Parsing ASD Heterogeneity: Neuroendophenotypes of Social Attention and Sensory Responsivity

在自闭症谱系障碍(ASD)的诊断保护伞下，观察到 受影响的个体，可能反映了不同的致病机制。然而，到目前为止，大多数研究都治疗了 ASD作为一种单一疾病，通常将ASD患者与匹配的对照组进行比较。这一战略并没有 只是阻碍了我们在解开引起自闭症的神经生物学机制方面的进展 症状学，但重要的是，这种方法也破坏了翻译研究的潜力 为自闭症的“精准医学”做出贡献。在这个项目中，我们将迈出关键的第一步，解剖 ASD通过结合最先进的成像方法观察到显著的异质性，新的方法 解释了遗传易感性，以及对患有自闭症的青年样本的深层表型特征。 具体地说，我们将收集和分析基于大脑的测量(休息状态和任务相关)的丰富数据集 FMRI)具有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，并研究这些属性与一系列丰富的表型指标之间的关系 我们中心感兴趣的领域。使用创新的fMRI激活范式作为社会行为的神经分析 注意力、感觉响应性和奖励功能，我们还将研究大脑反应模式如何在 相关的神经回路在个体内和个体之间共同变化，以确定神经如何过度- 对感觉刺激的反应性影响社会相关刺激的神经处理，并评估其区别程度 社会、感觉和奖赏反应的神经内表型与功能性连通性改变有关 大脑网络和行为表型。最后，在我们之前的成像遗传学研究的基础上，我们将 研究多基因风险以及选定的ASD相关多态上的风险变量如何影响 脑功能、网络连接和核心ASD症状学。我们最重要的假设是 将根据不同的大脑功能和连接性来识别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，如 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个ASD症状严重程度，而遗传 特定ASD相关多态的变异将选择性地调节大脑功能和网络 表达ASD风险基因的大脑回路中的连通性。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)与社会关注相关的创新范式 和对非典型感觉加工的动机，(C)将遗传风险与神经整合的新方法 和行为表型，以及(D)复杂的数据分析策略，以合理地对ASD样本进行分层， 拟议的研究将促进我们对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.