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 在关键的产前和幼儿期暴露于环境中可能会导致终身健康 后果这些安全-健康关系的机制是复杂的， 暴露（如化学毒物）影响内源性过程（如基因调控和 代谢），其扰乱导致不利健康结果的代谢途径。两种不良暴露 其健康后果对非裔美国人妇女和儿童的影响尤为严重， 强调健康差距开始于子宫内，并在产后扩大。在成果中 AA儿童不成比例地经历早产，神经发育缺陷和肥胖-所有 与环境暴露有关，但由于病因的复杂性而知之甚少。我们的团队已 调查早产和18个月内与产前和产后有关的神经发育 AA孕妇队列中环境毒物和生物心理社会危险因素的暴露 （R 01 NR 014800、R 01 MD 009064）及其婴儿（R 01 MD 009746），并通过我们的P50儿童环境 健康中心（P50 ES 026071）与埃默里赫拉克勒斯暴露体研究中心（P30）合作 ES 019776）。我们还评估了2-5岁儿童的肥胖和神经发育， 环境儿童健康结果（ECHO）计划（UG 3 OD 023318）。通过这种R24机制，我们 建议：（1）继续招募妊娠8-14周的AA妇女，在妊娠期间的三个时间点收集数据。 怀孕，并在正在进行的产后随访研究中参与分娩的母婴配对， 继续调查产前和幼儿期接触化学品和非化学品之间的关系， 化学应激源和儿童健康结果（队列维持目标）;（2）评价 高分辨率质谱联用气相色谱法（GC-HRMS）用于定量持久性有机污染物 有机污染物（POP）微升血清体积，通过比较测量的POP浓度与 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-暴露表征目标）;以及（3）调整多组学数据整合工具， 全面暴露评估和生物效应数据的显示、可视化和整合- 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），以及微生物组数据-以及与妊娠和出生结果相关性的分析 在我们的队列内和跨队列协作（资源基础设施-数据准备目标）。通过 这项工作，我们希望推进环境健康科学周围的化学品的评估 混合物（重点是持久性有机污染物）及其临床前（代谢和表观遗传）不良健康影响 在我们自己的孕妇和新生儿人口中， 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.