Project 1: Effect of Multi-Level Environmental Exposure on Birth Outcomes

项目1的主要数据将来自NIEHS资助的R21(R21 ES 014891-01A1，遗传学和空气污染暴露对出生结果的影响)。R21的A部分使用改进的空气污染和交通密度数据来检查它们对低出生体重和早产等不良生育结果的影响。R21的B部分评估了集合出生队列以提供唾液样本的可行性，以分析对空气污染影响的遗传和表观遗传易感性。在Pre-Center资助期间，我们将从加利福尼亚州圣华金河谷300,000多名新生儿的产前获得额外的空间精细化暴露数据。我们将采用新的统计方法来评估污染物混合物对生育结果可能产生的纵向和联合影响。除了空间细化的空气污染数据、详细的交通计数和密度数据、人口普查和邻里层面 特征，对于一些人口统计变量，将使用模拟的个人水平数据来控制 用于混淆和鉴定易感亚群。它将评估一项类似研究的可行性 旨在检查许多重要的儿童健康结果。结果的例子包括哮喘， 自闭症谱系障碍、癌症和代谢障碍，如肥胖。基因样本将从R21 B部分中确定的母亲/儿童那里获得，并储存起来，以供在全额中心赠款期间进行分析。将进行广泛的调查，以确定可能影响对空气污染影响的易感性的适当遗传多态集合以及与早产有关的遗传多态。将进行类似的调查，以确定基因多态与所列其他健康结果的风险相关。我们选择了一种成本效益高的方法，利用关于特定污染物的空前丰富的暴露数据集(CRPAQS)和现有的出生证明文件，同时为未来的研究开发出生队列和样本库。我们的研究还将利用为同一区域内进行的其他资助研究开发的建模策略。

The primary data for Project 1 will come from an R21 funded by NIEHS (R21 ES 014891-01A1, Influences of genetics and air pollution exposures on birth outcomes.) Part A ofthe R21 uses refined air pollution and traffic density data to examine their influence of on adverse birth outcomes such as low birth weight and premature birth. Part B of the R21 evaluates the feasibility of assembling a birth-cohort to provide saliva samples for the analysis of genetic and epigenetic susceptibility to the effects of air pollution. During the pre-Center funding, we will obtain additional spatially-refined exposure data from the prenatal periods of over 300, 000 birth in the San Joaquin Valley of California. We will implement novel statistical methods to evaluate possible longitudinal and joint of effects of pollutant mixtures on birth outcomes. In addition to the spatially-refined air pollution data, detailed traffic counts and density data, census and neighborhood-level characteristics, and for some demographic variables, simulated individual-level data will be used to control for confounding and identification of susceptible subgroups. It will evaluate the feasibility of a similar study design to examine numerous important children's health outcomes. Examples of outcomes include asthma, autism spectrum disorders, cancer, and metabolic disorders such as obesity. Genetic samples will be obtained from mothers/children identified in Part B ofthe R21 and stored for analysis during a full Center grant. Extensive investigation will be done to identify the proper set of genetic polymorphisms that may influence susceptibility to the effects of air pollution and those that are associated with preterm birth. Similar investigations will be done to identify genetic polymorphism associated with the risk ofthe other health outcomes listed. We have chosen a cost-efficient approach by making use of an exposure dataset of unparalleled richness with respect to specific pollutants (CRPAQS) and existing birth certificates files while at the same time developing a birth cohort and specimen bank for future research. Our study will also make use of modeling strategies developed for other funded studies conducted within the same region.