Neurodevelopmental variation of intrinsic functional connectivity and its relationship to psychosis risk and gene expression

项目摘要/摘要 更好地了解精神病是如何在童年和青春期出现的将会有所帮助 美国确定疾病的原因和治疗目标，以促进早期发现和干预。主 K01的目标是1)确定青少年静息状态功能连通性的年龄相关变异，以及 这种变异如何与精神病谱系症状相关，2)决定这些精神病的程度- 临床高危(CHR)患精神病的求助青少年有相关特征。 确定导致静息状态固有神经发育典型和非典型神经发育的遗传因素 功能连接。AIM 1将结合档案静息状态功能磁共振成像 (RsfMRI)数据来自费城神经发育队列(PNC，N=907)和高度兼容的 规范发展的纵向研究(露娜队列，N=223)。图论测量将被计算 从rsfmri数据，并被用来确定精神病谱系年轻人偏离的程度 典型发展。对于目标2，我将收集有关CHR青年(N=40)和典型发育中的rsfMRI数据 对照(N=50)，纵向，目的是确定年龄相关的改变在多大程度上介于- 和网络内连通性出现在CHR青年中。精神病的阳性症状，心理社会 功能和神经认知测量将在基线评估和后续行动中收集 评估。我将探索内在功能连接如何预测精神病症状的增加， 在这个队列中的功能和/或认知。在目标3中，来自PNC和露娜队列的遗传信息将 用于确定精神分裂症风险和神经发育的预期基因表达谱 基因与功能间和功能内的连通性的发展有关。我的训练计划将 关注1)整合基因组和神经影像数据以了解精神疾病的发展 障碍，2)对高维数据集进行分析，以确定障碍的机制和潜在风险 精神病的因素，以及3)获得发育神经科学的专业知识，并将这些知识应用于 精神病的神经发育模型。这项研究的结果将帮助我们识别机械过程 并确定与年龄相关的网络连接性变化的程度 在精神病发作之前完好无损或已经存在。通过培训计划，我将成为一名专家 在建模高维数据和识别青春期大脑的变化方面，我将使用这些 提高对精神病的预测，并确定干预的关键时间段。

Project Summary/Abstract Gaining a better understanding of how psychosis emerges during childhood and adolescence will help us identify causes of the illness and treatment targets to facilitate early detection and intervention. The main goals of this K01 are to 1) identify age-associated variation in resting-state functional connectivity in youth, and how that variation relates to psychosis spectrum symptoms, 2) determine to what extent these psychosis- related features are present in help-seeking youth at clinical high risk (CHR) for developing psychosis and 3) identify genetic factors that contribute to typical and atypical neurodevelopment of resting-state intrinsic functional connectivity. Aim 1 will combine archival resting-state functional magnetic resonance imaging (rsfMRI) data from the Philadelphia Neurodevelopmental Cohort (PNC, N=907) and a highly compatible longitudinal study of normative development (Luna cohort, N=223). Graph theory measures will be calculated from the rsfMRI data and be used to determine the extent to which psychosis spectrum youth deviate from typical development. For Aim 2, I will collect rsfMRI data on CHR youth (N=40) and typically developing controls (N=50), longitudinally, with a goal to determine to what extent age-associated alterations in between- and within- network connectivity are present in CHR youth. Positive symptoms of psychosis, psychosocial functioning, and neurocognitive measures will be collected at the baseline assessment and follow-up assessments. I will explore how intrinsic functional connectivity predicts increases in psychotic symptoms, functioning and/or cognition in this cohort. In Aim 3, genetic information from the PNC and Luna cohort will used to determine how expected gene expression profiles of schizophrenia risk and neurodevelopmental genes are associated with development of between- and within- functional connectivity. My training plan will focus on 1) integrating genomic and neuroimaging data to understand the development of psychiatric disorders, 2) conducting analyses of high dimensional data sets to identify mechanisms of and potential risk factors for psychosis, and 3) acquiring expertise in developmental neuroscience and apply this knowledge to neurodevelopmental models of psychosis. Results from this study will help us identify mechanistic processes of brain development and function and identify to what extent age-associated changes in network-connectivity are intact or already present prior to the onset of psychosis. Through the training plan, I will become an expert in modeling high dimensional data and identifying changes in the brain during adolescence, which I will use to improve the prediction of psychosis and identify critical time periods for intervention.