Neural signatures of outcome in preschoolers with autism

Objective.这一建议的重要目标是加深我们对 自闭症谱系障碍（ASD）。它的动机是迫切需要早期预后标志物能够解释 ASD结果的广泛异质性。为此，我们建议对幼儿进行纵向研究 ASD（2-3岁），以确定限制性发育的早期发育变化的神经生物学基础。 重复行为/兴趣（RRB）-ASD临床上最具损害性的方面之一-及其预测 对后期功能的贡献。该提案建立在相关发现和我们自己工作的汇合基础上 包括：1）临床证据表明，RRB在约29至42个月的年龄窗内发生变化， ASD成人功能的预后标志物; 2）脑发育功能连接组学的进展 它允许使用自然睡眠MRI对患有ASD的学龄前儿童的神经回路进行调查。我们特别针对 测试1）从24-36月龄到36-48月龄（T1，T2）内在功能连接是否发生变化 (iFC)躯体运动（SM）纹状体-皮层回路的变化与重复感觉运动的变化有关 (RSM)这些早期脑行为变化是否预示着以后（年龄：48-60岁） 3个月，T3）适应功能。探索性的目标将检查结构的潜在贡献 纹状体-皮质束的连接变化，并使用无偏的连接组范围测试全脑iFC 协会最后，我们将探索另一种数据驱动的分层聚类方法的价值， 基于T3时的多个临床维度表征结局。方法.我们预计将获得 完整的T1和T2脑行为数据来自100名年龄在24-36个月的ASD学龄前儿童， 按年进行前瞻性随访。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，多频带静息状态fMRI（R- 功能磁共振成像），并在可能的情况下，扩散张量）和表型评估严格选择，以深入 表型包括一系列ASD核心和相关症状。检查iFC和RSM的预测价值 改变（即，T1-T2）到以后的功能，儿童将在48-60个月（T3）时重新评估。的部分列表 评估包括：自闭症诊断观察计划-2，行为观察社会 沟通检查表、重复行为量表-修订版、临床医生和父母共病指标 精神病理学和适应功能大脑行为分析将主要依赖于R-fMRI，并探索 弥散张量成像意义研究结果将阐明在神经相关的变化，在RSM的 临床诊断后的最早实用时间。他们将提供一个发展知情的理解 结果的神经基础，从而使该领域更接近个人的神经分层。 这些知识对于开发神经科学知情的治疗至关重要。最大限度地发挥影响， 每年与NDAR和ABIDE共享去识别数据，以加速科学进步。

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.