Discovery of early life causes of autism spectrum disorder through retrospective metabolomics and proteome analysis of teeth

通过牙齿的回顾性代谢组学和蛋白质组分析发现自闭症谱系障碍的早期原因

• 批准号: 9809324
• 负责人: Syam S Andra
• 金额: $ 21.19万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9809324
• 关键词: 1 year old; Address; Affect; Biochemical; Biological; Biological Assay; Biological Markers; Blood; Chemicals; Child; Child Health; Childhood Acute Lymphocytic Leukemia; Clinical; Data; Development; Developmental Biology; Diagnosis; Direct Repeats; Disease; Early Diagnosis; Emerging Technologies; Environmental Exposure; Environmental Risk Factor; Etiology; Event; Exposure to; Eye Movements; Foundations; Genetic; Goals; Growth; Incidence; Individual; Inflammation; Investigation; Knowledge; Laboratories; Life; Link; Maps; Measurement; Measures; Metabolic; Metabolism; Metals; Methodology; Methods; Neonatal; Neurobiology; Neurologic Process; Nutrient; Onset of illness; Oxidative Stress; Participant; Pathway interactions; Population; Predisposition; Pregnancy; Prevalence; Process; Protein Analysis; Proteins; Proteome; Proteomics; Public Health; Questionnaires; Sample Size; Sampling; Second Pregnancy Trimester; Siblings; Statistical Methods; Stress; Sum; Techniques; Technology; Testing; Third Pregnancy Trimester; Time; Tooth Diseases; Tooth structure; Toxic effect; Trees; Twin Multiple Birth; Umbilical Cord Blood; Work; autism spectrum disorder; base; brain morphology; case control; cohort; design; disorder risk; early childhood; early life exposure; environmental chemical; fetal; high dimensionality; insight; interest; metabolome; metabolomics; metal metabolism; novel; postnatal development; postnatal period; prenatal; prenatal exposure; response; small molecule; temporal measurement; therapeutic target; treatment strategy

Summary/Abstract: Autism spectrum disorder (ASD) is a heterogeneous disease with an unknown etiology. The global increase in ASD incidence suggests that genetics alone is unlikely to be the major driver of ASD, but that the increased prevalence is likely due to altered exposures to environmental factors. In fact, we know that numerous environmental exposures (nutrients, chemicals, stress, etc.) impact child health, typically exerting their toxicity through either metabolites or perturbations in endogenous pathways, making metabolomics and protein analysis key emerging technologies to elucidate the relationships between these exposures and ASD. But how do we directly measure these early life exposures? Central to our study is the use of novel tooth matrix biomarkers, which take advantage of the incremental manner (similar to tree growth rings) of the developmental biology of teeth. The techniques that we have developed allow us to temporally distinguish exposure between the 2nd trimester, 3rd trimesters, and postnatal periods, enabling identification of the sensitive life stages for biological perturbations in fetal and neonatal development most strongly associated with ASD risk. For the present application, we will perform the first untargeted metabolomics analysis of ASD teeth to delineate unique alterations in corresponding autism and non-autism children. This will be supported by the first targeted highly multiplexed protein analysis of teeth (92 proteins) for delineating biological pathways of interest, including inflammation, oxidative stress and those associated with neurobiological processes. We will use novel statistical methodology, weighted quantile sum regression (WQS) that addresses time-varying effects of high-dimensional mixtures, and increases power when compared to traditional methods to discover biomarkers and biological pathways associated with ASD. Discovery will be performed on 40 ASD case-control sibling pairs, and replication on an independent population of 35 unrelated case-control pairs. Our method is a non-invasive advancement in technology to obtain direct and repeated measures of biomarkers associated with early life etiology of ASD.

摘要/摘要： 自闭症谱系障碍(ASD)是一种病因不明的异质性疾病。在全球范围内 ASD的发病率表明，基因本身不太可能是ASD的主要驱动因素，但增加的 患病率可能是由于暴露于环境因素的改变造成的。事实上，我们知道有很多人 环境暴露(营养素、化学物质、压力等)影响儿童健康，通常会产生毒性 通过代谢产物或内源途径的扰动，使代谢组学和蛋白质 分析关键的新兴技术，以阐明这些暴露与ASD之间的关系。但如何做到呢 我们是否直接测量了这些早期的生活暴露？我们研究的中心是使用新的牙齿基质 生物标志物，它利用了树的生长年轮的增量方式 牙齿发育生物学。我们开发的技术使我们能够在时间上区分 第二个三个月、第三个三个月和产后期间之间的暴露，使识别 胎儿和新生儿发育中生物扰动的敏感生命阶段与最密切相关 患有自闭症的风险。对于目前的应用，我们将进行第一次ASD的非靶向代谢组学分析 牙齿描绘相应的自闭症和非自闭症儿童的独特变化。这将得到支持 通过首次对牙齿(92种蛋白质)进行靶向高度多元化的蛋白质分析来描述生物途径 值得注意的问题，包括炎症、氧化应激和与神经生物学过程相关的那些。我们 将使用新的统计方法，即加权分位数和回归(WQS)，以解决时变问题 高维混合物的效果，与传统的发现方法相比，提高了功率 与ASD相关的生物标志物和生物学途径。Discovery将在40例ASD病例对照中进行 兄弟姐妹对，以及在35个不相关病例对照对的独立群体上复制。我们的方法是 非侵入性技术进步，以获得相关生物标志物的直接和重复测量 与ASD的早期生活病因学。