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?

使用一种新颖的结构神经影像评分来预测青少年的精神病风险，该评分可测量偏离规范发展的情况。

• 批准号: 10614565
• 负责人: MARIA JALBRZIKOWSKI
• 金额: $ 76.41万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10614565
• 关键词: 20 year old; Adolescence; Adolescent; Adult; Age; Behavioral; Big Data; Biological; Biological Markers; Brain; Brain region; Childhood; Classification; Clinical; Communities; Complement; Data; Data Set; Development; Diagnosis; Distress; Early Diagnosis; Early Intervention; Early identification; Family history of; Future; Genetic; Growth; Height; Heterogeneity; Image; Individual; Knowledge; MRI Scans; Magnetic Resonance Imaging; Maps; Measurement; Measures; Mental disorders; Methodology; Methods; Modeling; Performance; Persons; Philadelphia; Prevention approach; Primary Prevention; Proxy; Psychopathology; Psychoses; Psychotic Disorders; Research; Risk; Risk Factors; Risk Marker; Sampling; Schizophrenia; Severities; Structure; Symptoms; Testing; Time; Translating; Trauma; Weight; Youth; archived data; brain based; case control; cognitive development; cohort; community setting; cost effective; cost effectiveness; effective intervention; emerging adult; gray matter; improved; improved outcome; indexing; innovation; neural; neurodevelopment; neuroimaging; novel; obstetrical complication; pediatrician; polygenic risk score; portability; prevent; psychosis risk; psychotic symptoms; psychotic-like experiences; risk prediction; synergism

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.

项目概要/摘要 汇聚的证据支持这样的假设：偏离典型的大脑结构发育 发生在精神病发作之前，而对患有精神病的成年人的“大数据”神经影像学研究发现微妙， 在这项提议中，我们将整合有关规范的知识。 患有精神病的成人的结构性神经发育和结构性脑畸变的发现 具有成本效益的基于大脑的青少年精神病风险标记，以提高对高危人群的识别能力。 我们利用大规模精神病结构神经影像学研究的结果来创建“精神病” 神经影像评分”，反映一个人的精神病倾向的累积总结评分。 通过整合大脑结构的关键方面，将精神病神经影像评分传递给年轻人 在目标 1 中，我们将描述精神病的规范发展轨迹。 通过协调规范发展的许多档案数据集（N>5,000，2-30 年）进行神经影像评分 然后我们将评估与总体精神病神经影像学的年龄相关偏差有多大。 分数可将患有精神病谱系症状的青少年与典型发育中的青少年区分开来 费城神经发育队列（N=1209，10-22 岁）在目标 2 中，我们计划研究如何进行。 与年龄相关的总体精神病神经影像评分的偏差越大，则预示着不同的结果 与青少年大脑中类似精神病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）有助于表征这些特征 最后，在目标 3 中，我们建议使用误差测量模型来建立函数。 3T MRI 扫描生成的精神病神经影像评分与生成的精神病神经影像评分之间的关​​系 在青少年社区样本中使用低场 MRI 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学生物指标，最终改善 识别面临最大风险的年轻人，并允许更早、更有效的干预措施。