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

揭示不同产前人群的环境化学暴露及其与孕产妇和围产期健康的关系 (REVEAL)

• 批准号: 10587408
• 负责人: Tracey J. Woodruff
• 金额: $ 59.41万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10587408
• 关键词: Acceleration; Address; Affect; Analytical Chemistry; Binding; Biological; Biological Markers; Biological Monitoring; Birth Weight; Blood; Blood specimen; Chemical Exposure; Chemicals; Complex; Computational Technique; Computer software; Computing Methodologies; Concentration measurement; Data; Data Analyses; Databases; Development; Disease; Environmental Exposure; Evaluation; Exposure to; Gestational Age; Gestational Diabetes; Goals; Health; Human; Late pregnancy; Left; Link; Low Birth Weight Infant; Mass Spectrum Analysis; Maternal Health; Measurement; Measures; Methods; Modeling; Newborn Infant; Outcome; Output; Participant; Pathway interactions; Pattern; Persons; Phenotype; Plastics; Poly-fluoroalkyl substances; Population; Population Heterogeneity; Predisposition; Pregnancy; Pregnancy Outcome; Pregnancy Trimesters; Premature Birth; Prevalence; Production; Regulation; Research; Resolution; Risk; Rubber; Sampling; Second Pregnancy Trimester; Serum; Shotguns; Siloxanes; Software Tools; Source; Stains; Supercomputing; Techniques; Technology; Third Pregnancy Trimester; advanced analytics; adverse maternal outcomes; adverse pregnancy outcome; analytical method; analytical tool; chemical group; computerized tools; dashboard; data integration; data tools; environmental chemical; fetal; improved; lipid metabolism; machine learning algorithm; maternal serum; metabolome; novel; novel strategies; open source; perinatal health; perinatal outcomes; personal care products; pregnant; prenatal; prenatal exposure; prevent; public health intervention; study population; surfactant

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.

摘要 - 揭示不同产前人群中的环境化学暴露和 与孕产妇和围产期健康的关系 (REVEAL) 我们的更新应用程序以我们最初的 R01 为基础，通过推进分析化学和计算 更全面地表征产前化学暴露及其与不良母体和胎儿的联系的技术 围产期健康结果（例如妊娠糖尿病、早产和低出生体重）。 结果有所增加，并且与美国人口的产前接触化学物质有关。 广泛的环境化学品，包括塑料相关化学品以及全氟烷基和多氟烷基 物质（PFAS）已被证明会对健康产生不利影响，但技术挑战已经存在 巨大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已注册生产，其中数千种 高产量化学品主要在美国使用，但人类生物监测能力涵盖 在我们之前的 R01 中，我们首创了非靶向分析 (NTA)。 工作流程，使用高分辨率质量显着改进了计算和分析方法 我们是第一个在人口多样化的母婴群体中进行光谱测定（HRMS）的人。 识别出在美国大量使用的孕产妇和新生儿样本中的多种化学物质，这是以前从未有过的 在人体血液样本中检测到，包括个人护理产品和香水中使用的化学物质， 我们还鉴定了 50 多种有限的新型化学品。 没有关于其用途或来源的信息，并发现外源性和 内源性化合物、多种化学组（硅氧烷、PFAS 以及塑料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。 更新项目中，我们建议通过分析另外 750 名第二三个月的患者来扩大我们的研究人群 怀孕样本，其中 300 个样本与我们最初的三个月期样本相匹配，我们将做出贡献。 通过将 NTA 与改进的计算相结合，提高对产前化学暴露组的理解 方法包括化学可疑数据库 ~1,000,000 个外源和内源化学特征 与超级计算升级软件相结合，可识别约 500 种化学产前暴露情况， 我们将使用新的机器学习算法来估计它们的浓度。 多种外源性化学暴露、内源性效应生物标志物和 此次更新的总体目标是制定一个综合的孕产妇和围产期健康结果。 分析和计算工具包，可扩展识别和计算化学物质的能力 浓度及其与不良孕产妇和妊娠结局的联系，对信息公共卫生至关重要 防止有害化学物质暴露的干预措施。

项目成果

Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites.

血清暴露组和代谢组的高斯图形模型揭示了环境化学物质和内源代谢物之间的相互作用。

• 发表时间: 2021-04-07
• 影响因子: 4.6
• 作者: Bessonneau, Vincent;Gerona, Roy R;Trowbridge, Jessica;Grashow, Rachel;Lin, Thomas;Buren, Heather;Morello;Rudel, Ruthann A
• 通讯作者: Rudel, Ruthann A

Translating community-based participatory research into broadscale sociopolitical change: insights from a coalition of women firefighters, scientists, and environmental health advocates.

将基于社区的参与性研究转化为广泛的社会政治变革：女性消防员、科学家和环境健康倡导者联盟的见解。

• 发表时间: 2023-08-30
• 作者: Ohayon, Jennifer Liss;Rasanayagam, Sharima;Rudel, Ruthann A;Patton, Sharyle;Buren, Heather;Stefani, Tony;Trowbridge, Jessica;Clarity, Cassidy;Brody, Julia Green;Morello
• 通讯作者: Morello

Integrating Exposure Knowledge and Serum Suspect Screening as a New Approach to Biomonitoring: An Application in Firefighters and Office Workers.

整合暴露知识和血清疑似筛查作为生物监测的新方法：在消防员和办公室工作人员中的应用。

• 发表时间: 2020
• 影响因子: 11.4
• 作者: Grashow, Rachel;Bessonneau, Vincent;Gerona, Roy R;Wang, Aolin;Trowbridge, Jessica;Lin, Thomas;Buren, Heather;Rudel, Ruthann A;Morello
• 通讯作者: Morello