Georgopoulos Panos G, Sasso Alan F, Isukapalli Sastry S, Lioy Paul J, Vallero Daniel A, Okino Miles, Reiter Larry
Environmental and Occupational Health Sciences Institute (EOHSI), a joint institute of UMDNJ-RW Johnson Medical School & Rutgers University, Piscataway, NJ 08854, USA.
J Expo Sci Environ Epidemiol. 2009 Feb;19(2):149-71. doi: 10.1038/jes.2008.9. Epub 2008 Mar 26.
A conceptual/computational framework for exposure reconstruction from biomarker data combined with auxiliary exposure-related data is presented, evaluated with example applications, and examined in the context of future needs and opportunities. This framework employs physiologically based toxicokinetic (PBTK) modeling in conjunction with numerical "inversion" techniques. To quantify the value of different types of exposure data "accompanying" biomarker data, a study was conducted focusing on reconstructing exposures to chlorpyrifos, from measurements of its metabolite levels in urine. The study employed biomarker data as well as supporting exposure-related information from the National Human Exposure Assessment Survey (NHEXAS), Maryland, while the MENTOR-3P system (Modeling ENvironment for TOtal Risk with Physiologically based Pharmacokinetic modeling for Populations) was used for PBTK modeling. Recently proposed, simple numerical reconstruction methods were applied in this study, in conjunction with PBTK models. Two types of reconstructions were studied using (a) just the available biomarker and supporting exposure data and (b) synthetic data developed via augmenting available observations. Reconstruction using only available data resulted in a wide range of variation in estimated exposures. Reconstruction using synthetic data facilitated evaluation of numerical inversion methods and characterization of the value of additional information, such as study-specific data that can be collected in conjunction with the biomarker data. Although the NHEXAS data set provides a significant amount of supporting exposure-related information, especially when compared to national studies such as the National Health and Nutrition Examination Survey (NHANES), this information is still not adequate for detailed reconstruction of exposures under several conditions, as demonstrated here. The analysis presented here provides a starting point for introducing improved designs for future biomonitoring studies, from the perspective of exposure reconstruction; identifies specific limitations in existing exposure reconstruction methods that can be applied to population biomarker data; and suggests potential approaches for addressing exposure reconstruction from such data.
本文提出了一个用于从生物标志物数据结合辅助暴露相关数据进行暴露重建的概念性/计算框架，通过示例应用对其进行了评估，并在未来需求和机遇的背景下进行了审视。该框架采用基于生理的毒代动力学（PBTK）模型结合数值“反演”技术。为了量化“伴随”生物标志物数据的不同类型暴露数据的价值，开展了一项研究，重点是根据尿液中氯吡硫磷代谢物水平的测量来重建对氯吡硫磷的暴露。该研究采用了生物标志物数据以及来自马里兰州国家人类暴露评估调查（NHEXAS）的支持性暴露相关信息，同时使用MENTOR - 3P系统（用于人群基于生理的药代动力学建模的总风险建模环境）进行PBTK建模。本研究应用了最近提出的简单数值重建方法，并结合PBTK模型。使用（a）仅可用的生物标志物和支持性暴露数据以及（b）通过扩充可用观测值开发的合成数据进行了两种类型的重建研究。仅使用可用数据进行重建导致估计暴露值有很大差异。使用合成数据进行重建有助于评估数值反演方法并表征额外信息的价值，例如可以与生物标志物数据一起收集的特定研究数据。尽管NHEXAS数据集提供了大量支持性暴露相关信息，特别是与诸如国家健康和营养检查调查（NHANES）等全国性研究相比，但如此处所示，在几种情况下，这些信息对于详细重建暴露仍然不足。此处呈现的分析从暴露重建的角度为引入未来生物监测研究的改进设计提供了一个起点；识别了可应用于人群生物标志物数据的现有暴露重建方法中的具体局限性；并提出了从此类数据进行暴露重建的潜在方法。
