Connectomes Related to Anxiety and Depression in Adolescents

 描述（由申请人提供）：本提案是为了响应NIH资助机会与人类疾病相关的连接组（U 01）和响应NIMH的优先级/感兴趣的疾病领域情绪和焦虑障碍而提交的。这是马萨诸塞州总医院（MGH）、马萨诸塞州理工学院（MIT）、波士顿大学姆克林医院和圣路易斯华盛顿大学人类连接组项目（HCP）的研究人员共同努力的结果。我们相信，（1）MGH Martinos生物医学成像中心最先进的MRI技术和方法，（2）与HCP积极合作以验证神经成像协调，（3）波士顿范围内经验丰富的专业临床研究人员联盟，以及（4）跨焦虑和抑郁谱的跨诊断焦点可以提供满足资助机会的规范的高质量数据集。我们建议把重点放在一个巨大的临床需求和公共卫生影响的领域：更好地了解青春期精神疾病。我们将焦虑和抑郁作为影响许多青少年的多种传统精神病诊断的疾病，与青少年和年轻人的两个主要死亡原因（自杀和药物滥用相关事故）密切相关，并且被认为经常具有导致终身精神障碍的发展根源。我们的研究方法由两个原则指导：（1）严格遵守HCP协议，以便为科学界开发大规模，集成和不断增长的数据集，以及（2）与NIMH研究领域标准项目（RDoC）的两个结构相一致的研究方法，具体来说：（a）“急性威胁/恐惧”结构，其与特定神经网络中的非典型结构和功能相关，特别是杏仁核、眶额皮质（OFC）和腹内侧前额叶皮质（vmPFC）;和（B）“奖赏预测错误”结构，其与OFC、腹侧纹状体和中脑腹侧被盖区相关。在四年的时间里，我们的目标是（1）操作MRI数据收集和行为表征，与人类连接组项目（HCP）协调和验证;（2）招募和临床和行为表征，225名14-15岁的青少年，有和没有焦虑和/或抑郁症（180名患者，45名对照）;和（3）与参与者一起进行和分析HCP成像。我们假设，杏仁核-眶额皮层回路的激活程度越高，恐惧测量的得分越高，而纹状体-眶额皮层回路的激活程度越低，奖励-错误预期测量的得分越高。我们还将（a）检查神经成像分析是否通过公开可用并可与HCP集成的伪影检测工具和生理混叠校正进行增强，以及（B）创建特定年龄的人类束图谱和用于自动重建上述回路中涉及的白质束的工具，这些工具也将公开提供。

 DESCRIPTION (provided by applicant): This proposal is submitted in response to NIH Funding Opportunity Connectome Related to Human Disease (U01) and in response to NIMH's priority/disease area of interest mood and anxiety disorders. This is a collaborative effort among researchers at the Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), McLean Hospital, Boston University, and the Human Connectome Project (HCP) at Washington University in St. Louis. We believe that the combination of (1) state-of-the art MRI technology and methods at the MGH Martinos Center for Biomedical Imaging, (2) an active collaboration with the HCP to validate neuroimaging harmonization, (3) a Boston-wide consortium of experienced and expert clinical researchers, and (4) a transdiagnostic focus across the anxiety and depression spectrum can deliver a high- quality dataset that meets the specification of the Funding Opportunity. We propose to focus on an area of great clinical need and public health implication: better understanding of psychiatric disorders in adolescence. We target anxiety and depression as diseases that affect many adolescents across multiple traditional psychiatric diagnoses, that are strongly associated with two leading causes of death in adolescents and young adults (suicide and substance-abuse related accidents), and that are understood to frequently have developmental roots leading to lifelong psychiatric disorders. Our research approach is guided by two principles (1) careful adherence to HCP protocols so as to develop large-scale, integrated, and growing data sets available to the scientific community, and (2) a research approach aligned with two constructs from the NIMH Research Domain Criteria Project (RDoC), specifically: (a) the "Acute Threat/Fear" construct, which is associated with atypical structure and function in specific neural networks, especially amygdala, orbitofrontal cortex (OFC), and ventral medial prefrontal cortex (vmPFC); and (b) the "Reward Prediction Error" construct, which is associated with OFC, ventral striatum, and the midbrain ventral tegmental area. Across four years we aim to (1) operationalize MRI data collection and behavioral characterization that is harmonized and validated with the Human Connectome Project (HCP); (2) recruit and characterize clinically and behaviorally, 225 adolescents ages 14-15 with and without anxiety and/or depression (180 patients, 45 controls); and (3) perform and analyze HCP imaging with participants. We hypothesize that greater activation in the amygdala-OFC circuit will correlate with more severe scores on measures of fear, and that lesser activation of the striatal-OFC circuit will correlate with more severe scores on measures of reward-error expectancy. We will also (a) examine whether neuroimaging analyses are enhanced with artifact-detection tools and physiological aliasing correction that are publicly available and could be integrated with the HCP, and (b) create an age-specific human tract atlas and tools for automated reconstruction of white-matter tracts involved in the above circuits, which will also be made publicly available.