Severe disturbance of glucose metabolism in peripheral blood mononuclear cells of schizophrenia patients: a targeted metabolomic study.

BACKGROUND: Schizophrenia is a widespread and debilitating mental disorder. However, the underlying molecular mechanism of schizophrenia remains largely unknown and no objective laboratory tests are available to diagnose this disorder. The aim of the present study was to characterize the alternations of glucose metabolites and identify potential diagnostic biomarkers for schizophrenia. METHODS: Gas chromatography/mass spectrometry based targeted metabolomic method was used to quantify the levels of 13 glucose metabolites in peripheral blood mononuclear cells (PBMCs) derived from healthy controls, schizophrenia and major depression subjects (n = 55 for each group). RESULTS: The majority (84.6%) of glucose metabolites were significantly disturbed in schizophrenia subjects, while only two (15.4%) glucose metabolites were differently expressed in depression subjects relative to healthy controls in both training set (n = 35/group) and test set (n = 20/group). Antipsychotics had only a subtle effect on glucose metabolism pathway. Moreover, ribose 5-phosphate in PBMCs showed a high diagnostic performance for first-episode drug-naïve schizophrenia subjects. CONCLUSION: These findings suggested disturbance of glucose metabolism may be implicated in onset of schizophrenia and could aid in development of diagnostic tool for this disorder.

Combined application of NMR- and GC-MS-based metabonomics yields a superior urinary biomarker panel for bipolar disorder.

Bipolar disorder (BD) is a debilitating mental disorder that cannot be diagnosed by objective laboratory-based modalities. Our previous studies have independently used nuclear magnetic resonance (NMR)-based and gas chromatography-mass spectrometry (GC-MS)-based metabonomic methods to characterize the urinary metabolic profiles of BD subjects and healthy controls (HC). However, the combined application of NMR spectroscopy and GC-MS may identify a more comprehensive metabolite panel than any single metabonomic platform alone. Therefore, here we applied a dual platform (NMR spectroscopy and GC-MS) that generated a panel of five metabolite biomarkers for BD-four GC-MS-derived metabolites and one NMR-derived metabolite. This composite biomarker panel could effectively discriminate BD subjects from HC, achieving an area under receiver operating characteristic curve (AUC) values of 0.974 in a training set and 0.964 in a test set. Moreover, the diagnostic performance of this panel was significantly superior to the previous single platform-derived metabolite panels. Thus, the urinary biomarker panel identified here shows promise as an effective diagnostic tool for BD. These findings also demonstrate the complementary nature of NMR spectroscopy and GC-MS for metabonomic analysis, suggesting that the combination of NMR spectroscopy and GC-MS can identify a more comprehensive metabolite panel than applying each platform in isolation.