Revealing environmental chemical exposome in a diverse prenatal population and relationships to maternal and perinatal health (REVEAL)

摘要-揭示不同产前人群中的环境化学问题， 与孕产妇和围产期健康的关系（REVEAL） 我们的更新应用程序建立在我们原来的R 01通过推进分析化学和计算 技术，以更充分地描述产前化学麻烦及其与不利的孕产妇和 围产期健康结果（例如，妊娠糖尿病、早产和低出生体重）。这些疾病的发生率 结果有所增加，并与美国人口的化学品暴露有关。产前接触a 广泛的环境化学品，包括塑料相关化学品和全氟烷基和多氟烷基 PFAS物质（PFAS）已被证明对健康产生不利影响，但技术挑战已经离开 严重的数据差距阻碍了我们描述环境暴露和疾病驱动因素的能力。 全球有超过350，000种化学品和化合物混合物注册生产， 高产量化学品在美国被广泛使用，但人类生物监测能力涵盖了 很小一部分的化学麻烦。在我们之前的R 01中，我们开创了非靶向分析（NTA） 工作流程，使用高分辨率质量显著改进了计算和分析方法 在人口统计学上多样化的母婴对人群中进行光谱测定（GMS）。我们是第一个 确定在美国大量使用的孕产妇和新生儿样本中的多种化学品， 在人类血液样本中检测到的包括用于个人护理产品和香水的化学物质， 生产塑料、表面活性剂和污渍处理。我们还发现了50多种新的化学物质， 没有关于其用途或来源的信息，并发现外源和 内源性化合物，几种化学基团（硅氧烷，PFAS和塑料中使用的化学品， 橡胶）和脂质代谢和调节的生物标志物，支持与妊娠糖尿病的联系。为我们 更新项目，我们建议通过分析额外的750个第二孕期来扩大我们的研究人群。 妊娠样本中，300个样本与我们最初的妊娠晚期样本相匹配。我们将有助于 通过将NTA与改进的计算方法相结合， 方法包括化学嫌疑人数据库~ 1，000，000外源性和内源性化学特征， 结合升级的超级计算软件，可识别约500种产前化学品暴露， 使用新的机器学习算法来估计它们的浓度。我们将用这些数据来描述 多种外源性化学品暴露、内源性效应生物标志物和 孕产妇和围产期健康结果。这一更新的总体目标是发展一个综合的 一套分析和计算工具，可扩大识别和计算化学品的能力 浓度及其与不利的孕产妇和妊娠结果的联系， 采取干预措施，防止接触有害化学品。

ABSTRACT - Revealing environmental chemical exposome in a diverse prenatal population and relationships to maternal and perinatal health (REVEAL) Our renewal application builds on our original R01 by advancing analytical chemistry and computational techniques to characterize more fully the prenatal chemical exposome and its links to adverse maternal and perinatal health outcomes (e.g., gestational diabetes, preterm birth, and low birthweight). Prevalence of these outcomes has increased and is linked to chemical exposures in the US population. Prenatal exposures to a broad range of environmental chemicals, including plastic related chemicals and per- and polyfluoroalkyl substances (PFAS), have been shown to adversely affect health, but technological challenges have left significant data gaps hindering our ability to characterize environmental exposures and drivers of disease. Over 350,000 chemicals and compound mixtures are registered for production worldwide, and thousands of high–production volume chemicals are used extensively in the US, yet human biomonitoring capacity covers a very small fraction of the chemical exposome. In our previous R01 we pioneered a nontargeted analysis (NTA) workflow, with significantly improved computational and analytical methods using high-resolution mass spectrometry (HRMS) in a demographically diverse population of maternal-newborn pairs. We were the first to identify multiple chemicals in maternal and newborn sample used in high volumes in the US not previously detected in human blood samples including chemicals used in personal care products and fragrances, production of plastics, surfactants, and stain treatment. We also identified over 50 novel chemicals with limited to no information on their uses or sources and found significant associations between exogenous and endogenous compounds, several chemical groups (siloxanes, PFAS, and chemicals used in plastics and rubber) and biomarkers of lipid metabolism and regulation, supporting a link to gestational diabetes. For our renewal project, we propose to expand our study population by analyzing an additional 750 2nd trimester pregnancy samples, 300 of the samples matched to our original 3rd trimester samples. We will contribute to improved understanding of the prenatal chemical exposome by integrating NTA with improved computational methods including a chemical suspect database ~1,000,000 exogenous and endogenous chemical features in combination with upgraded software for supercomputing to identify ~500 chemical prenatal exposures and estimate their concentrations using new machine learning algorithms. We will use this data to characterize complex relationships between multiple exogenous chemical exposures, endogenous effect biomarkers, and maternal and perinatal health outcomes. The overarching goal of this renewal is to develop an integrated package of analytic and computational tools that allow expanded capacity to identify and calculate chemical concentrations and their link to adverse maternal and pregnancy outcomes, critical to information public health interventions to prevent harmful chemical exposures.