Methods for Data Integration and Risk Assessment for Environmental Mixtures

项目摘要 人类经常暴露于化学和其他环境因素的混合物中， 与环境混合物相关的健康影响的量化是建立 充分保护人类健康的环境政策。推进混合物科学的研究需要 环境健康跨学科创新：暴露科学、风险统计方法 毒理学和流行病学评估以及风险评估。因此，本提案提出了三个 具体目标跨越混合物科学的主要需求：暴露生物学（良好的发展 环境混合物的生物标志物），估计与产前和产后接触 环境混合物对儿童健康的影响，以及改进环境混合物风险评估指导值的方法， 混合物，以改善环境政策。具体来说，将曝光时间的关键方面， 目标1我们将（1）开发方法，整合来自高时间分辨率研究的信息， 关于在时间上更具针对性的生物标志物测量的研究中暴露的信息;以及（2）制定 在同一项研究中，在不同的时间尺度上结合多种暴露生物标志物的方法。 在目标2中，有了关于暴露混合物的新的时间分辨数据，我们将开发新的 这些模型可以评估（1）一次暴露是否可以“激发”一个人， 易受同时或随后的化学品暴露的影响，或（2）暴露于营养素或其他"保护性" 在特定时间的接触可以缓冲个人对其他时间经历的化学品接触的耐受性。 次然而，通过流行病学数据证明，仅仅确定化学品是有害因素， 没有充分告知公共健康风险评估人员环境暴露的"可接受范围"， 消费品，这是监管准则的基础。在目标3中，我们将开发新的 将监管指南值纳入分析暴露于以下物质的健康影响的模型， 化学和营养混合物。这个项目的关键是获得两个正在进行的激励数据， 儿童发育的妊娠队列研究。PROGRESS研究是墨西哥城的一项队列研究。牙齿 这些儿童的生物标志物提供了围产期金属暴露的高时间分辨率记录。的 SELMA研究是瑞典一项产前内分泌干扰物（EDC）的大型妊娠队列研究 现有的接触和饮食数据，使之有可能测试良好的食品的潜在缓解作用。 营养对内分泌干扰物的健康影响。

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.