Metabolomics of cerebrospinal fluids to identity novel biomarkers as a predictive tool for brain inflammatory conditions
- Publication Type:
- Thesis
- Issue Date:
- 2020
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Inflammation of the brain is increasingly recognised as important in encephalitis. The high mortality and morbidity rates of acute neuroinflammatory diseases has directed significant interest in the investigation of biomarkers to define neuroinflammation and explore mechanisms involved in the regulation of central nervous system immune responses. Metabolomics is a rapidly emerging research field increasingly recognised as a powerful approach for addressing the gaps in knowledge underlying the pathophysiologic mechanisms involved in neuroinflammation and accurate diagnostic biomarkers.
The advancements in analytical platforms followed by subsequent chemometrics tools have revolutionised untargeted metabolomics analyses. With liquid chromatography coupled to high resolution mass spectrometry moving to the forefront, an untargeted metabolomics analysis method was developed and optimised to identify multi-class metabolites in human cerebrospinal fluids. The detection of cerebrospinal fluid metabolites were determined based on a simple and rapid methanol precipitation sample preparation method. The chromatographic separation was achieved within a twenty minute gradient elution using hydrophilic interaction chromatography. The method exhibited good reproducibility, high efficiency chromatographic separation and strong mass resolving mass spectrometry analysis. The practicality and robustness of the developed method on a pilot study further demonstrated the potential of the untargeted metabolomics strategy to identify biomarkers and understand the biochemical pathways involved in neuroinflammation.
With metabolites as the downstream products of cellular function, the application of metabolomics data is to understand the pathogenesis of neuroinflammatory mechanisms involved in encephalitis. Preliminary evidence showed statistically discriminative metabolites in the tryptophan-kynurenine pathway, nitric oxide pathway and elevation of neopterin. The use of the adjacent ratios such as kynurenine/tryptophan, anthranilic acid/3-hydroxyanthranilic acid and ADMA/arginine in combination with neopterin can serve as a potential cerebrospinal fluid biomarker panel to predict neuroinflammation, particularly when routine tests and neuroimaging return a negative result in encephalitis patients. The emergence of cerebrospinal metabolomics holds significant promise incorporating omics research into a clinical diagnostic service.
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