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Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics.

ABSTRACT: The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.

SUBMITTER: Ramachandran PS

PROVIDER: S-EPMC8967864 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics.

Ramachandran P S PS Ramesh A A Creswell F V FV Wapniarski A A Narendra R R Quinn C M CM Tran E B EB Rutakingirwa M K MK Bangdiwala A S AS Kagimu E E Kandole K T KT Zorn K C KC Tugume L L Kasibante J J Ssebambulidde K K Okirwoth M M Bahr N C NC Musubire A A Skipper C P CP Fouassier C C Lyden A A Serpa P P Castaneda G G Caldera S S Ahyong V V DeRisi J L JL Langelier C C Crawford E D ED Boulware D R DR Meya D B DB Wilson M R MR

Nature communications 20220330 1

The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute me ...[more]

PMID: 35354815

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Project description:ObjectiveIt is widely acknowledged that central nervous system (CNS) infection is a serious infectious disease accompanied by various complications. However, the accuracy of current detection methods is limited, leading to delayed diagnosis and treatment. In recent years, metagenomic next-generation sequencing (mNGS) has been increasingly adopted to improve the diagnostic yield. The present study sought to evaluate the value of mNGS in CNS infection diagnosis.MethodsFollowing the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2022 guidelines, we searched relevant articles published in seven databases, including PubMed, Web of Science, and Cochrane Library, published from January 2014 to January 2022. High-quality articles related to mNGS applications in the CNS infection diagnosis were included. The comparison between mNGS and the gold standard of CNS infection, such as culture, PCR or serology, and microscopy, was conducted to obtain true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values, which were extracted for sensitivity and specificity calculation.ResultsA total of 272 related studies were retrieved and strictly selected according to the inclusion and exclusion criteria. Finally, 12 studies were included for meta-analysis and the pooled sensitivity was 77% (95% CI: 70-82%, I 2 = 39.69%) and specificity was 96% (95% CI: 93-98%, I 2 = 72.07%). Although no significant heterogeneity in sensitivity was observed, a sub-group analysis was conducted based on the pathogen, region, age, and sample pretreatment method to ascertain potential confounders. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for CNS infection was 0.91 (95% CI: 0.88-0.93). Besides, Deek's Funnel Plot Asymmetry Test indicated no publication bias in the included studies (Figure 3, p > 0.05).ConclusionOverall, mNGS exhibits good sensitivity and specificity for diagnosing CNS infection and diagnostic performance during clinical application by assisting in identifying the pathogen. However, the efficacy remains inconsistent, warranting subsequent studies for further performance improvement during its clinical application.Study registration numberINPLASY202120002.

Project description:BackgroundThe immunopathogenesis of tuberculosis-associated immune reconstitution inflammatory syndrome (IRIS) remains incompletely understood, and we know of only 1 disease site-specific study of the underlying immunology; we recently showed that Mycobacterium tuberculosis culture positivity and increased neutrophils in the cerebrospinal fluid (CSF) of patients with tuberculous meningitis (TBM) are associated with TBM-IRIS. In this study we investigated inflammatory mediators at the disease site in patients with TBM-IRIS.MethodsWe performed lumbar puncture at 3-5 time points in human immunodeficiency virus (HIV)-infected patients with TBM (n = 34), including at TBM diagnosis, at initiation of antiretroviral therapy (ART) (day 14), 14 days after ART initiation, at presentation of TBM-IRIS, and 14 days thereafter. We determined the concentrations of 40 mediators in CSF (33 paired with blood) with Luminex or enzyme-linked immunosorbent assays. Findings were compared between patients who developed TBM-IRIS (n = 16) and those who did not (TBM-non-IRIS; n = 18).ResultsAt TBM diagnosis and 2 weeks after ART initiation, TBM-IRIS was associated with severe, compartmentalized inflammation in the CSF, with elevated concentrations of cytokines, chemokines, neutrophil-associated mediators, and matrix metalloproteinases, compared with TBM-non-IRIS. Patients with TBM-non-IRIS whose CSF cultures were positive for M. tuberculosis at TBM diagnosis (n = 6) showed inflammatory responses similar to those seen in patients with TBM-IRIS at both time points. However, at 2 weeks after ART initiation, S100A8/A9 was significantly increased in patients with TBM-IRIS, compared with patients with TBM-non-IRIS whose cultures were positive at baseline.ConclusionsA high baseline M. tuberculosis antigen load drives an inflammatory response that manifests clinically as TBM-IRIS in most, but not all, patients with TBM. Neutrophils and their mediators, especially S100A8/A9, are closely associated with the central nervous system inflammation that characterizes TBM-IRIS.

Dataset Information

Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics.

Publications

Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics.

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