Research Papers:

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

Yi-Ning Dai, Hai-Jun Huang, Wen-Yuan Song, Yong-Xi Tong, Dan-Hong Yang, Ming-Shan Wang, Yi-Cheng Huang, Mei-Juan Chen, Jia-Jie Zhang, Ze-Ze Ren, Wei Zheng and Hong-Ying Pan _

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Oncotarget. 2017; 8:100095-100112. https://doi.org/10.18632/oncotarget.21942

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Yi-Ning Dai1,*, Hai-Jun Huang1,*, Wen-Yuan Song1, Yong-Xi Tong1, Dan-Hong Yang1, Ming-Shan Wang1, Yi-Cheng Huang1, Mei-Juan Chen1, Jia-Jie Zhang1, Ze-Ze Ren2, Wei Zheng1 and Hong-Ying Pan1

1Department of Infectious Diseases, Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China

2Department of Infectious Diseases, The Second Affiliated Hospital of Zhejiang Chinese Medicinal University, Hangzhou, Zhejiang, China

*These authors have contributed equally to this work

Correspondence to:

Hong-Ying Pan, email: [email protected]

Keywords: tuberculous meningitis; viral meningitis; bacterial meningitis; cryptococcal meningitis; metabolomics

Received: April 15, 2017     Accepted: June 30, 2017     Published: October 19, 2017


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.

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