Impaired glycolytic response in peripheral blood mononuclear cells of first-onset antipsychotic-naive schizophrenia patients

Abstract

Little is known about the biological mechanisms underpinning the pathology of schizophrenia. We have analysed the proteome of stimulated and unstimulated peripheral blood mononuclear cells (PBMCs) from schizophrenia patients and controls as a potential model of altered cellular signaling using liquid-chromatography mass spectrometry proteomic profiling. PBMCs from patients and controls were stimulated for 72 h in vitro using staphylococcal enterotoxin B. In total, 18 differentially expressed proteins between first-onset, antipsychotic-naive patients and controls in the unstimulated and stimulated conditions were identified. Remarkably, eight of these proteins were associated with the glycolytic pathway and patient-control differences were more prominent in stimulated compared with unstimulated PBMCs. None of these proteins were altered in chronically ill antipsychotic-treated patients. Non-linear multivariate statistical analysis showed that small subsets of these proteins could be used as a signal for distinguishing first-onset patients from controls with high precision. Functional analysis of PBMCs did not reveal any difference in the glycolytic rate between patients and controls despite increased levels of lactate and the glucose transporter-1, and decreased levels of the insulin receptor in patients. In addition, subjects showed increased serum levels of insulin, consistent with the idea that some schizophrenia patients are insulin resistant. These results show that schizophrenia patients respond differently to PBMC activation and this is manifested at disease onset and may be modulated by antipsychotic treatment. The glycolytic protein signature associated with this effect could therefore be of diagnostic and prognostic value. Moreover, these results highlight the importance of using cells for functional discovery and show that it may not be sufficient to measure protein expression levels in static states.