Prediction of treatment response and course of disease in schizophrenia using EEG high frequency oscillations as a correlate of glutamatergic neurotransmission

使用脑电图高频振荡作为谷氨酸能神经传递的相关性来预测精神分裂症的治疗反应和病程

• 批准号: 442515185
• 负责人: Privatdozent Dr. Gregor Leicht
• 金额: --
• 依托单位: Klinik und Poliklinik für Psychiatrie und Psychotherapie
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2020
• 资助国家: 德国
• 起止时间: 2019-12-31 至 无数据
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/442515185?language=en
• 关键词: Prediction; treatment; response; course; disease

Recently, an imbalance between excitation and inhibition (E/I-balance) towards elevated excitability has been implicated in the pathophysiology of schizophrenia. The E/I-balance is thought to be crucially dependent on a circuit mechanism involving inhibitory GABAergic and excitatory glutamatergic signaling. Critical evidence supporting this assumption comes from animal models, genetic work, postmortem studies, neuroimaging studies in patients, glutamatergic treatment effects and pharmacological models of schizophrenia. The applicant’s previous electroencephalography (EEG) work on altered high-frequency oscillatory activity (reduction of the auditory evoked gamma-band response) in different stages of schizophrenia also contributes to this evidence, as the microcircuit involving parvalbumin-positive GABAergic interneurons and glutamatergic pyramidal cells plays a crucial role for the generation of gamma oscillations. The reversal of gamma oscillation alterations has been shown to be predictive of antipsychotic activity with a unique profile for clozapine in animal work. However, to date, no study has comprehensively addressed the relationship between these findings in a single cohort of schizophrenia patients by combining magnetic resonance spectroscopy (MRS) measurements of GABA/glutamate concentrations utilizing a high MR field strength of 7-Tesla, EEG measurements of task evoked as well as ongoing resting state gamma oscillations and effects of pharmacological modulation with clozapine on these measures. Thus, the present proposal aims to integrate findings from MRS studies on glutamate and GABA concentrations, from EEG studies on high frequency gamma oscillations and about glutamatergic effects of clozapine treatment in schizophrenia patients. Using MR field strength of 7-Tesla at the Melbourne Brain Centre will improve the accuracy of MRS in examining the metabolites glutamate, GABA and glutathione compared to previous studies. The proposal wants to contribute to a better understanding of alterations of the E/I-imbalance in the pathophysiology of schizophrenia. For instance, linking EEG gamma measures and in vivo measures of glutamate and GABA of identical subjects is supposed to further reveal the nature of the apparent contradiction between increased resting state and diminished task evoked gamma oscillatory activity in schizophrenia. Furthermore, the proposal wants to contribute to the development of new biological markers for the prediction of treatment response to glutamatergic treatment strategies. If directly related to in vivo measures of glutamate and GABA, EEG high frequency oscillations as a correlate of neurotransmission might be a cheap and easily applicable alternative compared to MRS in future clinical routine. Finally, the proposed research aims to examine the applicability of resting state gamma network alterations in the prediction of the course of psychosis.

最近，兴奋和抑制（E/I-平衡）之间的不平衡对兴奋性升高已牵连在精神分裂症的病理生理。E/I平衡被认为是至关重要的依赖于涉及抑制性GABA能和兴奋性谷氨酸能信号传导的回路机制。支持这一假设的关键证据来自动物模型、遗传工作、尸检研究、患者神经影像学研究、精神分裂症的药物治疗效果和药理学模型。申请人先前关于精神分裂症不同阶段中改变的高频振荡活动（听觉诱发的γ-频带响应的减少）的脑电图（EEG）工作也有助于该证据，因为涉及小清蛋白阳性GABA能中间神经元和多巴胺能锥体细胞的微回路对于γ振荡的产生起关键作用。γ振荡改变的逆转已被证明是抗精神病药物活性的预测，在动物实验中氯氮平具有独特的特征。然而，到目前为止，没有研究已经全面解决了这些结果之间的关系，在一个单一的队列精神分裂症患者结合磁共振波谱（MRS）测量GABA/谷氨酸浓度利用高MR场强度的7特斯拉，脑电图测量任务诱发以及正在进行的静息状态γ振荡和药物调制与氯氮平对这些措施的影响。因此，本提案的目的是整合从MRS研究谷氨酸和GABA浓度的结果，从脑电图研究高频伽马振荡和氯氮平治疗精神分裂症患者的神经递质的影响。与以前的研究相比，在墨尔本脑中心使用7特斯拉的MR场强将提高MRS检查代谢物谷氨酸、GABA和谷胱甘肽的准确性。该提案希望有助于更好地了解精神分裂症病理生理学中E/I失衡的改变。例如，链接EEG伽马措施和体内措施的谷氨酸和GABA的相同的主题，应该进一步揭示的性质之间的明显矛盾增加的静息状态和减少任务诱发的伽马振荡活动的精神分裂症。此外，该提案希望有助于开发新的生物标志物，用于预测对药物治疗策略的治疗反应。如果直接相关的谷氨酸和GABA的体内测量，脑电图高频振荡作为神经传递的相关性可能是一个便宜的，易于应用的替代相比，MRS在未来的临床常规。最后，拟议的研究旨在研究静息状态伽马网络改变在预测精神病病程中的适用性。