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.

抽象的 尽管父母，研究人员，临床医生和教育者竭尽全力，但自闭症谱系障碍（ASD） 继续向大多数受影响的个人及其家人提出重大的终身挑战。研究 有ASD风险的婴儿的早期发育（例如患有ASD的老年兄弟姐妹的婴儿：“ HR婴儿兄弟姐妹” - 有大约20％的人开发ASD的人可以识别ASD的早期，预抑制性预测指标 然后改善早期筛查并促进性交感神经干预。这些人力资源婴儿的行为研究 兄弟姐妹在社会领域的第二年确定了非典型行为，有一些证据表明 第一年内的运动延迟和社会关注的差异。但是，部分原因是有限 婴儿的行为曲目，调查人员一直在努力确定一致的第一年行为 这可以以临床可行的方式预测ASD。我们建议最早的非典型措施 开发应直接测定大脑功能。婴儿脑成像研究（IBIS）网络已使用 MRI方法揭示了人力资源婴儿兄弟姐妹第一年的功能和结构性大脑变化。 这些大脑的变化是在ASD的行为特征出现之前存在的，并且可以准确预测 ASD在24个月大（正预测值> = 80％）。虽然科学有希望，但MRI的成本和 降低的可用性限制了其在HR婴儿中使用的潜在可伸缩性，以用作一般人口筛查员 临床环境。脑电图（EEG）和眼睛跟踪（ET）代表了两种可扩展的方法 可以测量大脑功能，并可以帮助识别婴儿早期ASD的预测生物标志物。 EEG和ET 在社区，现实世界中开发敏感且可访问。在2019年春季，婴儿大脑 成像研究（IBIS）网络将对250小时婴儿进行新的研究，旨在复制和扩展其 预测性MRI发现。在这里，我们建议将脑功能的脑电图和ET度量添加到本研究中 6个月和12个月大的IBIS的人力资源hr婴儿，并评估24个月大的临床结果 在24个月大时评估了临床结果。我们将在静止的情况下检查大脑网络功能 水平感官处理以及社会信息处理期间。我们的假设是这些可扩展 EEG/ET生物标志物将（AIM 1）准确识别使用ASD诊断和WILL（AIM 2）的婴儿 在24个月大时与ASD相关的行为。利用这个前所未有的融合机会 脑电图/ET在同一婴儿中具有神经成像，在AIM 3中，我们还建议探索预测性 这些组合度量的功能以及EEG/ET和MRI特征之间的关联。总体 该提议的目标是将自闭症的检测年龄降低到早期婴儿期，在之前进行干预 ASD特异性行为特征的出现可行，更有效。拟议中的积极发现 研究还将促进从人力资源婴儿到婴儿向婴儿的未来预测性测试的未来扩展 普通人群。