Neuronal Correlates of Autistic Traits in ADHD and Autism

 描述（由申请人提供）：本研究旨在对社交障碍的神经生物学基础进行首次调查，即，自闭症特征（AT），患有ADHD和ASD的儿童。AT是自闭症谱系障碍（ASD）的一个关键特征，发生在20-30%的ADHD儿童中。这些儿童的学业失败率相对较高，整体功能较差，突出了AT在ADHD儿童（ADHD+AT）中的临床意义。我们的目标是促进我们对ADHD和ASD的AT的理解，应用最先进的脑成像方法作为促进治疗进步的第一步。这些假设来自文献和我们的初步数据。我们的目的是测试梭状面区（FFA）和头端前扣带皮层（ACC）之间的内在功能连接（iFC）在ASD和ADHD诊断中支持AT。具体来说，我们假设：H1a：ASD儿童和ADHD+AT儿童的FFA-ACC iFC相对于ADHD但无AT的儿童（ADHD-AT）降低; H1b：在各组中，较弱的FFA-ACC iFC与更严重的AT相关。H2a：FFA-ACC iFC与情感人脸识别的准确性呈正相关，H2 b：FFA-ACC iFC与情感任务的准确性显著相关，而不是控制非情感任务。此外，我们将探讨1）R-fMRI和任务-fMRI连接之间的相似性; 2）超出FFA-ACC回路的脑-行为关系，推导出全脑体素R-fMRI指标和代表“社会脑”的感兴趣区域之间的iFC; 3）行为与结构连接的关系，由分数各向异性指数表示，重点是下额叶枕束和其他相关束;以及4）数据驱动方法，其结合可用的临床和成像数据以识别同质神经表型而不管诊断。方法.我们预计将从每组至少70名儿童中获得完整的数据集- ADHD+AT，ADHD-AT和ASD（总N=210），年龄，性别，全智商，惯用手和社会经济地位分组匹配。评估。部分清单包括：自闭症诊断观察表-2（对所有其他临床数据“盲”管理），K-SADS和ADI-R访谈，父母和教师评级量表。情绪面部识别任务和整体面部处理任务将评估情绪面部处理; Go-No Go任务和运动跟踪将测量注意力和运动。大脑行为分析将依赖于静息状态fMRI（R-fMRI），结构，扩散张量成像和任务fMRI（匹配面部任务）。意义该研究告知神经生物学的共享表型，并将使该领域更接近于AT个体的神经分层，这是开发神经科学知情治疗的关键一步。此外，我们将每年与国家自闭症研究数据库共享未识别的数据，以加速科学进步。

 DESCRIPTION (provided by applicant): This study aims to conduct the first investigation of the neurobiological underpinnings of social communicative impairments, i.e., autistic traits (AT), in children with ADHD and ASD. AT, a key feature of autism spectrum disorder (ASD), occurs in 20-30% of children with ADHD. These children incur relatively elevated school failure and poor global functioning, highlighting the clinical significance of AT in children with ADHD (ADHD+AT). We aim to advance our understanding of AT across ADHD and ASD, applying state of the art brain imaging methodology as a first step in efforts to foster advances in treatment. Hypotheses emanate from the literature and our preliminary data. We aim to test that intrinsic functional connectivity (iFC) between the fusiform face area (FFA) and rostral anterior cingulate cortex (ACC) underpins AT across ASD and ADHD diagnoses. Specifically, we hypothesize: H1a: FFA-ACC iFC is reduced in children with ASD and in those with ADHD+AT, relative to children with ADHD but no AT (ADHD-AT); H1b: Across groups, weaker FFA-ACC iFC is associated with more severe AT. H2a: FFA-ACC iFC is positively associated with accuracy in emotion face recognition, and H2b: FFA-ACC iFC is significantly more related to accuracy on an emotion task than on a control non-emotion task. In addition, we will explore 1) similarities between R-fMRI and task-fMRI connectivity; 2) brain-behavior relationships beyond the FFA-ACC circuit, deriving whole-brain voxelwise R- fMRI metrics and iFC between regions-of-interest representing the `social brain'; 3) behavioral relations with structural connectivity indexed by fractional anisotroy, focusing on the inferior frontal occipital fasciculus, and other relevant tracts; and 4) data-drive approaches combining available clinical and imaging data to identify homogenous neurophenotypes regardless of diagnosis. Methods. We anticipate obtaining complete datasets from at least 70 children per group - ADHD+AT, ADHD-AT, and ASD (total N=210), group-matched for age, sex, full IQ, handedness and socioeconomic status. Assessments. A partial list includes: Autism Diagnostic Observation Schedule-2 (administered "blind" to all other clinical data), K-SADS and ADI-R interviews, Parent and Teacher rating scales. The emotion face recognition task, and the holistic configural face processing task will assess emotion face processing; a Go-No Go task, and motion tracking will measure attention and motion. Brain-behavior analyses will rely on resting state fMRI (R-fMRI), structural, diffusion tensor imaging and task- fMRI (matching face task). Significance. The study informs the neurobiology of a shared phenotype, and will bring the field closer to a neural stratification of individuals with AT a critical step for developing neuroscientifically-informed treatments. Additionally, we will share unidentified data with National Database for Autism Research yearly to accelerate scientific progress.