Novel Biomarker to Identify Critical Windows of Susceptibility to Metal Mixture

 描述(由申请人提供)：神经发育和认知功能是公共卫生领域最重要的成果之一，特别是随着知识经济的兴起。虽然人们普遍认为，同时存在几种有毒物质暴露可以改变中枢神经系统的发育轨迹，但旨在解决混合化学暴露问题的研究很少，而且代表着公共卫生领域的迫切需要。开展混合物研究固有的多重障碍，如果要在这一领域取得进展，就必须克服这些障碍。明显的障碍包括需要大样本量和预期数据来评估暴露时间(即关键的发展窗口)。另外两个障碍包括风险暴露、分类错误和缺乏统计方法 维度相互作用。我们的提案直接解决了所有这些障碍，并将为研究可广泛应用于环境健康的化学混合物建立一个框架。我们开发了一种新的生物标记物，可以使用乳牙客观地重建过去化学暴露的剂量和时间。该生物标记物不同于标准的牙齿生物标记物，因为它结合了复杂的组织学和化学分析，精确地采样了与特定生命阶段对应的牙本质层，生成了怀孕中期和晚期以及儿童早期的综合、纵向每周暴露估计。作为第一步，我们的提案将解决混合金属敞口问题。然而，我们注意到，我们的方法可以并将在未来应用于有机化学品，我们正在并行开发它们在牙齿中的分析方法。另一方面，我们还将应用尖端的统计机器学习方法。在这项研究中，我们将重点介绍五种对公众健康有意义的金属/金属，即锰(Mn)、铅(Pb)、砷(As)、锌(Zn)和镉(Cd)。我们将在墨西哥的早期生命暴露和神经毒理学(ELENT)中进行这项研究，这是一个预期出生的队列，使用社会科学、遗传学和毒理学的先进方法来评估影响神经发育的跨学科风险因素。

 DESCRIPTION (provided by applicant): Neurodevelopment and cognitive function are among the most important outcomes in public health, particularly with the rise of knowledge-based economies. While it is widely believed that the simultaneous presence of several toxic exposures can alter developmental trajectories of the central nervous system, studies designed to address mixed chemical exposures are rare, and represent a critical need in the field of public health. Multiple barriers are inherent to conducting mixtures research and must be overcome if this field is to progress. Obvious barriers include the need for large sample sizes and prospective data to assess exposure timing (i.e. critical developmental windows). Two additional barriers include exposure misclassification and lack of statistical approaches available for higher dimensional interactions. Our proposal addresses all of these barriers directly and will establish a framework for the study of chemical mixtures that can be applied broadly in environmental health. We have developed a novel biomarker that can objectively reconstruct the dose and timing of past chemical exposure using deciduous teeth. This biomarker differs from standard tooth biomarkers as it combines sophisticated histological and chemical analyses to precisely sample dentine layers corresponding to specific life stages, generating integrated, longitudinal weekly exposure estimates in the second and third trimesters and during early childhood. Our proposal will address mixed metal exposure, as a first step. We note, however, that our approach can and will be applied to organic chemicals in the future, and we are in parallel developing methods for their analysis in teeth. On another front, we will also apply cutting-edge statistical machine learning methods. In this study, we will focus on five metals/metalloids that are of public health significance, manganese (Mn), lead (Pb), arsenic (As), zinc (Zn) and cadmium (Cd). We will conduct this study in the Early Life Exposures in MExico and NeuroToxicology (ELEMENT), a prospective birth cohort using advanced methods in social science, genetics and toxicology to assess transdisciplinary risk factors impacting neurodevelopment.