Extracellular vesicle biomarkers for complement dysfunction in schizophrenia

Ting Xue,Wenxin Liu, Lijun Wang, Yuan Shi, Ying Hu, Jing Yang, Guiming Li,Hongna Huang,Donghong Cui

BRAIN(2024)

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摘要
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-naive 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. Using proteome profiling and machine learning, Xue et al. identify extracellular vesicle-based biomarkers that distinguish schizophrenia from bipolar disorder and major depressive disorder. Personalized discrimination scores based on these biomarkers predict schizophrenia diagnosis and antipsychotic response at the individual level.
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关键词
extracellular vesicle,proteomics,machine learning,schizophrenia,antipsychotic response
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