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: 10452439
• 负责人: Shafali Spurling Jeste
• 金额: $ 85.51万
• 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/10452439
• 关键词: Address; Affect; Age; Age-Months; Attention; 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; Structure; 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做出了巨大努力，但自闭症谱系障碍(ASD) 继续对大多数受影响的个人及其家人构成重大的终生挑战。的研究 有自闭症风险的婴儿的早期发育(例如患有自闭症的大龄兄弟姐妹的婴儿：“HR婴儿兄弟姐妹”-- 有大约20%的机会发展为ASD)可以识别ASD的早期、症状前预测因素 然后改进早期筛查，促进症状前干预。这些HR婴儿的行为研究 兄弟姐妹在出生第二年的社会领域中发现了不典型的行为，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 婴儿的行为曲目，研究人员一直在努力识别一致的第一年出生行为 以临床可操作的方式预测未来的ASD。我们认为，非典型肺炎的最早措施 发育应该直接分析大脑功能。婴儿脑成像研究(IBIS)网络使用了 MRI方法显示出生一年的HR婴儿兄弟姐妹的脑功能和结构变化。 这些大脑变化是在ASD的行为特征出现之前就存在的，并准确地预测 24个月龄ASD(阳性预测值=80%)。虽然在科学上很有希望，但核磁共振的成本和 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(EEG)和眼球跟踪(ET)代表了两种可扩展的方法 可以测量大脑功能，并有助于在婴儿早期识别ASD的预测生物标志物。EEG和ET 对发展敏感，并可在社区、现实世界环境中使用。2019年春天，婴儿大脑 影像研究(IBIS)网络将启动一项针对250名HR婴儿的新研究，旨在复制和扩展其 具有预测性的MRI表现。在这里，我们建议将脑电和脑功能的ET测量添加到这项研究中，测试 来自IBIS的6个月和12个月的HR婴儿，并在24个月大时用 在24个月龄时评估临床结果。我们将在休息时、低谷期间检查大脑网络功能 水平感觉加工，以及在社会信息加工中。我们的假设是这些可扩展的 EEG/ET生物标志物将(目标1)准确地识别出后来被诊断为ASD的婴儿，并将(目标2)联系起来 与24个月龄的自闭症相关行为有关。利用这一前所未有的机会整合 在同一组婴儿的EEG/ET和神经成像中，在目标3中，我们还建议探索预测 这些联合测量的威力，以及EEG/ET和MRI特征之间的关联。最重要的是 这项建议的目标是将自闭症的发现年龄降低到早期婴幼儿，在 出现ASD特有的行为特征是可行且更有效的。建议中的积极结果 这项研究还将促进未来将症状前预测测试从HR婴儿扩展到 普通民众。