Unraveling the health effects of environmental mixtures: an NIEHS priority

Long-term impact of Hurricane Maria on point-of-use drinking water quality in Puerto Rico and associated potential adverse health effects

Drinking water security in Puerto Rico (PR) is increasingly challenged by both regulated and emerging anthropogenic contaminants, which was exacerbated by the Hurricane Maria (HM) due to impaired regional water cycle and damaged water infrastructure. Leveraging the NIEHS PROTECT (Puerto Rico Testsite for Exploring Contamination Threats) cohort, this study assessed the long-term tap water (TW) quality changes from March 2018 to November 2018 after HM in PR, by innovatively integrating two different effect-based quantitative toxicity assays with a targeted analysis of 200 organic and 22 inorganic pollutants. Post-hurricane PR TW quality showed recovery after >6-month period as indicated by the decreased number of contaminants showing elevated average concentrations relative to pre-hurricane samples, with significant difference of both chemical and toxicity levels between northern and southern PR. Molecular toxicity profiling and correlation revealed that the HM-accelerated releases of certain pesticides and PPCPs could exert increased cellular oxidative and/or AhR (aryl hydrocarbon receptor)-mediated activities that may persist for more than six months after HM. Maximum cumulative ratio and adverse outcome pathway (AOP) assessment identified the top ranked detected TW contaminants (Cu, Sr, V, perfluorooctanoic acid) that potentially associated with different adverse health effects such as inflammation, impaired reproductive systems, cancers/tumors, and/or organ toxicity. These insights can be incorporated into the regulatory framework for post-disaster risk assessment, guiding water quality control and management for public health protection.

The Association Between the Non-essential Metal Mixture and Handgrip Strength in Chinese Community-Dwelling Older Adults

There is limited research on the effects of non-essential metal (NEM) mixture on handgrip strength in the elderly. This study aimed to assess the associations of single NEMs and their mixture with handgrip strength in Chinese community-dwelling older adults. A total of 3807 elderly people aged 60 years or above were included in this study. Measurement of urinary aluminum (Al), arsenic (As), barium (Ba), cadmium (Cd), and gallium (Ga) concentrations was conducted by inductively coupled plasma mass spectrometry (ICP-MS). Handgrip strength was measured using a hand dynamometer. Four statistical models, including general linear regression and generalized additive models (GAMs), as well as Bayesian kernel machine regression (BKMR) and quantile-based computation regression (QGC) models, were used to assess the individual and joint effects of urine NEMs with handgrip strength, respectively. After adjusting for covariates, Ga (ß = - 0.27; 95% CI, - 0.54 ~  - 0.01) and As ( β  = - 0.34; 95% CI, - 0.61 ~  - 0.07) were negatively associated with handgrip strength. The GAMs and BKMR further suggested that the negative associations of Ga and As with handgrip strength were linear and inverted U-shaped, respectively. The BKMR and QGC models showed that the NEM mixture was negatively related to handgrip strength, with Ga and As contributing the most within the mixture. Moreover, we also observed an interaction between As and Ga on handgrip strength. Longitudinal studies are needed to verify these findings.

Mixed contaminant exposure in tapwater and the potential implications for human-health in disadvantaged communities in California

Water is an increasingly precious resource in California as years of drought, climate change, pollution, as well as an expanding population have all stressed the state's drinking water supplies. Currently, there are increasing concerns about whether regulated and unregulated contaminants in drinking water are linked to a variety of human-health outcomes particularly in socially disadvantaged communities with a history of health risks. To begin to address this data gap by broadly assessing contaminant mixture exposures, the current study was designed to collect tapwater samples from communities in Gold Country, the San Francisco Bay Area, two regions of the Central Valley (Merced/Fresno and Kern counties), and southeast Los Angeles for 251 organic chemicals and 32 inorganic constituents. Sampling prioritized low-income areas with suspected water quality challenges and elevated breast cancer rates. Results indicated that mixtures of regulated and unregulated contaminants were observed frequently in tapwater throughout the areas studied and the types and concentrations of detected contaminants varied by region, drinking-water source, and size of the public water system. Multiple exceedances of enforceable maximum contaminant level(s) (MCL), non-enforceable MCL goal(s) (MCLG), and other health advisories combined with frequent exceedances of benchmark-based hazard indices were also observed in samples collected in all five of the study regions. Given the current focus on improving water quality in socially disadvantaged communities, our study highlights the importance of assessing mixed-contaminant exposures in drinking water at the point of consumption to adequately address human-health concerns (e.g., breast cancer risk). Data from this pilot study provide a foundation for future studies across a greater number of communities in California to assess potential linkages between breast cancer rates and tapwater contaminants.

Exposure to Endocrine Disruptors in Early life and Neuroimaging Findings in Childhood and Adolescence: a Scoping Review

PURPOSE OF REVIEW: Evidence suggests neurotoxicity of endocrine disrupting chemicals (EDCs) during sensitive periods of development. We present an overview of pediatric population neuroimaging studies that examined brain influences of EDC exposure during prenatal period and childhood. RECENT FINDINGS: We found 46 studies that used magnetic resonance imaging (MRI) to examine brain influences of EDCs. These studies showed associations of prenatal exposure to phthalates, organophosphate pesticides (OPs), polyaromatic hydrocarbons and persistent organic pollutants with global and regional brain structural alterations. Few studies suggested alteration in functional MRI associated with prenatal OP exposure. However, studies on other groups of EDCs, such as bisphenols, and those that examined childhood exposure were less conclusive. These findings underscore the potential profound and lasting effects of prenatal EDC exposure on brain development, emphasizing the need for better regulation and strategies to reduce exposure and mitigate impacts. More studies are needed to examine the influence of postnatal exposure to EDC on brain imaging.

Associations between prenatal metal and metalloid mixtures in teeth and reductions in childhood lung function

BACKGROUND

Metal(oid)s have been cross-sectionally associated with lung function outcomes in childhood but there is limited data on their combined effects starting in utero. Child sex may further modify these effects.

OBJECTIVE

Examine associations between in utero and early life exposure to metals assessed via novel dentine biomarkers and childhood lung function and explore effect modification by child sex.

METHODS

Analyses included 291 children enrolled in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study, a longitudinal birth cohort study in Mexico City. Weekly dentine levels of arsenic (As), cadmium (Cd), cobalt (Co), copper (Cu), manganese (Mn), nickel (Ni), and lead (Pb) were measured from 15 weeks pre-birth to 15 weeks post birth in deciduous children's teeth. Lung function was tested at ages 8-14 years and then modeled as age, height and sex adjusted z-scores. Associations were modeled using lagged weighted quantile sum (LWQS) regression to evaluate the potential for a time-varying mixture effect adjusting for maternal age and education at enrollment and exposure to environmental tobacco smoke in pregnancy. Models were also stratified by sex.

RESULTS

We identified a window of susceptibility at 12-15 weeks pre-birth in which the metal mixture was associated with lower FVC z-scores in children aged 8-14 years. Cd and Mn were the largest contributors to the mixture effect (70 %). There was also some evidence of effect modification by sex, in which the mean weights and weighted correlations over the identified window was more evident in males when compared to females. In the male stratum, Cd, Mn and additionally Pb also dominated the mixture association.

CONCLUSIONS

Prenatal metal(oid) exposure was associated with lower lung function in childhood. These findings underscore the need to consider both mixtures and windows of susceptibility to fully elucidate effects of prenatal metal(oid) exposure on childhood lung function.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

Combined Exposures and Mixtures Research: An Enduring NIEHS Priority

BACKGROUND

The National Institute of Environmental Health Sciences (NIEHS) continues to prioritize research to better understand the health effects resulting from exposure to mixtures of chemical and nonchemical stressors. Mixtures research activities over the last decade were informed by expert input during the development and deliberations of the 2011 NIEHS Workshop "Advancing Research on Mixtures: New Perspectives and Approaches for Predicting Adverse Human Health Effects." NIEHS mixtures research efforts since then have focused on key themes including a) prioritizing mixtures for study, b) translating mixtures data from in vitro and in vivo studies, c) developing cross-disciplinary collaborations, d) informing component-based and whole-mixture assessment approaches, e) developing sufficient similarity methods to compare across complex mixtures, f) using systems-based approaches to evaluate mixtures, and g) focusing on management and integration of mixtures-related data.

OBJECTIVES

We aimed to describe NIEHS driven research on mixtures and combined exposures over the last decade and present areas for future attention.

RESULTS

Intramural and extramural mixtures research projects have incorporated a diverse array of chemicals (e.g., polycyclic aromatic hydrocarbons, botanicals, personal care products, wildfire emissions) and nonchemical stressors (e.g., socioeconomic factors, social adversity) and have focused on many diseases (e.g., breast cancer, atherosclerosis, immune disruption). We have made significant progress in certain areas, such as developing statistical methods for evaluating multiple chemical associations in epidemiology and building translational mixtures projects that include both in vitro and in vivo models.

DISCUSSION

Moving forward, additional work is needed to improve mixtures data integration, elucidate interactions between chemical and nonchemical stressors, and resolve the geospatial and temporal nature of mixture exposures. Continued mixtures research will be critical to informing cumulative impact assessments and addressing complex challenges, such as environmental justice and climate change. https://doi.org/10.1289/EHP14340.

The Need for an Alternative Health Claim Process for Foods Based on Both Nutrient and Contaminant Profiles

Most authorized health claims on foods have been established on the basis of single dietary components, mainly micronutrients, such as vitamins, minerals, and possibly bioactives. Failure to sufficiently define and characterize the nutritional profile of a food product is one of the main reasons for rejection or incomplete status for thousands of health claim applications, whereas the food's contaminant profile is simply not accounted for. The objective of this work was to highlight the accumulating scientific evidence supporting a reform of the health claim evaluation process for foods toward more holistic approaches. This would entail the characterization of multiple nutrient-contaminant pairs and contaminant mixture profiles at contaminant levels currently considered "safe," including their interactions that would impact human health outcome(s) in a net positive or negative direction. The notion of a stable nutritional profile in food commodities has been challenged by studies reporting a variable food contaminant content and a declining content of proteins/micronutrients in crops due to anthropogenic greenhouse gas emissions. A holistic approach in the health claim process for foods would entail the incorporation of cumulative risk assessment and/or risk-benefit protocols that effectively combine health risks and benefits associated with multiple nutritional and contaminant attributes of the food/diet under evaluation.

Urinary volatile organic compound metabolites and COPD among US adults: mixture, interaction and mediation analysis

BACKGROUND

Volatile organic compounds (VOCs) encompass hundreds of high production volume chemicals and have been reported to be associated with adverse respiratory outcomes such as chronic obstructive pulmonary disease (COPD). However, research on the combined toxic effects of exposure to various VOCs on COPD is lacking. We aimed to assess the effect of VOC metabolite mixture on COPD risk in a large population sample.

METHODS

We assessed the effect of VOC metabolite mixture on COPD risk in 5997 adults from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020 (pre-pandemic) using multivariate logistic regression, Bayesian weighted quantile sum regression (BWQS), quantile-based g-Computation method (Qgcomp), and Bayesian kernel machine regression (BKMR). We explored whether these associations were mediated by white blood cell (WBC) count and total bilirubin.

RESULTS

In the logistic regression model, we observed a significantly increased risk of COPD associated with 9 VOC metabolites. Conversely, N-acetyl-S-(benzyl)-L-cysteine (BMA) and N-acetyl-S-(n-propyl)-L-cysteine (BPMA) showed insignificant negative correlations with COPD risk. The overall mixture exposure demonstrated a significant positive relationship with COPD in both the BWQS model (adjusted odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.06, 1.58) and BKMR model, and with marginal significance in the Qgcomp model (adjusted OR = 1.22, 95% CI: 0.98, 1.52). All three models indicated a significant effect of the VOC metabolite mixture on COPD in non-current smokers. WBC count mediated 7.1% of the VOC mixture associated-COPD in non-current smokers.

CONCLUSIONS

Our findings provide novel evidence suggesting that VOCs may have adverse associations with COPD in the general population, with N, N- Dimethylformamide and 1,3-Butadiene contributing most. These findings underscore the significance of understanding the potential health risks associated with VOC mixture and emphasize the need for targeted interventions to mitigate the adverse effects on COPD risk.

Analysis of gasoline-related pollutant exposures and risks in California between 1996 and 2014

BACKGROUND

Gasoline-powered vehicles and equipment are an important source of air pollution in California. Many gasoline-related pollutants pose significant health concerns. The California Air Resources Board strictly regulates the state's gasoline formulation and vehicle emissions.

OBJECTIVE

To investigate exposure trends for gasoline-related air pollutants between 1996 and 2014, capturing the period before and after the removal of methyl t-butyl ether (MTBE).

METHODS

We identified gasoline-related chemicals with known or suspected health concerns and adequate ambient air monitoring data. Average exposures to the general public were estimated from 1996 to 2014 in five major air basins and statewide. We determined the fractions of exposures attributable to gasoline use and evaluated cancer and non-cancer risks for chemicals with available cancer potencies and health reference values.

RESULTS

We found that average gasoline-attributable cancer risks for the general California population from the most highly emitted carcinogens (acetaldehyde, benzene, 1,3-butadiene, and formaldehyde) declined by over 80% between 1996 and 2014. This decline occurred despite roughly constant statewide gasoline sales, an increase in vehicle miles traveled, and an approximately 10% increase in vehicle registrations over this same period. Naphthalene, measured as a volatile organic compound (VOC), was the most abundant gasoline-related polycyclic aromatic hydrocarbon (PAH). From 1996 to 2014, gasoline-attributable cancer risks for naphthalene were estimated to drop approximately threefold in the South Coast Air Basin. Exposures to gasoline-related chemicals associated with non-cancer health effects, such as chronic respiratory toxicity or neurotoxicity, were generally below levels of concern. The exception was acrolein, with gasoline-related exposures in 2014 estimated to be high enough to pose risks for respiratory toxicity.

IMPACT STATEMENT

Our historical analysis demonstrated the success of California's regulatory efforts to reduce gasoline-related air pollutant exposures and risks to the general public. New efforts are focused on addressing gasoline-related and other air pollution in heavily impacted communities affected by multiple environmental and social stressors.

Modeling PAH Mixture Interactions in a Human In Vitro Organotypic Respiratory Model

One of the most significant challenges in human health risk assessment is to evaluate hazards from exposure to environmental chemical mixtures. Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous contaminants typically found as mixtures in gaseous and particulate phases in ambient air pollution associated with petrochemicals from Superfund sites and the burning of fossil fuels. However, little is understood about how PAHs in mixtures contribute to toxicity in lung cells. To investigate mixture interactions and component additivity from environmentally relevant PAHs, two synthetic mixtures were created from PAHs identified in passive air samplers at a legacy creosote site impacted by wildfires. The primary human bronchial epithelial cells differentiated at the air-liquid interface were treated with PAH mixtures at environmentally relevant proportions and evaluated for the differential expression of transcriptional biomarkers related to xenobiotic metabolism, oxidative stress response, barrier integrity, and DNA damage response. Component additivity was evaluated across all endpoints using two independent action (IA) models with and without the scaling of components by toxic equivalence factors. Both IA models exhibited trends that were unlike the observed mixture response and generally underestimated the toxicity across dose suggesting the potential for non-additive interactions of components. Overall, this study provides an example of the usefulness of mixture toxicity assessment with the currently available methods while demonstrating the need for more complex yet interpretable mixture response evaluation methods for environmental samples.

Integrating Data Across Multiple Sites in the Northeastern United States to Examine Associations Between a Prenatal Metal Mixture and Child Cognition

We applied a novel hierarchical Bayesian weighted quantile sum (HBWQS) regression to combine data across 3 study sites to examine associations between prenatal exposure to metals and cognitive functioning in childhood. Data from 326 mother-child dyads enrolled in an ongoing cohort study, the Programming of Intergenerational Stress Mechanisms (PRISM) Study, based in New York, New York (recruitment in 2013-2020) and Boston, Massachusetts (recruitment 2011-2013), and the First Thousand Days of Life (FTDL) cohort study (recruitment 2012-2019), based in northern Virginia, were used. Arsenic, cadmium, manganese, lead, and antimony were measured in urine collected during pregnancy. Cognitive functioning was assessed in children aged 3-11 years using the National Institutes of Health Toolbox Cognition Battery. The HBWQS regression showed a negative association between the urinary metal mixture and the Cognition Early Childhood Composite Score in the PRISM New York City (β = -3.67, 95% credible interval (CrI): -7.61, -0.01) and FTDL (β = -3.76, 95% CrI: -7.66, -0.24) samples, with a similar trend in the PRISM Boston sample (β = -3.24, 95% CrI: -6.77, 0.144). We did not detect these associations in traditionally pooled models. HBWQS regression allowed us to account for site heterogeneity and detect associations between prenatal metal-mixture exposure and cognitive outcomes in childhood. Given the ubiquity of metals exposure, interventions aimed at reducing prenatal exposure may improve cognitive outcomes in children. This article is part of a Special Collection on Environmental Epidemiology.

Cross-sectional and prospective associations of early childhood circulating metals with early and mid-childhood cognition in the Project Viva cohort

BACKGROUND

Relatively little is known about the immediate and prospective neurodevelopmental impacts of joint exposure to multiple metals (i.e., metal mixtures) in early childhood.

OBJECTIVES

To estimate associations of early childhood (∼3 years of age) blood metal concentrations with cognitive test scores at early and mid-childhood (∼8 years of age).

METHODS

We studied children from the Project Viva cohort. We measured erythrocyte concentrations of seven essential (Co, Cu, Mg, Mn, Mo, Se, and Zn) and eight non-essential metals (As, Ba, Cd, Cs, Hg, Pb, Sn, and Sr) in early childhood blood samples. Trained research assistants administered cognitive tests assessing vocabulary, visual-motor ability, memory, and general intelligence (standard deviations: ∼10 points), in early and mid-childhood. We employed multivariable linear regression to examine associations of individual metals with test scores adjusting for confounders, other concurrently measured metals, and first-trimester maternal blood metals. We also estimated joint associations and explored interaction between metals in mixture analyses.

RESULTS

We analyzed 349 children (median whole blood Pb ∼1 μg/dL). In cross-sectional analyses, each doubling of Pb was associated with lower visual-motor function (mean difference: -2.43 points, 95% confidence interval (CI): -4.01, -0.86) and receptive vocabulary, i.e., words understood (-1.45 points, 95% CI: -3.26, 0.36). Associations of Pb with mid-childhood cognition were weaker and less precise by comparison. Mg was positively associated with cognition in cross-sectional but not prospective analyses, and cross-sectional associations were attenuated in a sensitivity analysis removing adjustment for concurrent metals. We did not observe joint associations nor interactions.

DISCUSSION

In this cohort with low blood Pb levels, increased blood Pb was robustly associated with lower cognitive ability in cross-sectional analyses, even after adjustment for prenatal Pb exposure, and regardless of adjustment for metal co-exposures. However, associations with mid-childhood cognition were attenuated and imprecise, suggesting some buffering of Pb neurotoxicity in early life.

WHAT THIS STUDY ADDS

Relatively few studies have comprehensively separated the effects of neurotoxic metals such as lead (Pb) from pre- and postnatal co-occurring metals, nor examined persistence of associations across childhood. In a cohort of middle-class children, we found higher early childhood (∼3 y) blood Pb was associated with lower scores on cognitive tests, independent of other metals and prenatal blood Pb. However, early childhood Pb was only weakly associated with cognition in mid-childhood (∼8 y). Our results suggest the effects of low-level Pb exposure may attenuate over time in some populations, implying the presence of factors that may buffer Pb neurotoxicity in early life.

Statistical methods for chemical mixtures: a roadmap for practitioners

Quantitative characterization of the health impacts associated with exposure to chemical mixtures has received considerable attention in current environmental and epidemiological studies. With many existing statistical methods and emerging approaches, it is important for practitioners to understand when each method is best suited for their inferential goals. In this study, we conduct a review and comparison of 11 analytical methods available for use in mixtures research, through extensive simulation studies for continuous and binary outcomes. These methods fall in three different classes: identifying important components of a mixture, identifying interactions and creating a summary score for risk stratification and prediction. We carry out an illustrative data analysis in the PROTECT birth cohort from Puerto Rico. Most importantly we develop an integrated package "CompMix" that provides a platform for mixtures analysis where the practitioner can implement a pipeline for several types of mixtures analysis. Our simulation results suggest that the choice of methods depends on the goal of analysis and there is no clear winner across the board. For selection of important toxicants in the mixture and for identifying interactions, Elastic net by Zou et al. (Enet), Lasso for Hierarchical Interactions by Bien et al (HierNet), Selection of nonlinear interactions by a forward stepwise algorithm by Narisetty et al. (SNIF) have the most stable performance across simulation settings. Additionally, the predictive performance of the Super Learner ensembling method by Van de Laan et al. and HierNet are found to be superior to the rest of the methods. For overall summary or a cumulative measure, we find that using the Super Learner to combine multiple Environmental Risk Scores can lead to improved risk stratification properties. We have developed an R package "CompMix: A comprehensive toolkit for environmental mixtures analysis", allowing users to implement a variety of tasks under different settings and compare the findings. In summary, our study offers guidelines for selecting appropriate statistical methods for addressing specific scientific questions related to mixtures research. We identify critical gaps where new and better methods are needed.

The Associations between Exposure to Multiple Heavy Metals and Total Immunoglobulin E in U.S. Adults

Immunoglobulin E (IgE) is a type of immunoglobulin, and elevated serum total IgE is often present in allergic diseases. Exposure to environmental heavy metals has been markedly linked to allergic diseases, leading to elevated total IgE levels. However, studies concerning the effects of multiple metal exposures on total IgE levels are limited. Therefore, the current study seeks to explore the correlation between heavy-metal co-exposure and total IgE levels based on the National Health and Nutrition Examination Survey (NHANES, 2005-2006). Participants possessed complete data on total IgE levels, 11 urinary metal concentrations and other covariates. The correlations between 11 metals and total IgE levels were analyzed using multiple linear regression, and total IgE levels were a continuous variable. Total IgE levels exceeding 150 kU/L were considered sensitized. Binary logistic regression analyses were employed to assess the correlation between metal exposure and the occurrence of an allergic state. Then, the association between co-exposure to the 11 metals and total IgE levels or the occurrence of sensitization status was further analyzed by Bayesian kernel machine regression (BKMR), a multi-contaminant model. There were 1429 adults with complete data included. Based on the median concentration, molybdenum (Mo) had the highest concentration (46.60 μg/L), followed by cesium (Cs), barium (Ba), lead (Pb), and mercury (Hg). And the median (interquartile range) for total IgE levels was 43.7 (17.3, 126.0) kU/L. Multiple linear regression results showed that Pb was significantly and positively associated with total IgE levels (β = 0.165; 95% CI: 0.046, 0.284). Binary logistic regression showed a significant positive correlation between urinary Pb (OR: 1.258; 95% CI: 1.052, 1.510) and tungsten (W) (OR: 1.251; 95% CI: 1.082, 1.447). Importantly, the BKMR model found a positive correlation between combined-metal exposure and total IgE levels and the occurrence of sensitization status. The mixed heavy-metal exposure was associated with increased total IgE levels, and this association may be driven primarily by the exposure of Pb and W. This study provides new insights into the relationship between heavy-metal exposure and allergic diseases. More research is needed to confirm these findings.

Changes in chemical occurrence, concentration, and bioactivity in the Colorado River before and after replacement of the Moab, Utah wastewater treatment plant

Long-term (2010-19) water-quality monitoring on the Colorado River downstream from Moab Utah indicated the persistent presence of Bioactive Chemicals (BC), such as pesticides and pharmaceuticals. This stream reach near Canyonlands National Park provides critical habitat for federally endangered species. The Moab wastewater treatment plant (WWTP) outfall discharges to the Colorado River and is the nearest potential point-source to this reach. The original WWTP was replaced in 2018. In 2016-19, a study was completed to determine if the new plant reduced BC input to the Colorado River at, and downstream from, the outfall. Water samples were collected before and after the plant replacement at sites upstream and downstream from the outfall. Samples were analyzed for as many as 243 pesticides, 109 pharmaceuticals, 20 hormones, 51 wastewater indicator chemicals, 20 metals, and 8 nutrients. BC concentrations, hazard quotients (HQs), and exposure activity ratios (EARs) were used to identify and prioritize contaminants for their potential to have adverse biological effects on the health of native and endangered wildlife. There were 22 BC with HQs >1, mostly metals and hormones; and 23 BC with EARs >0.1, mostly hormones and pharmaceuticals. Most high HQs or EARs were associated with samples collected at the WWTP outfall site prior to its replacement. Discharge from the new plant had reduced concentrations of nutrients, hormones, pharmaceuticals, and other BC. For example, all 16 of the hormones detected at the WWTP outfall site had maximum concentrations in samples collected prior to the WWTP replacement. The WWTP replacement had less effect on instream concentrations of metals and pesticides, BC whose sources are less directly tied to domestic wastewater. Study results indicate that improved WWTP technology can create substantial reductions in concentrations of non-regulated BC such as pharmaceuticals, in addition to regulated contaminants such as nutrients.

Preterm Birth and Metal Mixture Exposure among Pregnant Women from the Navajo Birth Cohort Study

BACKGROUND

Preterm 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.

OBJECTIVES

We 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).

METHODS

Maternal 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.

RESULTS

Results 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.

DISCUSSION

Given 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.

Review on new approach methods to gain insight into the feto-maternal interface physiology

Non-human animals represent a large and important feature in the history of biomedical research. The validity of their use, in terms of reproducible outcomes and translational confidence to the human situation, as well as ethical concerns surrounding that use, have been and remain controversial topics. Over the last 10 years, the communities developing microphysiological systems (MPS) have produced new approach method (NAMs) such as organoids and organs-on-a-chip. These alternative methodologies have shown indications of greater reliability and translatability than animal use in some areas, represent more humane substitutions for animals in these settings, and - with continued scientific effort - may change the conduct of basic research, clinical studies, safety testing, and drug development. Here, we present an introduction to these more human-relevant methodologies and suggest how a suite of pregnancy associated feto-maternal interface system-oriented NAMs may be integrated as reliable partial-/full animal replacements for investigators, significantly aid animal-/environmental welfare, and improve healthcare outcomes.

Effects of disinfection by-products in swimming pool environments on the immunological mechanisms of respiratory diseases

Swimming in pools is a popular and healthy recreational activity. However, potential adverse health effects from disinfection byproduct (DBP) exposure in pool water are concerning. This study evaluated how such DBP exposure affects the respiratory system. DBP exposure was simulated with an animal-specific pool environment model. Experimental animals were exposed to DBPs for a specified duration and frequency over 4 weeks. The wet and dry weights of murine lungs were measured, with no significant differences observed. There were no significant differences in interkeukin (IL)-2/4/10, and interferon-γ levels. However, IL-6 expression decreased in the experimental group. To investigate the effects of DBP exposure on immune cell response, various samples, such as bronchoalveolar lavage fluid, lymph nodes, spleen, and thymus, were collected for T-cell isolation and fluorescence-activated cell sorting. Asthma-related blood cell distribution was analyzed using a complete blood count test; no significant differences were found. Thus, DBP exposure through this model did not induce substantial lung tissue damage, major alterations in cytokine expression (besides IL-6), significant immune cell responses, or changes in asthma-associated blood cell distribution. However, considering earlier results, future studies should focus on specific types, intensity, and duration of exercise that could affect DBP exposure-related immune-inflammatory responses.

Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.

Association between gestational levels of toxic metals and essential elements and cerebral palsy in children

Introduction

Cerebral palsy (CP) is the most common motor disability in childhood, but its causes are only partly known. Early-life exposure to toxic metals and inadequate or excess amounts of essential elements can adversely affect brain and nervous system development. However, little is still known about these as perinatal risk factors for CP. This study aims to investigate the associations between second trimester maternal blood levels of toxic metals, essential elements, and mixtures thereof, with CP diagnoses in children.

Methods

In a large, population-based prospective birth cohort (The Norwegian Mother, Father, and Child Cohort Study), children with CP diagnoses were identified through The Norwegian Patient Registry and Cerebral Palsy Registry of Norway. One hundred forty-four children with CP and 1,082 controls were included. The relationship between maternal blood concentrations of five toxic metals and six essential elements and CP diagnoses were investigated using mixture approaches: elastic net with stability selection to identify important metals/elements in the mixture in relation to CP; then logistic regressions of the selected metals/elements to estimate odds ratio (OR) of CP and two-way interactions among metals/elements and with child sex and maternal education. Finally, the joint effects of the mixtures on CP diagnoses were estimated using quantile-based g-computation analyses.

Results

The essential elements manganese and copper, as well as the toxic metal Hg, were the most important in relation to CP. Elevated maternal levels of copper (OR = 1.40) and manganese (OR = 1.20) were associated with increased risk of CP, while Hg levels were, counterintuitively, inversely related to CP. Metal/element interactions that were associated with CP were observed, and that sex and maternal education influenced the relationships between metals/elements and CP. In the joint mixture approach no significant association between the mixture of metals/elements and CP (OR = 1.00, 95% CI = [0.67, 1.50]) was identified.

Conclusion

Using mixture approaches, elevated levels of copper and manganese measured in maternal blood during the second trimester could be related to increased risk of CP in children. The inverse associations between maternal Hg and CP could reflect Hg as a marker of maternal fish intake and thus nutrients beneficial for foetal brain development.

Mixtures of Metals and Micronutrients in Early Pregnancy and Cognition in Early and Mid-Childhood: Findings from the Project Viva Cohort

BACKGROUND

The developing fetal brain is sensitive to many environmental exposures. However, the independent and joint effects of prenatal exposure to metals and micronutrients on child cognition are not well understood.

OBJECTIVES

Our aim was to evaluate associations of first-trimester (∼ 10 wk) maternal erythrocyte concentrations of mixtures of nonessential and essential metals and micronutrients with early (∼ 3 y) and mid-childhood (∼ 8 y) cognitive test scores in Project Viva, a prebirth cohort in Boston, Massachusetts, USA.

METHODS

We measured concentrations of five essential metals (Cu, Mg, Mn, Se, Zn) and two micronutrients (vitamin B12 and folate), together termed the "nutrient mixture," as well as six nonessential metals (As, Ba, Cd, Cs, Hg, Pb), together termed the "neurotoxic mixture," in first-trimester (∼ 10 wk) maternal erythrocytes (metals) or plasma (micronutrients). We assessed visual-motor function and receptive vocabulary in early childhood (∼ 3 y), and visual-motor function, visual memory, and fluid and crystallized intelligence in mid-childhood (∼ 8 y). We employed adjusted quantile g-computation and linear regression to estimate mixture and individual component associations, respectively.

RESULTS

Analyses included 900 mother-child pairs (74% college graduates; 52% male children). In mixture analyses, a quartile increase in the nutrient mixture was associated with a mean difference in early childhood receptive vocabulary score of 1.58 points [95% confidence interval (CI): 0.06, 3.10], driven by Zn and Se. A quartile increase in the neurotoxic mixture was associated with a mean difference in mid-childhood visual-motor score of - 3.01 points (95% CI: - 5.55 , - 0.47 ), driven by Ba and Cs. Linear regressions supported quantile g-computation findings for mixture component contributions.

DISCUSSION

Maternal circulating concentrations of several essential (Zn and Se) and nonessential (Ba and Cs) metals were associated with some domains of child cognition. In this folate-replete cohort, first-trimester circulating concentrations of known neurotoxic metals, such as Pb, were not associated with child cognition. https://doi.org/10.1289/EHP12016.

Contrasting Association of Maternal Plasma Biomarkers of Smoking and 1-Carbon Micronutrients with Offspring DNA Methylation: Evidence of Aryl Hydrocarbon Receptor Repressor Gene-Smoking-Folate Interaction

BACKGROUND

Maternal prenatal smoking is known to alter offspring DNA methylation (DNAm). However, there are no effective interventions to mitigate smoking-induced DNAm alteration.

OBJECTIVES

This study investigated whether 1-carbon nutrients (folate, vitamins B6, and B12) can protect against prenatal smoking-induced offspring DNAm alterations in the aryl hydrocarbon receptor repressor (AHRR) (cg05575921), GFI1 (cg09935388), and CYP1A1 (cg05549655) genes.

METHODS

This study included mother-newborn dyads from a racially diverse US birth cohort. The cord blood DNAm at the above 3 sites were derived from a previous study using the Illumina Infinium MethylationEPIC BeadChip. Maternal smoking was assessed by self-report and plasma biomarkers (hydroxycotinine and cotinine). Maternal plasma folate, and vitamins B6 and B12 concentrations were obtained shortly after delivery. Linear regressions, Bayesian kernel machine regression, and quantile g-computation were applied to test the study hypothesis by adjusting for covariables and multiple testing.

RESULTS

The study included 834 mother-newborn dyads (16.7% of newborns exposed to maternal smoking). DNAm at cg05575921 (AHRR) and at cg09935388 (GFI1) was inversely associated with maternal smoking biomarkers in a dose-response fashion (all P < 7.01 × 10-13). In contrast, cg05549655 (CYP1A1) was positively associated with maternal smoking biomarkers (P < 2.4 × 10-6). Folate concentrations only affected DNAm levels at cg05575921 (AHRR, P = 0.014). Regression analyses showed that compared with offspring with low hydroxycotinine exposure (<0.494) and adequate maternal folate concentrations (quartiles 2-4), an offspring with high hydroxycotinine exposure (≥0.494) and low folate concentrations (quartile 1) had a significant reduction in DNAm at cg05575921 (M-value, ß ± SE = -0.801 ± 0.117, P = 1.44 × 10-11), whereas adequate folate concentrations could cut smoking-induced hypomethylation by almost half. Exposure mixture models further supported the protective role of adequate folate concentrations against smoking-induced aryl hydrocarbon receptor repressor (AHRR) hypomethylation.

CONCLUSIONS

This study found that adequate maternal folate can attenuate maternal smoking-induced offspring AHRR cg05575921 hypomethylation, which has been previously linked to a range of pediatric and adult diseases.

Epidemiologic roadblocks in studying elongated mineral particles and mesothelioma risk

Elongated mineral particles (EMPs) are a type of both occupational and environmental exposures that have generated interest in the scientific community due to their potential health effects. Their possible association with mesothelioma represents an area of concern. We provide an overview of the current challenges around epidemiological assessments of EMP exposure and mesothelioma risk, including methodological aspects that need to be addressed when designing and analyzing a study on EMP exposure and mesothelioma. Future work is needed to investigate the relationship between EMPs and mesothelioma, focused on an improved definition of EMP exposure and accounting for other concomitant sources of carcinogen exposure.

A weighted quantile sum regression with penalized weights and two indices

Background

New statistical methodologies were developed in the last decade to face the challenges of estimating the effects of exposure to multiple chemicals. Weighted Quantile Sum (WQS) regression is a recent statistical method that allows estimating a mixture effect associated with a specific health effect and identifying the components that characterize the mixture effect.

Objectives

In this study, we propose an extension of WQS regression that estimates two mixture effects of chemicals on a health outcome in the same model through the inclusion of two indices, one in the positive direction and one in the negative direction, with the introduction of a penalization term.

Methods

To evaluate the performance of this new model we performed both a simulation study and a real case study where we assessed the effects of nutrients on obesity among adults using the National Health and Nutrition Examination Survey (NHANES) data.

Results

The method showed good performance in estimating both the regression parameter and the weights associated with the single elements when the penalized term was set equal to the magnitude of the Akaike information criterion of the unpenalized WQS regression. The two indices further helped to give a better estimate of the parameters [Positive direction Median Error (PME): 0.022; Negative direction Median Error (NME): -0.044] compared to the standard WQS without the penalization term (PME: -0.227; NME: 0.215). In the case study, WQS with two indices was able to find a significant effect of nutrients on obesity in both directions identifying sodium and magnesium as the main actors in the positive and negative association, respectively.

Discussion

Through this work, we introduced an extension of WQS regression that improved the accuracy of the parameter estimates when considering a mixture of elements that can have both a protective and a harmful effect on the outcome; and the advantage of adding a penalization term when estimating the weights.

Sex Specificity in the Mixed Effects of Blood Heavy Metals and Cognitive Function on Elderly: Evidence from NHANES

The way that males and females react to environmental exposures and negative impacts on their neurological systems is often different. Although previous research has examined the cognitively impairing effects of solitary metal exposures, the relationship between metal mixtures and cognitive function, particularly when considering an individual's sex, remains elusive. This study aimed to investigate the sex differences in the association between multiple metal combinations and cognitive function in older Americans. This research employed the 2011-2014 NHANES survey of elderly Americans. The association between five mixed metals and four cognitive tests (the animal fluency test (AFT), the digit symbol substitution test (DSST), the instant recall test (IRT), and the delayed recall test (DRT)) were investigated with generalized linear regression model (GLM), Bayesian kernel machine regression model (BKMR), weighted quantile sum regression model (WQS), and quantile g-computation regression model (Qgcomp). A total of 1833 people, including 883 males and 950 females, enrolled in this cross-sectional study. We discovered that blood lead and blood cadmium were negatively associated with cognitive performance, while blood selenium demonstrated a positive association with cognitive function in older people. The negative relationship of heavy metal combinations on cognitive function might be somewhat reduced or even reversed via selenium. The IRT, AFT, and DSST are three of the four cognitive tests where men had more dramatic positive or negative results. There was a sex-specific connection between blood metal ratios and cognitive function among older Americans, as evidenced by the more significant relationship between mixed metals and cognitive performance in men (either positively or negatively). These results emphasize the impacts of ambient heavy metal exposure on cognitive function by employing sex-specific methods.

Sex-specific relationships between prenatal exposure to metal mixtures and birth weight in a Chinese birth cohort

Birth weight is an indicator linking intrauterine environmental exposures to later-life diseases, and intrauterine metal exposure may affect birth weight in a sex-specific manner. We investigated sex-specific associations between prenatal exposure to metal mixtures and birth weight in a Chinese birth cohort. The birth weight of 1296 boys and 1098 girls were recorded, and 10 metals in maternal urine samples collected during pregnancy were measured using inductively coupled plasma mass spectrometry. Bayesian Kernel Machine Regression was used to estimate the association of individual metals or metal mixtures and birth weight for gestational age (BW for GA). The model showed a sex-specific relationship between prenatal exposure to metal mixtures and BW for GA with a significant negative association in girls and a non-significant positive association in boys. Cadmium (Cd) and nickel (Ni) were positively and negatively associated with BW for GA in girls, respectively. Moreover, increasing thallium (Tl) concentration lowered the positive association between Cd and BW for GA and enhanced the negative association between Ni and BW for GA in girls. When exposure to other metals increased, the positive association with Cd diminished, whereas the negative association with Ni or Tl increased. Our findings provide evidence supporting the complex effects of intrauterine exposure to metal mixtures on the birth weight of girls and further highlight the sex heterogeneity in fetal development influenced by intrauterine environmental factors.

Mammary Gland Development in Male Rats Perinatally Exposed to Propiconazole, Glyphosate, or their Mixture

This study aimed to assess whether perinatal exposure to propiconazole (PRO), glyphosate (GLY) or their mixture (PROGLY) alters key endocrine pathways and the development of the male rat mammary gland. To this end, pregnant rats were orally exposed to vehicle, PRO, GLY, or a mixture of PRO and GLY from gestation day 9 until weaning. Male offspring were euthanized on postnatal day (PND) 21 and PND60. On PND21, GLY-exposed rats showed reduced mammary epithelial cell proliferation, whereas PRO-exposed ones showed increased ductal p-Erk1/2 expression without histomorphological alterations. On PND60, GLY-exposed rats showed reduced mammary gland area and estrogen receptor alpha expression and increased aromatase expression, whereas PRO-exposed ones showed enhanced lobuloalveolar development and increased lobular hyperplasia. However, PROGLY did not modify any of the endpoints evaluated. In summary, PRO and GLY modified the expression of key molecules and the development of the male mammary gland individually but not together.

Association between whole blood essential trace elements and cognitive function in older adults

BACKGROUND

Essential trace elements (ETEs) are essential nutrients for keeping the nervous system functioning. Associations between ETEs and cognitive function are still inconclusive and limited.

OBJECTIVES

We aimed to investigate the individual and joint associations between ETEs and cognitive function among older adults.

METHODS

A population (N = 2181) at an average age≥ 65 from Yiwu cohort in China was available for this study. Whole blood chromium (Cr), selenium (Se), manganese (Mn), and copper (Cu) concentrations were measured by inductively coupled plasma mass spectrometry (ICP-MS). Cognitive function was assessed using the Mini-Mental State Examination (MMSE), consisting of five specific cognitive domains: orientation, registry, attention and calculation, recall, and language and praxis. Linear regression, restricted cubic spline (RCS) analysis, and Bayesian kernel machine regression (BKMR) were used to analyze the individual and joint associations between ETEs and cognitive function.

RESULTS

The association between Cr and MMSE score presented an inverted-U shape (Q3 versus Q1: β = 0.774, 95 % CI: 0.297, 1.250; Q4 versus Q1: β = 0.481, 95 % CI: 0.006, 0.956); and Cr was especially associated with the registry, recall, and language and praxis. Per IQR (36.32 μg/L) increase of Se was positively associated with the MMSE score (β = 0.497, 95 % CI: 0.277, 0.717) and all five cognitive domains. The BKMR showed that the dose-response association between Se and cognitive function increased initially and then decreased with increasing Se concentration when fixed the other ETEs in median. ETEs mixture was positively associated with cognitive function, and Se (posterior inclusion probabilities, PIPs = 0.915) was the most important contributor within the ETEs mixture.

CONCLUSIONS

The nonlinear association between Cr and cognitive function suggested further exploration of an appropriate concentration range for ETEs. A positive association between mixed ETEs and cognitive function is a reminder that their joint association should be considered. Further prospective studies or intervention studies are warranted to validate our findings in the future.

Exposures to pesticides and risk of cancer: Evaluation of recent epidemiological evidence in humans and paths forward

Knowledge of the role in cancer etiology of environmental exposures as pesticides is a prerequisite for primary prevention. We review 63 epidemiological studies on exposure to pesticides and cancer risk in humans published from 2017 to 2021, with emphasis on new findings, methodological approaches, and gaps in the existing literature. While much of the recent evidence suggests causal relationships between pesticide exposure and cancer, the strongest evidence exists for acute myeloid leukemia (AML) and colorectal cancer (CRC), diseases in which the observed associations were consistent across several studies, including high-quality prospective studies and those using biomarkers for exposure assessment, with some observing dose-response relationships. Though high-quality studies have been published since the IARC monograph on organophosphate insecticides in 2017, there are still gaps in the literature on carcinogenic evidence in humans for a large number of pesticides. To further knowledge, we suggest leveraging new techniques and methods to increase sensitivity and precision of exposure assessment, incorporate multi-omics data, and investigate more thoroughly exposure to chemical mixtures. There is also a strong need for better and larger population-based cohort studies that include younger and nonoccupationally exposed individuals, particularly during developmental periods of susceptibility. Though the existing evidence has limitations, as always in science, there is sufficient evidence to implement policies and regulatory action that limit pesticide exposure in humans and, hence, further prevent a significant burden of cancers.

Bayesian multiple index models for environmental mixtures

An important goal of environmental health research is to assess the risk posed by mixtures of environmental exposures. Two popular classes of models for mixtures analyses are response-surface methods and exposure-index methods. Response-surface methods estimate high-dimensional surfaces and are thus highly flexible but difficult to interpret. In contrast, exposure-index methods decompose coefficients from a linear model into an overall mixture effect and individual index weights; these models yield easily interpretable effect estimates and efficient inferences when model assumptions hold, but, like most parsimonious models, incur bias when these assumptions do not hold. In this paper, we propose a Bayesian multiple index model framework that combines the strengths of each, allowing for non-linear and non-additive relationships between exposure indices and a health outcome, while reducing the dimensionality of the exposure vector and estimating index weights with variable selection. This framework contains response-surface and exposure-index models as special cases, thereby unifying the two analysis strategies. This unification increases the range of models possible for analysing environmental mixtures and health, allowing one to select an appropriate analysis from a spectrum of models varying in flexibility and interpretability. In an analysis of the association between telomere length and 18 organic pollutants in the National Health and Nutrition Examination Survey (NHANES), the proposed approach fits the data as well as more complex response-surface methods and yields more interpretable results.

Advancing Exposomic Research in Prenatal Respiratory Disease Programming

Disease programming reflects interactions between genes and the environment. Unlike the genome, environmental exposures and our response to exposures change over time. Starting in utero, the respiratory system and related processes develop sequentially in a carefully timed cascade, thus effects depend on both exposure dose and timing. A multitude of environmental and microbial exposures influence respiratory disease programming. Effects result from toxin-induced shifts in a host of molecular, cellular, and physiologic states and their interacting systems. Moreover, pregnant women and the developing child are not exposed to a single toxin, but to complex mixtures.

Association between trimester-specific exposure to thirteen endocrine disrupting chemicals and preterm birth: Comparison of three statistical models

BACKGROUND

Growing evidence indicated that maternal exposure to some endocrine disrupting chemicals (EDCs) may increase the risk of preterm birth (PTB). However, few studies have evaluated the joint effect of EDCs on PTB.

OBJECTIVES

This study aimed to evaluate the associations of maternal EDCs mixture in the 1st, 2nd, and 3rd trimesters during pregnancy with PTB, and identify the vital components that mainly contribute to PTB.

METHODS

This study included 847 pregnant women that provided urine samples for all three trimesters. Urinary concentrations of thirteen EDC metabolites (four phthalates, two parabens, three phenols, and four benzotriazoles and benzothiazoles) were examined. Logistic regression model, quantile g-computation and Bayesian kernel machine regression (BKMR) models were applied to study the association.

RESULTS

Logistic regression model suggested that only bisphenol A (BPA) in the 1st trimester significantly increased the OR of PTB after adjusting for BPA exposure in the 2nd and 3rd trimesters. Quantile g-computation model identified that urinary EDCs mixture in the 1st trimester were positively associated with PTB [OR (95 % CI): 1.98 (1.10, 3.58)], and the most heavily weighted component for PTB was BPA (26 %), followed by mono-2ethylhexyl phthalate (MEHP) (22 %). BKMR model determined a significant association between EDCs mixture in the 1st trimester and PTB when all EDC concentrations were at or above their 55th percentile compared with the median. The BKMR model found that BPA and MEHP were associated with an increase in the estimated probability of PTB, when the other EDCs were held to their 50th and 75th percentiles, respectively, in the 1st trimester.

CONCLUSIONS

The results of mixture analysis models indicated that exposure to higher EDCs mixture in the 1st trimester may increase the risk of PTB. BPA was considered as the most contributing factor for PTB among the detected EDCs.

Impact of mixtures of persistent organic pollutants on breast cancer aggressiveness

INTRODUCTION

Breast cancer (BC) is frequent with a poor prognosis in case of metastasis. The role of the environment has been poorly evaluated in its progression. We searched to assess whether a mixture of pollutants could be responsible of BC aggressiveness.

METHODS

Patients undergoing surgery for their BC were prospectively included in the METAPOP cohort. Forty-two POPs were extracted, among them 17 dioxins (PCDD/F), 16 polychlorobiphenyls (PCB), 8 polybromodiphenylethers (PBDE) and 2,2',4,4',5,5'-hexabromobiphenyl (PBB153) were measured in the adipose tissue surrounding the tumor. BC aggressiveness was defined using tumor size and metastasis (distant or lymph nodes). Two complementary models were used to evaluate the impact of the mixture of pollutants: the BKMR (Bayesian Kernel machine regression) and WQS (weighted quantile sum regression) models. The WQS estimates the weight (positive or negative) of a certain chemical based on its quantile and the BKMR model applies a kernel-based approach to estimate posterior inclusion probabilities. The sub-group of patients with a body mass index (BMI) > 22 kg/ m² was also analyzed.

RESULTS

Ninety-one patients were included. Of these, 38 patients presented a metastasis, and the mean tumor size was 25.4 mm. The mean BMI was 24.5 kg/m² (+/- 4.1). No statistical association was found in the general population. However, in patients with a BMI > 22 kg/ m², our mixture was positively associated with tumor size (OR: 9.73 95 %CI: 1.30-18.15) and metastasis (OR = 3.98 95 %CI = 1.09-17.53) using the WQS model. Moreover, using the BKMR model on chemical families, dioxin like chemicals and PCDD were associated with a higher risk of metastasis.

DISCUSSION

These novel findings identified a mixture associated with breast cancer aggressiveness in patients with a BMI > 22 kg/ m².

Inflammation and oxidative stress as mediators of the impacts of environmental exposures on human pregnancy: Evidence from oxylipins

Inflammation and oxidative stress play major roles in healthy and pathological pregnancy. Environmental exposure to chemical pollutants may adversely affect maternal and fetal health in pregnancy by dysregulating these critical underlying processes of inflammation and oxidative stress. Oxylipins are bioactive lipids that play a major role in regulating inflammation and increasing lines of evidence point towards an importance in pregnancy. The biosynthetic production of oxylipins requires oxygenation of polyunsaturated fatty acids, which can occur through several well-characterized enzymatic and nonenzymatic pathways. This review describes the state of the science of epidemiologic evidence on oxylipin production in pregnancy and its association with 1) key pregnancy outcomes and 2) environmental exposures. We searched PubMed for studies of pregnancy that measured one or more oxylipin analytes during pregnancy or delivery. We evaluated oxylipin associations with three categories of adverse pregnancy outcomes, including preeclampsia, preterm birth, and fetal growth restriction, along with several categories of environmental pollutants. The majority of studies evaluated one to two oxylipins, most of which focused on oxylipins produced from nonenzymatic processes of oxidative stress. However, an increasing number of recent studies have leveraged technological advancements to profile a large number of oxylipins produced from distinct biosynthetic pathways. Although the literature indicated robust evidence that oxylipins produced via nonenzymatic pathways are associated with pregnancy outcomes and environmental exposures, evidence for enzymatically produced oxylipins showed that associations may differ between biosynthetic pathways. Along with summarizing this evidence, we review promising therapeutic options to regulate oxylipin production and provide a set of recommendations for future epidemiologic studies in these research areas. Further evidence is needed to improve our understanding of how oxylipins may act as key biological mediators for the adverse effects of environmental pollutants on pregnancy outcomes.

Environmental mixtures and breast cancer: identifying co-exposure patterns between understudied vs breast cancer-associated chemicals using chemical inventory informatics

BACKGROUND

Although evidence linking environmental chemicals to breast cancer is growing, mixtures-based exposure evaluations are lacking.

OBJECTIVE

This study aimed to identify environmental chemicals in use inventories that co-occur and share properties with chemicals that have association with breast cancer, highlighting exposure combinations that may alter disease risk.

METHODS

The occurrence of chemicals within chemical use categories was characterized using the Chemical and Products Database. Co-exposure patterns were evaluated for chemicals that have an association with breast cancer (BC), no known association (NBC), and understudied chemicals (UC) identified through query of the Silent Spring Institute's Mammary Carcinogens Review Database and the U.S. Environmental Protection Agency's Toxicity Reference Database. UCs were ranked based on structure and physicochemical similarities and co-occurrence patterns with BCs within environmentally relevant exposure sources.

RESULTS

A total of 6793 chemicals had data available for exposure source occurrence analyses. 50 top-ranking UCs spanning five clusters of co-occurring chemicals were prioritized, based on shared properties with co-occuring BCs, including chemicals used in food production and consumer/personal care products, as well as potential endocrine system modulators.

SIGNIFICANCE

Results highlight important co-exposure conditions that are likely prevalent within our everyday environments that warrant further evaluation for possible breast cancer risk.

IMPACT STATEMENT

Most environmental studies on breast cancer have focused on evaluating relationships between individual, well-known chemicals and breast cancer risk. This study set out to expand this research field by identifying understudied chemicals and mixtures that may occur in everyday environments due to their patterns of commercial use. Analyses focused on those that co-occur alongside chemicals associated with breast cancer, based upon in silico chemical database querying and analysis. Particularly in instances when understudied chemicals share physicochemical properties and structural features with carcinogens, these chemical mixtures represent conditions that should be studied in future clinical, epidemiological, and toxicological studies.

Environmental mixtures and breast cancer: identifying co-exposure patterns between understudied vs breast cancer-associated chemicals using chemical inventory informatics

BACKGROUND

Although evidence linking environmental chemicals to breast cancer is growing, mixtures-based exposure evaluations are lacking.

OBJECTIVE

This study aimed to identify environmental chemicals in use inventories that co-occur and share properties with chemicals that have association with breast cancer, highlighting exposure combinations that may alter disease risk.

METHODS

The occurrence of chemicals within chemical use categories was characterized using the Chemical and Products Database. Co-exposure patterns were evaluated for chemicals that have an association with breast cancer (BC), no known association (NBC), and understudied chemicals (UC) identified through query of the Silent Spring Institute's Mammary Carcinogens Review Database and the U.S. Environmental Protection Agency's Toxicity Reference Database. UCs were ranked based on structure and physicochemical similarities and co-occurrence patterns with BCs within environmentally relevant exposure sources.

RESULTS

A total of 6793 chemicals had data available for exposure source occurrence analyses. 50 top-ranking UCs spanning five clusters of co-occurring chemicals were prioritized, based on shared properties with co-occuring BCs, including chemicals used in food production and consumer/personal care products, as well as potential endocrine system modulators.

SIGNIFICANCE

Results highlight important co-exposure conditions that are likely prevalent within our everyday environments that warrant further evaluation for possible breast cancer risk.

IMPACT STATEMENT

Most environmental studies on breast cancer have focused on evaluating relationships between individual, well-known chemicals and breast cancer risk. This study set out to expand this research field by identifying understudied chemicals and mixtures that may occur in everyday environments due to their patterns of commercial use. Analyses focused on those that co-occur alongside chemicals associated with breast cancer, based upon in silico chemical database querying and analysis. Particularly in instances when understudied chemicals share physicochemical properties and structural features with carcinogens, these chemical mixtures represent conditions that should be studied in future clinical, epidemiological, and toxicological studies.

Leveraging Multiple Data Streams for Prioritization of Mixtures for Hazard Characterization

There is a growing need to establish alternative approaches for mixture safety assessment of polycyclic aromatic hydrocarbons (PAHs). Due to limitations with current component-based approaches, and the lack of established methods for using whole mixtures, a promising alternative is to use sufficiently similar mixtures; although, an established framework is lacking. In this study, several approaches are explored to form sufficiently similar mixtures. Multiple data streams including environmental concentrations and empirically and predicted toxicity data for cancer and non-cancer endpoints were used to prioritize chemical components for mixture formations. Air samplers were analyzed for unsubstituted and alkylated PAHs. A synthetic mixture of identified PAHs was created (Creosote-Fire Mix). Existing toxicity values and chemical concentrations were incorporated to identify hazardous components in the Creosote-Fire Mix. Sufficiently similar mixtures of the Creosote-Fire Mix were formed based on (1) relative abundance; (2) toxicity values; and (3) a combination approach incorporating toxicity and abundance. Hazard characterization of these mixtures was performed using high-throughput screening in primary normal human bronchial epithelium (NHBE) and zebrafish. Differences in chemical composition and potency were observed between mixture formation approaches. The toxicity-based approach (Tox Mix) was the most potent mixture in both models. The combination approach (Weighted-Tox Mix) was determined to be the ideal approach due its ability to prioritize chemicals with high exposure and hazard potential.

A nested case-control study of serum polychlorinated biphenyls and papillary thyroid cancer risk among U.S. military service members

BACKGROUND AND OBJECTIVES

Although polychlorinated biphenyls (PCBs) were banned decades ago, populations are continuously exposed to PCBs due to their persistence and bioaccumulation/biomagnification in the environment. Results from limited epidemiologic studies linking PCBs to thyroid cancer have been inconclusive. This study aimed to investigate the association between individual PCBs and PCB mixture and papillary thyroid cancer (PTC), the most common thyroid cancer histologic subtype.

METHODS

We carried out a nested case-control study including 742 histologically confirmed PTC cases diagnosed in 2000-2013 and 742 individually matched controls among U.S. military service members. Pre-diagnostic serum samples that were collected on average nine years before PTC diagnosis were used to measure PCB congeners by gas chromatography isotope dilution high resolution mass spectrometry (GC/ID-HRMS). Conditional logistic regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression were employed to estimate the association between single PCB congeners as well as their mixture and PTC.

RESULTS

Four PCB congeners (PCB-74, PCB-99, PCB-105, PCB-118) had significant associations and dose-response relationships with increased risk of PTC in single congener models. When considering the effects from all measured PCBs and their potential interactions in the BKMR model, PCB-118 showed positive trends of association with PTC. Increased exposure to the PCB congeners as a mixturewas also associated with an increased risk of PTC in the WQS model, with the mixture dominated by PCB-118, followed by PCB-74 and PCB-99. One PCB congener, PCB-187, showed an inverse trend of association with PTC in the mixture analysis.

DISCUSSION

This study suggests that exposure to certain PCBs as well as a mixture of PCBs were associated with an increased risk of PTC. The observed association was mainly driven by PCB-118, and to a lesser extent by PCB-74 and PCB-99. The findings warrant further investigation.

The complex relationship of air pollution and neighborhood socioeconomic status and their association with cognitive decline

BACKGROUND

Air pollution and neighborhood socioeconomic status (nSES) have been shown to affect cognitive decline in older adults. In previous studies, nSES acts as both a confounder and an effect modifier between air pollution and cognitive decline.

OBJECTIVES

This study aims to examine the individual and joint effects of air pollution and nSES on cognitive decline on adults 50 years and older in Metro Atlanta, USA.

METHODS

Perceived memory and cognitive decline was assessed in 11,897 participants aged 50+ years from the Emory Healthy Aging Study (EHAS) using the cognitive function instrument (CFI). Three-year average air pollution concentrations for 12 pollutants and 16 nSES characteristics were matched to participants using census tracts. Individual exposure linear regression and LASSO models explore individual exposure effects. Environmental mixture modeling methods including, self-organizing maps (SOM), Bayesian kernel machine regression (BKMR), and quantile-based G-computation explore joint effects, and effect modification between air pollutants and nSES characteristics on cognitive decline.

RESULTS

Participants living in areas with higher air pollution concentrations and lower nSES experienced higher CFI scores (beta: 0.121; 95 % CI: 0.076, 0.167) compared to participants living in areas with low air pollution and high nSES. Additionally, the BKMR model showed a significant overall mixture effect on cognitive decline, suggesting synergy between air pollution and nSES. These joint effects explain protective effects observed in single-pollutant linear regression models, even after adjustment for confounding by nSES (e.g., an IQR increase in CO was associated with a 0.038-point lower (95 % CI: -0.06, -0.01) CFI score).

DISCUSSION

Observed protective effects of single air pollutants on cognitive decline can be explained by joint effects and effect modification of air pollutants and nSES. Researchers must consider nSES as an effect modifier if not a co-exposure to better understand the complex relationships between air pollution and nSES in urban settings.

Association of preconception mixtures of phenol and phthalate metabolites with birthweight among subfertile couples

Although parental preconception exposure to some phenols and phthalates have been associated with reduced birthweight, few studies have examined these chemicals as complex mixtures.

AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications

Metabolomics describes a high-throughput approach for measuring a repertoire of metabolites and small molecules in biological samples. One utility of untargeted metabolomics, unbiased global analysis of the metabolome, is to detect key metabolites as contributors to, or readouts of, human health and disease. In this perspective, we discuss how artificial intelligence (AI) and machine learning (ML) have promoted major advances in untargeted metabolomics workflows and facilitated pivotal findings in the areas of disease screening and diagnosis. We contextualize applications of AI and ML to the emerging field of high-resolution mass spectrometry (HRMS) exposomics, which unbiasedly detects endogenous metabolites and exogenous chemicals in human tissue to characterize exposure linked with disease outcomes. We discuss the state of the science and suggest potential opportunities for using AI and ML to improve data quality, rigor, detection, and chemical identification in untargeted metabolomics and exposomics studies.

Associations between exposure to a mixture of phenols, parabens, and phthalates and sex steroid hormones in children 6-19 years from NHANES, 2013-2016

BACKGROUND

Humans are typically exposed to mixtures of environmental endocrine-disrupting chemicals simultaneously, but most studies have considered only a single chemical or a class of similar chemicals.

OBJECTIVES

We examined the association of exposure to mixtures of 7 chemicals, including 2 phenols [bisphenol A (BPA) and bisphenol S (BPS)], 2 parabens [methylparaben (MeP) and propyl paraben (PrP)], and 3 phthalate metabolites [Mono-benzyl phthalate (MBzP), mono-isobutyl phthalate (MiBP), mono (carboxyoctyl) phthalate (MCOP)] with sex steroid hormones.

METHODS

A total of 1179 children aged 6-19 years who had complete data on both 7 chemicals and sex steroid hormones of estradiol (E₂), total testosterone (TT), and sex hormone-binding globulin (SHBG) were analyzed from the U.S. National Health and Nutrition Examination Survey 2013-2016. Free androgen index (FAI) calculated by TT/SHBG, and the ratio of TT to E₂ (TT/E₂) were also estimated. Puberty was defined if TT ≥ 50 ng/dL in boys, E₂ ≥ 20 pg/mL in girls; otherwise prepuberty was defined. Linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were performed to estimate the associations of individual chemical or chemical mixtures with sex hormones.

RESULTS

The linear regression showed that 2 phenols, 2 parabens, and 3 phthalate metabolites were generally negatively associated with E₂, TT, FAI, and TT/E₂, while positively with SHBG. Moreover, these associations were more pronounced among pubertal than prepubertal children. The aforementioned associations were confirmed when further applying WQS and BKMR, and the 3 phthalates metabolites were identified to be the most heavily weighing chemicals.

CONCLUSIONS

Exposure to phenols, parabens, and phthalates, either individuals or as a mixture, was negatively associated with E₂, TT, FAI and TT/E₂, while positively with SHBG. Those associations were stronger among pubertal children.

Understanding the combined effects of multiple stressors: A new perspective on a longstanding challenge

Wildlife populations and their habitats are exposed to an expanding diversity and intensity of stressors caused by human activities, within the broader context of natural processes and increasing pressure from climate change. Estimating how these multiple stressors affect individuals, populations, and ecosystems is thus of growing importance. However, their combined effects often cannot be predicted reliably from the individual effects of each stressor, and we lack the mechanistic understanding and analytical tools to predict their joint outcomes. We review the science of multiple stressors and present a conceptual framework that captures and reconciles the variety of existing approaches for assessing combined effects. Specifically, we show that all approaches lie along a spectrum, reflecting increasing assumptions about the mechanisms that regulate the action of single stressors and their combined effects. An emphasis on mechanisms improves analytical precision and predictive power but could introduce bias if the underlying assumptions are incorrect. A purely empirical approach has less risk of bias but requires adequate data on the effects of the full range of anticipated combinations of stressor types and magnitudes. We illustrate how this spectrum can be formalised into specific analytical methods, using an example of North Atlantic right whales feeding on limited prey resources while simultaneously being affected by entanglement in fishing gear. In practice, case-specific management needs and data availability will guide the exploration of the stressor combinations of interest and the selection of a suitable trade-off between precision and bias. We argue that the primary goal for adaptive management should be to identify the most practical and effective ways to remove or reduce specific combinations of stressors, bringing the risk of adverse impacts on populations and ecosystems below acceptable thresholds.

Association of both prenatal and early childhood multiple metals exposure with neurodevelopment in infant: A prospective cohort study

BACKGROUND

Impaired neurodevelopment of children has become a growing public concern; however, the associations between metals exposure and neurocognitive function have remained largely unknown.

OBJECTIVES

We systematically evaluated the associations of multiple metals exposure during pregnancy and childhood on the neurodevelopment of children aged 2-3 years.

METHODS

We measured 22 metals in the serum and urine among703 mother-child pairs from the Guangxi Birth Cohort Study. The neurocognitive development of children was assessed by the Gesell Development Diagnosis Scale (GDDS; Chinese version). Multiple linear regression models were used to evaluate the relationship between the metals (selected by elastic net regression) and the outcomes. The Bayesian kernel machine regression (BKMR) was used to evaluate the possible joint effect between the multiple metal mixture and the outcomes.

RESULTS

Prenatal aluminum (Al) exposure was negatively associated with the fine motor developmental quotient (DQ) (β = -1.545, 95%CI: 2.231, -0.859), adaption DQ (β = -1.182, 95%CI: 1.632, -0.732), language DQ (β = -1.284, 95% CI: 1.758, -0.809), and social DQ (β = -1.729, 95% CI: 2.406, -1.052) in the multi-metal model. Prenatal cadmium (Cd) exposure was negatively associated with gross motor DQ (β = -2.524, 95% CI: 4.060, -0.988), while postpartum Cd exposure was negatively associated with language DQ (β = -1.678, 95% CI: 3.227, -0.129). In stratified analyses, infants of different sexes had different sensitivities to metal exposure, and neurobehavioral development was more significantly affected by metal exposure in the first and second trimester. BKMR analysis revealed a negative joint effect of the Al, Cd, and selenium (Se) on the language DQ score; postpartum Cd exposure played a major role in this relationship.

CONCLUSION

Prenatal exposure to Al, Ba, Cd, molybdenum (Mo), lead (Pb), antimony (Sb), and strontium (Sr), and postpartum exposure to cobalt (Co), Cd, stannum (Sn), iron (Fe), nickel (Ni), and Se are associated with neurological development of infants. The first and second trimester might be the most sensitive period when metal exposure affects neurodevelopment.

Prenatal exposure to chemical mixtures and working memory among adolescents

Working memory is the ability to keep information in one's mind and mentally manipulate it. Decrements in working memory play a key role in many behavioral and psychiatric disorders, therefore identifying modifiable environmental risk factors for such decrements is important for mitigating these disorders. There is some evidence that prenatal exposure to individual chemicals may adversely impact working memory among children, but few studies have explored the association of co-exposure to multiple chemicals with this outcome in adolescence, a time when working memory skills undergo substantial development. We investigated the association of organochlorines (DDE, HCB, PCBs) and metals (lead, manganese) measured in cord serum and cord blood, respectively, with working memory measured with the Wide Range Assessment of Memory and Learning, 2nd Edition among 373 adolescents living near a Superfund site in New Bedford, Massachusetts. We used Bayesian Kernel Machine Regression (BKMR) and linear regression analyses and assessed effect modification by sex and prenatal social disadvantage. In BKMR models, we observed an adverse joint association of the chemical mixture with Verbal, but not Symbolic, Working Memory. In co-exposure and covariate-adjusted linear regression models, a twofold increase in cord blood manganese was associated with lower working memory scaled scores, with a stronger association with Verbal Working Memory (difference = -0.75; 95% CI: -1.29, -0.20 points) compared to Symbolic Working Memory (difference = -0.44; 95% CI: -1.00, 0.12 points). There was little evidence of effect modification by sex and some evidence associating organochlorine pesticides with poorer working memory scores among those with greater prenatal social disadvantage. This study provided evidence of an adverse joint association of a chemical mixture with a verbal working memory task among adolescents, as well as an adverse association of prenatal manganese exposure with working memory.

A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals

A 2019 retrospective study analyzed wristband personal samplers from fourteen different communities across three different continents for over 1530 organic chemicals. Investigators identified fourteen chemicals (G14) detected in over 50% of personal samplers. The G14 represent a group of chemicals that individuals are commonly exposed to, and are mainly associated with consumer products including plasticizers, fragrances, flame retardants, and pesticides. The high frequency of exposure to these chemicals raises questions of their potential adverse human health effects. Additionally, the possibility of exposure to mixtures of these chemicals is likely due to their co-occurrence; thus, the potential for mixtures to induce differential bioactivity warrants further investigation. This study describes a novel approach to broadly evaluate the hazards of personal chemical exposures by coupling data from personal sampling devices with high-throughput bioactivity screenings using in vitro and non-mammalian in vivo models. To account for species and sensitivity differences, screening was conducted using primary normal human bronchial epithelial (NHBE) cells and early life-stage zebrafish. Mixtures of the G14 and most potent G14 chemicals were created to assess potential mixture effects. Chemical bioactivity was dependent on the model system, with five and eleven chemicals deemed bioactive in NHBE and zebrafish, respectively, supporting the use of a multi-system approach for bioactivity testing and highlighting sensitivity differences between the models. In both NHBE and zebrafish, mixture effects were observed when screening mixtures of the most potent chemicals. Observations of BMC-based mixtures in NHBE (NHBE BMC Mix) and zebrafish (ZF BMC Mix) suggested antagonistic effects. In this study, consumer product-related chemicals were prioritized for bioactivity screening using personal exposure data. High-throughput high-content screening was utilized to assess the chemical bioactivity and mixture effects of the most potent chemicals.

Exposure to Metal Mixtures in Association with Cardiovascular Risk Factors and Outcomes: A Scoping Review

Since the National Institute of Environmental Health Sciences (NIEHS) declared conducting combined exposure research as a priority area, literature on chemical mixtures has grown dramatically. However, a systematic evaluation of the current literature investigating the impacts of metal mixtures on cardiovascular disease (CVD) risk factors and outcomes has thus far not been performed. This scoping review aims to summarize published epidemiology literature on the cardiotoxicity of exposure to multiple metals. We performed systematic searches of MEDLINE (PubMed), Scopus, and Web of Science to identify peer-reviewed studies employing statistical mixture analysis methods to evaluate the impact of metal mixtures on CVD risk factors and outcomes among nonoccupationally exposed populations. The search was limited to papers published on or after 1998, when the first dedicated funding for mixtures research was granted by NIEHS, through 1 October 2021. Twenty-nine original research studies were identified for review. A notable increase in relevant mixtures publications was observed starting in 2019. The majority of eligible studies were conducted in the United States (n = 10) and China (n = 9). Sample sizes ranged from 127 to 10,818. Many of the included studies were cross-sectional in design. Four primary focus areas included: (i) blood pressure and/or diagnosis of hypertension (n = 15), (ii) risk of preeclampsia (n = 3), (iii) dyslipidemia and/or serum lipid markers (n = 5), and (iv) CVD outcomes, including stroke incidence or coronary heart disease (n = 8). The most frequently investigated metals included cadmium, lead, arsenic, and cobalt, which were typically measured in blood (n = 15). The most commonly utilized multipollutant analysis approaches were Bayesian kernel machine regression (BKMR), weighted quantile sum regression (WQSR), and principal component analysis (PCA). To our knowledge, this is the first scoping review to assess exposure to metal mixtures in relation to CVD risk factors and outcomes. Recommendations for future studies evaluating the associations of exposure to metal mixtures with risk of CVDs and related risk factors include extending environmental mixtures epidemiologic studies to populations with wider metals exposure ranges, including other CVD risk factors or outcomes outside hypertension or dyslipidemia, using repeated measurement of metals to detect windows of susceptibility, and further examining the impacts of potential effect modifiers and confounding factors, such as fish and seafood intake.