Air Pollution, Multidimensional Behavior, and Neuroimaging in Children with Neurodevelopmental Disorders

项目摘要 我是受过双重训练的神经科学家和环境流行病学家。我的主要研究兴趣是 早期生活环境暴露对大脑发育的影响。该提案的目的是获得 在生物统计学，流行病学和数据科学的培训，支持我过渡到一个独立的 大数据环境发育神经科学新兴领域的跨学科研究员。我 提出了一种新的应用滞后加权分位数和（LWQS）回归连接时间 通过诊断和跨诊断（多维）解决空气污染（颗粒物< 2.5 µm; PM2.5） 行为和神经变化）的儿童自闭症谱系障碍（ASD）和注意力缺陷 多动症（ADHD）。我利用丰富的，现有的行为和磁共振成像（MRI） 表型分析来自一个成熟的大数据生物库，健康大脑网络（HBN），沿着一个新的 每周PM2.5暴露的时空模型。我推测，在关键时期， 产前发育窗口与ASD和ADHD诊断增加相关， transdiagnosis方法抓住了暴露的人口负担。在K99阶段，我建议揭开 产前环境PM2.5暴露与行为（目标1）和MRI（目标2）之间的机制联系 ASD和ADHD儿童的表型。在R 00阶段，我建议获得纵向行为 和MRI数据，以检查产前PM2.5暴露与发育轨迹之间的关联（目标3）。 为了实现这些科学目标，我将从一个专家指导团队那里获得培训和指导， 跨学科的专业知识，这将为我提供均衡的培训，在技术技能和专业 发展技术技能将涵盖：1）高维度纵向分析方法与博士克里斯 Gennings，2）Megan Horton博士的环境发展流行病学，以及3）大数据处理 核磁共振和行为数据集与迈克·米勒姆博士。霍顿博士还将领导我的专业发展 技能培训，包括赠款写作，项目管理，战略规划，以实现短期和长期的， 长期目标，保持科学的严谨性和可重复性，并培养专业网络。拟议 补充培训计划使我能够率先使用大数据来调查 在典型和精神发育性疾病中的多维暴露和行为及神经影像学结果 孩子我的长期职业目标是利用大数据来评估气候变化对儿童健康的影响。 大脑和行为的结果。我将使用这个K99/R 00作为未来R 01赠款和职业生涯的基础， 独立终身教职员这种应用克服了环境发展的障碍 神经科学，从而提高我们的能力，以确定机制之间的联系气候， 相关的环境暴露和神经发育障碍。

PROJECT SUMMARY I am a dually trained neuroscientist and environmental epidemiologist. My primary research interest is the impact of early life environmental exposures on the developing brain. The goal of this proposal is to gain training in biostatistics, epidemiology, and data science, supporting my transition into an independent transdisciplinary researcher in the emerging field of big-data environmental developmental neuroscience. I propose a novel application of the lagged weighted quantile sum (LWQS) regression to link temporally resolved air pollution (particulate matter < 2.5 µm; PM2.5) with diagnostic and transdiagnostic (multi-dimensional behavioral and neural changes) in children with autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). I leverage rich, existent behavioral and magnetic resonance imaging (MRI) phenotyping from a well-established big-data biobank, the Healthy Brain Network (HBN), along with a novel spatiotemporal model of weekly PM2.5 exposure. I hypothesize that higher PM2.5 exposure during critical windows of prenatal development is associated with increased ASD and ADHD diagnosis, and a transdiagnostic approach captures the population burden of exposure. In the K99 phase, I propose to uncover mechanistic links between prenatal ambient PM2.5 exposure and behavioral (Aim 1) and MRI (Aim 2) phenotypes in children with ASD and ADHD. In the R00 phase, I propose to acquire longitudinal behavioral and MRI data to examine associations between prenatal PM2.5 exposure on developmental trajectories (Aim 3). To achieve these scientific goals, I will obtain training and mentorship from an expert mentoring team with transdisciplinary expertise which will provide me with balanced training in both technical skills, and professional development. Technical skills will cover: 1) high dimensional longitudinal analytic approaches with Dr. Chris Gennings, 2) environmental developmental epidemiology with Dr. Megan Horton, and 3) processing of big-data MRI and behavioral datasets with Dr. Mike Milham. Dr. Horton will also lead my professional development skills training, including grant writing, project management, strategic planning to accomplish short- and long- term goals, maintaining scientific rigor and reproducibility, and cultivating a professional network. The proposed complementary training plan positions me to pioneer the use of big data to investigate the link between multidimensional exposures and behavioral and neuroimaging outcomes in typically and atypically developing children. My long-term career goal is to use big data to assess the impact of the changing climate on children’s brain and behavioral outcomes. I will use this K99/R00 as a foundation for a future R01 grant and career as an independent tenure-track faculty member. This application overcomes barriers in environmental developmental neuroscience thus advancing our ability to identify mechanisms underlying associations between climate- related environmental exposures and neurodevelopmental disorders.