Predicting psychosis risk in youth using a novel structural neuroimaging score that measures deviation from normative development. Can we bring it to communities using portable, low-field MRI?

项目摘要/摘要 越来越多的证据支持这样一种假设，即偏离典型的大脑结构发育 发生在精神病发作之前，而对成年精神病患者的大数据神经成像研究发现微妙， 大脑中广泛存在的灰质紊乱。在本提案中，我们将协同使用有关规范的知识 成人精神病患者的结构性神经发育和结构性脑异常的发现 具有成本效益的基于大脑的青年精神病风险标记物。为了更好地识别那些风险最高的人， 我们利用对精神病的大规模结构性神经成像研究的结果来创造一种 神经成像得分‘，反映一个人的精神错乱倾向的累积总结得分。我们首先的目标是 通过整合结构脑的关键方面将精神病神经成像评分传递给年轻人 发展。在目标1中，我们将描述精神病的标准发展轨迹 通过协调规范发展的许多档案数据集进行神经成像评分(N&GT；5000，2-30年 旧的)。然后，我们将评估与年龄相关的更大偏差如何与总体精神病神经成像 SCORE将患有精神病谱系症状的青年与典型的发育期青年区分开来 费城神经发育队列(N=1209，10-22岁)。在目标2中，我们计划研究如何 与精神病综合神经影像评分的年龄相关偏差越大，预测就越明显 青春期大脑和青春期精神病样经历相关的发展轨迹 认知发展研究(N=11,875)。我们还将评估已知精神病风险的程度 因素(例如，精神病家族史、产科并发症、创伤)有助于描述这些 轨迹。最后，在目标3中，我们建议使用误差测量建模来建立函数 3T MRI神经影像评分与精神分裂症神经影像评分的关系 在一个社区的年轻人样本中使用低场磁共振扫描。这项研究的结果将使我们能够创造更多 负担得起的、临床上可获得的严重精神病理生物学指标，最终改善 确定处于最大风险的年轻人，并允许进行更早、更有效的干预。

Project Summary/Abstract Converging lines of evidence support the hypothesis that deviations from typical brain structure development take place prior to psychosis onset, while ‘big data’ neuroimaging studies of adults with psychosis find subtle, widespread gray matter disruptions in the brain. In this proposal, we will synergize knowledge about normative structural neurodevelopment and findings of structural brain aberrations in adults with psychosis to develop cost-effective brain-based markers of psychosis risk in youth. To improve identification of those at greatest risk, we leverage results from large-scale structural neuroimaging studies of psychosis to create a ‘Psychosis Neuroimaging Score’, a cumulative summary score that reflects one’s psychosis liability. We first aim to transport the Psychosis Neuroimaging Score to youth by incorporating crucial aspects of structural brain development. In Aim 1, we will characterize the normative developmental trajectory of the Psychosis Neuroimaging Score by harmonizing many archival datasets of normative development (N>5,000, 2-30 years old). We will then evaluate how greater age-associated deviation from the aggregate Psychosis Neuroimaging Score differentiates youth with psychosis spectrum symptoms from typically developing youth in the Philadelphia Neurodevelopmental Cohort (N=1209, 10-22 years old). In Aim 2, we plan to examine how greater age-associated deviation from the aggregate Psychosis Neuroimaging Score predicts distinct developmental trajectories associated with psychotic-like experiences in youth from the Adolescent Brain and Cognitive Development Study (N=11,875). We will also assess the extent to which known psychosis risk factors (e.g., family history of psychosis, obstetric complications, trauma) contribute to characterization of these trajectories. Finally, in Aim 3, we propose to use measurement-in-error modeling to establish a functional relationship between Psychosis Neuroimaging scores generated from 3T MRI scans and those generated using low-field MRI scans in a community sample of youth. Results from this study will allow us to create more affordable, clinically accessible biological indicators of severe psychopathology, ultimately improving identification of young people at greatest risk and allowing earlier, more effective interventions.