Toward Scalable Biomarker-Based Prediction of ASD in High-Risk Infants

基于生物标志物的高危婴儿自闭症谱系障碍 (ASD) 可扩展预测

• 批准号: 10475316
• 负责人: Shafali Spurling Jeste
• 金额: $ 74.94万
• 依托单位: CHILDREN'S HOSPITAL OF LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-16 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10475316
• 关键词: Address; Affect; Age; Age-Months; Attention; Autism Diagnosis; Behavior; Behavioral; Biological Assay; Biological Markers; Brain; Brain imaging; Clinical; Cognition; Collaborations; Communities; Databases; Detection; Development; Diagnosis; Dimensions; Early Intervention; Electroencephalography; Family; Frequencies; Functional Magnetic Resonance Imaging; Funding; Future; General Population; Goals; Heterogeneity; Image; Impairment; Individual; Infant; Intervention; Language; Life; Magnetic Resonance Imaging; Measures; Methodology; Methods; Modeling; Motor; National Institute of Mental Health; Neurophysiology - biologic function; Outcome; Parents; Phase; Predictive Value; Reporting; Research Personnel; Rest; Risk; Scientific Inquiry; Sensory; Severities; Siblings; Symptoms; Testing; Time; auditory processing; autism spectrum disorder; base; behavioral study; clinical biomarkers; clinically actionable; cohort; community setting; cost; design; early screening; efficacy evaluation; high risk; high risk infant; imaging study; improved; infancy; information processing; interest; multimodality; neuroimaging; outcome prediction; predictive marker; predictive modeling; predictive test; social; social attention; social communication; visual processing; visual tracking

ABSTRACT Despite tremendous effort by parents, researchers, clinicians, and educators, autism spectrum disorder (ASD) continues to present a significant, lifelong challenge to most affected individuals and their families. Studies of early development in infants at risk for ASD (such as infants with older siblings with ASD: “HR infant siblings” – who have a ~20% chance of developing ASD) can identify early, presymptomatic predictors of ASD that can then improve early screening and promote presymptomatic intervention. Behavioral studies of these HR infant siblings have identified atypical behaviors in the second year of life in the social domain, with some evidence of motor delays and differences in social attention within the first year. However, in part because of the limited behavioral repertoire of infants, investigators have struggled to identify consistent first-year-of-life behaviors that predict later ASD in a clinically actionable manner. We propose that the earliest measures of atypical development should directly assay brain function. The Infant Brain Imaging Study (IBIS) Network has used MRI methods to reveal functional and structural brain changes in the first year of life in HR infant siblings. These brain changes are present prior to the emergence of behavioral features of ASD and accurately predict ASD at 24 months of age (positive predictive value >= 80%). While scientifically promising, MRI's cost and reduced availability limit its potential scalability for use in HR infants to use as a general population screener in clinical settings. Electroencephalography (EEG) and eye tracking (ET) represent two scalable methods that can measure brain function and can help to identify predictive biomarkers of ASD in early infancy. EEG and ET are developmentally sensitive and accessible in community, real-world settings. In spring 2019, the Infant Brain Imaging Study (IBIS) Network will launch a new study of 250 HR infants designed to replicate and extend its predictive MRI findings. Here, we propose to add EEG and ET measures of brain function to this study, testing HR infants from IBIS at 6 and 12 months of age, and assessing clinical outcomes at 24 months of age with clinical outcomes assessed at 24 months of age. We will examine brain network function at rest, during low level sensory processing, and during social information processing. Our hypothesis is that these scalable EEG/ET biomarkers will (Aim 1) accurately identify infants with a later diagnosis of ASD and will (Aim 2) relate to ASD-associated behaviors at 24 months of age. Capitalizing on this unprecedented opportunity to integrate EEG/ET with neuroimaging in the same cohort of infants, in Aim 3 we also propose to explore the predictive power of these combined measures, and the association between EEG/ET and MRI features. The overarching goal of this proposal is to lower the age of detection of autism to early infancy, making intervention before the emergence of ASD-specific behavioral features feasible and more effective. Positive findings in the proposed study will also facilitate the future extension of presymptomatic predictive testing from HR infants to infants in the general population.

摘要 尽管父母、研究人员、临床医生和教育工作者付出了巨大的努力，自闭症谱系障碍（ASD） 对大多数受影响的个人及其家庭来说，艾滋病毒/艾滋病仍然是一个重大的终身挑战。研究 有ASD风险的婴儿的早期发育（如患有ASD的年长兄弟姐妹的婴儿：“HR婴儿兄弟姐妹”- 有~20%的机会发展为ASD）可以识别ASD的早期症状前预测因子， 加强早期筛查，促进症状前干预。这些HR婴儿的行为研究 兄弟姐妹在第二年的社会领域中发现了非典型行为，有一些证据表明， 运动延迟和第一年内社会注意力的差异。然而，部分原因是有限的 研究人员一直在努力确定婴儿出生后第一年的行为 以临床可行的方式预测未来的ASD。我们建议，最早的措施， 发育应该直接检测大脑功能。婴儿脑成像研究（IBIS）网络使用了 MRI方法揭示HR婴儿兄弟姐妹在生命第一年的功能和结构脑变化。 这些大脑变化在ASD的行为特征出现之前就存在了，并准确地预测了ASD的发生。 24个月时ASD（阳性预测值>= 80%）。虽然在科学上很有前途，但MRI的成本和 可用性的降低限制了其在HR婴儿中用作一般人群筛查的潜在可扩展性， 临床环境。脑电图（EEG）和眼动跟踪（ET）代表了两种可扩展的方法， 可以测量大脑功能，并有助于确定婴儿早期ASD的预测生物标志物。EEG和ET 是发展敏感的，在社区，现实世界的环境中可以获得。2019年春季，婴儿大脑 成像研究（IBIS）网络将启动一项新的研究，250 HR婴儿，旨在复制和扩展其 预测性MRI结果。在这里，我们建议在这项研究中增加EEG和ET测量大脑功能，测试 来自IBIS的6个月和12个月大的HR婴儿，并评估24个月大时的临床结局， 在24个月大时评估临床结果。我们将检查休息时的大脑网络功能， 水平的感觉处理，并在社会信息处理。我们的假设是，这些可扩展的 EEG/ET生物标志物将（目标1）准确识别出后来诊断为ASD的婴儿，并将（目标2）与 24个月大时与自闭症谱系障碍相关的行为。利用这一前所未有的机会， EEG/ET与神经影像学在同一队列的婴儿，在目标3中，我们还提出了探索预测 这些组合措施的功效，以及EEG/ET和MRI特征之间的关联。总体 这项建议的目标是将自闭症的发现年龄降低到婴儿早期， ASD特异性行为特征的出现可行且更有效。拟议预算中的积极结果 这项研究还将促进未来将先兆预测测试从HR婴儿扩展到 普通民众。