Neuronal Correlates of Autistic Traits in ADHD and Autism

 描述(申请人提供)：这项研究旨在对ADHD和ASD儿童社交沟通障碍的神经生物学基础进行第一次调查，即自闭症特征(AT)。AT是自闭症谱系障碍(ASD)的一个重要特征，发生在20%-30%的ADHD儿童中。这些儿童导致相对较高的学业失败和较差的全球功能，突出了ADHD(ADHD+AT)儿童AT的临床意义。我们的目标是在ADHD和ASD中促进我们对AT的理解，应用最先进的脑成像方法作为努力促进治疗进步的第一步。假设来源于文献和我们的初步数据。我们的目标是在ASD和ADHD的诊断中测试支持AT的梭状面部区域(FFA)和嘴前扣带皮质(ACC)之间的内在功能连接(IFC)。具体地说，我们假设：H1a：与ADHD但没有AT的儿童(ADHD-AT)相比，在ASD儿童和ADHD+AT儿童中，FFA-ACC IFC降低；H1b：跨组，FFA-ACC IFC较弱与更严重的AT相关。H_2A：FFA-ACC IFC与情绪面孔识别的准确性呈正相关，H_2B：FFA-ACC IFC与情绪任务的准确性显著高于对照非情绪任务。此外，我们将探索1)R-fMRI和任务-fMRI连接性之间的相似性；2)FFA-ACC回路以外的脑-行为关系，推导出全脑体素R-fMRI指标和代表“社交大脑”的感兴趣区域之间的IFC；3)行为与结构连接性的关系，通过分数各向异性索引，重点关注额枕下束和其他相关束；以及4)数据驱动方法，结合现有的临床和成像数据，以确定同质的神经表型，而不管诊断如何。方法：研究方法。我们预计从每组至少70名儿童-ADHD+AT、ADHD-AT和ASD(总N=210)-获得完整的数据集，在年龄、性别、完全智商、利手和社会经济地位方面进行分组匹配。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进行盲目管理)、K-SADS和ADI-R访谈、家长和教师评定量表。情绪面孔识别任务和整体结构面孔处理任务将评估情绪面孔处理；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功能磁共振成像(R-fMRI)、结构、扩散张量成像和任务-功能磁共振成像(匹配面部任务)。意义重大。这项研究为神经生物学提供了共同的表型，并将使该领域更接近AT患者的神经分层，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身份不明的数据，以加快科学进步。

 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.