An environment-wide association study in autism spectrum disorders using novel bioinformatics methods and metabolomics via mass spectrometry

 描述（由申请人提供）：自闭症谱系障碍（ASD）是一种神经发育障碍，90%的病例病因不明。在过去的十年中，ASD的患病率在美国以惊人的速度增加，而在英国，患病率在20世纪90年代增加了五倍后，在过去的十年中一直相对稳定。诊断时年龄较小仅占患病率增加的12%，仅包容性诊断-增加56%-无法解释过去十年的增长率。此外，最近关于遗传性的双胞胎研究已经承认，相对于遗传性（38%-49%），共享的环境因素可能解释更大比例的责任差异（41-52%）。因此，遗传因素解释的方差可能等于或小于环境风险因素。我们已经确定了ASD患者血液基因表达的变化，并发现了ASD和基因组同质亚组的生物标志物。与微阵列和基因组测序不同的是，由于个人暴露历史的固有差异，尚未建立测量个人暴露的统一技术平台。我们已经开发了一种新的气相色谱-质谱（GC-MS）和液相色谱-高分辨率质谱（LC-HRMS）和代谢分析方法来测量人血清中的外源性和内源性低分子量分析物，以最大限度地提高化学空间覆盖率。为了分析ASD中的全人群关联，我们开发了一个“全环境关联研究”（EWAS）框架，以进行数据驱动的搜索，以了解ASD患者的暴露与多种环境暴露（例如，N = 250至1000）与疾病状态迭代。我们将利用一个独特的和预先存在的队列，由在波士顿儿童医院招募的同意儿童组成，以进行EWAS（目标1），检查母亲与子女“继承”之间的暴露关系（目标2），并研究干扰素组和基因组之间的相互作用（目标3）。拟议研究的结果将解决三个关键问题的环境风险因素，促进ASD和基于麻烦的研究。首先，我们将讨论哪些是可以衡量的。一个候选环境化学物质的目录，可以在产妇和先证者的血液稳定测量将创建和传播给科学界。其次，我们将发现哪些环境风险因素与ASD相关。最后，我们的研究结果将提供初步数据，以支持在拟议项目完成后，该研究领域急需的后续研究：1）执行纵向出生队列研究，以检查EWAS中发现的环境风险因素解释的风险，以及2）调查EWAS识别的因素如何修改ASD的遗传易感性。

 DESCRIPTION (provided by applicant): Autism spectrum disorder (ASD) is a neurodevelopmental disorder with unknown etiology in 90% of cases. Over the past decade, the prevalence of ASD has increased at an alarming rate in the U.S. while in the UK the prevalence has been relatively stable in the past decade after a five-fold increase in the 1990s. Younger age at diagnosis only accounts for 12% of increases in prevalence and inclusive diagnosis alone - a 56% increase - cannot explain the increasing rate in the past decade. Moreover, recent twin studies on heritability have acknowledged that shared environmental factors may explain a larger proportion of the variance in liability (41-52%) relative to heritability (38%-49%. Therefore, the variance explained by genetic factors may be equal, or less than, that by environmental risk factors. We have characterized blood gene expression changes in ASD, and discovered biomarkers of ASD and genomically homogeneous subgroups. Unlike microarrays and genome sequencing, a unified technological platform to measure personal exposures has not been established due to the inherent variability in individual exposure history. We have developed a novel gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-high resolution mass spectrometry (LC-HRMS) and metabolic profiling approach to measure exogenous and endogenous low molecular weight analytes in human serum to maximize chemical space coverage. To analyze exposome-wide associations in ASD, we developed an "Environment-Wide Association Study" (EWAS) framework to conduct a data-driven search for exposures in the patients with ASD associate multiple environmental exposures (e.g., N = 250 to 1000) iteratively with disease status. We will leverage a unique and pre-existing cohort consisting of consenting children recruited at Boston Children's Hospital to conduct EWAS (Aim 1), examine the relationship between exposures between mother and "inherited" by their children (Aim 2) and investigate interactions between the exposome and genome (Aim 3). The outcome of the proposed study will address three critical questions of environmental risk factors contributing ASD and exposome-based research. First, we shall address what can be measured. A catalog of candidate environmental chemicals that can be stably measured in maternal and proband's blood will be created and disseminated to the scientific community. Second, we will discover what environmental risk factors are associated with ASD. Finally, our findings will provide preliminary data to support follow-up studies much needed in this area of research after completion of the proposed project: 1) to execute a longitudinal birth cohort studies to examine the risk explained by environmental risk factors found in EWAS in this proposal, and 2) to investigate how EWAS-identified factors modify genetic predisposition for ASD.