Advances In Exposure Assessment Research Articles

Seminar: Functional Exposomics and Mechanisms of Toxicity-Insights from Model Systems and NAMs.

Significant progress has been made over the past decade in measuring the chemical components of the exposome, providing transformative population-scale frameworks in probing the etiologic link between environmental factors and disease phenotypes. While the analytical technologies continue to evolve with reams of data being generated, there is an opportunity to complement exposome-wide association studies (ExWAS) with functional analyses to advance etiologic search at organismal, cellular, and molecular levels. Exposomics is a transdisciplinary field aimed at enabling discovery-based analysis of the nongenetic factors that contribute to disease, including numerous environmental chemical stressors. While advances in exposure assessment are enhancing population-based discovery of exposome-wide effects and chemical exposure agents, functional screening and elucidation of biological effects of exposures represent the next logical step toward precision environmental health and medicine. In this work, we focus on the use, strategies, and prospects of alternative approaches and model systems to enhance the current human exposomics framework in biomarker search and causal understanding, spanning from bench-based nonmammalian organisms and cell culture to computational new approach methods (NAMs). We visit the definition of the functional exposome and exposomics and discuss a need to leverage alternative models as opposed to mammalian animals for delineating exposome-wide health effects. Under the "three Rs" principle of reduction, replacement, and refinement, model systems such as roundworms, fruit flies, zebrafish, and induced pluripotent stem cells (iPSCs) are advantageous over mammals (e.g., rodents or higher vertebrates). These models are cost-effective, and cell-specific genetic manipulations in these models are easier and faster, compared to mammalian models. Meanwhile, in silico NAMs enhance hazard identification and risk assessment in humans by bridging the translational gaps between toxicology data and etiologic inference, as represented by in vitro to in vivo extrapolation (IVIVE) and integrated approaches to testing and assessment (IATA) under the adverse outcome pathway (AOP) framework. Together, these alternatives offer a strong toolbox to support functional exposomics to study toxicity and causal mediators underpinning exposure-disease links. https://doi.org/10.1289/EHP13120.

Large-scale citizen science provides high-resolution nitrogen dioxide values and health impact while enhancing community knowledge and collective action

We present outcomes from a large-scale air quality citizen science campaign (xAire, 725 measurements) to demonstrate its positive contribution in the interplay between advances in exposure assessment and developments in policy or collective action. A broad partnership with 1,650 people from communities around 18 primary schools across Barcelona provided the capacity to obtain unprecedented high-resolution NO2 levels and an updated asthma Health Impact Assessment. It is shown that NO2 levels vary considerably with at some cases very high levels. More than a 1,000 new cases of childhood asthma could be prevented each year by lowering NO2 levels. Representativity of site selection and the minimal number of samplers for land use regression modelling are considered. Enhancement of community knowledge and attitudes towards collective response were observed and identified as key drivers for successful large-scale monitoring campaigns. The results encourage strengthening collaboration with local communities when exploring environmental health issues.

Toxicity testing in the 21st century: progress in the past decade and future perspectives.

Advances in the biological sciences have led to an ongoing paradigm shift in toxicity testing based on expanded application of high-throughput in vitro screening and in silico methods to assess potential health risks of environmental agents. This review examines progress on the vision for toxicity testing elaborated by the US National Research Council (NRC) during the decade that has passed since the 2007 NRC report on Toxicity Testing in the 21st Century (TT21C). Concomitant advances in exposure assessment, including computational approaches and high-throughput exposomics, are also documented. A vision for the next generation of risk science, incorporating risk assessment methodologies suitable for the analysis of new toxicological and exposure data, resulting in human exposure guidelines is described. Case study prototypes indicating how these new approaches to toxicity testing, exposure measurement, and risk assessment are beginning to be applied in practice are presented. Overall, progress on the 20-year transition plan laid out by the US NRC in 2007 has been substantial. Importantly, government agencies within the United States and internationally are beginning to incorporate the new approach methodologies envisaged in the original TT21C vision into regulatory practice. Future perspectives on the continued evolution of toxicity testing to strengthen regulatory risk assessment are provided.

Advances in Comprehensive Exposure Assessment: Opportunities for the US Military.

Review advances in exposure assessment offered by the exposome concept and new -omics and sensor technologies. Narrative review of advances, including current efforts and potential future applications by the US military. Exposure assessment methods from both bottom-up and top-down exposomics approaches are advancing at a rapid pace, and the US military is engaged in developing both approaches. Top-down approaches employ various -omics technologies to identify biomarkers of internal exposure and biological effect. Bottom-up approaches use new sensor technology to better measure external dose. Key challenges of both approaches are largely centered around how to integrate, analyze, and interpret large datasets that are multidimensional and disparate. Advances in -omics and sensor technologies may dramatically enhance exposure assessment and improve our ability to characterize health risks related to occupational and environmental exposures, including for the US military.

Bayesian distributed lag interaction models to identify perinatal windows of vulnerability in children's health.

Epidemiological research supports an association between maternal exposure to air pollution during pregnancy and adverse children's health outcomes. Advances in exposure assessment and statistics allow for estimation of both critical windows of vulnerability and exposure effect heterogeneity. Simultaneous estimation of windows of vulnerability and effect heterogeneity can be accomplished by fitting a distributed lag model (DLM) stratified by subgroup. However, this can provide an incomplete picture of how effects vary across subgroups because it does not allow for subgroups to have the same window but different within-window effects or to have different windows but the same within-window effect. Because the timing of some developmental processes are common across subpopulations of infants while for others the timing differs across subgroups, both scenarios are important to consider when evaluating health risks of prenatal exposures. We propose a new approach that partitions the DLM into a constrained functional predictor that estimates windows of vulnerability and a scalar effect representing the within-window effect directly. The proposed method allows for heterogeneity in only the window, only the within-window effect, or both. In a simulation study we show that a model assuming a shared component across groups results in lower bias and mean squared error for the estimated windows and effects when that component is in fact constant across groups. We apply the proposed method to estimate windows of vulnerability in the association between prenatal exposures to fine particulate matter and each of birth weight and asthma incidence, and estimate how these associations vary by sex and maternal obesity status in a Boston-area prospective pre-birth cohort study.

Bisphenols: More unnecessary surprises

ABSTRACTA recent biomonitoring study “Bisphenol A, Bisphenol S, and 4-Hydroxyphenyl 4-Isoprooxyphenylsulfone (BPSIP) in Urine and Blood of Cashiers” reported on levels of BPA, BPS, and a novel BPS-derivative (BPSIP) in cashiers compared to non-cashiers. Our study was the first to detect BPSIP in humans. In this commentary we discuss our findings in the context of considering bisphenols as a class in health assessments and how technological advances in exposure assessment could be utilized to more efficiently identify emerging chemicals of interest.

Invited Commentary: Extremely Low-Frequency Magnetic Fields and Breast Cancer--Now It Is Enough!

Research on an association between extremely low frequency (ELF) magnetic fields and breast cancer has been conducted since the 1980s, based on the hypothesis that ELF fields suppress melatonin production and melatonin protects against breast cancer development. In this issue of the Journal, Li et al. (Am J Epidemiol. 2013;178(7):1038-1045) present a well-designed study on occupational exposure to ELF fields and breast cancer that adds to the already large pool of data that has not supported the hypothesis. Over time, the quality and statistical power of studies within this research area have increased considerably, and advances in exposure assessment have reduced exposure misclassification. The evidence is consistently negative. A World Health Organization health risk assessment concluded in 2005 that the evidence from experimental and epidemiologic studies is sufficient to give confidence that ELF magnetic fields do not cause breast cancer. The new study adds even more confidence to this conclusion. We should now focus our time and research resources on more promising hypotheses, the results of which could make a difference for public health and advance science. Further epidemiologic studies on ELF fields and breast cancer are likely to have little new knowledge to add.

Monitoring Environmental Exposures: Now It’s Personal

Most diseases are thought to arise from the combined effects of genes and the environment. While great strides have been made in our understanding of human genetics, the contribution of environmental exposures to disease remains poorly understood. This lack of understanding impedes real progress in identifying genetically susceptible people whose responses to environmental agents are severe or unique relative to the general population. If identified, targeted prevention and treatment strategies might be applied to these groups, with potentially lifesaving results. Without more personal exposure information, however, scientists have a limited ability to identify pollution-susceptibility genes that elevate disease risk. This mismatch between exposure and genetic research slows the identification of environmental factors that—if altered or removed—could even prevent some diseases from occurring in the first place. “Genes aren’t modifiable,” explains Frederica Perera, a professor of environmental health sciences at the Mailman School of Public Health of Columbia University. “So, these environmental components in diet, food, water, and air are the only ones we can act on for disease prevention.” Exposure is, at a core level, the instance of environmental stimuli such as chemicals, infectious agents, diet, and lifestyle factors interacting with the human body. But studying human exposures poses difficult challenges. Scientists studying the effects of chemical pollutants can’t ethically dose people, so they often base their dose–response estimates on animal models. Further, they base their estimates of human exposure on indirect measures taken from a person’s home or work environment, along with assumptions about individual behaviors that influence the risk of coming into contact with a given pollutant. In a typical study, epidemiologists might use census figures, questionnaires, and general environmental monitoring data (such as samples of water from a household tap or soil in a schoolyard) to estimate how much of a given chemical an individual has come into contact with, and for how long. But while these studies approximate population-level exposures, they provide little information about real exposures to individual people. And because of this, scientists know little about how specific pollutants—particularly in combination with each other, with diet, and with physical activity—affect any individual’s response to the pollutant. With a clear need for progress, exposure assessment has recently come under the spotlight. This year, the NIEHS launched the Exposure Biology Program (EBP), a four-year effort with two overarching goals: to improve exposure assessment technology, and to identify biomarkers for common pathogenic mechanisms that reflect the human response to environmental agents. Such biomarkers could include changes in metabolites, proteins, or DNA that reflect the individual’s genetic susceptibility to environmental harm. “Right now we don’t really understand how exposure levels translate to human health risk, so our goal is to fill that gap,” says EBP coordinator Brenda Weis, a senior scientific advisor at NIEHS. “We need to get a better measure of exposure at the point of human contact, and we need to integrate those measures with biological response measures derived from samples taken directly from exposed people. So, this is a more ‘medical’ approach to exposure assessment—in the sense that measures are taken on a personal level—rather than the broader, ecological approaches we’ve been using so far.”