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.

抽象的 尽管家长、研究人员、主教和教育工作者付出了巨大努力，自闭症谱系障碍 (ASD) 继续对大多数受影响的个人及其家庭提出重大的、终生的挑战。 有自闭症谱系障碍风险的婴儿的早期发育（例如有患有自闭症谱系障碍的哥哥姐姐的婴儿：“HR 婴儿兄弟姐妹” – 有大约 20% 的机会患上 ASD 的人）可以识别 ASD 的早期、症状前预测因子，这些预测因子可以 然后改进早期筛查并促进对这些 HR 婴儿的症状前干预。 兄弟姐妹在生命的第二年发现了社交领域的非典型行为，并有一些证据表明 然而，第一年内的运动迟缓和社会注意力的差异部分是由于有限。 婴儿的行为库，研究人员一直在努力找出一致的第一年行为 以临床上可行的方式预测以后的自闭症谱系障碍（ASD） 我们提出了非典型的最早测量方法。 发育应直接测定大脑功能。婴儿脑成像研究 (IBIS) 网络已使用该方法。 MRI 方法可揭示 HR 婴儿兄弟姐妹在生命第一年的功能和结构大脑变化。 这些大脑变化在自闭症谱系障碍行为特征出现之前就已经存在，并能准确预测 24 个月大的自闭症谱系障碍（阳性预测值 >= 80%）虽然在科学上有希望，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 脑电图 (EEG) 和眼动追踪 (ET) 代表了两种可扩展的方法。 可以测量大脑功能，并有助于识别婴儿早期 ASD 的预测生物标志物。 2019 年春季，婴儿大脑在社区和现实环境中具有发育敏感性和可访问性。 影像研究 (IBIS) 网络将启动一项针对 250 名 HR 婴儿的新研究，旨在复制和扩展其研究 在此，我们建议将脑功能的脑电图和 ET 测量添加到本研究中，进行测试。 来自 IBIS 的 6 个月和 12 个月大的 HR 婴儿，并在 24 个月大时评估临床结果 在 24 个月大时评估临床结果，我们将检查休息时和低血压期间的大脑网络功能。 我们的假设是这些可扩展的。 EEG/ET 生物标志物将（目标 1）准确识别后来诊断为 ASD 的婴儿，并将（目标 2）与 利用这个前所未有的机会来融入 24 个月大的 ASD 相关行为。 在同一组婴儿中进行 EEG/ET 和神经影像学检查，在目标 3 中，我们还建议探索预测 这些综合测量的功效，以及 EEG/ET 和 MRI 特征之间的关联。 该提案的目标是将自闭症的发现年龄降低到婴儿早期，在孩子出生之前进行干预。 ASD 特定行为特征的出现可行且更有效。 研究还将促进未来将症状前预测测试从 HR 婴儿扩展到其他婴儿 普通民众。