Metabolomics approach for multibiomarkers determination to investigate dengue virus infection in human patients

Abstract

Background: Dengue is one of the major public health problems in the world, affecting more than fifty million cases in tropical and subtropical region every year. The metabolome, as pathophysiological end-points, provide significant understanding of the mechanism and progression of dengue pathogenesis via changes in the metabolite profile of infected patients. Recent developments in diagnostic technologies provide metabolomics for the early detection of infectious diseases. Methods: The mid-stream urine was collected from 96 patients diagnosed with dengue fever at Penang General Hospital (PGH) and 50 healthy volunteers. Urine samples were analyzed with proton nuclear magnetic resonance (1H NMR) spectroscopy, followed by chemometric multivariate analysis. NMR signals highlighted in the orthogonal partial least square-discriminant analysis (OPLSDA) S-plots were selected and identified using Human Metabolome Database (HMDB) and Chenomx Profiler. A highly predictive model was constructed from urine profile of dengue infected patients versus healthy individuals with the total R2Y (cum) value 0.935, and the total Q2Y (cum) value 0.832. Results: Data showed that dengue infection is related to amino acid metabolism, tricarboxylic acid intermediates cycle and β-oxidation of fatty acids. Distinct variations in certain metabolites were recorded in infected patients including amino acids, various organic acids, betaine, valerylglycine, myoinositol and glycine. Conclusion: Metabolomics approach provides essential insight into host metabolic disturbances following dengue infection.