Fig 1.
Workflow of untargeted metabolomics in serum samples from children infected with DENV.
Fig 2.
PLS-DA regression model from untargeted metabolomics of serum samples from children infected with dengue and controls.
A. PLS-DA 2D Score plot exhibiting a tendence of separation between groups. B. Cross-validation of PLS-DA shows a Q2 of 0.7 for the regression model. C. VIP scores show a metabolite panel with 15 m/z with differential abundances between dengue and controls. PLSDA, Partial least square-discriminant analysis. VIP, variable importance in projection.
Table 1.
Lipids attribution for controls and dengue groups according with Lipid Maps database, obtained via exploratory metabolomics from human serum.
Fig 3.
Univariate ROC curves for individual analysis of the 15 m/z suggested as biomarkers.
The horizontal coordinates indicate the false positive rate; the vertical coordinates indicate the true positive rate; and the area under the curve (AUC) value indicates the prediction accuracy. ROC, Receptor operating characteristics.
Fig 4.
ROC curve analysis of a set of biomarkers obtained via untargeted metabolomics in serum samples from children infected with DENV compared to Control.
A. ROC curve view shows an area under ROC curve (AUC) of 0.962. B. Tester analysis shows 93% (70 out of 75) of correct classification. ROC, Receptor operating characteristics.