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以基因-脑-行为的整合思路探究重度抑郁症的疾病机理 —— 多学科交叉数据库的构建与深度数据分析
Alternative TitleIntegrating Multifactorial Interactions from Gene-Brain-Behavior to Investigate the Mechanism of Major Depressive Disorder — — The development of multi-level knowledge base and in-depth data analyses
Thesis Advisor王晶
Degree Grantor中国科学院研究生院
Place of Conferral北京
Degree Discipline心理学
Keyword重度抑郁症 数据库 功能磁共振 元分析 基因优先级排序
Abstract重度抑郁症 (MDD) 是一种异质性极强的复杂精神疾病。在疾病发生发展过程中,涉及众多生物学成分的交互作用。为了揭示MDD 的病理生理机制,多个领域的研究者们从不同角度进行探索,积累了丰富的研究资料。因此,构建涵盖多个学科层面的综合数据库,一方面可以为MDD 的研究提供重要的信息资源。
另一方面,整合不同层面致病因素之间的交互作用,可以构建起疾病知识网络,为MDD 的机制研究提供分析工具。目前,国际上还没有针对MDD 的此类生物医学数据库。为此,本论文开发了重度抑郁症多学科交叉数据库 (MK4MDD) ,它整合了多个学科对于MDD 病理生理机制的研究成果,内容涵盖基因、蛋白、细胞系统与通路、神经生物系统、大脑结构与功能、认知与行为、症状与体征、环境等。此外,MK4MDD 尤其关注不同层面致病因素之间的交互作用。通过对文献的深入阅读与人工提取数据,MK4MDD 目前共包含2,426 个与疾病发生发展有关的生物学指标及5,384 条建立在实证研究基础上的不同疾病指标之间的关系。通过深入的数据挖掘,借助可视化的生物信息工具,使该数据库成为MDD机制研究的综合分析平台。MK4MDD 不仅可以为整个研究过程提供全面的信息支持,同时还可以应用于候选生物学标记以及内表型等特定领域的研究中。
在MK4MDD 数据库的基础上,本论文又进一步对其中22 篇(总计341 位MDD 患者和367 位健康对照被试)涉及愉快体验的功能磁共振成像 (fMRI) 研究进行一系列的激活可能性估计 (ALE) 元分析。结果表明,额叶皮质纹状区构成了MDD 病人愉快体验普遍的神经基础,其活动方式以皮层下和边缘区的活动减弱以及皮层上脑区的活动增强为特征。此外,正性刺激激活MDD 病人的小脑、舌回、海马旁回及梭状回,而金钱奖赏则激活脑岛、楔前叶、楔叶、前额叶皮层及顶下小叶。在金钱奖赏的期待性和消费性阶段,都引起MDD 病人尾状核的活动减弱,而在奖赏的期待阶段,则有额中回和背侧前扣带回的活动增强。这些结果对于揭示快感缺失等MDD 核心症状的神经生物学机制具有重要意义。
最后,基于MK4MDD 提供的候选基因数据集,本论文利用五个基于多数据源的基因排序预测工具对MDD 候选基因进行优先级排序。在17 个训练基因基础上得到13 个具有高优先级的基因,并通过通路富集分析,对这些MDD 核心基因的生物功能进行深入探讨。这些结果将为后续的实验研究及功能信息学分析提供更好的靶点。
综上所述,本论文一方面为研究者提供了MDD 病理生理机制的多学科交叉数据库及综合分析平台,另一方面,通过元分析、候选基因优先级排序及通路富集分析等方法为后续研究提供了可能的理论假设与新的研究候选。同时,本研究所采用的多学科交叉的研究框架与相关方法可应用于其他复杂精神疾病的研究中。
Other AbstractMajor depressive disorder (MDD) is a complex neuropsychiatric syndrome with high heterogeneity. There are different levels of biological components that underlie MDD and interact with each other. To uncover the disease mechanism, large numbers of studies at different levels have been conducted. There is a growing need to integrate data from multiple levels of research into a database to provide a systematic review of current research results. The cross level integration will also help bridge gaps of different research levels for further understanding on MDD. So far, there has been no such effort for MDD. We offer researchers a Multi-level Knowledge base for MDD (MK4MDD) to study the interesting interplay of components in the pathological cascade of MDD, which contains genetic locus, protein and other molecule, cellular system and pathway, neural system, cognition and behavior, symptoms and signs, and environment. MK4MDD contains 2,426 components and 5,384 relationships between components based on reported experimental results obtained by diligent literature reading with manual curation. The powerful search and visualization tools make all data in MK4MDD form a cross-linked network to be applied to a broad range of both basic and applied research, such as on study of endophenotypes and. potential biomarkers.
Based on the functional magnetic resonance imaging (fMRI) studies provided in MK4MDD, we performed a series of activation likelihood estimation (ALE) meta-analyses across 22 fMRI studies that examined pleasure experience in MDD, with a total of 341 MDD patients and 367 healthy controls. We observed several frontostriatal regions that participated in pleasure experience in MDD, the common brain network in MDD was characterized by decreased subcortical and limbic areas activity and an increased cortical response. In addition, the cerebellum, lingual gyrus, parahippocampal gyrus and fusiform gyrus preferentially responded to positive stimuli in MDD, whereas the insula, precuneus, cuneus, PFC and inferior parietal lobule selectively responded to monetary rewards. Our results indicated a reduced caudate response during both monetary anticipation and outcome stages as well as increased activation in the middle frontal gyrus and dorsal anterior cingulate during reward anticipation in MDD. These results have important implications for the neurobiological mechanisms that underlie anhedonia, a core symptom of MDD.
Based on the genetic data provided in MK4MDD, we combined five multiple data sources based tools to prioritize MDD candidate genes in MK4MDD. 13 prioritized candidate genes were detected based on 17 training genes. Furthermore, pathway enrichment analysis was implemented in order to interpret the function of these MDD core genes.
In conclusion, the results in this paper will not only provide researchers with a central knowledge base and analysis platform for MDD etiological and pathophysiological mechanisms research, but also new hypotheses and clues for the etiology mechanism research of MDD. Meanwhile, a novel research framework and related methods established here can be applied to other complex psychiatry disorders.
Subject Area医学心理学
Document Type学位论文
Recommended Citation
GB/T 7714
张伟娜. 以基因-脑-行为的整合思路探究重度抑郁症的疾病机理 —— 多学科交叉数据库的构建与深度数据分析[D]. 北京. 中国科学院研究生院,2013.
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