Discrimination of dengue disease from healthy based on the chemometry of 1H nuclear magnetic resonance spectroscopy

Dengue is the most important human viral disease transmitted by arthropod vectors and over half of the world’s populations live in areas at risk of infection. the severity of the infection depends on the form of the disease,which can be symptomatic or asymptomatic. currently there is neither specific treatment nor vaccine to tackle this emerging disease. metabolomics applied in this study,aimed to provide a global snapshot of all small-molecule metabolites in urine as biological sample of choice to more focused studies of metabolism to distinguish between healthy and dengue infected subjects. fifty-two patients diagnosed with dengue fever at penang general hospital and fourty-three healthy individuals were recruited in this study. 1h-nuclear magnetic resonance (nmr) spectroscopy combined with multivariate analysis (mva) methods such as principal component analysis (pca),partial least square discriminant analysis (pls-da) and orthogonal pls-da (opls-da) were employed for statistical data exploration. the model score plot results showed that all three mvas showed very good spatial distributions with clear clusters/grouping between healthy individuals and dengue infected individuals. also,statistically,the pls-da and opls-da models had high reproducibility and predictivity values,> 0.5. in conclusion,this study established the potential of using a combination of 1h nmr spectroscopy and multivariate data analyses in differentiating healthy and non-healthy individuals,based on obtained score plots reflecting the metabolites pertubation,where spectral features contributing most to variation or separation are identified for further analysis. © 2015 penerbit utm press. all rights reserved.