Development of a predictive two-generation model to characterize prenatal and postnatal exposure to chemicals and their metabolites

开发预测两代模型来表征化学品及其代谢物的产前和产后暴露

• 批准号: RGPIN-2016-06101
• 负责人: Verner, MarcAndré
• 金额: $ 2.4万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=616099
• 关键词: Development; predictive; two; generation; model

Several chemicals, like polychlorinated biphenyls and bisphenol A, are routinely detected in cord blood and breast milk from the general population. This indicates that children are exposed to chemicals in the womb and postnatally through breastfeeding. These early-life exposures occur at a time of extensive development (e.g., brain development, immune system maturation) during which the fetus/child is particularly vulnerable to toxic insults. The assessment of children’s exposure to the wide variety of existing chemicals is a huge task. Indeed, more than 85,000 chemicals are currently on the market. In addition, multiple new chemicals enter the market each year. Current approaches to estimate exposure to chemicals, like measuring chemical levels in samples of blood and milk, are too costly and time-consuming to tackle this long list of chemicals. It is therefore paramount to develop novel versatile tools to rapidly evaluate children’s exposure to existing and emerging chemicals. My research program aims to develop predictive mathematical models to estimate mothers’ and children’s exposure to a large array of chemicals based on their chemical structure. These predictive models will allow identifying chemicals that are likely to transfer from the mother to the child across the placenta or through breastfeeding. These models will also be used to quantify the dose to which the developing child is exposed compared to the maternal dose. In addition, decision trees will be developed for non-specialists wishing to rapidly screen chemicals for their potential to reach the developing organism during pregnancy and lactation. The novel tools developed in my laboratory will help circumvent the limitations of current approaches to exposure assessment and inform risk assessors and decision makers in establishing safe exposure levels of existing and emerging chemicals. My research program will fill an important knowledge gap and help protect children from toxic insults.

一些化学物质，如多氯联苯和双酚A，在一般人群的脐带血和母乳中经常检测到。这表明儿童在子宫内和出生后通过母乳喂养接触化学物质。这些早期生活暴露发生在广泛发育的时期（例如，大脑发育、免疫系统成熟），在此期间胎儿/儿童特别容易受到毒性损伤。评估儿童接触各种现有化学品的情况是一项艰巨的任务。事实上，目前市场上有超过85，000种化学品。此外，每年都有多种新化学品进入市场。目前估计化学品暴露的方法，如测量血液和牛奶样本中的化学品水平，对于处理这一长串化学品来说过于昂贵和耗时。因此，至关重要的是开发新的通用工具，以快速评估儿童对现有和新出现的化学品的接触。我的研究项目旨在开发预测数学模型，以根据化学结构估计母亲和儿童接触大量化学物质的情况。这些预测模型将允许识别可能通过胎盘或母乳喂养从母亲转移到孩子身上的化学物质。这些模型还将用于量化与母体剂量相比，发育中儿童所受的剂量。此外，还将为希望快速筛选化学品以确定其在怀孕和哺乳期间进入发育中的生物体的可能性的非专业人员开发决策树。在我的实验室开发的新工具将有助于规避目前暴露评估方法的局限性，并为风险评估人员和决策者提供信息，以确定现有和新出现的化学品的安全暴露水平。我的研究计划将填补一个重要的知识空白，并帮助保护儿童免受有毒的侮辱。