Alterations of serum metabolic profile in major depressive disorder: A case-control study in the Chinese population

Figure 1 Metabolomic analysis of serum samples from major depressive disorder and healthy control groups. A: 2D partial least squares discriminant analysis scores plot of top 2 components; B: Overview of the performance of the top 5 components; C: The heatmap of representative metabolites to distinguish major depressive disorder and healthy control. ¹The model with three components has the highest Q2 value, thus demonstrating the best prediction performance. HC: Healthy control; MDD: Major depressive disorder; FA: Fatty acid; CMPF: 3-Carboxy-4-methyl-5-propyl-2-furanpropanoic acid.

Figure 2 Total 35 differential metabolites between major depressive disorder and healthy control groups. The abscissa represents each feature, and the ordinate represents the fold change after the log2 transformation. Red: Major depressive disorder (MDD) > healthy control (HC); Blue: MDD < HC. FC: Fold change; CMPF: 3-Carboxy-4-methyl-5-propyl-2-furanpropanoic acid.

Figure 3 Receiver operating characteristic analysis revealing candidate metabolomic biomarkers for major depressive disorder diagnosis. A-E: Receiver operating characteristic (ROC) curves of 8-HETE, 10-HDoHE, cortisol, 12-HHTrE, and 10-hydroxydecanoic acid. The left panel of each picture represents the ROC for differentiating the major depressive disorder (MDD) group from the healthy control (HC) group, and the boxplots on the right side are the feature intensities of the two groups. The y-axis refers to the relative value after normalization of the peak intensities; F: Multivariate ROC curves constructed with 2-100 metabolites based on the cross-validation performance. Each curve represents the potential of the top 5, 10, 15, 25, 50, and 100 features in differentiating the MDD group from the HC group; G: Predicted class probabilities (average of the cross-validations) for each sample using the 5-feature model of metabolites; H: Corresponding predictive accuracy of each partial least squares discriminant analysis model constructed with different numbers of features. The predictive accuracy of 5 to 100 features is from 90% to 95.7%, respectively. HC: Healthy control; MDD: Major depressive disorder; AUC: Area under the receiver operating characteristic curve.

Figure 4 Spearman correlations of metabolites and clinical variables in patients with major depressive disorder and healthy controls. The red background represents the positive correlations between the two compared variables, while the blue background represents the negative correlations. FA: Fatty acid; SHAPS: Snaith-Hamilton Pleasure Scale; GAD-7: Generalized Anxiety Disorder 7-item scale; WHO-5: 5-item World Health Organization Well-Being Index; HAMD-24: Hamilton Depression Rating Scale-24 items; BMI: Body mass index; BUN: Blood urea nitrogen; CREA: Creatinine; URIC: Uric acid; CMPF: 3-Carboxy-4-methyl-5-propyl-2-furanpropanoic acid.