Schizophrenia, a complex neuropsychiatric disorder, frequently experiences a high rate of misdiagnosis due to subjective symptom assessment. Consequently, there is an urgent need for innovative and objective diagnostic tools. In this study, we used cutting-edge extracellular vesicles’ (EVs) proteome profiling and XGBoost-based machine learning to develop new markers and personalized discrimination scores for schizophrenia diagnosis and prediction of treatment response. We analysed plasma and plasma-derived EVs from 343 participants, including 100 individuals with chronic schizophrenia, 34 first-episode and drug-naïve patients, 35 individuals with bipolar disorder, 25 individuals with major depressive disorder and 149 age- and sex-matched healthy controls. Our innovative approach uncovered EVs-based complement changes in patients, specific to their disease-type and status. The EV-based biomarkers outperformed their plasma counterparts, accurately distinguishing schizophrenia individuals from healthy controls with an area under curve (AUC) of 0.895, 83.5% accuracy, 85.3% sensitivity and 82.0% specificity. Moreover, they effectively differentiated schizophrenia from bipolar disorder and major depressive disorder, with AUCs of 0.966 and 0.893, respectively. The personalized discrimination scores provided a personalized diagnostic index for schizophrenia and exhibited a significant association with patients’ antipsychotic treatment response in the follow-up cohort. Overall, our study represents a significant advancement in the field of neuropsychiatric disorders, demonstrating the potential of EV-based biomarkers in guiding personalized diagnosis and treatment of schizophrenia.

Objective Sex differences have been observed in many aspects of schizophrenia, including cognitive deficits. Despite extensive research into the relationship between metabolic factors and cognitive deficits in schizophrenia, few studies have explored the potential sex difference in their association.Methods We recruited 358 schizophrenia patients and 231 healthy controls. The participants underwent measurements of body mass index (BMI), waist circumference, blood pressure, triglycerides, high-density lipoprotein cholesterol, and fasting blood glucose. Metabolic risk factors included abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. A collection of these metabolic risk factors has been defined as metabolic syndrome. These diagnoses were based on the criteria of the National Cholesterol Education Program’s Adult Treatment Panel III. Cognitive performance was measured using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). A descriptive analysis, difference analysis, and linear regression model were used to identify the metabolic risk factors for cognitive function in schizophrenia.Results Our findings revealed sex differences in the rate of abdominal obesity and hypertension in schizophrenic patients. Additionally, we observed sex differences in the association between metabolic risk factors and cognitive impairment in schizophrenia. Specifically, hyperglycemia was associated with the immediate memory index score of RBANS in male patients, while dyslipidemia was associated with language, attention, delayed memory index scores, and RBANS total score in female patients.Conclusion Our results suggest that sex should be considered when evaluating the impact of metabolic disorders on the cognitive function of schizophrenic patients. Moreover, our study identifies hyperglycemia and dyslipidemia as potential targets for precise treatment by sex stratification, which could benefit the improvement of cognitive impairment in schizophrenic patients.

Schizophrenia is a neurodevelopmental disorder that NMDA receptor (NMDAR) hypofunction appears centrally involved. Schizophrenia typically emerges in adolescence or early adulthood. Electrophysiological and several neurochemical changes have linked the GABA deficits to abnormal behaviors induced by NMDAR hypofunction. However, few studies have systematically investigated the molecular basis of GABA deficits, especially during adolescence. To address this issue, we transiently administrated MK-801 to mice on PND 10, which exhibited schizophrenia-relevant deficits in adolescence. Slice recording showed reduced GABA transmission and PVI⁺ hypofunction, indicating GABAergic hypofunction. Cortical proteomic evaluation combined with analysis of single cell data from the Allen Brain showed that various metabolic processes were enriched in top ranks and differentially altered in excitatory neurons, GABAergic interneurons, and glial cells. Notably, the GABA-related amino acid metabolic process was disturbed in both astrocytes and interneurons, in which we found a downregulated set of GABA-related proteins (GAD65, SYNPR, DBI, GAT3, SN1, and CPT1A). They synergistically regulate GABA synthesis, release, reuptake, and replenishment. Their downregulation indicates impaired GABA cycle and homeostasis regulated by interneuron-astrocyte communication in adolescence. Our findings on molecular basis of GABA deficits could provide potential drug targets of GABAergic rescue for early prevention and intervention.

The brain is susceptible to perturbations of redox balance, affecting neurogenesis and increasing the risks of psychiatric disorders. Thioredoxin-interacting protein (TXNIP) is an endogenous inhibitor of the thioredoxin antioxidant system. Its deletion or inhibition suggests protection for a brain with ischemic stroke or Alzheimer’s disease. Combined with conditional knockout mice and schizophrenia samples, we aimed to investigate the function of TXNIP in healthy brain and psychiatric disorders, which are under-studied. We found TXNIP was remarkedly expressed in the prefrontal cortex (PFC) during healthy mice’s prenatal and early postnatal periods, whereas it rapidly decreased throughout adulthood. During early life, TXNIP was primarily distributed in inhibitory and excitatory neurons. Contrary to the protective effect, the embryonic deletion of TXNIP in GABAergic (gamma-aminobutyric acid-ergic) neurons enhanced oxidative stress in PV⁺ interneurons of aging mice. The deleterious impact was brain region-specific. We also investigated the relationship between TXNIP and schizophrenia. TXNIP was significantly increased in the PFC of schizophrenia-like mice after MK801 administration, followed by oxidative stress. First episode and drug naïve schizophrenia patients with a higher level of plasma TXNIP displayed severer psychiatric symptoms than patients with a low level. We indicated a bidirectional function of TXNIP in the brain, whose high expression in the early stage is protective for development but might be harmful in a later period, associated with mental disorders.