Metagenomic Next-Generation Sequencing for Diagnosis of Infectious Encephalitis and Meningitis: A Large, Prospective Case Series of 213 Patients.
ABSTRACT: Purpose: We assessed the performance of metagenomic next-generation sequencing (mNGS) in the diagnosis of infectious encephalitis and meningitis. Methods: This was a prospective multicenter study. Cerebrospinal fluid samples from patients with viral encephalitis and/or meningitis, tuberculous meningitis, bacterial meningitis, fungal meningitis, and non-central nervous system (CNS) infections were subjected to mNGS. Results: In total, 213 patients with infectious and non-infectious CNS diseases were finally enrolled from November 2016 to May 2019; the mNGS-positive detection rate of definite CNS infections was 57.0%. At a species-specific read number (SSRN) ?2, mNGS performance in the diagnosis of definite viral encephalitis and/or meningitis was optimal (area under the curve [AUC] = 0.659, 95% confidence interval [CI] = 0.566-0.751); the positivity rate was 42.6%. At a genus-specific read number ?1, mNGS performance in the diagnosis of tuberculous meningitis (definite or probable) was optimal (AUC=0.619, 95% CI=0.516-0.721); the positivity rate was 27.3%. At SSRNs ?5 or 10, the diagnostic performance was optimal for definite bacterial meningitis (AUC=0.846, 95% CI = 0.711-0.981); the sensitivity was 73.3%. The sensitivities of mNGS (at SSRN ?2) in the diagnosis of cryptococcal meningitis and cerebral aspergillosis were 76.92 and 80%, respectively. Conclusion: mNGS of cerebrospinal fluid effectively identifies pathogens causing infectious CNS diseases. mNGS should be used in conjunction with conventional microbiological testing. Trial Registration: Chinese Clinical Trial Registry, ChiCTR1800020442.
Project description:Purpose:The application of metagenomic next-generation sequencing (mNGS) in the diagnosis of tuberculous meningitis (TBM) remains poorly characterized. Here, we retrospectively analyzed data from patients with TBM who had taken both mNGS and conventional tests including culture of Mycobacterium tuberculosis (MTB), polymerase chain reaction (PCR) and acid-fast bacillus (AFB) stain, and the sensitivity and specificity of these methods were compared. Methods:We retrospectively recruited TBM patients admitted to the hospital between December 2015 and October 2018. The first collection of cerebrospinal fluid (CSF) samples underwent both mNGS and conventional tests. In addition, patients with bacterial/cryptococcal meningitis or viral meningoencephalitis were mNGS positive controls, and a patient with auto-immune encephalitis was an mNGS negative control. Results:Twenty three TBM patients were classified as 12 definite and 11 clinical diagnoses, which were based on clinical manifestations, pathogen evidence, CSF parameters, brain imaging, and treatment response. The mNGS method identified sequences of Mycobacterium tuberculosis complex (MBTC) from 18 samples (18/23, 78.26%). In patients with definite TBM, the sensitivity of mNGS, AFB, PCR, and culture to detect MTB in the first CSF samples were 66.67, 33.33, 25, and 8.33%, respectively. The specificity of each method was 100%. Among the four negative mNGS cases (4/23, 17.39%), three turned out positive by repeated AFB stain. The agreement of mNGS with the total of conventional methods was 44.44% (8/18). Combination of mNGS and conventional methods increased the detection rate to 95.65%. One patient was diagnosed as complex of TBM and cryptococcal meningitis, in which AFB stain and cryptococcal antigen enzyme immunoassay were positive and the DNA of Cryptococcus neoformans was detected by mNGS. Conclusion:Our study indicates that mNGS is an alternative method to detect the presence of mycobacterial DNA in CSF samples from patients with TBM and deserves to be applied as a front-line CSF test.
Project description:Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific tests, sometimes over days to weeks, whereas metagenomic next-generation sequencing (mNGS) profiles all nucleic acid in a sample. In this single-center, prospective study, 68 hospitalized patients with known (<i>n</i> = 44) or suspected (<i>n</i> = 24) CNS infections underwent mNGS from RNA and DNA to identify potential pathogens and also targeted sequencing of viruses using hybrid capture. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects, 3 of whom had no clinical diagnosis by routine workup. Among subjects diagnosed with infection by serology and/or peripheral samples, we demonstrated the utility of mNGS to detect pathogen nucleic acid in CSF, importantly for the Ixodes scapularis tick-borne pathogens Powassan virus, Borrelia burgdorferi, and Anaplasma phagocytophilum. We also evaluated two methods to enhance the detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed the detection of varicella-zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with efficacy similar to that of pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. <b>IMPORTANCE</b> Meningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40 to 60% of people with meningitis or encephalitis have no clear cause of CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 prospectively enrolled patients with known (<i>n</i> = 44) or suspected (<i>n</i> = 24) CNS viral infection from a single center in New England and evaluated enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become integrated into the diagnostic toolkit for CNS infections.
Project description:<b>Background: </b>Tuberculous meningitis (TBM) is a severe form of extrapulmonary tuberculosis and its early diagnosis is very difficult leading to present with severe disability or die. The current study aimed to assess the accuracy of metagenomic next generation sequencing (mNGS) for TBM, and to identify a new test for the early diagnosis of TBM.<br><br><b>Methods: </b>We searched for articles published in Embase, PubMed, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data up to June 30, 2020 for studies that assessed the efficacy of mNGS for the diagnosis of TBM. Then, the accuracy between mNGS and a composite reference standard (CRS) in these articles was compared using the meta-analysis approach.<br><br><b>Results: </b>Four independent studies with 342 samples comparing mNGS and a CRS were included in this study. The sensitivity of mNGS for TBM diagnosis ranged from 27% to 84%. The combined sensitivity of mNGS was 61%, and the I2 value was 92%. Moreover, the specificity of mNGS for TBM diagnosis ranged from 96% to 100%. The combined specificity of mNGS was 98%, and the I2 value was 74%. The heterogeneity between studies in terms of sensitivity and specificity was significant. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for TBM was 0.98.<br><br><b>Conclusions: </b>The sensitivity of mNGS for TBM diagnosis was moderate. Furthermore, the specificity was extremely high, and the AUC of the SROC indicated a very good diagnostic efficacy. mNGS could be used as an early diagnostic method for TBM, however, the results should be treated with caution for the heterogeneity between studies was extremely significant.<br><br><b>Systematic review registration: </b>INPLASY202070100.
Project description:Background:Central nervous system (CNS) infections remain a major public health problem in Sub-Saharan Africa, causing 15%-25% of AIDS-related deaths. With widespread availability of antiretroviral therapy (ART) and the introduction of improved diagnostics, the epidemiology of infectious meningitis is evolving. Methods:We prospectively enrolled adults presenting with HIV-associated meningitis in Kampala and Mbarara, Uganda, from March 2015 to September 2017. Participants had a structured, stepwise diagnostic algorithm performed of blood cryptococcal antigen (CrAg), CSF CrAg, Xpert MTB/RIF for tuberculous (TB) meningitis (TBM), Biofire multiplex polymerase chain reaction, and traditional microscopy and cultures. Results:We screened 842 consecutive adults with HIV presenting with suspected meningitis: 57% men, median age 35 years, median CD4 26 cells/mcL, and 55% presented on ART. Overall, 60.5% (509/842) were diagnosed with first-episode cryptococcal meningitis and 7.4% (62/842) with second episode. Definite/probable TB meningitis was the primary diagnosis in 6.9% (58/842); 5.3% (n = 45) had microbiologically confirmed (definite) TB meningitis. An additional 7.8% (66/842) did not meet the diagnostic threshold for definite/probable TBM but received empiric TBM therapy. Bacterial and viral meningitis were diagnosed in 1.3% (11/842) and 0.7% (6/842), respectively. The adoption of a cost-effective stepwise diagnostic algorithm allowed 79% (661/842) to have a confirmed microbiological diagnosis at an average cost of $44 per person. Conclusions:Despite widespread ART availability, Cryptococcus remains the leading cause of HIV-associated meningitis. The second most common etiology was TB meningitis, treated in 14.7% overall. The increased proportion of microbiologically confirmed TBM cases reflects the impact of new improved molecular diagnostics.
Project description:Metagenomic next-generation sequencing (mNGS) for pan-pathogen detection has been successfully tested in proof-of-concept case studies in patients with acute illness of unknown etiology but to date has been largely confined to research settings. Here, we developed and validated a clinical mNGS assay for diagnosis of infectious causes of meningitis and encephalitis from cerebrospinal fluid (CSF) in a licensed microbiology laboratory. A customized bioinformatics pipeline, SURPI+, was developed to rapidly analyze mNGS data, generate an automated summary of detected pathogens, and provide a graphical user interface for evaluating and interpreting results. We established quality metrics, threshold values, and limits of detection of 0.2-313 genomic copies or colony forming units per milliliter for each representative organism type. Gross hemolysis and excess host nucleic acid reduced assay sensitivity; however, spiked phages used as internal controls were reliable indicators of sensitivity loss. Diagnostic test accuracy was evaluated by blinded mNGS testing of 95 patient samples, revealing 73% sensitivity and 99% specificity compared to original clinical test results, and 81% positive percent agreement and 99% negative percent agreement after discrepancy analysis. Subsequent mNGS challenge testing of 20 positive CSF samples prospectively collected from a cohort of pediatric patients hospitalized with meningitis, encephalitis, and/or myelitis showed 92% sensitivity and 96% specificity relative to conventional microbiological testing of CSF in identifying the causative pathogen. These results demonstrate the analytic performance of a laboratory-validated mNGS assay for pan-pathogen detection, to be used clinically for diagnosis of neurological infections from CSF.
Project description:Abstract Background Metagenomic next-generation sequencing (mNGS) of CSF can identify nearly all pathogens in a single test. We previously validated a CSF mNGS assay in a licensed clinical laboratory. To date, the utility of mNGS for infectious disease diagnosis has been described in case reports and small case series, but not in a large-scale clinical trial. Methods The PDAID (“Precision Diagnosis of Acute Infectious Diseases”) study was a 1-year nationwide prospective study across 8 tertiary care hospitals to evaluate the performance and utility of a clinical metagenomic sequencing assay for diagnosis of meningitis, encephalitis, or myelitis from cerebrospinal fluid (CSF) (ClinicalTrials.gov number NCT02910037). We recruited acutely ill hospitalized inpatients lacking a diagnosis at the time of enrollment. CSF samples were processed and analyzed by mNGS testing within 1 week of receipt in the clinical microbiology laboratory, with sequencing results reported in the patient medical record and used to make contemporaneous treatment decisions. Weekly clinical microbial sequencing boards were convened to discuss mNGS results with treating physicians, and clinical impact evaluated by surveys, chart review, and direct clinician feedback. Results A total of 204 patients were enrolled. Patients were severely ill (ICU 48%, average length of stay 26 days, overall 30-day mortality 7.4%). Fifty-nine neurologic infections were diagnosed in 57 patients (27.9%). mNGS identified 15 (25.4%) infections that were missed by all conventional microbiological tests, including emerging and/or uncommon pathogens such as St. Louis encephalitis virus, hepatitis E virus acquired by lung transplant, and Nocardia farcinica. Twelve of the 15 mNGS-only diagnoses (80%) had clinical impact, with 9 of 15 (60%) guiding appropriate treatment. For diagnosis of infections by direct detection CSF testing, mNGS had 79.1% sensitivity and 98.8% specificity, versus 65.1% sensitivity and 99.4% specificity by conventional testing. Conclusion A significant proportion of neurologic infections are missed despite extensive diagnostic testing performed in tertiary care hospitals. Clinical metagenomic CSF testing was found to be useful in increasing the number of diagnosed neurologic infections and providing actionable information for physicians. Disclosures All authors: No reported disclosures.
Project description:<h4>Background</h4>WHO recommends Xpert MTB/RIF as initial diagnostic testing for tuberculous meningitis. However, diagnosis remains difficult, with Xpert sensitivity of about 50-70% and culture sensitivity of about 60%. We evaluated the diagnostic performance of the new Xpert MTB/RIF Ultra (Xpert Ultra) for tuberculous meningitis.<h4>Methods</h4>We prospectively obtained diagnostic cerebrospinal fluid (CSF) specimens during screening for a trial on the treatment of HIV-associated cryptococcal meningitis in Mbarara, Uganda. HIV-infected adults with suspected meningitis (eg, headache, nuchal rigidity, altered mental status) were screened consecutively at Mbarara Regional Referral Hospital. We centrifuged CSF, resuspended the pellet in 2 mL of CSF, and tested 0·5 mL with mycobacteria growth indicator tube culture, 1 mL with Xpert, and cryopreserved 0·5 mL, later tested with Xpert Ultra. We assessed diagnostic performance against uniform clinical case definition or a composite reference standard of any positive CSF tuberculous test.<h4>Findings</h4>From Feb 27, 2015, to Nov 7, 2016, we prospectively evaluated 129 HIV-infected adults with suspected meningitis for tuberculosis. 23 participants were classified as probable or definite tuberculous meningitis by uniform case definition, excluding Xpert Ultra results. Xpert Ultra sensitivity was 70% (95% CI 47-87; 16 of 23 cases) for probable or definite tuberculous meningitis compared with 43% (23-66; 10/23) for Xpert and 43% (23-66; 10/23) for culture. With composite standard, we detected tuberculous meningitis in 22 (17%) of 129 participants. Xpert Ultra had 95% sensitivity (95% CI 77-99; 21 of 22 cases) for tuberculous meningitis, which was higher than either Xpert (45% [24-68]; 10/22; p=0·0010) or culture (45% [24-68]; 10/22; p=0·0034). Of 21 participants positive by Xpert Ultra, 13 were positive by culture, Xpert, or both, and eight were only positive by Xpert Ultra. Of those eight, three were categorised as probable tuberculous meningitis, three as possible tuberculous meningitis, and two as not tuberculous meningitis. Testing 6 mL or more of CSF was associated with more frequent detection of tuberculosis than with less than 6 mL (26% vs 7%; p=0·014).<h4>Interpretation</h4>Xpert Ultra detected significantly more tuberculous meningitis than did either Xpert or culture. WHO now recommends the use of Xpert Ultra as the initial diagnostic test for suspected tuberculous meningitis.<h4>Funding</h4>National Institute of Neurologic Diseases and Stroke, Fogarty International Center, National Institute of Allergy and Infectious Disease, UK Medical Research Council/DfID/Wellcome Trust Global Health Trials, Doris Duke Charitable Foundation.
Project description:<h4>Objectives</h4>To study the diagnostic accuracy of clinical and laboratory features in the diagnosis of central nervous system (CNS) infection and bacterial meningitis.<h4>Methods</h4>We included consecutive adult episodes with suspected CNS infection who underwent cerebrospinal fluid (CSF) examination. The reference standard was the diagnosis classified into five categories: 1) CNS infection; 2) CNS inflammation without infection; 3) other neurological disorder; 4) non-neurological infection; and 5) other systemic disorder.<h4>Results</h4>Between 2012 and 2015, 363 episodes of suspected CNS infection were included. CSF examination showed leucocyte count >5/mm<sup>3</sup> in 47% of episodes. Overall, 89 of 363 episodes were categorized as CNS infection (25%; most commonly viral meningitis [7%], bacterial meningitis [7%], and viral encephalitis [4%]), 36 (10%) episodes as CNS inflammatory disorder, 111 (31%) as systemic infection, in 119 (33%) as other neurological disorder, and 8 (2%) as other systemic disorders. Diagnostic accuracy of individual clinical characteristics and blood tests for the diagnosis of CNS infection or bacterial meningitis was low. CSF leucocytosis differentiated best between bacterial meningitis and other diagnoses (area under the curve [AUC] 0.95) or any neurological infection versus other diagnoses (AUC 0.93).<h4>Conclusions</h4>Clinical characteristics fail to differentiate between neurological infections and other diagnoses, and CSF analysis is the main contributor to the final diagnosis.
Project description:OBJECTIVE:In 2016, Catalonia experienced a pediatric brainstem encephalitis outbreak caused by enterovirus A71 (EV-A71). Conventional testing identified EV in the periphery but rarely in CSF. Metagenomic next-generation sequencing (mNGS) and CSF pan-viral serology (VirScan) were deployed to enhance viral detection and characterization. METHODS:RNA was extracted from the CSF (n = 20), plasma (n = 9), stool (n = 15), and nasopharyngeal samples (n = 16) from 10 children with brainstem encephalitis and 10 children with meningitis or encephalitis. Pathogens were identified using mNGS. Available CSF from cases (n = 12) and pediatric other neurologic disease controls (n = 54) were analyzed with VirScan with a subset (n = 9 and n = 50) validated by ELISA. RESULTS:mNGS detected EV in all samples positive by quantitative reverse transcription polymerase chain reaction (qRT-PCR) (n = 25). In qRT-PCR-negative samples (n = 35), mNGS found virus in 23% (n = 8, 3 CSF samples). Overall, mNGS enhanced EV detection from 42% (25/60) to 57% (33/60) (p-value = 0.013). VirScan and ELISA increased detection to 92% (11/12) compared with 46% (4/12) for CSF mNGS and qRT-PCR (p-value = 0.023). Phylogenetic analysis confirmed the EV-A71 strain clustered with a neurovirulent German EV-A71. A single amino acid substitution (S241P) in the EVA71 VP1 protein was exclusive to the CNS in one subject. CONCLUSION:mNGS with VirScan significantly increased the CNS detection of EVs relative to qRT-PCR, and the latter generated an antigenic profile of the acute EV-A71 immune response. Genomic analysis confirmed the close relation of the outbreak EV-A71 and neuroinvasive German EV-A71. A S241P substitution in VP1 was found exclusively in the CSF.
Project description:<h4>Background</h4>Tuberculous meningitis (TBM) is the most common form of neurotuberculosis and the fifth most common form of extrapulmonary TB. Early diagnosis and prompt treatment are the cornerstones of effective disease management. The accurate diagnosis of TBM poses a challenge due to an extensive differential diagnosis, low bacterial load and paucity of cerebrospinal fluid (CSF) especially in children.<h4>Methodology/principal findings</h4>We describe the utility of ELISA and qPCR for the detection of Mycobacterium tuberculosis (M. tb) proteins (GlcB, HspX, MPT51, Ag85B and PstS1) and DNA for the rapid diagnosis of TBM. CSF filtrates (n = 532) derived from children were classified as 'Definite' TBM (M. tb culture positive, n = 29), 'Probable and Possible' TBM (n = 165) and 'Not-TBM' including other cases of meningitis or neurological disorders (n = 338). ROC curves were generated from ELISA and qPCR data of 'Definite' TBM and Non-Tuberculous infectious meningitis (NTIM) samples and cut-off values were derived to provide ? 95% specificity. devR qPCR, GlcB, HspX and PstS1 ELISAs showed 100% (88;100) sensitivity and 96-97% specificity in 'Definite' TBM samples. The application of these cut-offs to 'Probable and Possible' TBM groups yielded excellent sensitivity (98%, 94;99) and specificity (98%, 96;99) for qPCR and for GlcB, HspX and MPT51 antigen ELISAs (sensitivity 92-95% and specificity 93-96%). A test combination of qPCR with GlcB and HspX ELISAs accurately detected all TBM samples at a specificity of ~90%. Logistic regression analysis indicated that these tests significantly added value to the currently used algorithms for TBM diagnosis.<h4>Conclusions</h4>The detection of M. tb GlcB/HspX antigens/devR DNA in CSF is likely to improve the utility of existing algorithms for TBM diagnosis and also hasten the speed of diagnosis.