Dataset Information

Bridging environmental mixtures and toxic effects.

ABSTRACT: Biological Response Indicator Devices Gauging Environmental Stressors (BRIDGES) is a bioanalytical tool that combines passive sampling with the embryonic zebrafish developmental toxicity bioassay to provide a quantitative measure of the toxicity of bioavailable complex mixtures. Passive sampling devices (PSDs), which sequester and concentrate bioavailable organic contaminants from the environment, were deployed in the Willamette and Columbia Rivers within and outside of the Portland Harbor Superfund site in Portland, OR, USA. Six sampling events were conducted in the summer and fall of 2009 and 2010. Passive sampling device extracts were analyzed for polycyclic aromatic hydrocarbon (PAH) compounds and screened for 1,201 chemicals of concern using deconvolution-reporting software. The developmental toxicity of the extracts was analyzed using the embryonic zebrafish bioassay. The BRIDGES tool provided site-specific, temporally resolved information about environmental contaminant mixtures and their toxicity. Multivariate modeling approaches were applied to paired chemical and toxic effects data sets to help unravel chemistry-toxicity associations. Modeling elucidated spatial and temporal trends in PAH concentrations and the toxicity of the samples and identified a subset of PAH analytes that were the most highly correlated with observed toxicity. Although the present study highlights the complexity of discerning specific bioactive compounds in complex mixtures, it demonstrates methods for associating toxic effects with chemical characteristics of environmental samples.

SUBMITTER: Allan SE

PROVIDER: S-EPMC3502726 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Bridging environmental mixtures and toxic effects.

Allan Sarah E SE Smith Brian W BW Tanguay Robert L RL Anderson Kim A KA

Environmental toxicology and chemistry 20121107 12

Biological Response Indicator Devices Gauging Environmental Stressors (BRIDGES) is a bioanalytical tool that combines passive sampling with the embryonic zebrafish developmental toxicity bioassay to provide a quantitative measure of the toxicity of bioavailable complex mixtures. Passive sampling devices (PSDs), which sequester and concentrate bioavailable organic contaminants from the environment, were deployed in the Willamette and Columbia Rivers within and outside of the Portland Harbor Super ...[more]

PMID: 23001962

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Project description:INTRODUCTION:Environmental exposure to toxic metals and metalloids is pervasive and occurs from multiple sources. The Health Effects of Arsenic Longitudinal Study (HEALS) is an ongoing prospective study predominantly focused on understanding health effects associated with arsenic exposure from drinking water. The goal of this project was to measure a suite of elements in urine to better understand potential exposure patterns and to identify common environmental sources of exposure among this semi-rural Bangladeshi population. METHODS:In a random sample of 199 adult HEALS participants (50% female), the concentrations of 15 urinary elements (As, Ba, Cd, Co, Cs, Cu, Mn, Mo, Ni, Pb, Se, Sr, Tl, W, Zn) were assessed by Inductively-Coupled Plasma Mass Spectrometry (ICP-MS) to assess commonalities with sociodemographic characteristics and potential sources of exposure. We used principal component analysis (PCA) with varimax normalized rotations, and hierarchical cluster analysis (CA), using Ward's method with Euclidean distances, to evaluate these relationships. RESULTS:PCA and CA showed similar patterns, suggesting 6 principal components (PC) and 5 clusters: 1)PC: Sr-Ni-Cs/ CA: Sr-Ni-Co; 2) Pb-Tl/Pb-Tl-Se-Cs; 3) As-Mo-W/As-Mo-W; 4) Ba-Mn/Ba-Mn; 5) Cu-Zn/Cu-Zn-Cd; and 6) Cd. There was a strong significant association between the As-Mo-W PC/cluster and water arsenic levels (p?<?0.001) and between the Cd PC and betel nut use (p?=?0.003). The Sr-Ni-Cs PC was not related to any of the socio-demographic characteristics investigated, including smoking status and occupation. The first PC, Sr-Ni-Cs, explained 21% of the variability; the third PC, As-Mo-W, explained 12.5% of the variability; and the sixth PC, Cd, explained 10% of the variability. Day laborers appeared to have the highest exposure. CONCLUSIONS:Groundwater and betel nut use are likely important sources of metal and metalloid exposure in this population. These findings will guide future exposure assessment research in Bangladesh and future epidemiologic research investigating the degree to which metal mixtures play a role in disease development.

Project description:BackgroundOptimization of mixture analyses is critical to assess potential impacts of human exposures to multiple pollutants. Single-index regression methods quantify total mixture association and chemical component contributions. Single-index methods include several variants of quantile g-computation (QGC) and weighted quantile sum regression (WQSr), though each has limitations.ObjectivesWe developed a novel permutation test for WQSr and compared its performance to extant versions of WQSr and QGC in simulation studies and an analysis of prenatal phthalates and childhood cognition.MethodsWQSr uses ensemble nonlinear optimization to identify weights for mixture exposures in an index associated with the outcome in a prespecified direction, with ensembles based on bootstrap resampling (WQSBS) or random subsetting of exposures (WQSRS). Statistical significance can be assessed without splitting the data (Nosplit), by splitting the data into training and test sets (Split), by repeatedly holding out test sets (RH), or by using a novel permutation test (PT) to obtain a more accurate p-value. QGC instead provides a sum mixture coefficient and component coefficients with no constraints on direction. In simulations, we compared false positive rates (FPR) and power to detect true associations and accuracy in estimating mixture weights. We also estimated associations between prenatal phthalate mixtures and childhood IQ in the Conditions Affecting Neurocognitive Development and Learning in Early Childhood cohort using each method.ResultsFPR was well controlled at ≤7% in all but the Nosplit WQSr variants. Among these methods, the WQSBS and WQSRS PT variants had the highest power (89%-98%), with lower power for QGC (85%-93%) and RH (60%-97%) or Split WQSr variants (40%-78%). WQSr methods estimated mixture weights 2-4 times more accurately than the QGC method. Coefficients for mixture associations with full scale IQ varied 3- to 4-fold across analytic methods.DiscussionWQSr paired with our novel permutation test best balanced power and false positive rate when assessing a mixture effect. As new methods develop, each should be examined for performance and applicability. https://doi.org/10.1289/EHP10570.

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Bridging environmental mixtures and toxic effects.

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Bridging environmental mixtures and toxic effects.

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