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National Institute of Environmental Health Sciences

 

Harvard School of Public Health: Details

Superfund Research Program

Epidemiology of Developmental Windows, Metal Mixtures and Neurodevelopment

Project Leaders: David C. Bellinger, David C. Christiani
Grant Number: P42ES16454
Funding Period: 2010-2015
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Summary

While lead poisoning has been extensively studied, exposure levels remain elevated in many vulnerable populations. Other toxic metals such as arsenic and manganese are also elevated in the environment, but their effects on neurodevelopment are poorly understood. Perhaps more importantly, the effects of mixed metal exposures are poorly understood, yet this exposure scenario is most reflective of the real world.

In this project, researchers pool data and resources from three cohort studies of metals and neurodevelopment. One in a developing country-Bangladesh, where metal exposures are unusually high; one in Mexico, a middle income country where metal exposures are moderately high; and one in the United States-Tar Creek, OK, where exposures are representative of a community near a US toxic waste site. These cohorts allow researchers to overcome barriers that prevented research in both metal mixtures and the role of developmental windows in neurotoxicology. The program has a final sample size of 2600 children with prospective data on metal exposure, and repeated neurophenotype measures. This gives the researchers sufficient power to model the effects of joint exposures to As/Pb, As/Mn and Mn/Pb and their three-way interactions on neurodevelopment. In addition, as the researchers have longitudinal exposure data, they can compare the effects of metal exposure during different developmental windows (i.e. pre vs. post-natal exposure) on neurodevelopment.

This project is also integrated with the nonbiomedial projects. For example, researchers will partner with Drs. Charles Harvey and Brent Coull to test the effect of deep wells on As/Mn biomarker levels in Bangladesh. They also partner with Drs. James Shrine and Brent Coull to validate statistical methods for site characterization and the incorporation of bioavailability/metal speciation data into geospatial models of exposure assessment at the Tar Creek Superfund site.

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