多中心多模态磁共振脑影像数据的抑郁症体素水平全脑连接研究

The pathogenesis of depression remains unclear. And therefore, the identification of significant biomarkers from multi-modal magnetic resonance imaging (MRI) data bears great importance to the understanding of depression's pathology, early diagnosis and intervention, even drug development. To analyse functional brain imaging data, we have developed whole brain association study and successfully applied it to a variety of mental disorders in our previous studies and found the altered brain circuits of depression, schizophrenia and autism respectively. In this study, our focus will be on integrating multi-site multi-modal MRI imaging data. First, we will investigate the structural and functional voxel-wise connections of brain network, by building reference networks of both healthy controls and diseased subjects using the MRI data. We will seek out inherent associations between networks built from different modalities using statistical tools, and based on that we will develop statistical procedures that handle multi-site multi-modal brain network association study. Finally, we will interrogate the depression datasets with the voxel-level brain network statistical procedures we have developed. We intend to reveal the neurological loop anomalies in depressive subjects, and systematically link these abnormal patterns to the clinical symptoms, shedding new insights into the pathogenesis of the disease and the fundamental theory of how brain connection anomalies lead to clinical symptoms.

对于抑郁的病理机制至今仍远未清楚，如何从多模态磁共振脑影像数据中找到抑郁症影像学的生物标记对于理解其病理机制、早期诊断以及药物研发都具有重要意义。针对脑功能数据分析，我们在之前的工作中提出全脑关联分析方法并已成功应用到多种精神疾病，找到抑郁症、精神分裂症以及自闭症异常的神经环路。本项目我们将基于多中心多模态磁共振数据，以不同体素之间的结构以及功能上的连接为切入点，首先建立体素水平健康对照与抑郁症患者的全脑体素水平多模态脑连接网络。利用统计分析方法深入挖掘不同模态脑连接之间内在联系，并在此基础上发展多中心多模态的脑连接关联分析统计计算方法。最后，对抑郁症展开体素水平多模态脑连接的关联分析，全面揭示抑郁症患者的神经环路异常模式，并系统地分析异常脑连接与临床症状的关系，帮助我们深入理解抑郁症发病以及临床症状的脑连接基础。

本项目围绕抑郁症的脑功能结构基础这一核心问题，基于大样本的多模态脑影像数据，发展新的数据统计分析方法，发现抑郁症的脑影像学生物标记，并进一步揭示抑郁症疾病的神经环路机制，为临床抑郁的诊断与治疗提供新思路。研究成果主要包括以下四个方面的成果：1）揭示抑郁症全脑体素水平脑功能连接的异常模式，进一步提出抑郁症非奖赏(non-reward)理论，阐释了奖惩环路与情绪调控、记忆环路在抑郁症中作用机制；2）以上述工作为基础，进一步揭示了睡眠问题与抑郁症关系的脑神经环路机制，为临床改善抑郁症患者的睡眠问题提供影像学依据；3）对抑郁症病人脑影像数据进行有向网络建模，为抑郁症大脑中的因果机制提供了一种新的研究方法与思路；4）以抑郁症密切关联的“奖惩”网络为对象，揭示奖惩环路在吸烟、饮酒的作用机制，为发展分别针对酒精与尼古丁成瘾的特异性治疗方法奠定理论基础。项目执行期间，发表了18篇SCI论文，发表在脑疾病与脑科学的知名国际杂志如JAMA Psychiatry (IF=17.4), Molecular Psychiatry(IF=12.3), Neurology (IF=8.77), eLife(IF=7.0)等。其中第一作者或通讯作者论文16篇。培养了三名博士生和两名博士后。