Gestational exposure to an epidemiologically defined mixture of phthalates leads to gonadal dysfunction in mouse offspring of both sexes

The increasing concern for the reproductive toxicity of abundantly used phthalates requires reliable tools for exposure risk assessment to mixtures of chemicals, based on real life human exposure and disorder-associated epidemiological evidence. We herein used a mixture of four phthalate monoesters (33% mono-butyl phthalate, 16% mono-benzyl phthalate, 21% mono-ethyl hexyl phthalate, and 30% mono-isononyl phthalate), detected in 1st trimester urine of 194 pregnant women and identified as bad actors for a shorter anogenital distance (AGD) in their baby boys. Mice were treated with 0, 0.26, 2.6 and 13 mg/kg/d of the mixture, corresponding to 0x, 10x, 100x, 500x levels detected in the pregnant women. Adverse outcomes detected in the reproductive system of the offspring in pre-puberty and adulthood included reduced AGD index and gonadal weight, changes in gonadal histology and altered expression of key regulators of gonadal growth and steroidogenesis. Most aberrations were apparent in both sexes, though more pronounced in males, and exhibited a non-monotonic pattern. The phthalate mixture directly affected expression of steroidogenesis as demonstrated in a relevant in vitro model. The detected adversities at exposures close to the levels detected in pregnant women, raise concern on the existing safety limits for early-life human exposures and emphasizes the need for re-evaluation of the exposure risk.

In utero metal exposures measured in deciduous teeth and birth outcomes in a racially-diverse urban cohort

A growing number of studies have examined associations of metal exposures with birth outcomes, however, results from these studies have been inconsistent, and hampered by methodological limitations. We measured direct fetal exposure to three metals (lead, manganese and zinc) during the second and third trimester and examined its association with birth weight and gestational age at delivery. Participants in the Wayne County Health, Environment, Allergy and Asthma Longitudinal Study (WHEALS), a population-based birth cohort established between September 2003 and December 2007, were invited to donate teeth to the study. Lead, manganese and zinc during the second and third trimesters were measured via high-resolution microspatial mapping of dentin growth rings, a validated biomarker for prenatal metal exposure. Gestational age at delivery and infant birth weight were obtained from the delivery medical record. A total of 145 children had tooth metal measurements and birth outcome data. Mean birth weight was 3431 ± 472 g and mean gestational age at delivery was 39.0 ± 1.3 weeks. Overall, there was a positive association between second (β = 0.21, 95% CI: 0.05, 0.37, P = 0.01) and third trimester (β = 0.21, 95% CI: 0.05, 0.37, P = 0.01) tooth manganese and birth weight Z-score; this remained statistically significant after covariate adjustment. There was also a negative association between second trimester tooth lead level and birth weight Z-score (β = -0.20, 95% CI: -0.38, -0.02, P = 0.02), however, this was attenuated after adjusting for covariates. Mixture analysis revealed similar findings. There was evidence for a sex-specific effect of manganese with birth weight Z-score, with the association stronger in female compared to male infants. Overall, we found evidence suggesting that higher in utero manganese is associated with larger birth weight Z-scores and that these associations may vary by infant sex.

PVC flooring at home and uptake of phthalates in pregnant women

Phthalates are used as plasticizers in polyvinyl chloride (PVC) materials and it is known that phthalates may migrate into the surrounding environment and then become a source for human uptake. The aim of the study was to investigate whether residential PVC flooring was related to the urinary levels of phthalate metabolites determined in pregnant women. The data were from the Swedish SELMA study where sampling was conducted during the time period 2007-2010. Spot urine samples from 1674 women at the end of the first trimester were analyzed for 14 metabolites from seven phthalates and one phthalate alternative. Data on flooring material in the kitchen and the parents' bedrooms as well as potential confounders were collected by postal questionnaires at the same time as the urine samples were taken. Multiple regression modeling by least square geometric mean and weighted quantile sum regression was applied to log-transformed and creatinine-adjusted phthalate metabolite concentrations adjusted for potential confounders from questionnaire data. This study has found significantly higher urinary levels of the BBzP metabolite (MBzP) in pregnant women living in homes with PVC flooring as compared to homes with other flooring materials.

Bayesian varying coefficient kernel machine regression to assess neurodevelopmental trajectories associated with exposure to complex mixtures

Exposure to environmental mixtures can exert wide-ranging effects on child neurodevelopment. However, there is a lack of statistical methods that can accommodate the complex exposure-response relationship between mixtures and neurodevelopment while simultaneously estimating neurodevelopmental trajectories. We introduce Bayesian varying coefficient kernel machine regression (BVCKMR), a hierarchical model that estimates how mixture exposures at a given time point are associated with health outcome trajectories. The BVCKMR flexibly captures the exposure-response relationship, incorporates prior knowledge, and accounts for potentially nonlinear and nonadditive effects of individual exposures. This model assesses the directionality and relative importance of a mixture component on health outcome trajectories and predicts health effects for unobserved exposure profiles. Using contour plots and cross-sectional plots, BVCKMR also provides information about interactions between complex mixture components. The BVCKMR is applied to a subset of data from PROGRESS, a prospective birth cohort study in Mexico city on exposure to metal mixtures and temporal changes in neurodevelopment. The mixture include metals such as manganese, arsenic, cobalt, chromium, cesium, copper, lead, cadmium, and antimony. Results from a subset of Programming Research in Obesity, Growth, Environment and Social Stressors data provide evidence of significant positive associations between second trimester exposure to copper and Bayley Scales of Infant and Toddler Development cognition score at 24 months, and cognitive trajectories across 6-24 months. We also detect an interaction effect between second trimester copper and lead exposures for cognition at 24 months. In summary, BVCKMR provides a framework for estimating neurodevelopmental trajectories associated with exposure to complex mixtures.

Dentine biomarkers of prenatal and early childhood exposure to manganese, zinc and lead and childhood behavior

BACKGROUND

Metal exposure alters neurodevelopmental outcomes; little is known about critical windows of susceptibility when exposure exerts the strongest effect.

OBJECTIVE

To examine associations between dentine biomarkers of manganese (Mn), zinc (Zn) and lead (Pb) and later childhood behaviors.

METHODS

Subjects enrolled in a longitudinal birth cohort study in Mexico City provided naturally shed deciduous teeth. We estimated weekly prenatal and postnatal dentine Mn, Zn and Pb concentrations in teeth using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and measured behavior at ages 8-11 years of age using the Behavior Assessment System for Children, 2nd edition (BASC-2). We used distributed lag models and lagged weighted quantile sum regression to identify the role of individual and combined dentine biomarkers of Mn, Zn and Pb on behavioral outcomes controlling for maternal education and gestational age.

RESULTS

Among the 133 subjects included in this study, prenatal and early postnatal dentine Mn appeared protective against childhood behavioral problems, specifically hyperactivity and attention. Postnatal dentine Mn was associated with increased reporting of internalizing problems, specifically anxiety. At 6 months, a 1-unit increase (unit = 1 SD of log concentration) in Mn was associated with a 0.18-unit (unit = 1 SD of BASC-2 score) increase in internalizing symptoms score and a 0.25-unit increase in anxiety. Postnatal Pb was associated with increasing anxiety symptoms; at 12 months, a 1-unit increase in Pb was associated with a 0.4 unit increase in anxiety symptoms. When examined as a metal mixture, we observed two potential windows of susceptibility to increased anxiety symptoms: the first window (0-8 months) appeared driven by Mn, the second window (8-12 months) was driven by the metal mixture and dominated by Pb. A 1-unit increase in the mixture index was associated with a 0.7-unit increase in SD of anxiety symptoms.

CONCLUSIONS

Childhood behaviors may demonstrate postnatal windows of susceptibility to individual and mixed metal concentrations measured in deciduous teeth. Prenatal dentine Mn may be protective, while excessive early postnatal Mn may increase risk for adverse behaviors. In combination, higher concentrations of Mn, Zn and Pb may have an adverse impact on behavior.

Incorporating regulatory guideline values in analysis of epidemiology data

Fundamental to regulatory guidelines is to identify chemicals that are implicated with adverse human health effects and inform public health risk assessors about "acceptable ranges" of such environmental exposures (e.g., from consumer products and pesticides). The process is made more difficult when accounting for complex human exposures to multiple environmental chemicals. Herein we propose a new class of nonlinear statistical models for human data that incorporate and evaluate regulatory guideline values into analyses of health effects of exposure to chemical mixtures using so-called 'desirability functions' (DFs). The DFs are incorporated into nonlinear regression models to allow for the simultaneous estimation of points of departure for risk assessment of combinations of individual substances that are parts of chemical mixtures detected in humans. These are, in contrast to published so-called biomonitoring equivalent (BE) values and human biomonitoring (HBM) values that link regulatory guideline values from in vivo studies of single chemicals to internal concentrations monitored in humans. We illustrate the strategy through the analysis of prenatal concentrations of mixtures of 11 chemicals with suspected endocrine disrupting properties and two health effects: birth weight and language delay at 2.5 years. The strategy allows for the creation of a Mixture Desirability Function i.e., MDF, which is a uni-dimensional construct of the set of single chemical DFs; thus, it focuses the resulting inference to a single dimension for a more powerful one degree-of-freedom test of significance. Based on the application of this new method we conclude that the guideline values need to be lower than those for single chemicals when the chemicals are observed in combination to achieve a similar level of protection as was aimed for the individual chemicals. The proposed modeling may thus suggest data-driven uncertainty factors for single chemical risk assessment that takes environmental mixtures into account.

Intrauterine multi-metal exposure is associated with reduced fetal growth through modulation of the placental gene network

BACKGROUND

Intrauterine metal exposures and aberrations in placental processes are known contributors to being born small for gestational age (SGA). However, studies to date have largely focused on independent effects, failing to account for potential interdependence among these markers.

OBJECTIVES

We evaluated the inter-relationship between multi-metal indices and placental gene network modules related to SGA status to highlight potential molecular pathways through which in utero multi-metal exposure impacts fetal growth.

METHODS

Weighted quantile sum (WQS) regression was performed using a panel of 16 trace metals measured in post-partum maternal toe nails collected from the Rhode Island Child Health Study (RICHS, n = 195), and confirmation of the derived SGA-related multi-metal index was conducted using Bayesian kernel machine regression (BKMR). We leveraged existing placental weighted gene coexpression network data to examine associations between the SGA multi-metal index and placental gene expression. Expression of select genes were assessed using RT-PCR in an independent birth cohort, the New Hampshire Birth Cohort Study (NHBCS, n = 237).

RESULTS

We identified a multi-metal index, predominated by arsenic (As) and cadmium (Cd), that was positively associated with SGA status (Odds ratio = 2.73 [1.04, 7.18]). This index was also associated with the expression of placental gene modules involved in "gene expression" (β = -0.02 [-0.04, -0.01]) and "metabolic hormone secretion" (β = 0.02 [0.00, 0.05]). We validated the association between cadmium exposure and the expression of GRHL1 and INHBA, genes in the "metabolic hormone secretion" module, in NHBCS.

CONCLUSION

We present a novel approach that integrates the application of advanced bioinformatics and biostatistics methods to delineate potential placental pathways through which trace metal exposures impact fetal growth.

Prenatal lead exposure modifies the effect of shorter gestation on increased blood pressure in children

BACKGROUND

High blood pressure (BP) in childhood is frequently renal in origin and a risk factor for adult hypertension and cardiovascular disease. Shorter gestations are a known risk factor for increased BP in adults and children, due in part to a nephron deficit in children born preterm. As nephrogenesis is incomplete until 36 weeks gestation, prenatal lead exposure occurring during a susceptible period of renal development may contribute to programming for later life renal disease. The relationship between shorter gestation and children's BP has not yet been explored to identify i) critical windows using nonlinear piecewise models or ii) combined with other early life risk factors such as prenatal lead exposure.

OBJECTIVES

(1) To evaluate the nonlinear relationship between lower gestational age and childhood BP measured at 4-6 years of age, and (2) to investigate modification by prenatal lead exposure.

METHODS

In a prospective longitudinal birth cohort, we assessed 565 children between 4 and 6 years of age (mean: 4.8 years) in the PROGRESS cohort in Mexico City, Mexico. Gestational age at delivery was calculated using maternal report of last menstrual period (LMP) and confirmed with Capurro physical examination at birth. We measured pregnant women's blood lead levels (BLLs) in the second trimester via inductively coupled plasma-mass spectrometry and children's BP using an automated device. We performed both linear and nonlinear piecewise regression analyses to examine associations of gestational age with children's BP adjusting for children's age, sex, height, prenatal exposure to smoke, and maternal socioeconomic status. We stratified to assess modification by prenatal lead exposure, and used a data-adaptive approach to identify a lead cutpoint.

RESULTS

Maternal second trimester BLLs ranged from 0.7 to 17.8 μg/dL with 112 (20%) women above the CDC guideline level of 5 μg/dL. In adjusted linear regression models, a one week reduction in gestational age was associated with a 0.5 mm Hg (95%CI: 0.2, 0.8) increase in SBP and a 0.4 mm Hg (95%CI 0.1, 0.6) increase in DBP. Our nonlinear models suggested evidence for different magnitude estimates on either side of an estimated join-point at 35.9 weeks' gestation, but did not reach statistical significance. However, when stratified by prenatal lead exposure, we identified a cutpoint lead level of concern of 2.5 μg/dL that suggested an interaction between gestational age and blood lead. Specifically, for BLLs ≥ 2.5 μg/dL, SBP was 1.6 (95%CI: 0.3, 2.9) mm Hg higher per each week reduction in gestational age among children born before 37.0 weeks; and among children born after 37.0 weeks, this relationship was attenuated yet remained significant [β: 0.9, 95%CI (0.2, 1.6)]. At BLLs below 2.5 μg/dL, there was no appreciable association between lower gestational age and SBP.

CONCLUSIONS

Our findings suggest that shorter gestation combined with higher prenatal lead exposure contributes to a higher risk of increased SBP at 4-6 years of age, particularly among infants born <37 weeks gestation. Our results underscore the importance of preventing prenatal lead exposure - even levels as low as 2.5 μg/dL - especially among pregnant women at risk for preterm birth. Given that high BP in childhood is a risk factor for adult hypertension and cardiovascular disease later in life, these results may have implications that extend across the life span.

Temporal trends of phthalate exposures during 2007-2010 in Swedish pregnant women

BACKGROUND

The general population is exposed to phthalates, a group of chemicals with strong evidence for endocrine disrupting properties, commonly used in a large number of consumer products. Based on published research and evidence compiled by environmental agencies, certain phthalate applications and products have become restricted, leading to an increasing number of "new generation compounds" coming onto the market during recent years replacing older phthalates. Some examples of such newer compounds are di-iso-nonyl phthalate (DiNP), di-iso-decyl phthalate (DiDP), and most recently di-isononyl-cyclohexane-1,2-dicarboxylate (DiNCH).

OBJECTIVES

In order to evaluate temporal trends in phthalate exposure, first trimester urinary biomarkers of phthalates were measured in the Swedish SELMA study over a period of 2.5 years (2007-2010).

METHODS

We collected first morning void urine samples around week 10 of pregnancy from 1651 pregnant women. Spot samples were analyzed for 13 phthalate metabolites and one phthalate replacement and least square geometric mean (LSGM) levels of the metabolites were compared between the sampling years when adjusted for potential confounders.

RESULTS

All 14 metabolites were detectable in more than 99% of the SELMA subjects. The levels were generally comparable to other studies, but the SELMA subjects showed slightly higher exposure to butyl-benzyl phthalate (BBzP) and di-butyl phthalate (DBP). Di-ethyl-hexyl phthalate (DEHP) metabolites levels decreased while DiNP, DiDP/di-2-propylheptyl phthalate (DPHP), and DiNCH metabolites levels increased during the sampling period.

CONCLUSIONS

Urinary metabolite levels of the older phthalates and more recently introduced phthalate replacement compound changed during the short sampling period in this Swedish pregnancy cohort. Our results indicate that replacement of phthalates can make an impact on human exposure to these chemicals. During this particularly vulnerable stage of life, phthalate exposures are of particular concern as the impacts, though not immediately noticeable, may increase the risk for health effects later in life.

Quality of Prenatal and Childhood Diet Predicts Neurodevelopmental Outcomes among Children in Mexico City

Adequate nutrition is important for neurodevelopment. Although nutrients are ingested in combination, the impact of specific nutrients within the context of a nutrient mixture has not been studied with respect to health, such as neurodevelopment. Therefore, we examined the impact of prenatal and childhood nutrient mixtures on neurodevelopmental outcomes. Participants included mother⁻child pairs in the Programming Research in Obesity, Growth, Environment, and Social Stress (PROGRESS) prospective birth cohort in Mexico City. We assessed prenatal and child micro- and macronutrient profiles among 65 and 329 children, respectively, via food frequency questionnaires. Neurodevelopmental outcomes of 4⁻6-year-old children were measured using the McCarthy Scales of Children's Abilities (MSCA). We conducted weighted quantile sum (WQS) regression analyses to calculate indices reflecting "good" and "poor" prenatal and childhood nutrition. After adjusting for maternal education, socioeconomic status, the Home Observation for Measurement of the Environment (HOME) score, and total caloric intake, the good prenatal and childhood nutrition indices predicted more favorable neurodevelopment, while both poor nutrition indices predicted poorer neurodevelopment. These associations were stronger in prenatal than childhood models. Monounsaturated fats predicted various neurodevelopmental abilities relatively strongly in both models. Prenatal and childhood consumption of combinations of beneficial nutrients may contribute to more favorable neurodevelopment.

Modeling the health effects of time-varying complex environmental mixtures: Mean field variational Bayes for lagged kernel machine regression

There is substantial interest in assessing how exposure to environmental mixtures, such as chemical mixtures, affect child health. Researchers are also interested in identifying critical time windows of susceptibility to these complex mixtures. A recently developed method, called lagged kernel machine regression (LKMR), simultaneously accounts for these research questions by estimating effects of time-varying mixture exposures, and identifying their critical exposure windows. However, LKMR inference using Markov chain Monte Carlo methods (MCMC-LKMR) is computationally burdensome and time intensive for large datasets, limiting its applicability. Therefore, we develop a mean field variational Bayesian inference procedure for lagged kernel machine regression (MFVB-LKMR). The procedure achieves computational efficiency and reasonable accuracy as compared with the corresponding MCMC estimation method. Updating parameters using MFVB may only take minutes, while the equivalent MCMC method may take many hours or several days. We apply MFVB-LKMR to PROGRESS, a prospective cohort study in Mexico. Results from a subset of PROGRESS using MFVB-LKMR provide evidence of significant positive association between second trimester cobalt levels and z-scored birthweight. This positive association is heightened by cesium exposure. MFVB-LKMR is a promising approach for computationally efficient analysis of environmental health datasets, to identify critical windows of exposure to complex mixtures.

Dynamical features in fetal and postnatal zinc-copper metabolic cycles predict the emergence of autism spectrum disorder

Metals are critical to neurodevelopment, and dysregulation in early life has been documented in autism spectrum disorder (ASD). However, underlying mechanisms and biochemical assays to distinguish ASD cases from controls remain elusive. In a nationwide study of twins in Sweden, we tested whether zinc-copper cycles, which regulate metal metabolism, are disrupted in ASD. Using novel tooth-matrix biomarkers that provide direct measures of fetal elemental uptake, we developed a predictive model to distinguish participants who would be diagnosed with ASD in childhood from those who did not develop the disorder. We replicated our findings in three independent studies in the United States and the UK. We show that three quantifiable characteristics of fetal and postnatal zinc-copper rhythmicity are altered in ASD: the average duration of zinc-copper cycles, regularity with which the cycles recur, and the number of complex features within a cycle. In all independent study sets and in the pooled analysis, zinc-copper rhythmicity was disrupted in ASD cases. In contrast to controls, in ASD cases, the cycle duration was shorter (F = 52.25, P < 0.001), regularity was reduced (F = 47.99, P < 0.001), and complexity diminished (F = 57.30, P < 0.001). With two distinct classification models that used metal rhythmicity data, we achieved 90% accuracy in classifying cases and controls, with sensitivity to ASD diagnosis ranging from 85 to 100% and specificity ranging from 90 to 100%. These findings suggest that altered zinc-copper rhythmicity precedes the emergence of ASD, and quantitative biochemical measures of metal rhythmicity distinguish ASD cases from controls.

Modeling Pediatric Body Mass Index and Neighborhood Environment at Different Spatial Scales

In public health research, it has been well established that geographic location plays an important role in influencing health outcomes. In recent years, there has been an increased emphasis on the impact of neighborhood or contextual factors as potential risk factors for childhood obesity. Some neighborhood factors relevant to childhood obesity include access to food sources, access to recreational facilities, neighborhood safety, and socioeconomic status (SES) variables. It is common for neighborhood or area-level variables to be available at multiple spatial scales (SS) or geographic units, such as the census block group and census tract, and selection of the spatial scale for area-level variables can be considered as a model selection problem. In this paper, we model the variation in body mass index (BMI) in a study of pediatric patients of the Virginia Commonwealth University (VCU) Medical Center, while considering the selection of spatial scale for a set of neighborhood-level variables available at multiple spatial scales using four recently proposed spatial scale selection algorithms: SS forward stepwise regression, SS incremental forward stagewise regression, SS least angle regression (LARS), and SS lasso. For pediatric BMI, we found evidence of significant positive associations with visit age and black race at the individual level, percent Hispanic white at the census block group level, percent Hispanic black at the census tract level, and percent vacant housing at the census tract level. We also found significant negative associations with population density at the census tract level, median household income at the census tract level, percent renter at the census tract level, and exercise equipment expenditures at the census block group level. The SS algorithms selected covariates at different spatial scales, producing better goodness-of-fit in comparison to traditional models, where all area-level covariates were modeled at the same scale. These findings underscore the importance of considering spatial scale when performing model selection.

Neonatal intensive care unit phthalate exposure and preterm infant neurobehavioral performance

Every year in the United States, more than 300,000 infants are admitted to neonatal intensive care units (NICU) where they are exposed to a chemical-intensive hospital environment during a developmentally vulnerable period. The neurodevelopmental impact of environmental exposure to phthalates during the NICU stay is unknown. As phthalate exposure during the third trimester developmental window has been implicated in neurobehavioral deficits in term-born children that are strikingly similar to a phenotype of neurobehavioral morbidity common among children born premature, the role of early-life phthalate exposure on the neurodevelopmental trajectory of premature infants may be clinically important. In this study, premature newborns with birth weight <1500g were recruited to participate in a prospective environmental health cohort study, NICU-HEALTH (Hospital Exposures and Long-Term Health), part of the DINE (Developmental Impact of NICU Exposures) cohort of the ECHO (Environmental influences on Child Health Outcomes) program. Seventy-six percent of eligible infants enrolled in the study. Sixty-four of 81 infants survived and are included in this analysis. 164 urine specimens were analyzed for phthalate metabolites using high-performance liquid chromatography/tandem mass spectrometry. The NICU Network Neurobehavioral Scale (NNNS) was performed prior to NICU discharge. Linear and weighted quantile sum regression quantified associations between phthalate biomarkers and NNNS performance, and between phthalate biomarkers and intensity of medical intervention. The sum of di(2-ethylhexyl) phthalate metabolites (∑DEHP) was associated with improved performance on the Attention and Regulation scales. Specific mixtures of phthalate biomarkers were also associated with improved NNNS performance. More intense medical intervention was associated with higher ∑DEHP exposure. NICU-based exposure to phthalates mixtures was associated with improved attention and social response. This suggests that the impact of phthalate exposure on neurodevelopment may follow a non-linear trajectory, perhaps accelerating the development of certain neural networks. The long-term neurodevelopmental impact of NICU-based phthalate exposure needs to be evaluated.

Uncovering neurodevelopmental windows of susceptibility to manganese exposure using dentine microspatial analyses

BACKGROUND

Associations between manganese (Mn) and neurodevelopment may depend on dose and exposure timing, but most studies cannot measure exposure variability over time well.

OBJECTIVE

We apply temporally informative tooth-matrix biomarkers to uncover windows of susceptibility in early life when Mn is associated with visual motor ability in childhood. We also explore effect modification by lead (Pb) and child sex.

METHODS

Participants were drawn from the ELEMENT (Early Life Exposures in MExico and NeuroToxicology) longitudinal birth cohort studies. We reconstructed dose and timing of prenatal and early postnatal Mn and Pb exposures for 138 children by analyzing deciduous teeth using laser ablation-inductively coupled plasma-mass spectrometry. Neurodevelopment was assessed between 6 and 16 years of age using the Wide Range Assessment of Visual Motor Abilities (WRAVMA). Mn associations with total WRAVMA scores and subscales were estimated with multivariable generalized additive mixed models. We examined Mn interactions with Pb and child sex in stratified models.

RESULTS

Levels of dentine Mn were highest in the second trimester and declined steeply over the prenatal period, with a slower rate of decline after birth. Mn was positively associated with visual spatial and total WRAVMA scores in the second trimester, among children with lower (< median) tooth Pb levels: one standard deviation (SD) increase in ln-transformed dentine Mn at 150 days before birth was associated with a 0.15 [95% CI: 0.04, 0.26] SD increase in total score. This positive association was not observed at high Pb levels. In contrast to the prenatal period, significant negative associations were found in the postnatal period from ~ 6 to 12 months of age, among boys only: one SD increase in ln-transformed dentine Mn was associated with a 0.11 [95% CI: - 0.001, - 0.22] to 0.16 [95% CI: - 0.04, - 0.28] SD decrease in visual spatial score.

CONCLUSIONS

Using tooth-matrix biomarkers with fine scale temporal profiles of exposure, we found discrete developmental windows in which Mn was associated with visual-spatial abilities. Our results suggest that Mn associations are driven in large part by exposure timing, with beneficial effects found for prenatal levels and toxic effects found for postnatal levels.

Maternal Lifetime Stress and Prenatal Psychological Functioning and Decreased Placental Mitochondrial DNA Copy Number in the PRISM Study

Psychosocial stress contributes to placental oxidative stress. Mitochondria are vulnerable to oxidative stress, which can lead to changes in mitochondrial DNA copy number (mtDNAcn). We examined associations of maternal lifetime stress, current negative life events, and depressive and posttraumatic-stress-disorder symptom scores with placental mtDNAcn in a racially/ethnically diverse sample (n = 147) from the Programming of Intergenerational Stress Mechanisms (PRISM) study (Massachusetts, March 2011 to August 2012). In linear regression analyses adjusted for maternal age, race/ethnicity, education, prenatal fine particulate matter exposure, prenatal smoking exposure, and the sex of the child, all measures of stress were associated with decreased placental mtDNAcn (all P values < 0.05). Weighted-quantile-sum (WQS) regression showed that higher lifetime stress and depressive symptoms accounted for most of the effect on mtDNAcn (WQS weights: 0.25 and 0.39, respectively). However, among white individuals, increased lifetime stress and posttraumatic stress disorder symptoms explained the majority of the effect (WQS weights: 0.20 and 0.62, respectively) while among nonwhite individuals, lifetime stress and depressive symptoms accounted for most of the effect (WQS weights: 0.27 and 0.55, respectively). These analyses are first to link increased maternal psychosocial stress with reduced placental mtDNAcn and add to literature documenting racial/ethnic differences in the psychological sequelae of chronic stress that may contribute to maternal-fetal health.

Recurrence quantification analysis to characterize cyclical components of environmental elemental exposures during fetal and postnatal development

Environmental exposures to essential and toxic elements may alter health trajectories, depending on the timing, intensity, and mixture of exposures. In epidemiologic studies, these factors are typically analyzed as a function of elemental concentrations in biological matrices measured at one or more points in time. Such an approach, however, fails to account for the temporal cyclicity in the metabolism of environmental chemicals, which if perturbed may lead to adverse health outcomes. Here, we conceptualize and apply a non-linear method–recurrence quantification analysis (RQA)–to quantify cyclical components of prenatal and early postnatal exposure profiles for elements essential to normal development, including Zn, Mn, Mg, and Ca, and elements associated with deleterious health effects or narrow tolerance ranges, including Pb, As, and Cr. We found robust evidence of cyclical patterns in the metabolic profiles of nutrient elements, which we validated against randomized twin-surrogate time-series, and further found that nutrient dynamical properties differ from those of Cr, As, and Pb. Furthermore, we extended this approach to provide a novel method of quantifying dynamic interactions between two environmental exposures. To achieve this, we used cross-recurrence quantification analysis (CRQA), and found that elemental nutrient-nutrient interactions differed from those involving toxicants. These rhythmic regulatory interactions, which we characterize in two geographically distinct cohorts, have not previously been uncovered using traditional regression-based approaches, and may provide a critical unit of analysis for environmental and dietary exposures in epidemiological studies.

New Research Strategy for Measuring Pre- and Postnatal Metal Dysregulation in Psychotic Disorders

While previous studies have found evidence for detrimental effects of metals on neurodevelopment, the long-term effects on mental health remain unclear. The objective was to explore the effect of early metal exposure on risk of psychotic disorder and on symptom severity following illness onset. Through the use of validated tooth-biomarkers, we estimated pre- and postnatal exposure levels of essential elements (copper, magnesium, manganese, and zinc) and elements associated with neurotoxicity (lead, arsenic, lithium, and tin). We found consistently higher levels of lithium in patients compared to controls. Higher levels of magnesium and lower levels of zinc were associated with more severe psychopathology over 20 years after metal exposure. The results show promise for the use of teeth biomarkers in examining early environmental risk for psychosis and underscore the relevance of studying metal exposure during critical neurodevelopmental periods.

Prenatal exposure to PM2.5 and birth weight: A pooled analysis from three North American longitudinal pregnancy cohort studies

A common practice when analyzing multi-site epidemiological data is to include a term for 'site' to account for unmeasured effects at each location. This practice should be carefully considered when site can have complex relationships with important demographic and exposure variables. We leverage data from three longitudinal North American pregnancy cohorts to demonstrate a novel method to assess study heterogeneity and potential combinability of studies for pooled analyses in order to better understand how to consider site in analyses. Results from linear regression and fixed effects meta-regression models run both prior to and following the proposed combinability analyses were compared. In order to exemplify this approach, we examined associations between prenatal exposure to particulate matter and birth weight. Analyses included mother-child dyads (N=1966) from the Asthma Coalition on Community Environment and Social Stress (ACCESS) Project and the PRogramming of Intergenerational Stress Mechanisms (PRISM) study in the northeastern United States, and the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study in Mexico City. Mothers' daily third trimester exposure to particulate matter≤2.5μm in diameter (PM_2.5) was estimated using a validated satellite-based spatio-temporally resolved model in all studies. Fenton birth weight for gestational age z-scores were calculated. Linear regression analyses within each cohort separately did not find significant associations between PM_2.5 averaged over the third trimester and Fenton z-scores. The initial meta-regression model also did not find significant associations between prenatal PM_2.5 and birthweight. Next, propensity scores and log linear models were used to assess higher order interactions and determine if sites were comparable with regard to sociodemographics and other covariates; these analyses demonstrated that PROGRESS and ACCESS were combinable. Adjusted linear regression models including a 2-level site variable according to the pooling indicated by the log linear models (ACCESS and PROGRESS as one level and PRISM as another) revealed that a 5μg/m³ increase in PM_2.5 was associated with a 0.075 decrease in Fenton z-score (p<0.0001); linear models including a 3-level site variable did not reveal significant associations. By assessing the combinability of heterogeneous populations prior to combining data using a method that more optimally accounts for underlying cohort differences, we were able to identify significant associations between prenatal PM_2.5 exposure and birthweight that were not detected using standard methods.

Extending the Distributed Lag Model framework to handle chemical mixtures

Distributed Lag Models (DLMs) are used in environmental health studies to analyze the time-delayed effect of an exposure on an outcome of interest. Given the increasing need for analytical tools for evaluation of the effects of exposure to multi-pollutant mixtures, this study attempts to extend the classical DLM framework to accommodate and evaluate multiple longitudinally observed exposures. We introduce 2 techniques for quantifying the time-varying mixture effect of multiple exposures on an outcome of interest. Lagged WQS, the first technique, is based on Weighted Quantile Sum (WQS) regression, a penalized regression method that estimates mixture effects using a weighted index. We also introduce Tree-based DLMs, a nonparametric alternative for assessment of lagged mixture effects. This technique is based on the Random Forest (RF) algorithm, a nonparametric, tree-based estimation technique that has shown excellent performance in a wide variety of domains. In a simulation study, we tested the feasibility of these techniques and evaluated their performance in comparison to standard methodology. Both methods exhibited relatively robust performance, accurately capturing pre-defined non-linear functional relationships in different simulation settings. Further, we applied these techniques to data on perinatal exposure to environmental metal toxicants, with the goal of evaluating the effects of exposure on neurodevelopment. Our methods identified critical neurodevelopmental windows showing significant sensitivity to metal mixtures.

Association Between Dietary Intake and Function in Amyotrophic Lateral Sclerosis

Importance

There is growing interest in the role of nutrition in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS).

Objective

To evaluate the associations between nutrients, individually and in groups, and ALS function and respiratory function at diagnosis.

Design, Setting, and Participants

A cross-sectional baseline analysis of the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress study was conducted from March 14, 2008, to February 27, 2013, at 16 ALS clinics throughout the United States among 302 patients with ALS symptom duration of 18 months or less.

Exposures

Nutrient intake, measured using a modified Block Food Frequency Questionnaire (FFQ).

Main Outcomes and Measures

Amyotrophic lateral sclerosis function, measured using the ALS Functional Rating Scale-Revised (ALSFRS-R), and respiratory function, measured using percentage of predicted forced vital capacity (FVC).

Results

Baseline data were available on 302 patients with ALS (median age, 63.2 years [interquartile range, 55.5-68.0 years]; 178 men and 124 women). Regression analysis of nutrients found that higher intakes of antioxidants and carotenes from vegetables were associated with higher ALSFRS-R scores or percentage FVC. Empirically weighted indices using the weighted quantile sum regression method of "good" micronutrients and "good" food groups were positively associated with ALSFRS-R scores (β [SE], 2.7 [0.69] and 2.9 [0.9], respectively) and percentage FVC (β [SE], 12.1 [2.8] and 11.5 [3.4], respectively) (all P < .001). Positive and significant associations with ALSFRS-R scores (β [SE], 1.5 [0.61]; P = .02) and percentage FVC (β [SE], 5.2 [2.2]; P = .02) for selected vitamins were found in exploratory analyses.

Conclusions and Relevance

Antioxidants, carotenes, fruits, and vegetables were associated with higher ALS function at baseline by regression of nutrient indices and weighted quantile sum regression analysis. We also demonstrated the usefulness of the weighted quantile sum regression method in the evaluation of diet. Those responsible for nutritional care of the patient with ALS should consider promoting fruit and vegetable intake since they are high in antioxidants and carotenes.

Effects of an environmentally-relevant mixture of pyrethroid insecticides on spontaneous activity in primary cortical networks on microelectrode arrays

Pyrethroid insecticides exert their insecticidal and toxicological effects primarily by disrupting voltage-gated sodium channel (VGSC) function, resulting in altered neuronal excitability. Numerous studies of individual pyrethroids have characterized effects on mammalian VGSC function and neuronal excitability, yet studies examining effects of complex pyrethroid mixtures in mammalian neurons, especially in environmentally relevant mixture ratios, are limited. In the present study, concentration-response functions were characterized for five pyrethroids (permethrin, deltamethrin, cypermethrin, β-cyfluthrin and esfenvalerate) in an in vitro preparation containing cortical neurons and glia. As a metric of neuronal network activity, spontaneous mean network firing rates (MFR) were measured using microelectorde arrays (MEAs). In addition, the effect of a complex and exposure relevant mixture of the five pyrethroids (containing 52% permethrin, 28.8% cypermethrin, 12.9% β-cyfluthrin, 3.4% deltamethrin and 2.7% esfenvalerate) was also measured. Data were modeled to determine whether effects of the pyrethroid mixture were predicted by dose-addition. At concentrations up to 10μM, all compounds except permethrin reduced MFR. Deltamethrin and β-cyfluthrin were the most potent and reduced MFR by as much as 60 and 50%, respectively, while cypermethrin and esfenvalerate were of approximately equal potency and reduced MFR by only ∼20% at the highest concentration. Permethrin caused small (∼24% maximum), concentration-dependent increases in MFR. Effects of the environmentally relevant mixture did not depart from the prediction of dose-addition. These data demonstrate that an environmentally relevant mixture caused dose-additive effects on spontaneous neuronal network activity in vitro, and is consistent with other in vitro and in vivo assessments of pyrethroid mixtures.