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Background Estimating the health effects of multi-pollutant mixtures is of increasing interest in environmental epidemiology. Recently, a new approach for estimating the health effects of mixtures, Bayesian kernel machine regression (BKMR), has been developed. This method estimates the multivariable exposure-response function in a flexible and parsimonious way, conducts variable selection on the (potentially high-dimensional) vector of exposures, and allows for a grouped variable selection approach that can accommodate highly correlated exposures. However, the application of this novel method has been limited by a lack of available software, the need to derive interpretable output in a computationally efficient manner, and the inability to apply the method to non-continuous outcome variables. Methods This paper addresses these limitations by (i) introducing an open-source software package in the R programming language, the bkmr R package, (ii) demonstrating methods for visualizing high-dimensional exposure-response functions, and for estimating scientifically relevant summaries, (iii) illustrating a probit regression implementation of BKMR for binary outcomes, and (iv) describing a fast version of BKMR that utilizes a Gaussian predictive process approach. All of the methods are illustrated using fully reproducible examples with the provided R code. Results Applying the methods to a continuous outcome example illustrated the ability of the BKMR implementation to estimate the health effects of multi-pollutant mixtures in the context of a highly nonlinear, biologically-based dose-response function, and to estimate overall, single-exposure, and interactive health effects. The Gaussian predictive process method led to a substantial reduction in the runtime, without a major decrease in accuracy. In the setting of a larger number of exposures and a dichotomous outcome, the probit BKMR implementation was able to correctly identify the variables included in the exposure-response function and yielded interpretable quantities on the scale of a latent continuous outcome or on the scale of the outcome probability. Conclusions This newly developed software, integrated suite of tools, and extended methodology makes BKMR accessible for use across a broad range of epidemiological applications in which multiple risk factors have complex effects on health.

Exposure to chemical mixtures is recognized as the real-life scenario in all populations, needing new statistical methods that can assess their complex effects. We aimed to assess the joint effect of in utero exposure to arsenic, manganese, and lead on children's neurodevelopment. We employed a novel statistical approach, Bayesian kernel machine regression (BKMR), to study the joint effect of coexposure to arsenic, manganese, and lead on neurodevelopment using an adapted Bayley Scale of Infant and Toddler Development™. Third Edition, in 825 mother-child pairs recruited into a prospective birth cohort from two clinics in the Pabna and Sirajdikhan districts of Bangladesh. Metals were measured in cord blood using inductively coupled plasma-mass spectrometry. Analyses were stratified by clinic due to differences in exposure profiles. In the Pabna district, which displayed high manganese levels [interquartile range (IQR): 4.8, 18 μg/dl], we found a statistically significant negative effect of the mixture of arsenic, lead, and manganese on cognitive score when cord blood metals concentrations were all above the 60th percentile (As≥0.7 μg/dl, Mn≥6.6 μg/dl, Pb≥4.2 μg/dl) compared to the median (As=0.5 μg/dl, Mn=5.8 μg/dl, Pb=3.1 μg/dl). Evidence of a nonlinear effect of manganese was found. A change in log manganese from the 25th to the 75th percentile when arsenic and manganese were at the median was associated with a decrease in cognitive score of −0.3 (−0.5, −0.1) standard deviations. Our study suggests that arsenic might be a potentiator of manganese toxicity. Employing a novel statistical method for the study of the health effects of chemical mixtures, we found evidence of neurotoxicity of the mixture, as well as potential synergism between arsenic and manganese. https://doi.org/10.1289/EHP614.

Research on the health effects of chemical mixtures has focused mainly on early life rather than adolescence, a potentially important developmental life stage. We examined associations of a metal mixture with general cognition in a cross-sectional study of adolescents residing near ferromanganese industry, a source of airborne metals emissions. We measured manganese (Mn), lead (Pb), copper (Cu), and chromium (Cr) in hair, blood, urine, nails, and saliva from 635 Italian adolescents 10-14 years of age. Full-scale, verbal, and performance intelligence quotient (FSIQ, VIQ, PIQ) scores were assessed using the Wechsler Intelligence Scale for Children-III. Multivariable linear regression and Bayesian kernel machine regression (BKMR) were used to estimate associations of the metal mixture with IQ. In secondary analyses, we used BKMR's hierarchical variable selection option to inform biomarker selection for Mn, Cu, and Cr. Median metal concentrations were as follows: hair Mn, ; hair Cu, ; hair Cr, ; and blood Pb, . Adjusted models revealed an inverted U-shaped association between hair Cu and VIQ, consistent with Cu as an essential nutrient that is neurotoxic in excess. At low levels of hair Cu (10th percentile, ), higher concentrations (90th percentiles) of the mixture of Mn, Pb, and Cr ( , , and , respectively) were associated with a 2.9 (95% CI: , )-point decrease in VIQ score, compared with median concentrations of the mixture. There was suggestive evidence of interaction between Mn and Cu. In secondary analyses, saliva Mn, hair Cu, and saliva Cr were selected as the biomarkers most strongly associated with VIQ score. Higher adolescent levels of Mn, Pb, and Cr were associated with lower IQ scores, especially at low Cu levels. Findings also support further investigation into Cu as both beneficial and toxic for neurobehavioral outcomes. https://doi.org/10.1289/EHP6803.

Metal exposure during pregnancy influences maternal and child health. Oxidative stress and inflammation may mediate adverse effects of heavy metals, whereas essential metals may act as antioxidants. Mitochondrial DNA is a prime target for metal-induced oxidative damage. Telomere dysfunction is attributed to imbalances between reactive oxidant species and antioxidants. We evaluated individual and joint associations of prenatal metals with mitochondrial DNA copy number (mtDNAcn) and telomere length (TL) in maternal and cord blood as biomarkers of inflammation and oxidative stress. We measured six nonessential metals (arsenic, barium, cadmium, cesium, lead, mercury) and four essential metals (magnesium, manganese, selenium, zinc) in first-trimester maternal red blood cells in Project Viva, a U.S. prebirth cohort. We measured relative mtDNAcn ( ) and TL ( ) in second-trimester maternal blood and mtDNAcn ( ) and TL ( ) in cord blood. We used multivariable linear regression and quantile g-computation to estimate associations between prenatal metals and the biomarkers. We used generalized additive models and Bayesian kernel machine regression to examine nonlinearity and interactions. A 2-fold increase in maternal magnesium was associated with lower maternal [ , 95% confidence interval (CI): , ] and cord blood ( , 95% CI: , ) mtDNAcn. Lead was associated with higher maternal mtDNAcn ( , 95% CI: 0.01, 0.06). Selenium was associated with longer cord blood TL ( , 95% CI: 0.01 0.50). An association was observed between the nonessential metal mixture and higher maternal mtDNAcn ( , 95% CI: 0.01, 0.07). There was a nonlinear relationship between cord blood mtDNAcn and magnesium; maternal mtDNAcn and barium, lead, and mercury; and maternal TL and barium. Maternal exposure to metals such as lead, magnesium, and selenium was associated with mtDNAcn and TL in maternal second trimester and cord blood. Future work will evaluate whether these biomarkers are associated with child health. https://doi.org/10.1289/EHP9294.

Lead (Pb) and mercury (Hg) neurotoxicity is well established. In recent years, a growing body of evidence suggests that environmental exposure to other metals including arsenic (As), cadmium (Cd), and manganese (Mn) and their mixtures also poses public health threats. In this paper, we summarize the recent literature examining the relationship of prenatal and childhood environmental metal exposures with cognitive and behavioral outcomes in children. We conducted a literature search to identify epidemiologic studies that examined the relationship of Cd, Mn, and metal mixtures with children’s neurodevelopmental/cognitive and behavioral outcomes. We restricted the search to peer-reviewed studies published in English between January 2009 and March 2015. We identified a total of 31 articles of which 16, 17, and 16 studies examined the effects of Cd, Mn, or metal mixtures, respectively. Based on our review, there is suggestive evidence that prenatal/childhood Cd exposure may be associated with poorer cognition, but additional research is clearly needed. We found little evidence of behavioral effects of early life Cd exposure, and no studies found a significant relationship with attention deficit hyperactivity disorder. Studies of early life Mn exposure consistently reported negative impacts on both cognition and behavior. There is also growing evidence that co-exposure to multiple metals can result in increased neurotoxicity compared to single-metal exposure, in particular during early life. Few studies have evaluated behavioral effects related to metal co-exposure.

Reduced fetal growth increases the risk for adverse health outcomes. Growing evidence suggests that metal exposures contribute to reduced fetal growth, but little is known about the effects of complex metal mixtures. We investigated the impact of a complex mixture of metals on birth weight for gestational age (BW for GA) in the Maternal and Developmental Risks from Environmental and Social Stressors study, a predominately lower-income Hispanic pregnancy cohort in Los Angeles, California. Cadmium (Cd), cobalt (Co), mercury (Hg), nickel (Ni), molybdenum (Mo), lead (Pb), antimony (Sb), tin (Sn), and thallium (Tl) were measured by inductively coupled plasma mass spectrometry (ICP-MS) in maternal urine samples collected in early pregnancy (median GA: 13.1 wk). Speciated urinary arsenic (As) ( As) was measured by high-performance liquid chromatography coupled to ICP-MS. Primary analyses focused on a mixture of seven metals that have previously been associated individually with fetal growth (i.e., As, Cd, Co, Hg, Ni, Pb, Tl) ( ). In exploratory analyses, we additionally examined three metals that have been less studied in relation to fetal growth (i.e., Mo, Sb, Sn). Covariate-adjusted Bayesian kernel machine regression was used to investigate metal mixture associations with BW for GA -scores. In primary analyses, Hg and Ni ranked highest as predictors of BW for GA. An inverse linear association was estimated for Hg, whereas a positive association was estimated for Ni at low-to-moderate concentrations. A potential interaction between Hg and Ni was also identified. In our exploratory analysis, Sb ranked highest as a predictor of BW for GA, followed by Hg and Ni. Our findings suggest that in this understudied population, Hg may reduce fetal growth, whereas Ni may promote fetal growth. We also identified Sb as a potential metal of concern for this population, which merits additional investigation. https://doi.org/10.1289/EHP7201.

Limited epidemiologic data exist on prenatal arsenic exposure and fetal growth, particularly in the context of co-exposure to other toxic metals. We examined whether prenatal arsenic exposure predicts birth outcomes among a rural U.S. population, while adjusting for exposure to lead and manganese. We collected maternal and umbilical cord blood samples at delivery from 622 mother-infant pairs residing near a mining-related Superfund site in Northeast Oklahoma. Whole blood arsenic, lead, and manganese were measured using inductively coupled plasma mass spectrometry. We modeled associations between arsenic concentrations and birth weight, gestational age, head circumference, and birth weight for gestational age. Median (25th-75th percentile) maternal and umbilical cord blood metal concentrations, respectively, were as follows: arsenic, 1.4 (1.0-2.3) and 2.4 (1.8-3.3) μg/L; lead, 0.6 (0.4-0.9) and 0.4 (0.3-0.6) μg/dL; manganese, 22.7 (18.8-29.3) and 41.7 (32.2-50.4) μg/L. We estimated negative associations between maternal blood arsenic concentrations and birth outcomes. In multivariable regression models adjusted for lead and manganese, an interquartile range increase in maternal blood arsenic was associated with -77.5 g (95% CI: -127.8, -27.3) birth weight, -0.13 weeks (95% CI: -0.27, 0.01) gestation, -0.22 cm (95% CI: -0.42, -0.03) head circumference, and -0.14 (95% CI: -0.24, -0.04) birth weight for gestational age z-score units. Interactions between arsenic concentrations and lead or manganese were not statistically significant. In a population with environmental exposure levels similar to the U.S. general population, maternal blood arsenic was negatively associated with fetal growth. Given the potential for relatively common fetal and early childhood arsenic exposures, our finding that prenatal arsenic can adversely affect birth outcomes is of considerable public health importance. Claus Henn B, Ettinger AS, Hopkins MR, Jim R, Amarasiriwardena C, Christiani DC, Coull BA, Bellinger DC, Wright RO. 2016. Prenatal arsenic exposure and birth outcomes among a population residing near a mining-related Superfund site. Environ Health Perspect 124:1308-1315; http://dx.doi.org/10.1289/ehp.1510070.

Environmental manganese exposure has been associated with adverse neurodevelopmental outcomes among school-aged children; yet, few studies have evaluated prenatal exposure. Our study examines associations between prenatal manganese concentrations and placental transfer of manganese with neurodevelopment in 224 2-y-old children residing near the Tar Creek Superfund Site. We collected maternal and cord blood at delivery, measured manganese using inductively coupled plasma mass spectrometry, and assessed neurodevelopment using the Bayley Scales of Infant Development-II. Associations between manganese and mental (MDI) and psychomotor (PDI) development indices were estimated in multivariable models. Placental transfer, approximated by cord/maternal manganese ratio, cord/total manganese ratio (total=maternal+cord), and by joint classification according to high or low (above or below median) maternal and cord manganese, was evaluated as a predictor of neurodevelopment. Median levels [interquartile ranges (IQR)] of manganese in maternal and cord blood, respectively, were 24.0 (19.5-29.7) and 43.1 (33.5-52.1) μg/L. Adjusting for lead, arsenic, and other potential confounders, an IQR increase in maternal manganese was associated with -3.0 (95% CI: -5.3, -0.7) points on MDI and -2.3 (95% CI: -4.1, -0.4) points on PDI. Cord manganese concentrations were not associated with neurodevelopment scores. Cord/maternal and cord/total manganese ratios were positively associated with MDI [cord/maternal: β=2.6 (95% Cl: −0.04, 5.3); cord/total: β=22.0 (95% Cl: 3.2, 40.7)] and PDI (cord/maternal: β=1.7 (95% Cl: −0.5, 3.9); cord/total: β=15.6 (95% Cl: 0.3, 20.9)). Compared to mother-child pairs with low maternal and cord manganese, associations with neurodevelopment scores were negative for pairs with either high maternal, high cord, or high maternal and cord manganese. Maternal blood manganese concentrations were negatively associated with early childhood neurodevelopment scores in our study. Findings highlight the importance of understanding maternal exposures during pregnancy and factors influencing placental transfer. https://doi.org/10.1289/EHP925.

Prenatal exposure to some per- and polyfluoroalkyl substances (PFASs) may disrupt maternal and neonatal thyroid function, which is critical for normal growth and neurodevelopment. We examined associations of PFAS exposure during early pregnancy with maternal and neonatal thyroid hormone levels. We studied 732 mothers and 480 neonates in Project Viva, a longitudinal prebirth cohort in Boston, Massachusetts. We quantified six PFASs, including perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), and maternal thyroid hormones [thyroxine (T ), Free T Index (FT I), thyroid stimulating hormone (TSH)] in plasma samples collected at a median 9.6 wk gestation and neonatal T levels from postpartum heel sticks. We estimated associations of PFAS concentrations with thyroid hormone levels using covariate-adjusted linear regression models and explored effect measure modification by maternal thyroid peroxidase antibody (TPOAb) status and infant sex. PFAS concentrations were not associated with maternal T , but PFOA, perfluorohexane sulfonate (PFHxS), and 2-(N-methyl-perfluorooctane sulfonamido) acetate (MeFOSAA) were inversely associated with maternal FT I [e.g., -1.87% (95% confidence interval (CI): -3.40, -0.31) per interquartile (IQR) increase in PFOA]. PFAS concentrations [PFOA, PFOS, and perfluorononanoate (PFNA)] were inversely associated with TSH levels in TPOAb-positive women only. Prenatal PFOS, PFOA, and PFHxS concentrations were inversely associated with T levels in male [e.g., PFHxS, quartile 4 vs.1: -2.51μg/dL (95% CI: -3.99, -1.04 )], but not female neonates [0.40μg/dL (95% CI: -0.98, 1.79)]. In this study, prenatal exposure to some PFASs during early pregnancy was inversely associated with maternal FT I and neonatal T in male infants. These results support the hypothesis that prenatal exposure to PFASs influences thyroid function in both mothers and infants. https://doi.org/10.1289/EHP2534.

Residential proximity to ferroalloy production has been associated with increased manganese exposure, which can adversely affect health, particularly among children. Little is known, however, about which environmental samples contribute most to internal levels of manganese and other ferroalloy metals. We aimed to characterize sources of exposure to metals and evaluate the ability of internal biomarkers to reflect exposures from environmental media. In 717 Italian adolescents residing near ferromanganese industry, we examined associations between manganese, lead, chromium, and copper in environmental samples (airborne particles, surface soil, indoor/outdoor house dust) and biological samples (blood, hair, nails, saliva, urine). In multivariable regression analyses adjusted for child age and sex, a 10% increase in soil Mn was associated with increases of 3.0% (95% CI: 1.1%, 4.9%) in nail Mn and 1.6% (95% CI: −0.2%, 3.4%) in saliva Mn. Weighted-quantile-sum (WQS) regression estimated that higher soil and outdoor dust Mn accounted for most of the effect on nail Mn (WQS weights: 0.61 and 0.22, respectively, out of a total of 1.0). Higher air and soil Mn accounted for most of the effect on saliva Mn (WQS weights: 0.65 and 0.29, respectively). These findings can help inform biomarker selection in future epidemiologic studies and guide intervention strategies in exposed populations.