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Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

ABSTRACT: 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.

SUBMITTER: Xue T

PROVIDER: S-EPMC10907082 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

Xue Ting T Liu Wenxin W Wang Lijun L Shi Yuan Y Hu Ying Y Yang Jing J Li Guiming G Huang Hongna H Cui Donghong D

Brain : a journal of neurology 20240301 3

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 pla ...[more]

PMID: 37816260

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Project description:Besides motor symptoms, many individuals with Parkinson's disease develop cognitive impairment perhaps due to coexisting α-synuclein and Alzheimer's disease pathologies and impaired brain insulin signalling. Discovering biomarkers for cognitive impairment in Parkinson's disease could help clarify the underlying pathogenic processes and improve Parkinson's disease diagnosis and prognosis. This study used plasma samples from 273 participants: 103 Parkinson's disease individuals with normal cognition, 121 Parkinson's disease individuals with cognitive impairment (81 with mild cognitive impairment, 40 with dementia) and 49 age- and sex-matched controls. Plasma extracellular vesicles enriched for neuronal origin were immunocaptured by targeting the L1 cell adhesion molecule, then biomarkers were quantified using immunoassays. α-Synuclein was lower in Parkinson's disease compared to control individuals (P = 0.004) and in cognitively impaired Parkinson's disease individuals compared to Parkinson's disease with normal cognition (P < 0.001) and control (P < 0.001) individuals. Amyloid-β42 did not differ between groups. Phosphorylated tau (T181) was higher in Parkinson's disease than control individuals (P = 0.003) and in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P < 0.001) and controls (P < 0.001). Total tau was not different between groups. Tyrosine-phosphorylated insulin receptor substrate-1 was lower in Parkinson's disease compared to control individuals (P = 0.03) and in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.02) and controls (P = 0.01), and also decreased with increasing motor symptom severity (P = 0.005); serine312-phosphorylated insulin receptor substrate-1 was not different between groups. Mechanistic target of rapamycin was not different between groups, whereas phosphorylated mechanistic target of rapamycin trended lower in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.05). The ratio of α-synuclein to phosphorylated tau181 was lower in Parkinson's disease compared to controls (P = 0.001), in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P < 0.001) and decreased with increasing motor symptom severity (P < 0.001). The ratio of insulin receptor substrate-1 phosphorylated serine312 to insulin receptor substrate-1 phosphorylated tyrosine was higher in Parkinson's disease compared to control individuals (P = 0.01), in cognitively impaired compared to cognitively normal Parkinson's disease individuals (P = 0.02) and increased with increasing motor symptom severity (P = 0.003). α-Synuclein, phosphorylated tau181 and insulin receptor substrate-1 phosphorylated tyrosine contributed in diagnostic classification between groups. These findings suggest that both α-synuclein and tau pathologies and impaired insulin signalling underlie Parkinson's disease with cognitive impairment. Plasma neuronal extracellular vesicles biomarkers may inform cognitive prognosis in Parkinson's disease.

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Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

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Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

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