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
基本信息
- 批准号:9809324
- 负责人:
- 金额:$ 21.19万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:1 year oldAddressAffectBiochemicalBiologicalBiological AssayBiological MarkersBloodChemicalsChildChild HealthChildhood Acute Lymphocytic LeukemiaClinicalDataDevelopmentDevelopmental BiologyDiagnosisDirect RepeatsDiseaseEarly DiagnosisEmerging TechnologiesEnvironmental ExposureEnvironmental Risk FactorEtiologyEventExposure toEye MovementsFoundationsGeneticGoalsGrowthIncidenceIndividualInflammationInvestigationKnowledgeLaboratoriesLifeLinkMapsMeasurementMeasuresMetabolicMetabolismMetalsMethodologyMethodsNeonatalNeurobiologyNeurologic ProcessNutrientOnset of illnessOxidative StressParticipantPathway interactionsPopulationPredispositionPregnancyPrevalenceProcessProtein AnalysisProteinsProteomeProteomicsPublic HealthQuestionnairesSample SizeSamplingSecond Pregnancy TrimesterSiblingsStatistical MethodsStressSumTechniquesTechnologyTestingThird Pregnancy TrimesterTimeTooth DiseasesTooth structureToxic effectTreesTwin Multiple BirthUmbilical Cord BloodWorkautism spectrum disorderbasebrain morphologycase controlcohortdesigndisorder riskearly childhoodearly life exposureenvironmental chemicalfetalhigh dimensionalityinsightinterestmetabolomemetabolomicsmetal metabolismnovelpostnatal developmentpostnatal periodprenatalprenatal exposureresponsesmall moleculetemporal measurementtherapeutic targettreatment strategy
项目摘要
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。
项目成果
期刊论文数量(0)
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{{ truncateString('Syam S Andra', 18)}}的其他基金
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:
10000917 - 财政年份:2019
- 资助金额:
$ 21.19万 - 项目类别:
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