Methods for Data Integration and Risk Assessment for Environmental Mixtures

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Project Summary Humans are routinely exposed to mixtures of chemical and other environmental factors, making the quantification of health effects associated with environmental mixtures a critical goal for establishing environmental policy sufficiently protective of human health. Advancing research on mixtures science requires innovation across a span of disciplines in environmental health: exposure science, statistical methods for risk estimation in toxicology and epidemiology, and risk assessment. Accordingly, this proposal structures three specific aims spanning the primary needs in mixtures science: exposure biology (the development of good biomarkers for environmental mixtures), estimation of risk associated with pre- and post-natal exposures to environmental mixtures in children's health, and methods for improving guidance values in risk assessment of mixtures to improve environmental policy. Specifically, incorporating the critical aspect of exposure timing, in Aim 1 we will (1) develop methods that integrate information from studies with highly temporally resolved information on exposure into studies with more temporally targeted biomarker measures; and (2) develop methods that incorporate multiple biomarkers of exposure at varying temporal scales within the same study. Armed with new temporally resolved data on exposure mixtures, in Aim 2, we will develop new classes of models that can assess whether either (1) exposure at one time can “prime” an individual to be more susceptible to a concurrent or subsequent chemical exposure, or (2) exposure to a nutrient or other “protective” exposure at a given time can buffer an individual's tolerance to chemical exposures experienced at other times. However, simply identifying chemicals that are bad actors evidenced through epidemiology data does not adequately inform public health risk assessors about “acceptable ranges” of environmental exposures from consumer products, which is fundamental to regulatory guidelines. In Aim 3, we will develop new classes of models that incorporate and evaluate regulatory guideline values into analyses of health effects of exposure to chemical and nutritional mixtures. Essential to this project is access to motivating data from two on-going pregnancy cohort studies of child development. The PROGRESS study is a cohort in Mexico City. Teeth biomarkers from these children provide a high temporal-resolution record of perinatal exposures to metals. The SELMA study is a large pregnancy cohort in Sweden with prenatal endocrine disrupting chemicals (EDC) exposure and dietary data available, making it possible to test for the potential mitigating effect of good nutrition on health effects from EDCs.