The Autistic Brain Over 45: The Anatomic, Functional, and Cognitive Phenotype

项目摘要 对于成年自闭症患者的神经和认知变化或长期预后知之甚少 年龄超过50岁的谱系障碍（ASD），尽管仅在美国就有数十万人 ASD患者将在未来几十年达到这个年龄组。横截面研究结果表明，新的 出现认知、感觉运动和心理健康问题，并发生加速的脑组织损失。 大脑的功能和结构连接也受到影响，如静息状态功能性MRI所示， 弥散磁共振成像 该项目旨在描述ASD中大脑解剖和功能的中晚期轨迹， 以及认知和行为变化，并确定预测不良结果的风险因素，包括 GABA浓度下降和兴奋性的怀疑影响：抑制老化的不平衡。拟议 更新将利用现有的40-70岁ASD患者队列（队列1）和匹配的典型 参与者比较（TC）。此外，一个新的队列（队列2）的50个人与ASD和70 TC 将招募40-70岁的参与者。将对两个队列进行纵向随访，每隔 3.5-5年。将在每个时间点采集大量数据，包括多模式MRI扫描、 来自MR光谱、诊断、认知和行为评估的GABA浓度，以及 医疗和个人历史信息。 该项目将追求三个具体目标。目标1将确定以下方面的变化（和变化率）： 大脑解剖学、功能和连通性，并将这些与3个疑似风险领域的行为变化联系起来 运动、执行和情感功能。目标2将测试GABA的组间差异和年龄效应 集中和网络整合与隔离。目标3将确定行为和神经风险因素 不良（或积极）结果（例如，在适应不良行为，日常生活技能丧失的量表上） 机器学习，并根据GABA水平、差异变化率或 差异域特异性。

Project Summary Extremely little is known about neural and cognitive changes or long-term prognosis for adults with autism spectrum disorders (ASD) older than 50 years of age, although in the US alone hundreds of thousands of people with ASD will reach this age group in the coming decades. Cross-sectional findings suggest that new cognitive, sensorimotor, and mental health problems emerge and that accelerated brain tissue loss occurs. Functional and structural brain connectivity is also affected, as shown with resting state functional MRI and diffusion MRI. This project aims to characterize mid- to late-life trajectories of brain anatomy and function in ASD, as well as cognitive and behavioral change, and identify risk factors that predict poor outcomes including suspected effects of declining GABA concentrations and excitatory:inhibitory imbalance in aging. The proposed renewal will leverage an existing cohort (Cohort 1) of 40-70 year olds with ASD and matched typical comparison (TC) participants. In addition, a new cohort (Cohort 2) of 50 individuals with ASD and 70 TC participants age 40-70 will be recruited. Both cohorts will be followed longitudinally, with data collection every 3.5-5 years. Extensive data will be acquired at each time-point, including multimodal MRI scans, measures of GABA concentration from MR spectroscopy, diagnostic, cognitive, and behavioral assessments, as well as medical and personal history information. The project will pursue 3 specific aims. Aims 1 will identify alterations (and altered rates of change) in brain anatomy, function, and connectivity and relate these to behavioral changes in 3 suspected risk domains of Motor, Executive, and Affective function. Aim 2 will test for group differences and effects of age in GABA concentrations and in network integration and segregation. Aim 3 will identify behavioral and neural risk factors of adverse (or positive) outcomes (e.g. on scales of maladaptive behavior, loss of daily living skills) using machine learning, and identify ASD subgroups based on GABA levels, differential rates of change, or differential domain-specificity.