Prenatal Exposure to Endocrine Disrupting Chemical Mixtures and ASD Risk

由于每68名美国儿童中就有一名患有自闭症，确定可改变的危险因素至关重要。最近的证据来自 双胞胎和家庭研究支持起源于子宫的环境因素的实质性作用 易感的遗传因素。出生前大脑发育受激素机制的影响很大，而且 内分泌干扰物(EDCs)穿过胎盘到达没有完全能力的胎儿 代谢和清除外源生物。接触EDCs是无处不在的，这种接触与 广泛的神经发育不良后果。目前有证据表明内分泌细胞是自闭症的危险因素。 更有限，主要是考虑到在关键时期需要足够的样本量和暴露评估 窗户。在研究内分泌细胞对ASD的潜在影响时，考虑内分泌细胞也可能特别重要 作为混合物。这是因为低剂量暴露仍然影响荷尔蒙水平，荷尔蒙水平的微小变化 已知具有重要的生物学后果，EDC混合物的综合影响超过 预期来自可比水平的单一EDC暴露或假设简单相加效应的模型 在混合物成分中。拟议的项目独特而高效地利用了电子数据中心的可用性 在两个类似设计的怀孕队列(HOME和EARLI队列)中暴露生物标记物，以便 对474名母子双方产前接触EDC混合物和ASD相关表型进行研究。校长 结果将是社会响应性量表(SRS)，这是一种经过验证的父母报告测量 自闭症的特征。我们将使用一种新的两步统计方法结合贝叶斯核机器回归 (BKMR)使用弹性净值正则化来评估EDC混合物的累积效果并突出特定的 推动混合物产生的化学物质--理解这些环境影响的关键优先事项 曝光。这一方法将应用于73个EDC的可用生物标志物。我们还将重新运行 这种建模方法根据性别、认知状态和有无年长的人来定义 患有自闭症的兄弟姐妹(EARLI中的所有受试者都影响了年长的兄弟姐妹)，以探索效果改变。 最后，由于产前孕妇甲状腺激素紊乱与神经发育有关 结果，我们将应用我们的建模方法来估计复杂的EDC混合物与母体 探索性分析中的产前甲状腺激素水平。将对子组进行敏感性分析 符合ASD诊断标准的儿童。这项研究将调查一类流行的、可修改的候选人 通过生物标志物评估的环境ASD危险因素。我们的工作将是最大的前瞻性研究 到目前为止，EDC混合物对ASD相关结局的影响是首批采用最新先进技术的公司之一 认识到混合物暴露的复杂性的分析方法；因此，这里的发现有可能 大大提高了我们对内分泌细胞在不利神经发育中的作用的理解。

With 1 in 68 US children affected by ASD, it is critical to identify modifiable risk factors. Recent evidence from twin and family studies supports a substantive role for environmental factors originating in utero in addition to predisposing genetic factors. Prenatal brain development is heavily influenced by hormonal mechanisms, and endocrine disrupting chemicals (EDCs) cross the placenta to reach a fetus that is without full capacity to metabolize and clear xenobiotics. Exposure to EDCs is ubiquitous, and such exposure has been linked to a broad range of adverse neurodevelopmental outcomes. The evidence for EDCs as an ASD risk factor is currently more limited, largely given the need for sufficient sample sizes and exposure assessments during critical windows. In studying potential impacts of EDCs on ASD, it may also be particularly important to consider EDCs as mixtures. This is because low-dose exposure still affects hormone levels, small changes in hormone levels are known to have biologically important consequences, and combined effects of EDC mixtures exceed those expected from single EDC exposures at comparable levels or from models assuming simple additive effects among mixture components. The proposed project uniquely and efficiently leverages the availability of EDC exposure biomarkers in two similarly designed pregnancy cohorts (the HOME and EARLI cohorts) in order to study prenatal EDC mixture exposure and ASD-related phenotype in 474 maternal child dyads. The principal outcome will be the Social Responsiveness Scale (SRS), a validated parent-report measure of quantitative autism traits. We will use a novel two-step statistical approach combining Bayesian Kernel Machine Regression (BKMR) with elastic net regularization to assess the cumulative effect of EDC mixtures and to highlight specific chemicals driving the mixture association - key priorities for understanding the impact of these environmental exposures. This approach will be applied to available biomarkers for a group of 73 EDCs. We will also re-run this modeling approach in subgroups defined by sex, cognitive status, and presence or absence of an older sibling with an ASD (all subjects in EARLI have affected older siblings) in order to explore effect modification. Finally, because prenatal maternal thyroid hormone disruption has been linked to neurodevelopmental outcomes, we will apply our modeling approach to estimate complex EDC mixture associations with maternal prenatal thyroid hormone levels in exploratory analyses. Sensitivity analyses will be performed on the subgroup of children meeting ASD diagnostic criteria. This study will investigate a prevalent, modifiable class of candidate environmental ASD risk factors as assessed through biomarkers. Our work will be the largest prospective study to date of EDC mixture effects on ASD-related outcomes and among the first to employ the latest sophisticated analytic methods that acknowledge the complexity of mixture exposure; thus, findings here have the potential to substantially advance our understanding of the role of EDCs in adverse neurodevelopment.