Examining dietary modifiers of associations between air pollution and autism-related outcomes in two cohorts

项目摘要 产前空气污染暴露已多次被确定为自闭症谱系障碍（ASD）的风险因素， 支持与直径小于2.5微米的颗粒物（PM2.5）、臭氧和 二氧化氮（NO2）。其他领域的研究表明，饮食可能是空气污染风险的关键调节剂， 与自闭症相关的途径，但只有一项研究，检查叶酸和空气污染的联合影响， 关于ASD风险然而，一系列的饮食因素除了叶酸，包括多不饱和脂肪酸 （PUFA）和维生素D可能有助于抵消暴露的影响。此外，鉴于营养素不起作用， 如果将营养物与污染物隔离开来，研究单一营养物与污染物的相互作用可能只能提供部分情况。此外，时间- 这种修改的窗口尚未确定。在拟议的研究中，我们将解决这些差距， 研究产前饮食如何改变空气污染物与ASD相关结果的关系， 同伙护士健康研究3（NHS 3）是一项正在进行的大型前瞻性护士队列研究， 包括妊娠子队列的US（n> 7，000）。早期自闭症风险纵向调查（Early Autism Risk Longitudinal Investigation，EARLI） 是一个高风险的队列，跟踪那些已经有一个ASD孩子的母亲， 直到孩子3岁（n~200）。ASD相关结局将在两项研究中获得， 反应量表（SRS）评分以及ASD诊断，使我们能够考虑两个维度的特征 和诊断水平的风险。两项研究都将有空气污染暴露分配， PM2.5、NO2和臭氧来自同一方法，产前营养数据来自经验证的食物频率 问卷调查利用这些数据，我们的目标是：1）检查空气污染-ASD协会的修改， 叶酸、维生素D和多不饱和脂肪酸; 2）评估空气污染物和营养素对ASD相关疾病的相互作用。 多重暴露框架内的结果; 3）检查空气污染与ASD关系的时间窗口 饮食中的营养成分可能是最有效的。目标1分析将使用线性和逻辑回归来检查 分别与SRS评分和ASD诊断在营养缺乏定义的分层内的相关性 每个队列中的状态和先前的相互作用。在目标2中，我们将使用贝叶斯核机器回归（BKMR） 在更广泛的饮食背景下考虑营养素-污染物相互作用，考虑更广泛的营养素 并考虑对ASD结果的潜在综合影响。在目标3中，我们将使用分布式滞后模型来 考虑空气污染物与ASD相关结果的潜在关键窗口，其中营养素 改性剂可能具有最强的效果。在这个建议中，我们解决了一个关键的，但研究不足的研究领域。 由于空气污染暴露的广泛发生，并且由于饮食是容易获得的，个人- 水平的可变因素，该项目的研究结果提出了一个大的公共卫生影响的潜力。

PROJECT SUMMARY Prenatal air pollution exposure has been repeatedly identified as risk factor for autism spectrum disorder (ASD), with support for associations with particulate matter less than 2.5 microns in diameter (PM2.5), ozone, and nitrogen dioxide (NO2). Research from other fields suggests diet may be a key modulator of air pollution risks in pathways relevant to autism, yet only one study, examining the joint effects of folate and air pollution, has been published on ASD risk. However, a range of dietary factors beyond folate, including polyunsaturated fatty acids (PUFAs) and vitamin D, may serve to offset effects of exposures. In addition, given that nutrients do not act in isolation, studying single nutrient-pollutant interactions may provide only part of the picture. Further, time- windows for such modification have not been identified. In the proposed study, we will address these gaps and examine how prenatal diet may modify air pollutant associations with ASD-related outcomes in two prospective cohorts. The Nurses’ Health Study 3 (NHS3) is an ongoing, large prospective cohort of nurses from across the US that includes a pregnancy sub-cohort (n>7,000). The Early Autism Risk Longitudinal Investigation (EARLI) is a high-risk cohort that followed mothers who already had a child with ASD through a subsequent pregnancy until that child was age 3 (n~200). ASD-related outcomes will be captured in both studies according to Social Responsiveness Scale (SRS) scores, as well as ASD diagnosis, allowing us to consider both dimensional traits across the population and diagnostic-level risks. Both studies will have air pollution exposure assignments for PM2.5, NO2, and ozone from the same method and prenatal nutrient data from validated food frequency questionnaires. Using these data, our aims are to: 1) Examine modification of air pollutant-ASD associations by folate, vitamin D, and PUFAs; 2) Evaluate interactions between air pollutants and nutrients on ASD-related outcomes within a multi-exposure framework; and 3) Examine time windows in the air pollution-ASD relationship when dietary nutrients might be most impactful. Aim 1 analyses will use linear and logistic regression to examine associations with SRS scores and ASD diagnosis, respectively, within strata of nutrients defined by deficiency status and prior interaction in each cohort. In Aim 2, we will use Bayesian Kernel Machine Regression (BKMR) to consider nutrient-pollutant interactions within the context of broader diet, accounting for a wider set of nutrients and considering potential combined effects on ASD outcomes. In Aim 3, we will use distributed lag models to consider potential critical windows of air pollutant associations with ASD-related outcomes in which nutrient modifiers may have strongest effects. In this proposal we address a critical, yet understudied, area of research. Due to the widespread occurrence of air pollution exposure, and because diet is a readily accessible, individual- level modifiable factor, findings from this project present the potential for a large public health impact.