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功能性网络连接中断作为精神分裂症治疗抵抗的生物标志物。

Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia.

机构信息

School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand.

Department of Psychiatry, University of Cambridge, Cambridge and Peterborough Foundation NHS Trust, Herchel Smith Buidling for Brain & Mind Sciences, Forvie Site, Robinson Way, Cambridge CB2 0SZ, United Kingdom; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom.

出版信息

Schizophr Res. 2018 May;195:160-167. doi: 10.1016/j.schres.2017.10.015. Epub 2017 Oct 16.


DOI:10.1016/j.schres.2017.10.015
PMID:29042073
Abstract

Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalization Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc t-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis.

摘要

精神分裂症可能是由神经递质(如多巴胺和乙酰胆碱)调节的功能连接中断引起的。这些神经递质的调节作用可能解释了抗精神病药如何减轻精神分裂症的症状,并解释了在临床实践中观察到的抗精神病药反应的变异性。基于抗精神病药的假定机制和精神分裂症连接中断的证据,我们假设使用基于网络的统计方法评估的功能网络连接在精神分裂症的治疗反应亚型和健康对照之间会存在差异。从 17 名健康对照者以及对一线非典型抗精神病药反应良好的精神分裂症患者(一线反应者;FLR,n=18)、至少两次抗精神病药治疗失败但对氯氮平有反应(治疗抵抗性精神分裂症;TRS,n=18)或至少两次抗精神病药和一次氯氮平治疗失败(超治疗抵抗性精神分裂症;UTR,n=16)中获得静息态功能磁共振成像数据。使用高级归一化工具包和 BrainWavelet 工具箱对数据进行预处理。使用 Matlab 中的网络统计工具箱评估网络连接。方差分析显示组间功能连接存在显著差异,这种差异从小脑和顶叶区域延伸到额叶皮层(p<0.05)。事后 t 检验显示 UTR 患者的网络连接较弱,与健康对照组相比,但组间无其他差异。结果表明 UTR 患者与健康对照组之间的功能连接存在明显差异。未来的工作必须确定这些变化是否发生在治疗开始之前,以及它们是否可用于预测首发精神病期间对抗精神病药的耐药性。

相似文献

[1]
Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia.

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[2]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
An artificial intelligence-derived metabolic network predicts psychosis in Alzheimer's disease.

Brain Commun. 2025-4-25

[2]
Distinct structural deficits in treatment-resistant schizophrenia and their putative neurotransmitter basis: a source-based morphometry analysis.

Neuropsychopharmacology. 2025-5-28

[3]
Consistent frontal-limbic-occipital connections in distinguishing treatment-resistant and non-treatment-resistant schizophrenia.

Neuroimage Clin. 2025

[4]
Functional Connectivity Biomarkers in Schizophrenia.

Adv Neurobiol. 2024

[5]
Altered resting-state functional connectivity in a thalamo-cortico-cerebellar network in patients with schizophrenia.

Sci Rep. 2024-11-1

[6]
Schizophrenia and magnetic resonance imaging research: A scientometric analysis during 2014 to 2023.

Medicine (Baltimore). 2024-10-25

[7]
Aberrant connectivity in the hippocampus, bilateral insula and temporal poles precedes treatment resistance in first-episode psychosis: a prospective resting-state functional magnetic resonance imaging study with connectivity concordance mapping.

Brain Commun. 2024-5-4

[8]
A systematic review of neuroimaging studies of clozapine-resistant schizophrenia.

Schizophrenia (Heidelb). 2023-9-26

[9]
A Functional Connectome-Based Neural Signature for Individualized Prediction of Antipsychotic Response in First-Episode Psychosis.

Am J Psychiatry. 2023-11-1

[10]
Resting-state functional MRI in treatment-resistant schizophrenia.

Front Neuroimaging. 2023-4-6

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