Mapping lifespan trajectories of white matter in autism and improving reproducibility through shared diffusion MRI data

通过共享扩散 MRI 数据绘制自闭症患者白质的寿命轨迹并提高可重复性

• 批准号: 10648969
• 负责人: Janice Hau
• 金额: $ 18.81万
• 依托单位: SAN DIEGO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10648969
• 关键词: Acceleration; Adolescence; Adolescent; Adult; Affect; Age; Aging; Anisotropy; Behavioral; Brain; Brain imaging; Childhood; Cognitive; Communities; Corpus Callosum; Cross-Sectional Studies; Data; Data Set; Databases; Development; Diagnostic; Diffusion Magnetic Resonance Imaging; Dimensions; Functional disorder; Growth; Human; Image; Individual; Joints; Knowledge; Life; Link; Location; Longevity; Maps; Measures; Methodology; Methods; Modeling; National Institute of Mental Health; Neural Pathways; Neuroanatomy; Outcome; Participant; Pattern; Policy Developments; Process; Protocols documentation; Quality Control; Reproducibility; Research; Resource Sharing; Resources; Sample Size; Sampling; Scanning; Sequence Analysis; Severities; Site; Specificity; Standardization; Structure; Symptoms; Techniques; Time; Uncertainty; Work; age effect; age group; aged; autism spectrum disorder; cognitive ability; cognitive development; connectome; data archive; data exchange; data harmonization; data resource; early childhood; experience; improved; in vivo; indexing; individuals with autism spectrum disorder; insight; multimodality; neural; neural circuit; neurodevelopment; neuroimaging; rate of change; sex; shared database; social; social communication impairment; spatiotemporal; thalamocortical tract; therapy development; white matter

Abstract Autism spectrum disorder (ASD) affects many aspects of development (e.g., social, cognitive) throughout life, and altered neurodevelopment in early life is considered an important feature of ASD pathophysiology. There is, however, considerable uncertainty regarding the neuromaturational trajectory of ASD beyond early childhood—into the transitional periods of adolescence and aging. White matter is necessary for the development of specialized brain circuits. White matter tracts follow a protracted developmental trajectory, peaking in the third to fourth decades of life, and, critically, their maturation may be differentially altered in ASD. Diffusion MRI (dMRI) is currently the most effective non-invasive technique for probing white matter in vivo. Studies of white matter using dMRI in ASD in later childhood to adulthood, however, have provided inconsistent findings. A major hindrance to reproducible white matter results in ASD is low statistical power. Over the last decade, extensive shared multimodal ASD datasets have been made available through large initiatives such as the Autism Brain Imaging Data Exchange, and National Database for Autism Research. The dMRI data from these resources, however, are currently underutilized. In addition, large consortia studies (e.g., the Human Connectome Project) have made high-quality dMRI data available in healthy individuals across the lifespan. Recent methodological advances in data harmonization of dMRI data allow mitigating differences across imaging sites and protocols. This project aims to leverage available multi-site dMRI data (>2600 participants; >600 ASD, >2000 TD; from up to 17 sites) to perform joint large-scale analyses that will elucidate the spatiotemporal pattern of white matter atypicalities in ASD across the lifespan (age 2-70 years). We propose to i) Aggregate, process, and quality control dMRI datasets of individuals with ASD and TD controls from shared databases, and ii) Examine cross- sectional lifespan age trajectories of microstructural measures of white matter tracts at the group level, and multivariate patterns of white matter microstructure at the individual level (using deep normative modeling), in ASD relative to TD controls, and link atypicality of white matter patterns with ASD symptoms. Exploratory analyses on the effects of sex and cognitive abilities will also be performed. This research may aid treatment and policy development by identifying the location and timing of vulnerable neural pathways and circuits in ASD, and, additionally, promote reproducible diffusion MRI research.

摘要 自闭症谱系障碍（ASD）影响发育的许多方面（例如，社会， 认知），并在生命早期改变神经发育被认为是一个 ASD病理生理学的重要特征。然而，有相当大的不确定性， 关于ASD的神经成熟轨迹， 青春期和衰老的过渡期。白色物质是必要的， 专门的大脑回路的发展。白色物质束沿着一个 发展轨迹，在生命的第三到第四个十年达到顶峰，而且，关键的是，他们的 ASD的成熟可能会发生差异性改变。弥散磁共振成像（dMRI）是目前 用于探测体内白色物质有效的非侵入性技术。白色物质的研究 然而，在儿童后期到成年期的ASD中使用dMRI， 调查结果。ASD中可重现的白色物质结果的主要障碍是统计学低 动力.在过去的十年里，广泛共享的多模式ASD数据集已经 通过诸如自闭症脑成像数据等大型项目提供 国家自闭症研究数据库（National Database for Autism Research）这些dMRI数据 然而，目前资源利用不足。此外，大型财团研究（例如， 人类连接组计划）已经在健康人群中提供了高质量的dMRI数据， 在整个生命周期中。最近在数据统一方面取得的方法进步 的dMRI数据允许减轻成像部位和方案之间的差异。这个项目 旨在利用可用的多部位dMRI数据（>2600名参与者; >600名ASD，>2000名 TD;最多17个站点）进行联合大规模分析， ASD中白色物质在整个生命周期（2-70岁）的时空模式 年）。我们建议i）聚合，处理和质量控制dMRI数据集， 来自共享数据库的ASD和TD控制的个人，以及ii）检查交叉- 白色物质束显微结构测量的截面寿命年龄轨迹. 组水平和个体白色物质微结构的多变量模式 水平（使用深度规范建模），在ASD中相对于TD控制，以及链路的可靠性 有ASD症状的白色物质模式。对性别影响的探索性分析 和认知能力也将被测试。这项研究可能有助于治疗和政策 通过识别脆弱的神经通路的位置和时间， ASD中的电路，此外，还促进了可重复的扩散MRI研究。