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

使用新颖的生物信息学方法和代谢组学通过质谱进行自闭症谱系障碍的环境关联研究

• 批准号: 9275026
• 负责人: Sek Won Kong
• 金额: $ 40.61万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9275026
• 关键词: Address; Age; Air; Area; Autistic Disorder; Behavior; Bioinformatics; Biological; Biological Markers; Biological Monitoring; Birth; Blood; Boston; Catalogs; Characteristics; Chemicals; Chemistry; Child; Cohort Studies; Communities; Consent; Coupled; DNA Methylation; DNA Microarray Chip; DNA Sequence; Data; Diagnosis; Diet; Disease; Electronic Health Record; Environment; Environmental Epidemiology; Environmental Exposure; Environmental Risk Factor; Epigenetic Process; Ethanol; Etiology; Exposure to; Follow-Up Studies; Gene Expression; Genes; Genetic; Genetic Predisposition to Disease; Genetic Risk; Genome; Genomics; Goals; Heritability; Human; Individual; Inherited; Investigation; Joints; Lead; Liquid Chromatography; Longevity; Mass Fragmentography; Mass Spectrum Analysis; Measures; Metabolic; Methods; Methylmercury Compounds; Molecular Weight; Monitor; Mothers; Nature; Neurodevelopmental Disorder; Neuropsychology; Outcome; Parents; Patients; Pediatric Hospitals; Pediatrics; Performance; Pharmaceutical Preparations; Pharmacology; Phenotype; Plasma; Prevalence; Process; Recording of previous events; Recruitment Activity; Research; Resolution; Risk; Rubella virus; Sampling; Serum; Severities; Subgroup; Systems Biology; Toxic Environmental Substances; Toxicology; Twin Studies; Valproic Acid; Variant; Water Pollutants; Work; autism spectrum disorder; base; biomarker discovery; cohort; disorder control; disorder risk; environmental chemical; gene function; genome sequencing; in utero; metabolic profile; metabolome; metabolomics; microbiome; novel; nutrition; proband; public health relevance; response; transcriptome

 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.

 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。过去十年中，美国 ASD 患病率以惊人的速度增长，而英国的患病率在 20 世纪 90 年代增加了五倍后，过去十年相对稳定。诊断时的年轻化仅占患病率增加的 12%，仅包容性诊断（增加了 56%）无法解释过去十年的增加率。此外，最近关于遗传性的双胞胎研究承认，共同的环境因素可以解释相对于遗传性（38％-49％）的责任方差（41-52％）的较大比例。因此，遗传因素解释的方差可能等于或小于环境风险因素的方差。我们已经描述了自闭症谱系障碍（ASD）的血液基因表达变化，并发现了自闭症谱系障碍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，由于个人暴露历史的固有变异性，尚未建立测量个人暴露的统一技术平台。我们开发了一种新型气相色谱-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分析效率。 空间覆盖。为了分析 ASD 中的暴露组范围内的关联，我们开发了一个“全环境关联研究”(EWAS) 框架，以数据驱动的方式搜索 ASD 患者的暴露情况，将多种环境暴露（例如，N = 250 至 1000）反复与疾病状态相关联。我们将利用由波士顿儿童医院招募的同意儿童组成的独特且预先存在的队列来进行 EWAS（目标 1），检查母亲之间的暴露与其子女“遗传”之间的关系（目标 2），并研究暴露组与基因组之间的相互作用（目标 3）。拟议研究的结果将解决促进 ASD 和基于暴露组的研究的环境风险因素的三个关键问题。首先，我们将讨论可以测量的内容。将创建可在母体和先证者血液中稳定测量的候选环境化学物质目录，并 传播给科学界。其次，我们将发现哪些环境风险因素与自闭症谱系障碍相关。最后，我们的研究结果将提供初步数据，以支持该研究领域在完成拟议项目后急需的后续研究：1）执行纵向出生队列研究，以检查本提案中 EWAS 中发现的环境风险因素所解释的风险，以及 2）调查 EWAS 识别的因素如何改变遗传易感性 自闭症谱系障碍。