Parsing ASD Heterogeneity: Neuroendophenotypes of Social Attention and Sensory Responsivity

解析 ASD 异质性：社会注意力和感觉反应的神经内表型

• 批准号: 10192837
• 负责人: Mirella Dapretto
• 金额: $ 72.31万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10192837
• 关键词: Affect; Base of the Brain; Behavioral; Biological Assay; Biological Markers; Brain; Childhood; Clinical; Data; Data Analytics; Data Set; Development; Diagnosis; Dimensions; Electroencephalography; Etiology; Female; Fostering; Functional Magnetic Resonance Imaging; Funding; Gender; Genetic; Genetic Polymorphism; Genetic Predisposition to Disease; Genetic Risk; Genomic approach; Genotype; Goals; Heterogeneity; Human; Image; Impairment; Individual; Individual Differences; Link; Maps; Measures; Motivation; National Institute of Mental Health; Outcome; Pattern; Phenotype; Population; Property; Protocols documentation; Psychiatry; Reproducibility; Research; Research Domain Criteria; Resolution; Rest; Rewards; Risk; Sampling; Scanning; Sensorimotor functions; Sensory; Severities; Sex Differences; Site; Social Interaction; Stimulus; Subgroup; Symptoms; Translational Research; Work; Youth; adolescent with autism spectrum disorder; analytical method; autism spectrum disorder; base; behavioral phenotyping; brain behavior; cohort; comorbidity; connectome; efficacious intervention; endophenotype; genetic variant; imaging genetics; imaging modality; individuals with autism spectrum disorder; innovation; interest; large datasets; magnetic resonance imaging/electroencephalography; male; neural circuit; neurobiological mechanism; neuroimaging; neuromechanism; novel; novel strategies; personalized intervention; precision medicine; relating to nervous system; repetitive behavior; response; risk variant; sensory stimulus; sex; social; social attention; social communication; symptomatology; virtual

PROJECT DESCRIPTION Despite the tremendous variability observed across individuals diagnosed with Autism Spectrum Disorder (ASD), most research to date has treated ASD as a unitary condition, comparing individuals with ASD to neurotypical controls. This approach has hindered our progress in unraveling the neurobiological mechanisms that give rise to ASD symptomatology and it also undermines the potential of translational research to contribute to `precision medicine' in ASD. In this project, we take a critical step toward dissecting the significant heterogeneity observed in ASD by combining state-of-the-art imaging methods, novel approaches to account for genetic susceptibility, and a deep phenotypic characterization of a large and unique sample of males and females with ASD that we curated as part of our recently renewed ACE Network (MH100028). Capitalizing on the comprehensive assays already collected in this cohort (i.e., phenotyping, genotyping, MRI, EEG) and our involvement in the Human Connectome Project - Development (MH109589), here we will collect and analyze a rich dataset of brain-based measures of unparalleled resolution and quality in order to characterize individual differences in brain network properties and examine how these relate to a vast phenotypic battery of measures tapping into key domains of interest. Using resting-state fMRI and innovative fMRI activation tasks as neural assays of social and sensory responsivity, we will examine how functional connectivity and brain responses in associated neural circuits co-vary within and between individuals in order to determine how atypical reactivity to sensory stimuli impacts neural processing of socially relevant stimuli, and assess how distinct neural endophenotypes of social and sensory responsivity relate to altered functional connectivity and behavioral phenotypes. Building upon our prior imaging-genetics work, we will also examine how polygenic risk, and risk genetic variants on ASD-associated polymorphisms, influence brain function, connectivity, as well as core ASD symptoms. Our overarching hypothesis is that both distinct and shared neuroendophenotypes will be identified across our sample based on different brain function and connectivity metrics and that these will map onto varying dimensions of social and sensory atypicalities manifested at the neural and behavioral level. We further expect that higher polygenic risk will predict increasingly aberrant patterns of brain activity, connectivity, and overall symptom severity, whereas genetic variance on ASD-associated polymorphisms will selectively modulate brain function and connectivity in brain circuits where these ASD risk genes are expressed. By employing (a) cutting-edge imaging methods to examine brain function and connectivity, (b) innovative paradigms to relate social attention and motivation to sensory processing atypicalities, (c) novel approaches to integrate genetic risk with neural and behavioral phenotypes, and (d) sophisticated data-analytic strategies to sensibly stratify our ASD sample, this research will further our understanding of the neural mechanisms underlying heterogeneity in ASD and ultimately inform more personalized and efficacious interventions.

项目描述 尽管在被诊断患有自闭症谱系障碍的个体中观察到巨大的变异性， (ASD)迄今为止，大多数研究都将ASD视为一种单一的疾病，将ASD患者与 神经型对照。这种方法阻碍了我们在揭示神经生物学机制方面的进展 这导致了ASD的出现，它也破坏了转化研究的潜力， 有助于自闭症患者的“精准医疗”。在这个项目中，我们朝着解剖重要的一步迈出了关键的一步。 通过结合最先进的成像方法和新的解释方法，在ASD中观察到异质性 遗传易感性，以及对大量独特的男性样本进行深入的表型表征， 我们最近更新的ACE网络（MH 100028）的一部分。充分利用 已经在该群组中收集的综合测定（即，表型分型、基因分型、MRI、EEG）和我们的 参与人类连接组项目-开发（MH 109589），在这里，我们将收集和分析一个 丰富的基于大脑的测量数据集，具有无与伦比的分辨率和质量， 大脑网络特性的差异，并研究这些差异如何与大量的表型测量组合相关 进入关键领域的兴趣。使用静息态fMRI和创新的fMRI激活任务作为神经 社会和感官反应的分析，我们将研究如何功能连接和大脑反应， 相关的神经回路在个体内部和个体之间共同变化，以确定非典型反应性如何 感官刺激影响神经处理的社会相关的刺激，并评估如何不同的神经 社会和感觉反应的内表型与改变的功能连接和行为相关 表型在我们先前的成像遗传学工作的基础上，我们还将研究多基因风险， ASD相关多态性的遗传变异，影响大脑功能，连接，以及核心ASD 症状我们的总体假设是，不同的和共享的神经内表型将被确定 基于不同的大脑功能和连通性指标， 在神经和行为水平上表现出的社会和感官相似性的不同维度。我们进一步 预计更高的多基因风险将预测越来越多的异常模式的大脑活动，连接， 总体症状严重程度，而ASD相关多态性的遗传变异将选择性地 调节大脑功能和这些ASD风险基因表达的大脑回路的连通性。通过 采用（a）尖端的成像方法来检查大脑功能和连接，（B）创新的 范式与社会注意力和动机的感觉处理的相似性，（c）新的方法， 将遗传风险与神经和行为表型相结合，以及（d）复杂的数据分析策略， 合理地分层我们的ASD样本，这项研究将进一步我们的神经机制的理解 ASD的潜在异质性，并最终为更个性化和有效的干预提供信息。