Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using (1)H-NMR-based metabolomics profiles.

Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance ((1)H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method.

[Discovering potential biomarkers of depression and drug intervention of paroxetine based on (1)H NMR metabolomics].

The purpose of this study was to find potential biomarkers in the serum of patients with depression and provide the basis for clinical diagnosis of depression. Sixteen patients of severe depression were selected according to the inclusion criteria and 16 healthy people were used in the control group. The depression patients took paroxetine for two weeks. The serum was collected from the patients and healthy control group before and after paroxetine treatment. The samples were analyzed by (1)H NMR based metabolomics to determine the changes in profiles of endogenous metabolites and metabolites with significant differences were selected in analysis. Related pathways and receiver operating characteristic (ROC) were examined in analysis of the correlation between the potential biomarkers and depression. Their feasibility and reliability was determined for the clinical practice. Significant differences were observed in the metabolic profile of serum of the patients and the healthy controls. Depression had an effect on metabolism for an increase in leucine, isoleucine and alanine, glutamate, glutamine and N-acetyl-glycoprotein and a decrease in glucose. Those may be considered as potential biomarkers of depression. Clinical application of the biomarkers may improve the objectivity of the diagnosis and treatment of depression by antidepressant drugs. The metabolomics approach is an effective tool in the investigation of biomarkers.