Temporal connectomics for infant brain: neurodevelopment modulated by pathology

婴儿大脑的颞连接组学：病理学调节的神经发育

• 批准号: 9247655
• 负责人: Ragini Verma
• 金额: $ 61.67万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2021-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9247655
• 关键词: Affect; Age; Age-Months; Anisotropy; Architecture; Attenuated; Autistic Disorder; Base of the Brain; Biological Markers; Brain; Brain imaging; Child; Chronology; Clinical; Collection; Communication; Data; Data Set; Development; Developmental Delay Disorders; Diagnosis; Diagnostic; Diffuse; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Early Intervention; Evolution; Family; Fiber; Funding; Gender; General Population; Geometry; Goals; Heritability; Image; Individual; Infant; Length; Life; Longitudinal prospective study; Machine Learning; Maps; Measures; Methods; Modeling; Neurodevelopmental Disorder; Outcome; Pathology; Pattern; Phenotype; Population; Recruitment Activity; Resolution; Risk; Sample Size; Sex Characteristics; Siblings; Specific qualifier value; Structure; Symptoms; Therapeutic Intervention; Time; Training; United States National Institutes of Health; Vertebral column; autism spectrum disorder; base; boys; cohesion; comparative; connectome; design; disorder risk; high risk; high risk infant; high risk population; imaging biomarker; imaging study; indexing; insight; learning strategy; longitudinal analysis; neurodevelopment; neuroimaging; novel; predictive marker; prospective; social communication; spatiotemporal; white matter

Abstract Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder affecting more than 1% of children (and almost 2% of boys), with those born in a high risk (HR) family with a child diagnosed with ASD having a ~20 fold greater risk than the general population. Although it can only be reliably diagnosed after the second year of life, ASD originates from a neurodevelopmental mechanism, with symptoms emerging as early as 6 months of age. Prospective large-scale longitudinal neuroimaging studies like the Infant Brain Imaging Study (IBIS), of those born into a high-risk (HR) family, are extremely valuable as they facilitate discovery of the earliest manifestations of ASD. The overarching goal of this proposal is a comprehensive comparative longitudinal analysis of brain organization of high- and low-risk populations, by using IBIS diffusion MRI (dMRI) data collected at 3 time points in the first 2 years of life, to elucidate the earliest manifestations of ASD and disorder trajectory. In addition, we aim to create a biomarker of ASD risk from brain connectivity features and their developmental trajectories, and to understand the brain bases of familial risk (independent of ASD). dMRI provides an insight into the structural organization of the brain represented as a connectome. “Miswiring” of the structural connectome can manifest as neuro-immaturity of WM and changes in network structures, that is, subnetworks (collection of strongly inter-connected regions associated with a distinct communication pattern), and the communication backbone (overall architecture of communication between subnetworks). Both connectivity and WM quality can be compromised in ASD compared to controls, suggesting a “miswired” connectome. Studying ASD related early developmental changes in connectivity requires design of novel analysis methods based on “longitudinal” connectomic features that are 4D features that incorporate their temporal evolution over development, culminating in the creation of novel imaging-based biomarkers. In Aim 1, we will create a new method of extracting longitudinal fiber tracts to identify and analyze differences between the developmental tract trajectories in LR-, HR- and HR+ subjects using geometry and quality features derived from the fiber bundles, to identify differences in neuro-immaturity. In aim 2, we will design novel methods to extract longitudinal network structures like structurally-cohesive and functionally-defined subnetworks and the global communication backbone, and investigate developmental differences modulated by familial risk and gender. Finally, in Aim 3 we will use the tract and network features extracted from Aims 1 and 2 to develop imaging based markers that will assist with early ASD prediction, identifying siblings who could gain from an early therapeutic intervention and provide an index of development in the form of brain connectivity “maturational age” to help characterize developmental delays and brain patterns corresponding to the same. The longitudinal analysis methods developed in the proposal will be generalizable to other clinical populations that can gain from longitudinal analysis spanning several time points.

抽象的 自闭症谱系障碍 (ASD) 是一种高度遗传性的神经发育障碍，影响超过 1% 的人 儿童（以及近 2% 的男孩），其中出生于高风险 (HR) 家庭且孩子被诊断患有自闭症谱系障碍 (ASD) 的儿童 其风险比一般人群高约 20 倍，尽管只有在确诊后才能可靠诊断。 在生命的第二年，自闭症谱系障碍（ASD）源于神经发育机制，症状很早就出现 6 个月大时进行前瞻性大规模纵向神经影像研究，例如婴儿脑成像。 针对出生在高风险 (HR) 家庭的人的研究 (IBIS) 非常有价值，因为它们有助于发现 ASD 的最早表现 该提案的总体目标是进行全面的比较。 使用 IBIS 扩散 MRI (dMRI) 对高危人群和低危人群的脑组织进行纵向分析 在生命最初 2 年的 3 个时间点收集数据，以阐明自闭症谱系障碍 (ASD) 的最早表现 此外，我们的目标是根据大脑连接特征创建 ASD 风险的生物标志物。 他们的发育轨迹，并了解家族风险的大脑基础（独立于 ASD）。 的“误接线” 结构连接组可以表现为WM的神经不成熟和网络结构的变化，即 子网络（与不同通信模式相关的强互连区域的集合）， 和通信主干（子网之间通信的总体架构）。 与对照相比，ASD 中的连接性和 WM 质量可能会受到影响，这表明“接线错误” 研究 ASD 相关的早期发育变化需要新颖的设计。 基于“纵向”连接体特征的分析方法，这些特征是结合了它们的 4D 特征 发展过程中的时间演化，最终创造出基于成像的新型生物标志物。 1、我们将创建一种提取纵向纤维束的新方法来识别和分析差异 使用几何和质量在 LR-、HR- 和 HR+ 受试者的发育束轨迹之间进行比较 源自纤维束的特征，以识别神经不成熟的差异 在目标 2 中，我们将设计。 提取纵向网络结构（如结构内聚和功能定义）的新方法 子网络和全球通信骨干网，并调查调制的发育差异 最后，在目标 3 中，我们将使用从目标 1 中提取的区域和网络特征。 2 开发基于成像的标记物，帮助早期 ASD 预测，识别患有自闭症谱系障碍 (ASD) 的兄弟姐妹 可以从早期治疗干预中获益，并以大脑的形式提供发育指数 连接性“成熟年龄”有助于表征发育迟缓和对应的大脑模式 该提案中开发的纵向分析方法将推广到其他临床。 可以从跨越多个时间点的纵向分析中获益的人群。