Abstract
We sought to evaluate the diagnostic accuracy of metabolomic biomarker profiles in neurological conditions (idiopathic intracranial hypertension (IIH), multiple sclerosis (MS) and cerebrovascular disease (CVD) compared to controls with either no neurological disease or mixed neurological diseases). Spectra of CSF (n = 87) and serum (n = 72) were acquired using (1)H NMR spectroscopy. Multivariate pattern recognition analysis was used to identify disease-specific metabolite biomarker profiles. The metabolite profiles were then used to predict the diagnosis of a second cohort of patients (n = 25). CSF metabolite profiles were able to predict diagnosis with a sensitivity and specificity of 80% for both IIH and MS. The CVD serum metabolite profile was 75% sensitive and specific. On analysing the second patient cohort, the established metabolite biomarker profiles generated from the first cohort showed moderate ability to segregate patients with IIH and MS (sensitivity:specificity of 63:75% and 67:75%, respectively). These findings suggest that NMR spectroscopic metabolic profiling of CSF and serum can identify differences between IIH, MS, CVD and mixed neurological diseases. Metabolomics may, therefore, have the potential to be developed into a clinically useful diagnostic tool. The identification of disease-unique metabolites may also impart information on disease pathology.
Published Version
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