Methods for Data Integration and Risk Assessment for Environmental Mixtures

项目摘要 人类经常暴露在化学和其他环境因素的混合物中，使 量化与环境混合物有关的健康影响是确定 充分保护人类健康的环境政策。推进混合物科学研究需要 环境健康跨学科创新：暴露科学、风险统计方法 毒理学和流行病学中的评估，以及风险评估。因此，这项提案构成了三个结构 跨越混合物科学主要需求的具体目标：暴露生物学(GOOD的发展 环境混合物的生物标记物)，与出生前和产后暴露于 儿童健康中的环境混合物以及改善儿童健康风险评估指导值的方法 混合体，以改善环境政策。具体地说，结合曝光计时的关键方面，在 目标1我们将(1)开发将来自研究的信息与高度时间分辨率相结合的方法 关于接触更具时间针对性的生物标志物措施的研究的信息；和(2)制定 将同一研究中不同时间尺度的暴露的多个生物标志物结合在一起的方法。 有了关于曝光混合物的新的时间分辨数据，在目标2中，我们将开发新的类别 可以评估以下两种情况之一的模型：(1)一次暴露是否可以使一个人变得更有活力 易同时接触或随后接触化学物质，或(2)暴露于营养物质或其他“保护性”物质 在给定的时间暴露可以缓冲个人对在其他地方经历的化学暴露的耐受性 泰晤士报。然而，简单地识别通过流行病学数据证明是不良行为的化学物质就能做到 没有充分告知公众健康风险评估人员有关环境暴露的“可接受范围” 消费品，这是监管指导方针的基础。在目标3中，我们将开发新的课程 将监管指导值纳入和评估暴露对健康影响的分析的模型 化学和营养混合物。该项目的关键是访问来自两个正在进行的项目的激励数据 儿童发育的妊娠队列研究。这项进展研究是墨西哥城的一个队列。牙 来自这些儿童的生物标记物提供了围产期接触金属的高时间分辨率记录。这个 SELMA研究是瑞典一项使用产前内分泌干扰物(EDC)的大型妊娠队列研究 可获得的暴露和饮食数据，使测试良好的潜在缓解效果成为可能 内分泌细胞的营养对健康的影响。

Project Summary Humans are routinely exposed to mixtures of chemical and other environmental factors, making the quantification of health effects associated with environmental mixtures a critical goal for establishing environmental policy sufficiently protective of human health. Advancing research on mixtures science requires innovation across a span of disciplines in environmental health: exposure science, statistical methods for risk estimation in toxicology and epidemiology, and risk assessment. Accordingly, this proposal structures three specific aims spanning the primary needs in mixtures science: exposure biology (the development of good biomarkers for environmental mixtures), estimation of risk associated with pre- and post-natal exposures to environmental mixtures in children's health, and methods for improving guidance values in risk assessment of mixtures to improve environmental policy. Specifically, incorporating the critical aspect of exposure timing, in Aim 1 we will (1) develop methods that integrate information from studies with highly temporally resolved information on exposure into studies with more temporally targeted biomarker measures; and (2) develop methods that incorporate multiple biomarkers of exposure at varying temporal scales within the same study. Armed with new temporally resolved data on exposure mixtures, in Aim 2, we will develop new classes of models that can assess whether either (1) exposure at one time can “prime” an individual to be more susceptible to a concurrent or subsequent chemical exposure, or (2) exposure to a nutrient or other “protective” exposure at a given time can buffer an individual's tolerance to chemical exposures experienced at other times. However, simply identifying chemicals that are bad actors evidenced through epidemiology data does not adequately inform public health risk assessors about “acceptable ranges” of environmental exposures from consumer products, which is fundamental to regulatory guidelines. In Aim 3, we will develop new classes of models that incorporate and evaluate regulatory guideline values into analyses of health effects of exposure to chemical and nutritional mixtures. Essential to this project is access to motivating data from two on-going pregnancy cohort studies of child development. The PROGRESS study is a cohort in Mexico City. Teeth biomarkers from these children provide a high temporal-resolution record of perinatal exposures to metals. The SELMA study is a large pregnancy cohort in Sweden with prenatal endocrine disrupting chemicals (EDC) exposure and dietary data available, making it possible to test for the potential mitigating effect of good nutrition on health effects from EDCs.