Parsing ASD Heterogeneity: Neuroendophenotypes of Social Attention and Sensory Responsivity

在自闭症谱系障碍（ASD）的诊断伞下，在不同年龄段观察到巨大的差异性。 受影响的个体，可能反映不同的病因机制。然而，迄今为止的大多数研究都认为， ASD作为一个单一的条件，通常比较个体与ASD匹配的控制。这一战略没有 这只会阻碍我们在揭示导致ASD的神经生物学机制方面的进展 但是，重要的是，这种方法也破坏了翻译研究的潜力， 有助于自闭症患者的“精准医疗”。在这个项目中，我们将迈出关键的第一步， 通过结合最先进的成像方法， 解释了遗传易感性，以及大量ASD青年样本的深层次表型特征。 具体来说，我们将收集和分析丰富的基于大脑的测量数据集（休息状态和任务相关 功能磁共振成像）的无与伦比的分辨率和质量，以表征大脑网络中的个体差异 属性，并研究这些如何可能涉及到一个丰富的表型电池的措施挖掘到关键 感兴趣的领域。使用创新的功能磁共振成像激活范式作为社会的神经测定 注意力，感官反应和奖励功能，我们还将研究大脑的反应模式， 相关的神经回路在个体内部和个体之间共同变化，以确定神经过度 对感官刺激的反应性影响社会相关刺激的神经处理，并评估如何区分 社会、感觉和奖赏反应的神经内表型与功能性神经元的连接改变有关。 大脑网络和行为表型。最后，基于我们先前的成像遗传学研究，我们将 研究多基因风险以及特定ASD相关多态性的风险变异如何影响 大脑功能、网络连接和核心ASD诊断学。我们的首要假设是， 基于不同的脑功能和连接性，将确定不同的和共享的神经内表型 这些指标将映射到社会和感官反应的不同维度， 行为和神经层面。我们进一步预计，更高的多基因风险将预示着越来越多的 大脑活动和连接的异常模式以及整体ASD症状的严重程度，而遗传 特定ASD相关多态性的变化将选择性地调节脑功能和网络 这些ASD风险基因表达的大脑回路的连接。通过采用（a）尖端技术 检查大脑功能和连通性的成像方法，（B）将社会注意力 和动机的感觉处理的相似性，（c）新的方法，以整合遗传风险与神经 和行为表型，以及（d）复杂的数据分析策略，以合理地分层我们的ASD样本， 这些研究将促进我们对ASD异质性背后的神经机制的理解 从而最终有助于开发更个性化和更有效的干预措施。

Under the diagnostic umbrella of Autism Spectrum Disorder (ASD), tremendous variability is observed across affected individuals, likely reflecting distinct etiological mechanisms. Yet, most research to date has treated ASD as a unitary condition, typically comparing individuals with ASD to matched controls. This strategy has not only hindered our progress in unraveling the neurobiological mechanisms that give rise to ASD symptomatology but, importantly, such an approach also undermines the potential of translational research to contribute to `precision medicine' in ASD. In this project, we will take a critical first 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 sample of youth with ASD. Specifically, we will collect and analyze a rich dataset of brain-based measures (resting-state and task-related fMRI) of unparalleled resolution and quality in order to characterize individual differences in brain network properties and examine how these may relate to a rich phenotypic battery of measures tapping into key domains of interest in our center. Using innovative fMRI activation paradigms as neural assays of social attention, sensory responsivity, and reward function, we will also examine how patterns of brain responses in associated neural circuits co-vary within and between individuals in order to determine how neural over- responsivity to sensory stimuli impacts neural processing of socially relevant stimuli, and assess how distinct neural endophenotypes of social, sensory, and reward responsivity relate to altered connectivity in functional brain networks and behavioral phenotypes. Lastly, building upon our prior imaging-genetics studies, we will examine how polygenic risk, as well as risk variants on selected ASD-associated polymorphisms, influence brain function, network connectivity, and core ASD symptomatology. Our overarching hypothesis is that both distinct and shared neuroendophenotypes will be identified based on different brain function and connectivity metrics and that these will map onto varying dimensions of social and sensory responsivities as manifested at the behavioral and neural level. We further expect that higher polygenic risk will be predictive of increasingly aberrant patterns of brain activity and connectivity as well as overall ASD symptom severity, whereas genetic variance on specific ASD-associated polymorphisms will selectively modulate brain function and network 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, the proposed studies will foster our understanding of the neural mechanisms underlying heterogeneity in ASD thereby ultimately contributing to the development of more personalized and efficacious interventions.