Discovering Eye Tracking Biomarkers of ASD with Diagnostic and Prognostic Power

发现具有诊断和预后能力的 ASD 眼动追踪生物标志物

• 批准号: 10318939
• 负责人: Karen L Pierce
• 金额: $ 71.06万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10318939
• 关键词: 3 year old; 4 year old; Address; Age; Area; Attention; Auditory; Biological Markers; Child; Childhood; Clinical; Cluster Analysis; Cognition; Cognitive; Collaborations; Computer software; Data; Detection; Development; Developmental Delay Disorders; Diagnosis; Diagnostic; Disease; Early Diagnosis; Emotional; Equipment; Eye Development; Face; Foundations; Frequencies; Funding; Future; General Population; Gold; Grant; Heterogeneity; Image; Individual; Language; Link; National Institute of Mental Health; Neurobehavioral Manifestations; Neurodevelopmental Disorder; Ocular Fixation; Parents; Pattern; Performance; Play; Predictive Value; Procedures; Prognosis; Prognostic Marker; Reporting; Reproducibility; Research; Research Personnel; Risk; Role; Sample Size; Sampling; Science; Scientist; Severities; Siblings; Signs and Symptoms; Site; Specificity; Speech; Standardization; Symptoms; Technology; Testing; Toddler; Visual; Washington; artificial neural network; autism spectrum disorder; autistic children; base; checkup examination; cohort; design; diagnostic accuracy; diagnostic biomarker; diagnostic signature; diagnostic value; disorder subtype; feature selection; gaze; individualized medicine; innovation; interest; joint attention; population based; prognostic; prognostic signature; prognostic value; programs; recruit; sample fixation; screening; social; social attention; standard of care; success; trait; visual tracking

Children with ASD, on average, are not identified and treated until around age 4‐years, several years beyond the first signs and symptoms. Even when toddlers are diagnosed as ASD, parents and clinicians have little information to guide treatment decisions or predict the early course of that child's next few years. Research is needed to discover objective biomarkers that detect ASD at early ages with high accuracy, indicate disorder subtypes linked to definable clinical profiles, and convey prognostic information. The discovery of such biomarkers have been elusive, in part, because most studies utilize small sample sizes and fail to include non‐ASD delay contrast groups which are essential to enhance specificity. Our proposal plans to fill this gap by leveraging eye tracking technology to determine if visual fixation patterns in a large sample of very young (12‐36 months) ASD and non‐ASD toddlers (n=225) from the general population can be used to discover an eye tracking biomarker profile of ASD. The prognostic power of our eye tracking biomarkers will be determined by linking initial eye tracking scores to clinical profiles 1‐2 years later. Given the heterogeneity in ASD, it is unlikely that a single eye tracking test would detect all toddlers. Here we plan to remedy this by testing the utility of a battery of 9 developmentally appropriate, short (~1‐minute each), eye tracking tests that each tap into a foundational domain in ASD symptoms including: visual social attention, gaze shifting, and auditory social attention. Our tests will objectively quantify key metrics such as overall fixation levels within social versus non‐social images, the frequency of gaze alterations during joint attention and gaze following tests and, using unique gaze contingent technology, the degree to which a toddler prefers to listen to prosodic, emotionally valent, motherese speech. Our preliminary findings suggest that several of our proposed eye tracking tests have extremely high diagnostic accuracy. Findings, however, are sometimes not replicated in science, and we proactively address this by proposing concurrent, independent and exact (equipment, software, paradigms, procedures) replication testing of each of our eye tracking tests within an independent cohort of toddlers at U. Washington (n=90 toddlers). Thus, in AIM 1 we will discover an eye tracking biomarker that detects ASD at early ages (12‐36 months) with high accuracy using artificial neural networks at UCSD, and then we will independently test replication of its performance at U Washington. To enhance interpretability, our approach will incorporate patterns of metrics from each eye tracking test to produce an Autism Risk Score (ARS) scaled from 0‐100 that represents the level of ASD risk for a toddler. In AIM 2, using a rich clinical battery that captures each toddler's social, language, cognitive and symptom severity profile derived from a combination of standardized, parent report, and free‐play testing, we will identify clinically meaningful eye‐tracking based subtypes of ASD using unbiased network clustering approaches. In AIM 3 we will examine the prognostic utility of our eye tracking test battery by identifying the degree to which eye tracking‐based profiles at ages 12‐36 months can predict social, language, cognitive and attention abilities 1‐2 years later.

平均而言，ASD儿童直到4岁左右才被发现和治疗，比正常年龄高出几年。 第一个迹象和症状。即使幼儿被诊断为ASD，父母和临床医生也几乎没有信息 来指导治疗决策或预测孩子未来几年的早期病程。的研究需要 发现客观的生物标志物，在早期检测ASD具有高准确性， 以确定临床特征，并传达预后信息。这些生物标志物的发现已经被 难以理解，部分原因是大多数研究使用的样本量较小，且未纳入非ASD延迟对比组 这对于增强特异性是必要的。我们的提案计划通过利用眼动追踪技术来填补这一空白 确定非常年幼（12 - 36个月）ASD和非ASD幼儿的大样本中的视觉注视模式 （n=225）可以用于发现ASD的眼跟踪生物标志物谱。的 我们的眼动追踪生物标志物的预后能力将通过将初始眼动追踪评分与临床 一两年后的档案考虑到ASD的异质性，单次眼动追踪测试不太可能检测到 都是蹒跚学步的孩子在这里，我们计划通过测试9个电池的实用性来弥补这一点， 简短（每个约1分钟），眼动追踪测试，每个测试都涉及ASD症状的基本领域，包括： 视觉社会注意力、目光转移和听觉社会注意力。我们的测试将客观地量化关键指标 例如，社交与非社交图像中的整体注视水平，在关节运动期间注视改变的频率， 注意力和注视跟随测试，并使用独特的注视条件技术， 更喜欢听有韵律、有感情、有母爱的演讲。我们的初步发现表明， 我们提出的眼动追踪测试具有极高的诊断准确性。然而，调查结果有时 在科学中无法复制，我们通过提出并发，独立和精确的建议来积极解决这个问题。 （设备，软件，范例，程序）在一个实验室内对我们的每一项眼动追踪测试进行复制测试。 一组独立的幼儿队列。华盛顿（n=90名幼儿）。因此，在AIM 1中，我们将发现眼动跟踪 使用人工神经网络在早期（12 - 36个月）以高准确度检测ASD的生物标志物， 加州大学圣地亚哥分校，然后我们将独立测试复制其性能在U华盛顿。加强 可解释性，我们的方法将结合从每个眼动跟踪测试的指标模式，以产生一个 自闭症风险评分（ARS）从0 - 100缩放，代表幼儿ASD风险水平。在AIM 2中，使用 丰富的临床电池，捕捉每个幼儿的社会，语言，认知和症状的严重程度， 从标准化、家长报告和自由发挥测试的组合中，我们将识别出有临床意义的 使用无偏网络聚类方法的基于眼动跟踪的ASD亚型。在AIM 3中，我们将检查 我们的眼动追踪测试组合的预后效用，通过确定基于眼动追踪的配置文件 在12 - 36个月时可以预测1 - 2年后的社交，语言，认知和注意力能力。