Neural signatures of outcome in preschoolers with autism

目标。这一建议的重要目标是加深我们对 自闭症谱系障碍(ASD)。其动机是迫切需要能够解释的早期预后标志物 ASD结果的广泛异质性。为此，我们建议对幼儿进行纵向研究。 用ASD(2-3年)来确定限制性发育障碍早期发育变化的神经生物学基础 重复行为/兴趣(RRB)--ASD最严重的临床损害因素之一--及其预测 对后来的功能做出了贡献。这项建议是建立在相关发现和我们自己的工作的汇合之上的 包括：1)临床证据表明RRB在~29个月到42个月之间的年龄窗口中发生变化 ASD成人功能的预后标志；2)脑发育功能连接学的进展 这使得使用自然睡眠核磁共振研究患有自闭症的学龄前儿童的神经回路成为可能。我们的目标是 测试1)从24-36岁到36-48个月龄(T1、T2)的固有功能连接性是否发生变化 躯体运动(SM)纹状体-皮质环路(IFC)与重复感觉运动的变化有关 (RSM)RRB亚域；2)这些早期脑行为变化是否预示着以后(年龄：48-60岁) 月，T3)适应性功能。探索性目标将考察结构性的潜在贡献 纹状体-皮质束的连通性改变，以及使用无偏连接全组测试全脑IFC 协会。最后，我们将探讨替代的、数据驱动的层次聚类方法的价值 根据T3时的多个临床维度来表征结果。方法：研究方法。我们期待着获得 100名患有ASD的学龄前儿童的完整T1和T2脑行为数据，年龄在24-36个月和 前瞻性地每年跟踪调查一次。在T1和T2，学龄前儿童将接受自然睡眠成像 最先进的MRI(高分辨率T1和T2加权结构MRI、多频段静息状态功能MRI(R- FMRI)，在可能的情况下，扩散张量)和表型评估经过严格选择，以深入 一系列ASD核心和相关症状的表型.检验IFC和RSM的预测价值 如果儿童功能发生变化(即T1-T2)，则在48-60个月(T3)时会重新评估。一份部分清单 评估包括：自闭症诊断观察表-2，行为观察表 沟通检查表、重复行为量表修订版、临床医生和家长共病措施 精神病理学和适应功能。大脑行为分析将主要依靠R-fMRI，并探索 扩散张量成像。意义重大。研究结果将阐明RSM变化的神经关联。 临床诊断后的最早实际时间。他们将提供一种对发展的了解 结果的神经基础，从而使这一领域更接近于个体的神经分层。 这些知识对于开发神经科学知情治疗是必不可少的。通过以下方式最大化影响 与ndar共享未识别的数据，并每年遵守，以加快科学进步。

Objective. This proposal has the important goal of furthering our understanding of the longitudinal course of autism spectrum disorder (ASD). It is motivated by the urgent need for early prognostic markers able to explain the extensive heterogeneity of ASD outcomes. To this end, we propose a longitudinal study of young children with ASD (2-3 years) to identify the neurobiological underpinnings of early developmental changes in restricted repetitive behavior/interests (RRB) – one of the most clinically impairing aspects of ASD - and their predictive contribution to later function. The proposal builds on the confluence of related findings and our own work including: 1) clinical evidence that RRB changes over the age window between ~29 and 42 months are prognostic markers of ASD adult functioning; and 2) advances in brain developmental functional connectomics that allow investigations of neural circuits in preschoolers with ASD using natural sleep MRI. We specifically aim to test 1) whether changes from 24-36 to 36-48 months-of-age (T1, T2) in the intrinsic functional connectivity (iFC) of somatomotor (SM) striatal-cortical circuitry are associated with changes in the repetitive sensory motor (RSM) subdomain of RRB; and 2) whether these early brain-behavioral changes predict later (age: 48-60 months, T3) adaptive functioning. Exploratory aims will examine the potential contributions of structural connectivity changes in striatal-cortical tracts, and test whole-brain iFC employing unbiased connectome-wide association. Finally, we will explore the value of an alternative, data-driven hierarchical clustering approach to characterizing outcomes based upon multiple clinical dimensions at T3. Methods. We anticipate obtaining complete T1 and T2 brain-behavioral data from 100 preschoolers with ASD enrolled at age 24-36 months and followed prospectively on a yearly basis. At T1 and T2, preschoolers will undergo natural sleep imaging with state-of-the-art MRI (high resolution T1- and T2-weighted structural MRI, multiband resting state fMRI (R- fMRI), and when possible, diffusion tensor) and phenotypic assessments rigorously selected to deeply phenotype a range of ASD core and associated symptoms. To examine the predictive value of iFC and RSM changes (i.e., T1-T2) to later function, children will be re-evaluated at 48-60 months (T3). A partial list of assessments includes: Autism Diagnostic Observation Schedule-2, Behavioral Observation Social Communication Checklist, Repetitive Behavior Scale-Revised, clinician and parent measures of comorbid psychopathology and adaptive functioning. Brain-behavior analyses will primarily rely on R-fMRI, and explore diffusion tensor imaging. Significance. Findings will elucidate the neural correlates of changes in RSM at the earliest practical time following clinical diagnosis. They will provide a developmentally informed understanding of the neural underpinnings of outcomes, thus bringing the field closer to a neural stratification of individuals. Such knowledge is essential for developing neuroscientifically-informed treatments. Impact is maximized by sharing de-identified data with the NDAR and ABIDE yearly to accelerate scientific progress.