Predicting Heterogeneous Neurodevelopmental Outcomes in School-age Children with Early Caregiving Adversities

项目摘要 患有严重早期护理不良(ECA)的儿童最容易受到精神病理的影响 长期忽视、虐待和影响神经发育的护理中断的结果。它目前是 据估计，解决ECA问题将导致全球精神疾病减少29.8%。现有 研究，包括这次续签的原始拨款的发现，已经证明有非常强烈的 暴露于ECA与精神病理风险增加和神经发育改变之间的联系 人口水平；然而，鉴于非洲经委会人口的异质性，在知识方面存在严重差距 关于体外循环如何增加对个别儿童的任何具体风险。拟议的研究解决了这一问题 严重的心理健康问题，结合使用经验和经验的复杂数据分析方法 学龄儿童的表型异质性与纵向神经影像和行为评估 孩子们。此方法将在将ECA和子结果与 负配价和认知控制系统(NVS/CCS)的研究领域标准结构。这个 本工作的总体目标是为环境影响评估的异质性影响建立一个解释性模型。 NVS/CCS神经发育轨迹的研究该项目的前提是，接触ECA的儿童 高度不同的发展历史以及不同的结果；因此，预测 非洲经委会的成果需要尖端、复杂的数据分析方法。我们假设数据驱动 方法将1)更准确地定义患有早期评估的学龄儿童的NVS/CCS结果，以及2) 为ECA和NVS/CCS轨迹之间的联系提供更可靠的解释模型。目标1A子类型 基于NVS/CCS 2.5年发展轨迹的幼儿认知功能障碍史。300名6-8岁儿童 儿童(从以前的机构和寄养机构抽样250人；50个社区比较)将提供 神经成像、行为和自我/照顾者每15个月报告一次，持续时间为2.5年。双聚类方法将 适用于基线和后续数据，以确定同质的NVS/CCS最终结果组 孩子们。目的1B开发一种解释性模型来预测儿童的发育轨迹亚型 早期生活概况和注册时的大脑/行为表型。机器学习 将方法应用于早期生活概况、基线NVS/CCS概况和性别，将预测发展轨迹 子类型。目标2确定在2.5年评估期内发生的不良和保护性生活事件 ECAs儿童2.5年随访结果的预测。将儿童性别和目前的生活包括在内- 这些事件将确定在整个童年中期的路径上的潜在分歧。这一前瞻性的设计 暴露于各种ECA的儿童旨在开发ECA轨迹亚型和 结果，这可以使我们了解符合以下目标的风险和保护因素 精准医学。

Project Summary Children with severe Early Caregiving Adversities (ECAs) are the most vulnerable to psychopathology as a result of prolonged neglect, abuse, and care disruptions that impact neurodevelopment. It is currently estimated that addressing ECAs would lead to a 29.8% reduction in worldwide psychiatric illness. Existing research, including findings from the original grant of this renewal, has demonstrated that there is a very strong link between ECA exposures and increased risk for psychopathology and altered neurodevelopment at the population level; and yet, given the heterogeneity in ECA populations, there is a critical gap in knowledge regarding how ECAs increase any specific risks to an individual child. The proposed research addresses this significant mental health problem by combining sophisitcated data-analysis methods that use experiential and phenotypic heterogeneity together with longitudinal neuroimaging and behavioral assessments in school-age children. This approach will increase precision when linking ECAs and child outcomes associated with the Research Domain Criteria constructs of Negative Valence and Cognitive Control Systems (NVS/CCS). The overarching goal of the present work is to create an explanatory model for the heterogeneous impact of ECAs on neurodevelopmental trajectories of NVS/CCS. This project's premise is that children exposed to ECAs have highly heterogeneous developmental histories as well as heterogeneous outcomes; therefore, prediction of ECA outcomes requires cutting-edge, sophisticated data analytic methods. We hypothesize that data-driven approaches will 1) more precisely define NVS/CCS outcomes for school-aged children with ECAs, and 2) provide a more robust explanatory model for links between ECAs and NVS/CCS trajectories. Aim 1A subtypes children with a history of ECAs based on 2.5-year developmental trajectories of NVS/CCS. 300 6-8 year old children (250 sampled from previous institutional and foster care; 50 community comparisons) will provide neuroimaging, behavioral, and self/caregiver reports every 15 months for 2.5 years. Biclustering methods will be applied to the baseline and follow-up data to identify homogeneous NVS/CCS final outcome clusters of children. Aim 1B develops an explanatory model to predict developmental trajectory subtypes for children with ECAs, from early life profiles and brain/behavior phenotypes at the time of enrollment. Machine learning methods applied to early life profiles, baseline NVS/CCS profiles, and sex, will predict developmental trajectory subtypes. Aim 2 identifies adverse and protective life events during the 2.5-year assessment period that are predictive of 2.5-year follow-up outcomes for children with ECAs. The inclusion of child-sex and current life- events will identify potential divergence in pathways across middle childhood. This prospective design of children exposed to various ECAs is designed to develop predictive models for ECA trajectory subtypes and outcomes, which can inform our understanding of risk and protective factors in accord with the goals of precision medicine.