Structural constraints on large-scale brain activity in psychosis associated with chromosome 22q11.2 deletion syndrome

与染色体 22q11.2 缺失综合征相关的精神病中大规模大脑活动的结构限制

• 批准号: 10092219
• 负责人: Eli Cornblath
• 金额: $ 3.31万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10092219
• 关键词: 22q11.2; Address; Architecture; Brain; Brain region; Chromosomes; Clinic; Clinical; Cognitive; Cognitive deficits; Complex; Conflict (Psychology); Coupling; Data; Development; DiGeorge Syndrome; Diffusion Magnetic Resonance Imaging; Disease; Executive Dysfunction; Exhibits; Functional Magnetic Resonance Imaging; Functional disorder; Genetic; Genetic Heterogeneity; Goals; Heterogeneity; Hippocampus (Brain); Human; Individual; Lead; Lesion; Machine Learning; Measures; Membrane; Memory; Memory impairment; Methods; Molecular; Neurons; Occupational; Pathologic; Pathology; Pathway Analysis; Patients; Pattern; Pennsylvania; Performance; Phenotype; Philadelphia; Physicians; Population; Prevalence; Probability; Property; Psychopathology; Psychoses; Reporting; Rest; Role; Sampling; Scanning; Schizophrenia; Science; Scientist; Secondary to; Self-Direction; Severities; Short-Term Memory; Structural defect; Structure; Structure-Activity Relationship; Symptoms; Task Performances; Techniques; Testing; Thalamic structure; Time; University Hospitals; Youth; base; brain abnormalities; brain dysfunction; career; cognitive control; cognitive neuroscience; cohort; early onset; insight; learning network; multimodality; neuroimaging; neuroimaging marker; neuropsychiatric disorder; neuropsychiatry; neurotransmission; novel; preservation; psychotic symptoms; regional difference; selective attention; symptomatology; targeted treatment; therapy development; white matter

Project Summary In the healthy brain, large-scale white matter architecture and local neuronal membrane properties facilitate seamless transitions between cognitive states. Patients with schizophrenia display significant white matter abnormalities with disorganized brain activity. However, the degree to which dysfunctional brain activity in psychosis arises from structural or functional pathology remains unknown. The identification of conclusive neuroimaging findings in this cohort has been challenged by 1) inadequate methods to assess distributed multimodal pathological phenotypes, and 2) the significant pathogenetic heterogeneity in schizophrenia. Practically, the latter challenge can be in part addressed by the study of chromosome 22q11.2 deletion syndrome (22qDS), where the prevalence of clinical schizophrenia is 25-fold higher than that of healthy individuals. The former challenge can be addressed by recent advances in network science and machine learning, which have generated insights about structure-function relationships in the healthy brain. Utilizing these methods to study the spectrum of psychotic symptoms in a population with a defined genetic lesion is a promising direction for investigating psychosis pathophysiology. In this proposal, we describe the development of a novel time-point-based analysis of functional neuroimaging data to study structure-function relationships in a sample of patients with 22qDS currently being seen at the Hospital for the University of Pennsylvania. Using neuroimaging data from a large sample of youths (n = 690) acquired through the Philadelphia Neurodevelopmental Cohort, our preliminary analyses demonstrate previously uncharacterized relationships between brain structure, brain activity, and working memory performance. In this proposal, we aim to 1) compare brain state transition dynamics across the psychotic spectrum of 22qDS, 2) compare structure-function coupling in 22qDS to healthy controls and relate structure-function coupling to psychotic symptom severity, and 3) relate state transition dynamics to working memory performance in 22qDS. A better understanding of the underlying mechanism of psychosis-spectrum symptoms would lay the groundwork for the development of targeted therapies for psychosis. Furthermore, utilizing a cohort with a known genetic lesion provides a unique opportunity to bridge our understanding of molecular mechanisms with neuroimaging biomarkers for psychosis-spectrum symptoms.

项目摘要 在健康的大脑中，大规模的白色物质结构和局部神经元膜特性 促进认知状态之间的无缝转换。精神分裂症患者表现出 明显的白色物质异常，大脑活动紊乱。然而， 精神病中的功能障碍性脑活动源于结构或功能病理学残留 未知在这一队列中确定结论性的神经影像学发现受到了挑战 1）评估分布的多模态病理表型的方法不足，2） 精神分裂症的显著发病异质性。实际上，后一个挑战可能部分是 染色体22q11.2缺失综合征（22 qDS）的研究解决了这一问题， 临床精神分裂症的发病率是健康人的25倍。前一个挑战可能是 网络科学和机器学习的最新进展解决了这个问题， 健康大脑的结构-功能关系的见解。利用这些方法研究 在具有确定遗传损伤的人群中，精神病症状谱是一个有希望的 精神病病理生理学研究方向。 在这个建议中，我们描述了一种新的基于时间点的功能分析的发展， 神经影像学数据，以研究22 qDS患者样本的结构-功能关系 目前正在宾夕法尼亚大学医院接受治疗使用神经成像数据， 通过费城神经发育队列获得的大量青年样本（n = 690）， 我们的初步分析表明，大脑和大脑之间 结构、大脑活动和工作记忆表现。在本提案中，我们的目标是：1）比较 22 qDS精神病谱中的大脑状态转换动力学，2）比较 健康人22 qDS结构-功能耦合及相关结构-功能 耦合到精神病症状的严重程度，和3）将状态转换动力学与工作 22 qDS的内存性能。 更好地理解精神病谱系症状的潜在机制将有助于 为精神病的靶向治疗的发展奠定了基础。此外，利用队列 与已知的遗传病变提供了一个独特的机会，以桥梁我们的理解，分子 神经影像学生物标志物对精神病谱系症状的作用机制。