Chronic Community Exposure to Environmental Metal Mixtures Is Associated with Selected Cytokines in the Navajo Birth Cohort Study (NBCS).
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ABSTRACT:
SUBMITTER: Thompson Gonzalez N
PROVIDER: S-EPMC9690552 | biostudies-literature | 2022 Nov
REPOSITORIES: biostudies-literature
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Chronic Community Exposure to Environmental Metal Mixtures Is Associated with Selected Cytokines in the Navajo Birth Cohort Study (NBCS).
Thompson González Nicole N Ong Jennifer J Luo Li L MacKenzie Debra D
International journal of environmental research and public health 20221113 22
Many tribal populations are characterized by health disparities, including higher rates of infection, metabolic syndrome, and cancer-all of which are mediated by the immune system. Members of the Navajo Nation have suffered chronic low-level exposure to metal mixtures from uranium mine wastes for decades. We suspect that such metal and metalloid exposures lead to adverse health effects via their modulation of immune system function. We examined the relationships between nine key metal and metall ...[more]
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Project description:BackgroundPreterm birth (PTB), defined as birth before 37 wk gestation, is associated with hypertension, diabetes, inadequate prenatal care, unemployment or poverty, and metal exposure. Indigenous individuals are more likely to have maternal risk factors associated with PTB compared with other populations in the United States; however, the role of environmental metals on PTB among pregnant Indigenous women remains uncertain. Previous research identified associations between PTB and individual metals, but there is limited investigation on metal mixtures and this birth outcome.ObjectivesWe used a mixtures analysis framework to investigate the association between metal mixtures and PTB among pregnant Indigenous women from the Navajo Birth Cohort Study (NBCS).MethodsMaternal urine and blood samples were collected at the time of study enrollment and analyzed for metals by inductively coupled plasma dynamic reaction cell mass spectrometry. Bayesian Profile Regression was used to identify subgroups (clusters) of individuals with similar patterns of coexposure and to model association with PTB.ResultsResults indicated six subgroups of maternal participants with distinct exposure profiles, including one group with low exposure to all metals and one group with total arsenic, cadmium, lead, and uranium concentrations exceeding representative concentrations calculated from the National Health and Nutrition Examination Survey (NHANES). Compared with the reference group (i.e., the lowest exposure subgroup), the subgroup with the highest overall exposure had a relative risk of PTB of 2.9 times (95% credible interval: 1.1, 6.1). Exposures in this subgroup were also higher overall than NHANES median values for women 14-45 years of age.DiscussionGiven the wide range of exposures and elevated PTB risk for the most exposed subgroups in a relatively small study, follow-up investigation is recommended to evaluate associations between metal mixture profiles and other birth outcomes and to test hypothesized mechanisms of action for PTB and oxidative stress caused by environmental metals. https://doi.org/10.1289/EHP10361.
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Project description:Contamination of soil and water by waste from abandoned uranium mines has led to chronic exposures to metal mixtures in Native American communities. Our previous work demonstrated that community exposures to mine waste increase the likelihood of developing cardiovascular disease, as well as the likelihood of developing multiple chronic diseases including diabetes, hypertension and kidney disease. Exposure to various environmental metals is associated with elevated oxidative stress, which is considered a contributor to these and other chronic disease states. The purpose of the current research was to assess potential associations between exposure to uranium and arsenic and evidence for increased oxidative stress as measured by urinary F2 -isoprostanes in pregnant women enrolled in the Navajo Birth Cohort Study. The current study also included an analysis of zinc as a potential mediator of oxidative stress in the study population. Urinary arsenic and uranium, serum zinc and urinary F2 -isoprostanes were measured for each study participant at enrollment. Study participants were pregnant women with median age of 26.8; 18.9% were enrolled in the 1st trimester, 44.7% were enrolled in the 2nd trimester, and 36.4% were enrolled in the 3rd trimester. Median urinary metal levels were 5.5 and 0.016 µg/g creatinine for arsenic and uranium, respectively. Multivariable regression analysis indicated a significant association between arsenic exposure and the lipid peroxidation product 8-iso-prostaglandin F2α, controlling for zinc and trimester. No associations were detected with uranium despite evidence that levels were in the Navajo Birth Cohort samples were 2.3 times the median reported for women in the National Health and Nutrition Examination Survey (2011-12). Zinc was not found to have any causal mediation of the effects of the other metals on oxidative stress. The current work is consistent with other studies that have detected an association between arsenic and elevated oxidative stress. In contrast to arsenic, uranium did not appear to increase oxidative stress response in this study population. These findings are relevant to assessing the potential human impact of chronic exposure to mixed metal waste from abandoned uranium mines.
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Project description:BackgroundStunting is an indicator of poor linear growth in children and is an important public health problem in many countries. Both nutritional deficits and toxic exposures can contribute to lower height-for-age Z-score (HAZ) and stunting (HAZ < -2).ObjectivesIn a community-based cross-sectional sample of 97 healthy children ages 6-59 months in Kampala, Uganda, we examined whether exposure to Pb, As, Cd, Se, or Zn were associated with HAZ individually or as a mixture.MethodsBlood samples were analyzed for a mixture of metals, which represent both toxins and essential nutrients. The association between HAZ and metal exposure was tested using multivariable linear regression and Weighted Quantile Sum (WQS) regression, which uses mixtures of correlated exposures as a predictor.ResultsThere were 22 stunted children in the sample, mean HAZ was -0.74 (SD = 1.84). Linear regression showed that Pb (β = -0.80, p = 0.021) and Se (β = 1.92, p = 0.005) were significantly associated with HAZ. The WQS models separated toxic elements with a presumed negative effect on HAZ (Pb, As, Cd) from essential nutrients with presumed positive effect on HAZ (Se and Zn). The toxic mixture was significantly associated with lower HAZ (β = -0.47, p = 0.03), with 62% of the effect from Pb. The nutrient WQS index did not reach statistical significance (β = -0.47, p = 0.16).DiscussionHigher blood lead and lower blood selenium level were both associated with lower HAZ. The significant associations by linear regression were reinforced by the WQS models, although not all associations reached statistical significance. These findings suggest that healthy children in this neighborhood of Kampala, Uganda, who have a high burden of toxic exposures, may experience detrimental health effects associated with these exposures in an environment where exposure sources are not well characterized.
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Project description:BackgroundNumerous studies have suggested significant associations between prenatal exposure to heavy metals and newborn anthropometric measures. However, little is known about the effect of various heavy metal mixtures at relatively low concentrations. Hence, this study aimed to investigate associations between prenatal exposures to a wide range of individual heavy metals and heavy metal mixtures with anthropometric measures of newborns.MethodsWe recruited 975 mother-term infant pairs from two major hospitals in Israel. Associations between eight heavy metals (arsenic, cadmium, chromium, mercury, nickel, lead, selenium, and thallium) detected in maternal urine samples on the day of delivery with weight, length, and head circumference at birth were estimated using linear and Bayesian kernel machine regression (BKMR) models.ResultsMost heavy metals examined in our study were observed in lower concentrations than in other studies, except for selenium. In the linear as well as the BKMR models, birth weight and length were negatively associated with levels of chromium. Birth weight was found to be negatively associated with thallium and positively associated with nickel.ConclusionBy using a large sample size and advanced statistical models, we could examine the association between prenatal exposure to metals in relatively low concentrations and anthropometric measures of newborns. Chromium was suggested to be the most influential metal in the mixture, and its associations with birth weight and length were found negative. Head circumference was neither associated with any of the metals, yet the levels of metals detected in our sample were relatively low. The suggested associations should be further investigated and could shed light on complex biochemical processes involved in intrauterine fetal development.
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Project description:BackgroundThere is increasing interest in examining the consequences of simultaneous exposures to chemical mixtures. However, a consensus or recommendations on how to appropriately select the statistical approach analyzing the health effects of mixture exposures which best aligns with study goals has not been well established. We recognize the limitations that existing methods have in effectively reducing data dimension and detecting interaction effects when analyzing chemical mixture exposures collected in high dimensional datasets with varying degrees of variable intercorrelations. In this research, we aim to examine the performance of a two-step statistical approach in addressing the analytical challenges of chemical mixture exposures using two simulated data sets, and an existing data set from the Navajo Birth Cohort Study as a representative case study.MethodsWe propose to use a two-step approach: a robust variable selection step using the random forest approach followed by adaptive lasso methods that incorporate both dimensionality reduction and quantification of the degree of association between the chemical exposures and the outcome of interest, including interaction terms. We compared the proposed method with other approaches including (1) single step adaptive lasso; and (2) two-step Classification and regression trees (CART) followed by adaptive lasso method.ResultsUtilizing simulated data sets and applying the method to a real-life dataset from the Navajo Birth Cohort Study, we have demonstrated good performance of the proposed two-step approach. Results from the simulation datasets indicated the effectiveness of variable dimension reduction and reliable identification of a parsimonious model compared to other methods: single-step adaptive lasso or two-step CART followed by adaptive lasso method.ConclusionsOur proposed two-step approach provides a robust way of analyzing the effects of high-throughput chemical mixture exposures on health outcomes by combining the strengths of variable selection and adaptive shrinkage strategies.
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Project description:BackgroundStudies have evaluated environmental exposure to toxic metals such as arsenic (As), cadmium (Cd), manganese (Mn), or lead (Pb) on birth size; however, information on potential effects of exposures to metal mixtures is limited.ObjectivesWe assessed the association between metal mixtures (As, Cd, Mn, Pb) in umbilical cord blood and neonate size in Bangladeshi children.MethodsIn this birth cohort study, pregnant women who were ≥18 years of age with an ultrasound-confirmed singleton pregnancy of ≤16wk gestation were recruited from two Bangladesh clinics between 2008 and 2011. Neonate size metrics were measured at the time of delivery. Metals in cord blood were measured using inductively coupled plasma mass spectrometry. We employed multivariable linear regression and Bayesian kernel machine regression (BKMR) to estimate associations of individual metals and metal mixtures with birth size parameters.ResultsData from 1,088 participants was assessed. We found a significant negative association between metal mixture and birth length and head circumference when all metal concentrations were above the 60th and 55th percentiles, respectively, compared with the median. An interquartile range (IQR) increase in log Cd concentration {log[Cd (in micrograms per deciliter)] IQR=2.51} was associated with a 0.13-standard deviation (SD) decrease in mean birth length (95% CI: -0.25, -0.02) and a 0.17-SD decrease in mean head circumference (95% CI: -0.28, -0.05), based on linear regression models adjusted for covariates and the other metals. An IQR increase in log Mn concentration {log[Mn (in micrograms per deciliter)] IQR=0.69} was associated with a 0.07-SD decrease in mean birth weight (95% CI: -0.15, 0.002).DiscussionMetal mixtures in cord blood were associated with reduced birth size in Bangladeshi children. Results from linear regression models adjusted and the BKMR mixtures analyses suggest adverse effects of Cd and Mn, as individual metal exposures, on birth size outcomes. https://doi.org/10.1289/EHP7502.
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Project description:BackgroundGestational exposures to single toxic chemicals have been associated with cognitive deficits in children, but few studies have explored chemical mixtures.ObjectivesTo evaluate the associations between gestational chemical biomarker mixtures and cognitive abilities in children from two prospective cohorts.MethodsThis study includes 617 birthing parent-child pairs from the Health Outcomes and Measures of the Environment (HOME) and Maternal-Infant Research on Environmental Chemicals (MIREC) Studies. We measured 29 chemical biomarkers (metals, persistent organic pollutants, perfluoroalkyl substances, organophosphate esters, phenols, phthalates, organophosphate pesticides, and parabens) in pregnant individuals during early pregnancy and their children's cognitive abilities at ages 3 to 5 years using Wechsler Intelligence Scales. We assessed linear associations using quantile g-computation and non-linear associations using Bayesian Kernel Machine Regression (BKMR) methods, adjusted for covariates.ResultsUsing quantile g-computation, we observed overall null associations between the chemical biomarker mixture and cognitive outcomes among preschool-age children. Although statistical significance was not attained for child sex as an effect modifier, our stratified analysis unveiled a moderate divergence in association trends. We noted a marginal inverse trend between the chemical biomarker mixture and cognitive scores [Full-Scale Intelligence Quotient (FSIQ) & Performance Intelligence Quotient (PIQ)] among males. Using quantile g-computation and BKMR methods, we observed that PBDE47, PFHxS, and di-ethyl organophosphates commonly contributed towards a decline in FSIQ scores in males. Among males, a quartile increase in the chemical biomarker mixture was associated with a 0.64-point decrease (95% CI: -2.59, 1.31) in the FSIQ score and a 1.59-point decrease (95% CI: -3.72, 0.54) in the PIQ score.ConclusionIn this study, we observed a weak negative trend between the gestational chemical biomarker mixture and cognitive scores (FSIQ/PIQ) among males. Further studies are needed to confirm the findings between the longitudinal chemical biomarkers and child cognitive scores at school ages.
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Project description:Contaminant mixtures are identified regularly in public and private drinking water supplies throughout the United States; however, the complex and often correlated nature of mixtures makes identification of relevant combinations challenging. This study employed a Bayesian clustering method to identify subgroups of water sources with similar metal and metalloid profiles. Additionally, a spatial scan statistic assessed spatial clustering of these subgroups and a human health metric was applied to investigate potential for human toxicity. These methods were applied to a dataset comprised of metal and metalloid measurements from unregulated water sources located on the Navajo Nation, in the southwest United States. Results indicated distinct subgroups of water sources with similar contaminant profiles and that some of these subgroups were spatially clustered. Several profiles had metal and metalloid concentrations that may have potential for human toxicity including arsenic, uranium, lead, manganese, and selenium. This approach may be useful for identifying mixtures in water sources, spatially evaluating the clusters, and help inform toxicological research investigating mixtures.
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