Identification of potential metabolic biomarkers of cerebrospinal fluids that differentiate tuberculous meningitis from other types of meningitis by a metabolomics study

Abstract

Tuberculous meningitis (TBM) is caused by tuberculosis infection of of the meninges, which are the membrane systems that encircle the brain, with a high morbidity and mortality rate. It is challenging to diagnose TBM among other types of meningitis, such as viral meningitis, bacterial meningitis and cryptococcal meningitis. We aimed to identify metabolites that are differentially expressed between TBM and the other types of meningitis by a global metabolomics analysis. The cerebrospinal fluids (CSF) from 50 patients with TBM, 17 with viral meningitis, 17 with bacterial meningitis, and 16 with cryptococcal meningitis were analyzed using ultra high performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). A total of 1161 and 512 features were determined in positive and negative electrospray ionization mode, respectively. A clear separation between TBM and viral, bacterial or cryptococcal meningitis was achieved by orthogonal projections to latent structures-discriminate analysis (OPLS-DA) analysis. Potential metabolic markers and related pathways were identified, which were mainly involved in the metabolism of amino acid, lipids and nucleosides. In summary, differential metabolic profiles of the CSF exist between TBM and other types of meningitis, and potential metabolic biomarkers were identified to differentiate TBM from other types of meningitis.

Tuberculous Meningitis: Pathogenesis, Immune Responses, Diagnostic Challenges, and the Potential of Biomarker-Based Approaches

“…The technique is used to identify metabolites that are associated with certain physiological or pathological conditions. Several studies have demonstrated significant differences in amino acids and energy metabolism in CSF samples of TBM patients compared with other groups, including patients with viral, bacterial, and cryptococcal meningitis ( 103 – 106 ). However, the diagnostic accuracy of the metabolites identified was not reported.…”

Biomarker discovery for tuberculosis using metabolomics

“…Another similar study ( Zhang et al, 2019 ) included bacterial meningitis (BM) in addition, and found that 23, 6, and 21 metabolites were able to differentiate TBM from VM, BM and meningitis-negative groups, respectively, albeit with a strong overlap between these different groups of differential metabolites. The MS-based metabolomics profiling of adult CSF by Dai et al (2017) included further a cohort of cryptococcal meningitis (CM, n = 16), in addition to TBM (n = 50), VM (n = 17) and BM (n = 17) patients. They reported 13, 16, and nine potential biomarkers, mainly involved in the metabolism of amino acid, lipids and nucleotides, which differentiate between TBM and VM, BM, and CM, respectively.…”

Is Ferroptosis a Future Direction in Exploring Cryptococcal Meningitis?

“…Metabolomics research has identified several potential metabolic biomarkers of CSF that can help distinguish different types of meningitis. According to different studies, glutamate and cysteine may be potential metabolic markers of CSF that can help distinguish CM from tuberculous meningitis ( 96 ). Similarly, another study evaluated the metabolic status of lung epithelial cells that were infected with C. neoformans .…”