多模态脑“三网”连接及脑代谢在抗精神病药物疗效机制中的研究

The mechanism of antipsychotic efficacy remains unknown. The abnormalities of connectivity and metabolism in the triple network model, i.e. default mode network (DMN), salience network (SN) and central executive network (CEN), have been proposed to be the potential target for antipsychotic therapy. In the preliminary experiment, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to analyze the risperidone treatment-related alterations of functional and anatomical connectivity attributes of triple network. It demonstrated that increases in functional connectivity between posterior cingulate cortex/precuneus (PCC/PCUN) and medial prefrontal cortex (mPFC), and alterations in functional connectivity of SN, correlated with improvement in positive symptoms after treatment. These results have been published. We also applied 1H-MRS study and found that the baseline N-acetylaspartate (NAA) level in the medial prefrontal cortex of the DMN may predict the alterations in functional connectivity between PCC/PCUN and mPFC. This study aims to investigate how antipsychotic treatment affects the functional and structural connectivity of the triple network, the interfunctional coordination among the triple networks, and the metabolites level of the key brain areas in the triple network, and then improve clinical symptoms and cognitive function. We would recruit drug-naive first-episode schizophrenia patients and treat them with 8-weeks of risperidone monotherapy. We would explore the associations of the triple network connectivity changes, and the metabolism level of the key brain areas including NAA, glutamate and glutamine, with improvement in clinical symptoms and cognitive function. This study aims at shedding new light on understanding antipsychotic treatment mechanism and establishing an objective evaluation system of antipsychotic efficacy based on “triple network connectivity-brain metabolism-symptoms-cognition”.

抗精神病药物疗效机制尚未明确。脑“三网”模型（默认网络、突显网络和中央执行网络）连接及代谢异常或可成为药物治疗靶点。本课题预实验联合fMRI与DTI构建“三网”功能及结构连接，发现利培酮治疗后患者默认网络后扣带回与前额叶皮质间连接变化，以及突显网络岛叶连接改变与阳性症状改善相关（相关结果均已发表）；联合1H-MRS发现默认网络前额叶皮质基线N-乙酰天门冬氨酸（NAA）水平可预测治疗后前额叶皮质与后扣带回间功能连接变化。本研究拟进一步调查药物治疗如何影响“三网”功能及结构连接，各网络间的功能协调作用，以及“三网”重要脑区代谢水平，并最终改善患者症状及认知功能，遂纳入首发精神分裂症患者并予8周利培酮治疗，分析“三网”连接及重要脑区NAA、谷氨酸/谷氨酰胺等脑化学物变化与症状及认知改善的关系，为理解药物疗效机制及建立“三网连接-脑代谢-症状-认知”疗效评价体系提供新思路。

抗精神病药物疗效机制尚未明确。脑“三网”模型（默认网络、突显网络和中央执行网络）连接及代谢异常或可成为药物治疗靶点。本项目在执行期内，采集了首发未治疗精神分裂症患者治疗前、后，以及健康对照多模态MRI数据、人口学资料、症状、认知评估数据，其中对精神分裂症患者采集了利培酮药物干预前后多模态脑影像数据。本项目联合fMRI与DTI构建“三网”功能及结构连接，发现了“三网”中的默认网络、突显网络的功能及结构连接治疗后发生变化，且这些影像学改变能预测患者阳性症状改善程度；联合1H-MRS发现默认网络前额叶皮质基线N-乙酰天门冬氨酸（NAA）水平可预测治疗后前额叶皮质与后扣带回间功能连接变化。通过进一步利用脑网络最新构建技术及深入挖掘数据，本项目发现“三网”中默认网络功能与结构连接间的耦合关系在治疗后发生改变，耦合变化背后有结构连接、功能连接基础，且其变化与患者治疗后阳性症状、阴性症状改善相关。在突显网络中，岛叶和前扣带皮层是两个重要的突显网络成分，本项目研究了精神分裂症患者岛叶分区动态功能连接(dFC)的异常模式以及抗精神病药物对这些连接的影响，发现：基线时，与健康对照组相比，患者岛叶亚区与楔前叶、辅助运动区和颞叶皮层之间的dFC差异降低，岛叶亚区与顶叶皮层之间的dFC差异增加；治疗后，异常连接的dFC归于正常，阳性症状明显改善，这些发现强调了精神分裂症患者岛叶细分亚区功能连接的异常模式，并提示这些异常可能在抗精神病药物治疗后得到改善。上述“三网”连接结果推动了精神分裂症病理机制及抗精神病药理机制研究，初步揭示了有关抗精神病药物治疗的神经机制，认为脑“三网”连接异常或可成为药物治疗靶点。在项目执行期内，项目负责人及团队已将项目研究结果发表SCI论文5篇，其中IF值10以上的论文2篇；培养了研究生2名；脑网络构建技术获批国家发明专利1项。

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