Impact of pre- and postnatal chemical mixture exposures on child neurobehavior and neuroimaging

项目摘要 在美国和加拿大，六分之一的儿童有一种或多种学习或行为问题，例如 学习障碍、焦虑、自闭症谱系障碍、品行障碍、抑郁或注意力缺陷 多动症(ADHD)。早期大脑发育对毒物暴露很敏感，包括重度毒物 金属、持久性有机污染物和内分泌干扰物。接触混合毒物 环境化学品在儿童中是现实存在的，化学混合物可能有不同的作用模式 影响神经元的增殖、迁移、分化、突触形成/修剪/可塑性、髓鞘形成、 和神经递质，对中枢神经系统造成不利影响。大多数环境问题 流行病学研究只考察了单一化学物质对神经行为结果的影响。 最近混合统计方法的发展和应用将提供巨大的潜力来揭示 单个化学品的影响、化学品之间的相互作用和累积暴露。这些方法 仅应用于对儿童神经行为的有限研究，还没有用于神经成像 结果。我们将使用两个现有的出生队列来检查出生前和出生后暴露于 化学混合物对儿童神经行为的影响。环境的健康结果和措施(家庭) 这项研究是以辛辛那提为基础的400名孕妇的出生队列，她们的孩子被跟踪到12岁，以及 环境化学品母婴研究(MIREC)是加拿大对1983名孕妇的研究 有孩子的妇女被跟踪到9-11岁。这两个北美出生的队列都测量了 60种环境污染物，包括铅、汞、镉、砷、多溴联苯醚、 多氯联苯、全氟烷基物质、有机氯和有机磷农药； 双酚A、邻苯二甲酸酯、三氯生和有机磷阻燃剂，以及儿童认知能力 (n&gt；1000)、行为(n&gt；1000)和神经成像(n=390)。我们将利用先进的统计方法 化学混合物，包括用于变量选择的弹性网络(ENET)、稀疏偏最小二乘(SPLS) 回归用于个体化学效应估计，贝叶斯核机回归(BKMR)用于 相互作用、非线性和联合效应。该项目将是第一批测试和量化 出生前和出生后接触化学混合物对神经行为和 在建立良好的队列中的神经成像结果。这些结果有可能极大地增加我们的 儿童对化学混合物发育神经毒性的认识及其对环境健康的影响 制定政策。

Project Summary One in six children in the U.S. and Canada have one or more learning or behavioral problems, such as learning disability, anxiety, autism spectrum disorder, conduct disorder, depression, or attention deficit hyperactivity disorder (ADHD). Early brain development is sensitive to toxicant exposures, including heavy metals, persistent organic pollutants, and endocrine disrupting chemicals. Exposure to mixtures of environmental chemicals is a reality in children, and chemical mixtures may have different modes of action affecting neuronal proliferation, migration, differentiations, synaptic formation/trimming/plasticity, myelination, and neurotransmitters, resulting in adverse impact on the central nervous system. Majority of environmental epidemiologic studies have only examined the impact of a single chemical on neurobehavioral outcomes. Recent development and application of mixture statistical methods will provide great potential to reveal the impact of an individual chemical, interactions between chemicals, and cumulative exposure. These methods have only been applied in limited studies of child neurobehavior and none has been used for neuroimaging outcomes. We will use two existing birth cohorts to examine the impact of both pre- and postnatal exposures to chemical mixtures on child neurobehavior. The Health Outcomes and Measures of the Environment (HOME) Study is a Cincinnati-based birth cohort of 400 pregnant women with children followed up to age 12 years, and the Maternal-Infant Research on Environmental Chemicals (MIREC) is a Canadian study of 1983 pregnant women with children followed up to age 9-11 years. The two North American birth cohorts both measured over 60 environmental contaminants, including lead, mercury, cadmium, arsenic, polybrominated diphenyl ethers, polychlorinated biphenyls, perfluoroalkyl substances, organochlorine and organophosphate pesticides, bisphenol A, phthalates, triclosan, and organophosphate flame retardants, as well as child cognitive abilities (n>1000), behavior (n>1000), and neuroimaging (n=390). We will utilize advanced statistical methods for chemical mixtures, including Elastic Net (ENET) for variable selection, Sparse Partial Least Squares (SPLS) regression for individual chemical effect estimation, and Bayesian Kernel Machine Regression (BKMR) for interactions, nonlinearities, and joint effects. This project will be among the first to test and quantify the potential impact of prenatal and postnatal exposures to chemical mixtures on neurobehavioral and neuroimaging outcomes in well-established cohorts. The results have the potential to greatly increase our understanding of developmental neurotoxicity of chemical mixtures in children and affect environmental health policy making.