bruce J, Soldatos, Ariane, Strnad, Luke, Doernberg, Sarah B, Jay, Cheryl A, Douglas, Vanja, Josephson, S Andrew, DeRisi, Joseph L, Wilson, Michael R, Wilson, Michael R, O'Donovan, Brian D, Gelfand, Jeffrey M, Sample, Hannah A, Chow, Felicia C, Betjemann, John P, Shah, Maulik P, Richie, Megan B, Gorman, Mark P, Hajj-Ali, Rula A, Calabrese, Leonard H, Zorn, Kelsey C, Chow, Eric D, Greenlee, John E, Blum, Jonathan H, Green, Gary, Khan, Lillian M, Banerji, Debarko, Langelier, Charles, Bryson-Cahn, Chloe, Harrington, Whitney, Lingappa, Jairam R, Shanbhag, Niraj M, Green, Ari J, Brew, Bruce J, Soldatos, Ariane, Strnad, Luke, Doernberg, Sarah B, Jay, Cheryl A, Douglas, Vanja, Josephson, S Andrew, and DeRisi, Joseph L
- Abstract
Importance:Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. Objective:To 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 Participants:In 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 Measures:Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. Results:The 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, Histopla
- Published
- 2018