Maintenance and Enhancement of the Atlanta African American Maternal-Child Cohort: Exposome Profiling via High-resolution Metabolomics and Integration of Microbiome-Metabolome-Epigenome Data

项目摘要 关键的产前和幼儿时期的环境暴露可能会导致终生健康 后果。这些暴露与健康关系的潜在机制很复杂，具有外源性 影响内源性过程（例如基因调控和 代谢），扰乱代谢途径，导致不良健康结果。两种不良暴露 其健康后果对非裔美国 (AA) 妇女和儿童的影响尤为严重， 强调健康差异始于子宫内，并在产后扩大。结果之中 AA 儿童不成比例地经历过早产、神经发育缺陷和肥胖——所有这些 与环境暴露有关，但由于病因复杂，人们对其了解甚少。我们的团队目前 调查早产和 18 个月内与产前和产后相关的神经发育 AA 孕妇群体中环境毒物暴露和生物心理社会危险因素 （R01NR014800、R01MD009064）及其婴儿（R01MD009746）以及通过我们的 P50 儿童环境 健康中心 (P50ES026071) 与埃默里大学 HERCULES 暴露研究中心 (P30) 合作 ES019776）。我们还根据以下标准评估 2-5 岁儿童的肥胖和神经发育情况： 环境儿童健康成果 (ECHO) 计划 (UG3OD023318)。通过这个R24机制，我们 建议：（1）继续招募妊娠8-14周的AA女性，收集妊娠期间三个时间点的数据 怀孕，并让已分娩的母子二人参与正在进行的产后随访研究，以允许 继续调查产前和儿童早期接触化学物质和非化学物质之间的关系 化学压力源和儿童健康结果（队列维护目标）； (2) 评估绩效 高分辨率质谱联用气相色谱法 (GC-HRMS) 用于量化持久性 通过将测得的 POP 浓度与实际值进行比较，得出有机污染物 (POP) 微升血清体积 在同一队列中使用传统的靶向分析化学方法进行测量（资源 基础设施——暴露特征目标）； (3) 采用多组学数据集成工具，以实现 综合暴露评估和生物效应数据的显示、可视化和集成—— 包括化学毒物浓度和代谢组学（KEGG 途径）、表观基因组学（基因甲基化 和表达）和微生物组数据——以及与妊娠和出生结果的关联分析 在我们的队列内和跨队列合作（资源基础设施 - 数据准备目标）。通过 这项工作，我们希望围绕化学品评估推进环境健康科学 混合物（重点关注持久性有机污染物）及其对临床前（代谢和表观遗传）健康的不利影响 我们自己的孕妇和新生儿人口差异很大，并支持其他群体 以及涉及使用高维多组学数据的跨队列合作。

PROJECT ABSTRACT Environmental exposures during the critical prenatal and early childhood periods can result in lifelong health consequences. Mechanisms underlying these exposure-health relationships are complex, with exogenous exposures (such as chemical toxicants) affecting endogenous processes (such as gene regulation and metabolism), which perturb metabolic pathways that lead to adverse health outcomes. Both adverse exposures and their health consequences disproportionately impact African American (AA) women and children, highlighting that health disparities begin in utero and are amplified postnatally. Among outcomes disproportionately experienced by AA children are preterm birth, neurodevelopmental deficits, and obesity – all linked to environmental exposures, yet poorly understood due to etiologic complexity. Our team is currently investigating preterm birth and neurodevelopment through 18-months in relation to pre- and postnatal exposures to environmental toxicants and biopsychosocial risk factors in cohorts of pregnant AA women (R01NR014800, R01MD009064) and their infants (R01MD009746) and via our P50 Children's Environmental Health Center (P50ES026071) in collaboration with the Emory HERCULES Exposome Research Center (P30 ES019776). We are also evaluating child obesity and neurodevelopment at 2-5 years of age under the Environmental Child Health Outcomes (ECHO) program (UG3OD023318). Through this R24 mechanism, we propose to: (1) Continue to enroll AA women at 8-14 wks' gestation, collect data at three time points during pregnancy, and engage delivered mother-child dyads in on-going postnatal follow-up studies to allow continued investigation of relationships between prenatal and early childhood exposures to chemical and non- chemical stressors and child health outcomes (Cohort Maintenance Aim); (2) Evaluate the performance of high-resolution mass spectrometry coupled with gas chromatography (GC-HRMS) for quantifying persistent organic pollutants (POPs) microliter serum volumes by comparing measured POP concentrations to those measured using conventional targeted analytic chemistry approaches in the same cohort (Resource Infrastructure – Exposure Characterization Aim); and (3) Adapt tools for multi-omic data integration to enable the display, visualization, and integration of comprehensive exposure assessment and biological effect data – to include chemical toxicant concentrations and metabolomic (KEGG pathway), epigenomic (gene methylation and expression), and microbiome data – and the analysis of associations with pregnancy and birth outcomes within our cohort and across cohort collaborations (Resource Infrastructure - Data Preparation Aim). Through this work, we expect to advance environmental health science around the assessment of chemical mixtures (with a focus on POPs) and their adverse preclinical (metabolic and epigenetic) health effects in our own high disparity population of pregnant women and newborns and to support other cohorts and cross-cohort collaborations involving the use of high-dimensional multi-omic data.