Pre- and Post-treatment Levels of Plasma Metabolites in Patients With Bipolar Depression.

Background: Bipolar disorder (BD) is a serious mental disease with complex clinical manifestations and high recurrence rate. The purpose of this study was to detect metabolites related to the diagnosis and efficacy evaluation of bipolar depression in plasma samples by metabolomics. Methods: Thirty-one bipolar depression patients were recruited and completed 8 weeks medication and a matched group of 47 healthy controls (HCs) was recruited. Nuclear magnetic resonance spectroscopy was used to profile plasma samples of bipolar depression patients at baseline and after 8 weeks medication, and HCs. Then Multivariate statistical analysis was performed to analyze differences of plasma metabolites among the three groups. Results: We detected seven specific differential metabolites in bipolar depression. Six of the metabolites were returned to the normal levels in different degrees after 8 weeks medication, only Glycine continuously decreased in the acute and significant improvement stages of bipolar depression (VIP > 1 and p < 0.05). These differential metabolites involved several metabolic pathways. Limitations: The small sample size was one of the most prominent limitations. Each BD patient was given an individualized medication regimen according to the clinical guidelines. Conclusion: There were metabolites changes before and after 8 weeks medication. Glycine may be a characteristic marker of bipolar depression and does not change with the improvement of bipolar depression, while other 6 differential metabolites may be biomarkers associated with the pathological development or the improvement of bipolar depression. And, these differential metabolites mainly related to energy metabolism, amino acid metabolism and gut microbiota metabolism.

Metabolic Profiling in Bipolar Disorder Patients During Depressive Episodes.

Bipolar disorder (BD) is a common and debilitating mental disorder. Bipolar depression is the main episode of BD. Furthermore, there are no objective biomarkers available for diagnosing the disorder. In this research, a Nuclear Magnetic Resonance (NMR) spectroscopy based on a metabonomics technique was used to analyze serum samples from 37 patients with bipolar depression and 48 healthy control participants to determine potential biomarkers for bipolar depression. In total, seven different metabolites were identified that could effectively distinguish patients from healthy controls. The metabolites indicated that disturbances of amino acid and energy metabolisms might be involved in the pathogenesis of BD. Finally, a panel consisting of four potential biomarkers (lactate, trimethylamine oxide, N-acetyl glycoprotein, and α-glucose) was identified, which showed a higher combined diagnostic ability with an area under the curve of 0.893. Our findings may contribute to the development of an objective method for diagnosing bipolar depression.