Dynamic changes of the structural and functional brain connectome in anorexia nervosa (revision)

神经性厌食症脑连接组结构和功能的动态变化（修订版）

• 批准号: 320247098
• 负责人: Professor Dr. Stefan Ehrlich, Ph.D.
• 金额: --
• 依托单位: Bereich Psychosoziale Medizin und Entwicklungsneurowissenschaften
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/320247098?language=en
• 关键词: Dynamic; changes; structural; functional; brain

Anorexia nervosa (AN) is a life-threatening eating disorder characterized by severe emaciation. In acute AN (acAN), reduction of brain mass is often readily visible in brain scans and several structural magnetic resonance imaging (sMRI) studies (including our own) have documented massive but reversible decreases in gray matter (GM) volume and thickness. These processes, which are accompanied by dramatic hormonal and metabolic changes are incredibly dynamic and unparalleled in psychiatry. Therefore, AN may be a valuable model disorder to study the brain's plasticity, i.e. changes in structural and functional neural connections (i.e. the connectome). Insights will contribute to the understanding of basic neural mechanisms and shed light on this enigmatic illness.The biological mechanisms underlying these (pseudo-)atrophic changes in AN remain elusive. For example, it is unclear whether they may be related to changes in white matter (WM), changes in the functional connectome (correlations between regional brain signal fluctuations measured using functional MRI (fMRI)) and how they might be linked to known cognitive impairments, clinical symptoms and weight restoration. We seek to elucidate (1) the specific patterns of structural brain alterations, specifically WM integrity and connectivity changes, associated with acAN using a combination of sMRI, diffusion tensor imaging (DTI) and modern mathematical and network theory analysis approaches. Critically, by following patients longitudinally during weight restoration therapy, we will assess the speed and degree of normalization. Second, we aim (2) to characterize changes in the functional connectome using highly time-resolved fMRI sequences to study static and dynamic resting state connectivity (i.e. the "chronnectome"). Ultimately, we aim (3) to understand the biological mechanisms underlying changes in the structural and functional brain connectome in the different states of AN. Using new myelin-sensitive MR sequences (mcDESPOT, quantitative T1 mapping) in addition to DTI and cross-modal analysis, we will study associations between GM- and WM-connectivity as well as local myelin changes more directly. We will also examine whether structural anomalies or changes of local fMRI signal patterns (e.g. amplitude of frequency fluctuations) are associated with abnormal static/dynamic functional connectivity and the changing hormonal parameters. Modern bioinformatics modelling techniques will reveal interdependencies between hormones and connectome characteristics and will identify predictors of weight gain and improvements in cognitive functioning. Using state of the art neuroimaging methodologies to triangulate the mechanisms underlying changes in the structural and functional connectome in AN will inform us not only about basic principles of the brain including how it is affected by energy depletion/repletion, but also has potential of revealing new targets for the development of better treatments for AN.

神经性厌食症（AN）是一种危及生命的饮食失调，其特征是严重消瘦。在急性AN （acAN）中，脑质量的减少通常在脑部扫描中很容易看到，一些结构磁共振成像（sMRI）研究（包括我们自己的研究）已经记录了灰质（GM）体积和厚度的大量但可逆的减少。这些过程伴随着戏剧性的荷尔蒙和代谢变化，在精神病学中是难以置信的动态和无与伦比的。因此，AN可能是研究大脑可塑性的一个有价值的模型障碍，即结构和功能神经连接（即连接组）的变化。洞察将有助于理解基本的神经机制，并阐明这种神秘的疾病。这些（伪）萎缩性变化背后的生物学机制仍然难以捉摸。例如，尚不清楚它们是否可能与白质（WM）的变化、功能连接组的变化（使用功能磁共振成像（fMRI）测量的区域大脑信号波动之间的相关性）有关，以及它们如何与已知的认知障碍、临床症状和体重恢复有关。我们试图通过sMRI、扩散张量成像（DTI）和现代数学和网络理论分析方法的结合来阐明(1)与acAN相关的大脑结构改变的具体模式，特别是WM完整性和连通性的变化。关键的是，在体重恢复治疗期间，通过纵向跟踪患者，我们将评估恢复正常的速度和程度。其次，我们的目标是(2)使用高时间分辨率的fMRI序列来表征功能连接组的变化，以研究静态和动态静息状态连接（即“时间连接组”）。最终，我们的目标是(3)了解不同AN状态下脑连接组结构和功能变化的生物学机制。利用新的髓磷脂敏感MR序列（mcDESPOT，定量T1映射）以及DTI和跨模态分析，我们将更直接地研究GM-和wm -连通性以及局部髓磷脂变化之间的关系。我们还将研究结构异常或局部fMRI信号模式的变化（例如频率波动幅度）是否与异常的静态/动态功能连接和激素参数的变化有关。现代生物信息学建模技术将揭示激素和连接体特征之间的相互依赖关系，并将确定体重增加和认知功能改善的预测因素。利用最先进的神经成像方法对AN的结构和功能连接组变化的机制进行三角测量，不仅可以告诉我们大脑的基本原理，包括它是如何受到能量消耗/补给的影响的，而且还具有揭示开发更好治疗AN的新靶点的潜力。