Uses of NHANES Biomarker Data for Chemical Risk Assessment: Trends, Challenges, and Opportunities

Anthropometric metabolic subtypes and health outcomes: A data-driven cluster analysis

AIMS

The aims of the study were to develop and validate WHOLISTIIC, a data-driven cluster analysis for identifying anthropometric metabolic subtypes.

MATERIALS AND METHODS

K-means cluster analysis was performed in 397 424 UK Biobank participants based on five domains, that is, central obesity (waist-to-height ratio), general obesity (body mass index [BMI]), limb strength (handgrip strength), insulin resistance (triglyceride to high-density lipoprotein cholesterol [HDLc] ratio) and inflammatory condition (neutrophil-to-lymphocyte ratio). Replication was done in the NHANES. Cox proportional hazards regression models were used to estimate the associations of clusters with incident adverse health outcomes.

RESULTS

Six replicable clusters were identified. Compared with individuals in cluster 1 (lowest BMI with preserved handgrip strength), individuals in cluster 2 (highest handgrip strength) were not at increased risk of all-cause mortality despite higher BMI, but had small yet significant increased risks of cardiovascular mortality, incident major adverse cardiovascular events (MACE), chronic renal failure and decreased risks of mortality due to respiratory disease, as well as incident dementia; individuals in cluster 3 (lowest handgrip strength and borderline elevated BMI), cluster 4 (highest triglyceride-to-HDLc ratio and moderately elevated BMI), cluster 5 (highest neutrophil-to-lymphocyte ratio and borderline elevated BMI) and cluster 6 (highest BMI) had substantially increased risks of all-cause, cardiovascular, and cancer mortality, incident MACE and chronic renal failure. The associations of anthropometric clusters with the risk of mortality were replicated in the NHANES cohort.

CONCLUSIONS

Anthropometric metabolic subtypes identified with easily accessible parameters reflecting multifaceted pathology of overweight and obesity were associated with distinct risks of long-term adverse health outcomes.

Biomonitoring-Based Risk Assessment of Pyrethroid Exposure in the U.S. Population: Application of High-Throughput and Physiologically Based Kinetic Models

Pyrethroid insecticides have been extensively utilized in agriculture and residential areas in the United States. This study evaluated the exposure risk by age using available biomonitoring data. We analyzed pyrethroid metabolite concentrations in urine using the National Health and Nutrition Examination Survey (NHANES) data. Reverse dosimetry was conducted with a high-throughput model and a physiologically based kinetic (PBK) model integrated with a Bayesian inference framework. We further derived Benchmark Dose (BMD) values and systemic points of departure in rats using Bayesian BMD and PBK models. Margins of exposure (MOE) were calculated to assess neurotoxic risk based on estimated daily oral intake and dose metrics in plasma and brain. Results from both models indicated that young children have higher pyrethroid exposure compared to other age groups. All estimated risk values were within acceptable levels of acute neurotoxic effect. Additionally, MOEs calculated from oral doses were lower than those derived from internal doses, highlighting that traditional external exposure assessments tend to overestimate risk compared to advanced internal dose-based techniques. In conclusion, combining high-throughput and PBK approaches enhances the understanding of human health risks associated with pyrethroid exposures, demonstrating their potential for future applications in exposure tracking and health risk assessment.

Association of urinary metabolites of polycyclic aromatic hydrocarbons with urinary incontinence in adults: A cross-sectional study

This study aims to investigate the association between polycyclic aromatic hydrocarbon (PAH) metabolites and urinary incontinence (UI) in the general adult population. This study analyzed six urinary PAH metabolites in the general adult population from the 2005-2016 National Health and Nutrition Examination Survey (NHANES). UI was distinguished into stress UI (SUI), urgency UI (UUI), mixed UI (MUI), and any UI by self-reported questionnaires. Multiple logistic regression, restricted cubic spline (RCS) regression, and quantile g-computation (QG-C) were applied to assess the association between PAHs (individual and mixture exposure) and the prevalence of UI. A total of 8,136 participants were included in our study. The participants had a median age of 45.9 years, and 48.7 % of individuals were female. Most ln-transformed PAHs were positively and linearly related to the prevalence of SUI and any UI in women (P < 0.05). Increasing prevalence of SUI was associated with the highest quantiles of 3-hydroxyfluorene (3-FLU) (OR = 1.72, 95%CI = 1.27-2.33, P for trend = 0.002), 2-hydroxyfluorene (2-FLU) (OR = 1.75, 95%CI = 1.29-2.38, P for trend = 0.008), and 1-hydroxypyrene (1-PYR) (OR = 1.44, 95%CI = 1.05-1.96, P for trend = 0.012) compared with the lowest quantiles in women. The mixture of urinary PAH metabolites was significantly associated with an increased prevalence of SUI (OR = 1.09, 95%CI: 1.01-1.19, P = 0.038) in women. Urinary 2-FLU had the greatest positive contribution to the overall effect, while 2-hydroxynapthalene (2-NAP) was the major negative contributor. Our study demonstrated that mixture exposure to PAHs is associated with the prevalence of SUI in adult women, which might be primarily driven by 2-FLU.

Variable power functional dilution adjustment of spot urine

Spot-urinary biomarkers are crucial in medical, epidemiological, and environmental studies, but their variability due to hydration levels requires precise dilution adjustments. Traditional methods, like conventional creatinine correction (CCRC), are limited in compensating for variations in urine concentration, causing substantial inconsistencies, particularly at the extremes of the diuresis spectrum. While restricting the creatinine (CRN) range to 0.3-3 g/L is recommended to ensure result stability, this approach excludes a substantial proportion of samples and permits notable fluctuations within the accepted range. This study introduces a novel variable power functional creatinine correction method (V-PFCRC) to normalize analytes to 1 g/L CRN by utilizing uncorrected analyte levels and two analyte-specific coefficients, c and d. Based on extensive urinary total weight arsenic data (n = 5,553), the mathematical derivation of these coefficients is detailed in this paper and forms the foundation of the corrective V-PFCRC formulas. The generalizability of V-PFCRC was evaluated using large spot-urinary datasets for four additional metals and an extensive dataset of urinary iodine levels (n > 58,000) and blood iodine. Validation against conventional methods-assessing vital statistical data, residual CRN bias, and correlations with concurrently detected blood levels of total arsenic and iodine- demonstrated the superior performance of V-PFCRC in reducing residual CRN bias and enhancing blood-urine correlations. The V-PFCRC method effectively addresses nonlinear hydration bias and the exposure-dependent variability of this bias, providing a more accurate representation of exposure and supply levels. The adaptability and efficiency of V-PFCRC suggest its broad applicability across various scientific disciplines, potentially transforming the precision and reliability of urinary biomarkers.

Association between mixed exposure of non-persistent pesticides and liver fibrosis in the general US population: NHANES 2013-2016

People are continually and simultaneously exposed to various non-persistent pesticides as these chemicals are ubiquitously distributed in the environment. Toxicological studies have indicated the associations between non-persistent pesticides and liver fibrosis in vitro and in vivo. However, epidemical study on the deleterious effect of non-persistent pesticides on the risk of liver fibrosis is rather limited. To examine the relationship between mixed non-persistent pesticides exposure and liver fibrosis, and to identify the potential pesticides of significant importance, this study enrolled the representative individuals from the NHANES 2013-2016 survey cycles, in which urinary non-persistent pesticides were measured. Liver fibrosis was determined based on the alternative noninvasive tests Fibrosis-4 index (FIB-4) and Hepamet Fibrosis Score (HFS). Survey-weighted linear/logistic regression and Bayesian kernel machine regression (BKMR) were used to detected the independent and combined associations between non-persistent pesticides and liver fibrosis, respectively. In single exposure analysis, significant and persistent associations were identified for 3,5,6-trichloropyridinol (TCPY), para-nitrophenol (PNP), glyphosate (GLYP) and 2,4-dichlorophenoxyacetic acid (2,4-D) exposure with both continuous and dichotomous liver fibrosis outcomes. Of them, TCPY and GLYP had the highest effect estimates, with the corresponding FIB-4 coefficient (β) being 0.09 (0.05-0.13, model 3) and 0.09 (0.06-0.12, model 3), respectively. In BKMR analysis, positive associations between pesticides mixture and FIB-4 and HFS liver fibrosis were identified. The results of Posterior Inclusion Probability (PIP) further showed that GLYP, TCPY, and PNP were the main contributors to the overall effects of pesticides mixture, and the corresponding PIPs were 1.000 (1.000), 1.000 (0.914) and 0.972 (0.819) for FIB-4 (HFS) liver fibrosis, respectively. This study indicates that exposure to non-persistent pesticides mixture is associated with increased risk of liver fibrosis in humans, and provide new insight into the hepatotoxic potential of non-persistent pesticides.

Trends in NHANES Biomonitored Exposures in California and the United States following Enactment of California's Proposition 65

BACKGROUND

The prevalence of toxic chemicals in US commerce has prompted some states to adopt laws to reduce exposure. One with broad reach is California's Proposition 65 (Prop 65), which established a list of chemicals that cause cancer, developmental harm, or reproductive toxicity. The law is intended to discourage businesses from using these chemicals and to minimize consumer exposure. However, a key question remains unanswered: Has Prop 65 reduced population-level exposure to the listed chemicals?

OBJECTIVE

We used national biomonitoring data from the Centers for Disease Control and Prevention (CDC) to evaluate the impact of Prop 65 on population-level exposures.

METHODS

We evaluated changes in blood and urine concentrations of 37 chemicals (including phthalates, phenols, VOCs, metals, PAHs, and PFAS), among US National Health and Nutrition Examination Survey (NHANES) participants in relation to the time of chemicals' Prop 65 listing. Of these, 11 were listed prior to, 11 during, and 4 after the biomonitoring period. The remaining 11 were not listed but were closely related to a Prop 65-listed chemical. Where biomonitoring data were available from before and after the date of Prop 65 listing, we estimated the change in concentrations over time for Californians compared with non-Californians, using a difference-in-differences model. We used quantile regression to estimate changes in exposure over time, as well as differences between Californians and non-Californians at the 25th, 75th, and 95th percentiles.

RESULTS

We found that concentrations of biomonitored chemicals generally declined nationwide over time irrespective of their inclusion on the Prop 65 list. Median bisphenol A (BPA) concentrations decreased 15% after BPA's listing on Prop 65, whereas concentrations of the nonlisted but closely related bisphenol S (BPS) increased 20% over this same period, suggesting chemical substitution. Californians generally had lower levels of biomonitored chemicals than the rest of the US population.

DISCUSSION

Our findings suggest that increased scientific and regulatory attention, as well as public awareness of the harms of Prop 65-listed chemicals, prompted changes in product formulations that reduced exposure to those chemicals nationwide. Trends in bisphenols and several phthalates suggest that manufacturers replaced some listed chemicals with closely related but unlisted chemicals, increasing exposure to the substitutes. Our findings have implications for the design of policies to reduce toxic exposures, biomonitoring programs to inform policy interventions, and future research into the regulatory and market forces that affect chemical exposure. https://doi.org/10.1289/EHP13956.

Which Environmental Pollutants Are Toxic to Our Ears?-Evidence of the Ototoxicity of Common Substances

Ototoxicity refers to the adverse effects of substances on auditory or vestibular functions. This study examines the evidence of ototoxicity's association with exposure to common environmental pollutants, as documented in toxicological profiles by the Agency for Toxic Substances and Disease Registry. Our aim was to evaluate whether the evidence supports modifying the charting of ototoxic effects in the summary tables of these toxicological profiles and providing a guide for scientists to access these data. Health outcomes of interest included hearing loss, vestibular effects, cochlear lesions, tonal alterations, cellular damage, and ototoxicity-related outcomes (neurological, nephrotoxic, hepatic, and developmental effects). We obtained ototoxicity information for 62 substances. Hearing-related effects were reported, along with neurological effects. Overall, 26 profiles reported strong evidence of ototoxicity, including 13 substances previously designated as ototoxic by other health and safety agencies. Commonly studied outcomes included hearing loss, damage to ear anatomy, and auditory dysfunction. Vestibular dysfunction and tinnitus are rarely studied. Our findings highlight the lack of conclusive evidence of ototoxic properties for many substances, especially for pesticides and herbicides. This review supports charting the evidence of ototoxicity separately in toxicological profiles' summary tables. Improving the communication of ototoxicity-related health effects might impact their recognition and prompt further research. A stronger evidence base could support improved prevention efforts in terms of serious health outcomes.

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 mediating role of obesity in the development of depression in individuals with diabetes: A population-based study from NHANES 2005-2014

OBJECTIVE

Depression is one of the common manifestations of diabetes population, and previous studies have shown that there is a correlation between depression and diabetes. This study was conducted retrospectively through the large National Health and Nutrition Examination Survey (NHANES) to explore the risk of depression in different individuals with diabetes.

METHODS

We collected data on a total of 33,001 individuals in 5 cycles of NHANES and compared the incidence of depression in the individuals with diabetes, pre-diabetes or without diabetes groups after weighting. A weighted logistic review was used to assess the association between diabetes and depression at different BMI, sex, and age levels. Mediating analysis was used to assess the risk of depression in people with obesity-mediated diabetes. In addition, the non-linear relationship between BMI and depression at different factor levels was evaluated using restricted cubic strips (RCS).

RESULTS

Diabetes was significantly associated with depression in obesity, especially for female (OR: 1.45, 95 % CI: 1.20-1.75, P < 0.001) and young (

CONCLUSIONS

There is a significant correlation between diabetes and depression, and obesity as a mediating variable mediates the correlation between diabetes and depression. Especially in obese, young (age < 60) and women, the phenomenon is more pronounced.

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Key Words

• Depression
• Diabetes
• Mediating effect
• Obesity

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MESH Headings

• Adolescent
• Humans
• Female
• Middle Aged
• Nutrition Surveys
• Retrospective Studies
• Depression/epidemiology
• Body Mass Index
• Obesity/epidemiology
• Obesity/complications
• Diabetes Mellitus/epidemiology

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Affiliation(s)

Yuxin Nong Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080 Guangzhou, China
Guangyu Wu Department of Neurology, Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative Diseases, Guangdong Neuroscience Institute, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080 Guangzhou, China
Junquan Lu Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080 Guangzhou, China
Xuebiao Wei Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 51080 Guangzhou, China.
Danqing Yu Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080 Guangzhou, China.

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In Vitro Toxicity Screening of Fifty Complex Mixtures in HepG2 Cells

To develop the risk prediction technology for mixture toxicity, a reliable and extensive dataset of experimental results is required. However, most published literature only provides data on combinations containing two or three substances, resulting in a limited dataset for predicting the toxicity of complex mixtures. Complex mixtures may have different mode of actions (MoAs) due to their varied composition, posing difficulty in the prediction using conventional toxicity prediction models, such as the concentration addition (CA) and independent action (IA) models. The aim of this study was to generate an experimental dataset comprising complex mixtures. To identify the target complex mixtures, we referred to the findings of the HBM4EU project. We identified three groups of seven to ten components that were commonly detected together in human bodies, namely environmental phenols, perfluorinated compounds, and heavy metal compounds, assuming these chemicals to have different MoAs. In addition, a separate mixture was added consisting of seven organophosphate flame retardants (OPFRs), which may have similar chemical structures. All target substances were tested for cytotoxicity using HepG2 cell lines, and subsequently 50 different complex mixtures were randomly generated with equitoxic mixtures of EC10 levels. To determine the interaction effect, we calculated the model deviation ratio (MDR) by comparing the observed EC10 with the predicted EC10 from the CA model, then categorized three types of interactions: antagonism, additivity, and synergism. Dose-response curves and EC values were calculated for all complex mixtures. Out of 50 mixtures, none demonstrated synergism, while six mixtures exhibited an antagonistic effect. The remaining mixtures exhibited additivity with MDRs ranging from 0.50 to 1.34. Our experimental data have been formatted to and constructed for the database. They will be utilized for further research aimed at developing the combined CA/IA approaches to support mixture risk assessment.

[Exposure characteristics and health risk assessment of 97 typical chemical pollutants in human serum]

Rapid industrial and agricultural developments in China have led to the wide use and discharge of chemical products and pesticides, resulting in extensive residues in environmental media. These residues can enter the human body through various pathways, leading to high exposure risks and health hazards. Because the human body is exposed to a variety of chemical pollutants, accurately quantifying the exposure levels of these pollutants in the human body and evaluating their health risks are of great importance. In this study, the serum concentrations of 97 typical chemical pollutants of 60 adults in central China were simultaneously determined using solid-phase extraction coupled with gas chromatography-tandem mass spectrometry (SPE-GC-MS/MS). In this method, 200 μL of a serum sample was mixed with 10 μL of an isotope-labeled internal standard solution. The sample was vortexed and refrigerated overnight at 4 ℃. Each sample was then deproteinized by the addition of 200 μL of 15% formic acid aqueous solution and vortexed. The serum sample was loaded into a preconditioned Oasis® PRiME HLB SPE cartridge and rinsed with 3 mL of methanol-water (6∶1, v/v). The SPE cartridge was subsequently vacuumed. The analytes were eluted with 3 mL of dichloromethane followed by 3 mL of n-hexane. The eluent was concentrated to near dryness under a gentle nitrogen stream and reconstituted with 100 μL of acetone. The samples were determined by GC-MS/MS and separated on a DB-5MS capillary column (30 m×0.25 mm×0.25 μm) with temperature programming. The column temperature was maintained at 70 ℃ for 2 min, increased at a rate of 25 ℃/min to 150 ℃, increased at a rate of 3 ℃/min to 200 ℃, and then held for 2 min. Finally, the column temperature was increased at a rate of 8 ℃/min to 300 ℃ and maintained at this temperature for 8 min. The samples were detected in multiple-reaction monitoring (MRM) mode and quantitatively analyzed using the internal standard method. Multiple linear regression models were used to analyze the effects of demographic characteristics, lifestyle habits, and diet on the concentrations of the chemical pollutants in the serum samples, and known biomonitoring equivalents (BEs) and human biomonitoring (HBM) values were combined to compute hazard quotients (HQs) and hazard indices (HIs) and evaluate the health risks of single and cumulative exposures to the chemical pollutants. The results showed that the main pollutants detected in human serum were organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs). The detection rates of eight pollutants, including hexachlorobenzene (HCB) (100%), pentachlorophenol (PCP) (100%), p,p'-dichlorodiphenylene (p,p'-DDE) (100%), PCB-138 (100%), PCB-153 (98.3%), β-hexachlorocyclohexane (β-HCH) (91.7%), fluorene (Flu) (85.0%), and anthracene (Ant) (75.0%), were greater than 70%. The serum levels of β-HCH were higher in females than in males, and age was positively correlated with exposure to p,p'-DDE, PCB-138, PCB-153, and β-HCH. Increased exposure levels to p,p'-DDE and β-HCH may be associated with a high frequency of meat intake, whereas increased exposure level to PCP may be associated with a high frequency of vegetable intake. The serum HQ of PCP was greater than 1 in 6.7% of the samples, and no risk was observed for HCB and p,p'-DDE exposure in the study population. Approximately 28.3% of the study subjects had HI values greater than 1. Overall, the general adult population in this region is widely exposed to a wide range of chemical pollutants, and gender, age, and diet are likely to be the main factors influencing the concentration of chemical pollutants. The health risk of single and compound exposures to chemical pollutants should not be ignored.

Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS

Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.

Association of exposures to serum terpenes with the prevalence of dyslipidemia: a population-based analysis

This study sought to examine hitherto unresearched relationships between serum terpenes and the prevalence of dyslipidemia. Serum terpenes such as limonene, α-pinene, and β-pinene from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) were used as independent variables in this cross-sectional study. Continuous lipid variables included total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), non-HDL-C, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), residual cholesterol (RC), and apolipoprotein B (Apo B). Binary lipid variables (elevated TC, ≥5.18 mmol/L; lowered HDL-C, <1.04 mmol/L in men, and <1.30 mmol/L in women; elevated non-HDL-C, ≥4.2 mmol/L; elevated TG, ≥1.7 mmol/L; elevated LDL-C, ≥3.37 mmol/L; elevated RC, ≥1.0 mmol/L; and elevated Apo B, ≥1.3 g/L) suggest dyslipidemia. The relationships between the mixture of serum terpenes with lipid variables were investigated using weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR). The study for TC, HDL-C, and non-HDL-C included a total of 1,528 people, whereas the analysis for TG, LDL-C, RC, and Apo B comprised 714 participants. The mean age of the overall participants was 47.69 years, and 48.77% were male. We found that tertiles of serum terpene were positively associated with binary (elevated TC, non-HDL-C, TG, LDL-C, RC, Apo B, and lowered HDL-C) and continuous (TC, non-HDL-C, TG, LDL-C, RC, and Apo B, but not HDL-C) serum lipid variables. WQS regression and BKMR analysis revealed that the mixture of serum terpenes was linked with the prevalence of dyslipidemia. According to our data, the prevalence of dyslipidemia was correlated with serum concentrations of three terpenes both separately and collectively.

Effect of polycyclic aromatic hydrocarbons on cancer risk causally mediated via vitamin D levels

Polycyclic aromatic hydrocarbons (PAHs) widely exist in environmental substrates and are closely related to individual circulating vitamin D levels and tumorigenesis. Therefore, we proposed to evaluate the relationship between PAH exposure, vitamin D, and the risks for 14 cancer types via a causal inference framework underlying the mediation analysis. We evaluated seven urine monohydroxylated PAH (OH-PAH) and serum vitamin D concentrations of 3306 participants from the National Health and Nutrition Examination Survey between the 2013 and 2016 survey cycles and measured PAH concentrations in 150 subjects from the Nanjing cohort. We observed a significant negative dose-response relationship between increased OH-PAH levels and vitamin D deficiency. Each unit increase in ∑OH-PAHs could lead to a decrease in vitamin D levels (βadj  = -0.98, Padj  = 2.05 × 10-4 ). Body mass index could have interaction effects with ∑OH-PAHs and affect vitamin D levels. Coexposure to naphthalene and fluorene metabolites mutually affected vitamin D levels. Notably, vitamin D could causally mediate the relationship between OH-PAHs and nine types of cancer (e.g., colorectal cancer, liver cancers, etc.). This study first emphasizes the causal cascade of individual OH-PAHs, vitamin D, and cancer risk, providing insights into prevention via the environment.

A Data-Driven Approach to Estimating Occupational Inhalation Exposure Using Workplace Compliance Data

A growing list of chemicals are approved for production and use in the United States and elsewhere, and new approaches are needed to rapidly assess the potential exposure and health hazard posed by these substances. Here, we present a high-throughput, data-driven approach that will aid in estimating occupational exposure using a database of over 1.5 million observations of chemical concentrations in U.S. workplace air samples. We fit a Bayesian hierarchical model that uses industry type and the physicochemical properties of a substance to predict the distribution of workplace air concentrations. This model substantially outperforms a null model when predicting whether a substance will be detected in an air sample, and if so at what concentration, with 75.9% classification accuracy and a root-mean-square error (RMSE) of 1.00 log10 mg m-3 when applied to a held-out test set of substances. This modeling framework can be used to predict air concentration distributions for new substances, which we demonstrate by making predictions for 5587 new substance-by-workplace-type pairs reported in the US EPA's Toxic Substances Control Act (TSCA) Chemical Data Reporting (CDR) industrial use database. It also allows for improved consideration of occupational exposure within the context of high-throughput, risk-based chemical prioritization efforts.

Butyl benzyl phthalate as a key component of phthalate ester in relation to cognitive impairment in NHANES elderly individuals and experimental mice

Phthalates are a group of neurotoxicants with cognitive-disrupting potentials. Given the structural diversity of phthalates, the corresponding neurotoxicity is dramatically altered. To identify the potential contributions of different phthalates on the process of cognitive impairment, data of 836 elders from the NHANES 2011-2014 cycles were used. Survey-weighted logistic regression and principal component analysis-weighted quantile sum regression (PCA-WQSR) models were applied to estimate the independent and combined associations of 11 urinary phthalate metabolites with cognitive deficit (assessed by 4 tests: Immediate Recall (IR), Delayed Recall (DR), Animal Fluency (AF), and Digit Symbol Substitution Test (DSST)) and to identify the potential phthalate with high weight. Laboratory mice were further used to examine the effect of phthalates on cognitive function and to explore the potential mechanisms. In logistic regression models, MBzP was the only metabolite positively correlated with four tests, with ORs of 2.53 (quartile 3 (Q3)), 2.26 (Q3), 2.89 (Q4) and 2.45 (Q2), 2.82 (Q4) for IR, DR, AF, and DSST respectively. In PCA-WQSR co-exposure models, low-molecular-weight (LMW) phthalates were the only PC positively linked to DSST deficit (OR: 1.93), which was further validated in WQSR analysis (WQS OR7-phthalates: 1.56 and WQS OR8-phthalates: 1.55); consistent with the results of logistic regression, MBzP was the dominant phthalate. In mice, butyl benzyl phthalate (BBP), the parent phthalate of MBzP, dose-dependently reduced cognitive function and disrupted hippocampal neurons. Additionally, the hippocampal transcriptome analysis identified 431 differential expression genes, among which most were involved in inhibiting the neuroactive ligand-receptor interaction pathway and activating the cytokine-cytokine receptor interaction pathway. Our study indicates the critical role of BBP in the association of phthalates and cognitive deficits among elderly individuals, which might be speculated that BBP could disrupt hippocampal neurons, activate neuroinflammation, and inhibit neuroactive receptors. Our findings provide new insight into the cognitive-disrupting potential of BBP.

Environmental Chemicals and their Association with Hyperparathyroidism

BACKGROUND

The incidence of hyperparathyroidism has increased in the USA. The previous work from our institution detected environmental chemicals (EC) within hyperplastic parathyroid tumors. The National Health and Nutrition Examination Survey (NHANES) is a program designed to assess the health status of people in the USA and includes measurements of EC in serum. Our aim was to determine which EC are associated with elevated parathyroid hormone (PTH) and calcium levels within NHANES.

METHODS

NHANES was queried from 2003-2016 for our analysis with calcium. A separate subgroup was queried from 2003-2006 that included PTH levels. Subjects with elevated calcium, and elevated PTH and normal Vitamin D levels were identified. Wilcoxon rank sum tests were used to analyze levels of EC in those with elevated calcium, and those with elevated PTH in the subgroup. All EC with p < 0.05 were then included in separate multivariate models adjusting for serum vitamin D and creatinine for PTH and albumin for calcium.

RESULTS

There were 51,395 subjects analyzed, and calcium was elevated in 2.1% (1080) of subjects. Our subgroup analysis analyzed 14,681 subjects, and PTH was elevated without deficient Vitamin D in 9.4% (1,377). Twenty-nine different polychlorinated biphenyls and the organochlorine pesticides hexachlorobenzene, transnonachlor, oxychlordane, and p,p'-dichlorodiphenyldichloroethylene (DDE) were found to be associated with elevated calcium and separately with elevated PTH (all p < 0.05).

CONCLUSION

In NHANES, 33 ECs were found to be associated with elevated calcium as well as elevated PTH levels on our subgroup analysis. These chemicals may lead us toward a causal link between environmental factors and the development of hyperparathyroidism and should be the focus of future studies looking at chemical levels within specimens.

Interpreting biomonitoring data: Introducing the international human biomonitoring (i-HBM) working group's health-based guidance value (HB2GV) dashboard

Human biomonitoring (HBM) data measured in specific contexts or populations provide information for comparing population exposures. There are numerous health-based biomonitoring guidance values, but to locate these values, interested parties need to seek them out individually from publications, governmental reports, websites and other sources. Until now, there has been no central, international repository for this information. Thus, a tool is needed to help researchers, public health professionals, risk assessors, and regulatory decision makers to quickly locate relevant values on numerous environmental chemicals. A free, on-line repository for international health-based guidance values to facilitate the interpretation of HBM data is now available. The repository is referred to as the "Human Biomonitoring Health-Based Guidance Value (HB2GV) Dashboard". The Dashboard represents the efforts of the International Human Biomonitoring Working Group (i-HBM), affiliated with the International Society of Exposure Science. The i-HBM's mission is to promote the use of population-level HBM data to inform public health decision-making by developing harmonized resources to facilitate the interpretation of HBM data in a health-based context. This paper describes the methods used to compile the human biomonitoring health-based guidance values, how the values can be accessed and used, and caveats with using the Dashboard for interpreting HBM data. To our knowledge, the HB2GV Dashboard is the first open-access, curated database of HBM guidance values developed for use in interpreting HBM data. This new resource can assist global HBM data users such as risk assessors, risk managers and biomonitoring programs with a readily available compilation of guidance values.

Disparities in chemical exposures among pregnant women and neonates by socioeconomic and demographic characteristics: A nontargeted approach

BACKGROUND

Exposure to environmental chemicals during pregnancy adversely affects maternal and infant health, and identifying socio-demographic differences in exposures can inform contributions to health inequities.

METHODS

We recruited 294 demographically diverse pregnant participants in San Francisco from the Mission Bay/Moffit Long (MB/ML) hospitals, which serve a primarily higher income population, and Zuckerberg San Francisco General Hospital (ZSFGH), which serves a lower income population. We collected maternal and cord sera, which we screened for 2420 unique formulas and their isomers using high-resolution mass spectrometry using LC-QTOF/MS. We assessed differences in chemical abundances across socioeconomic and demographic groups using linear regression adjusting for false discovery rate.

RESULTS

Our participants were racially diverse (31% Latinx, 16% Asian/Pacific Islander, 5% Black, 5% other or multi-race, and 43% white). A substantial portion experienced financial strain (28%) and food insecurity (20%) during pregnancy. We observed significant abundance differences in maternal (9 chemicals) and cord sera (39 chemicals) between participants who delivered at the MB/ML hospitals versus ZSFGH. Of the 39 chemical features differentially detected in cord blood, 18 were present in pesticides, one per- or poly-fluoroalkyl substance (PFAS), 21 in plasticizers, 24 in cosmetics, and 17 in pharmaceuticals; 4 chemical features had unknown sources. A chemical feature annotated as 2,4-dichlorophenol had higher abundances among Latinx compared to white participants, those delivering at ZSFGH compared to MB/ML, those with food insecurity, and those with financial strain. Post-hoc QTOF analyses indicated the chemical feature was either 2,4-dichlorophenol or 2,5-dichlorophenol, both of which have potential endocrine-disrupting effects.

CONCLUSIONS

Chemical exposures differed between delivery hospitals, likely due to underlying social conditions faced by populations served. Differential exposures to 2,4-dichlorophenol or 2,5-dichlorophenol may contribute to disparities in adverse outcomes.

Bayesian inference of chemical exposures from NHANES urine biomonitoring data

BACKGROUND

Knowing which environmental chemicals contribute to metabolites observed in humans is necessary for meaningful estimates of exposure and risk from biomonitoring data.

OBJECTIVE

Employ a modeling approach that combines biomonitoring data with chemical metabolism information to produce chemical exposure intake rate estimates with well-quantified uncertainty.

METHODS

Bayesian methodology was used to infer ranges of exposure for parent chemicals of biomarkers measured in urine samples from the U.S population by the National Health and Nutrition Examination Survey (NHANES). Metabolites were probabilistically linked to parent chemicals using the NHANES reports and text mining of PubMed abstracts.

RESULTS

Chemical exposures were estimated for various population groups and translated to risk-based prioritization using toxicokinetic (TK) modeling and experimental data. Exposure estimates were investigated more closely for children aged 3 to 5 years, a population group that debuted with the 2015-2016 NHANES cohort.

SIGNIFICANCE

The methods described here have been compiled into an R package, bayesmarker, and made publicly available on GitHub. These inferred exposures, when coupled with predicted toxic doses via high throughput TK, can help aid in the identification of public health priority chemicals via risk-based bioactivity-to-exposure ratios.

Literature review and evaluation of biomarkers, matrices and analytical methods for chemicals selected in the research program Human Biomonitoring for the European Union (HBM4EU)

Humans are potentially exposed to a large amount of chemicals present in the environment and in the workplace. In the European Human Biomonitoring initiative (Human Biomonitoring for the European Union = HBM4EU), acrylamide, mycotoxins (aflatoxin B1, deoxynivalenol, fumonisin B1), diisocyanates (4,4'-methylenediphenyl diisocyanate, 2,4- and 2,6-toluene diisocyanate), and pyrethroids were included among the prioritized chemicals of concern for human health. For the present literature review, the analytical methods used in worldwide biomonitoring studies for these compounds were collected and presented in comprehensive tables, including the following parameter: determined biomarker, matrix, sample amount, work-up procedure, available laboratory quality assurance and quality assessment information, analytical techniques, and limit of detection. Based on the data presented in these tables, the most suitable methods were recommended. According to the paradigm of biomonitoring, the information about two different biomarkers of exposure was evaluated: a) internal dose = parent compounds and metabolites in urine and blood; and b) the biologically effective = dose measured as blood protein adducts. Urine was the preferred matrix used for deoxynivalenol, fumonisin B1, and pyrethroids (biomarkers of internal dose). Markers of the biological effective dose were determined as hemoglobin adducts for diisocyanates and acrylamide, and as serum-albumin-adducts of aflatoxin B1 and diisocyanates. The analyses and quantitation of the protein adducts in blood or the metabolites in urine were mostly performed with LC-MS/MS or GC-MS in the presence of isotope-labeled internal standards. This review also addresses the critical aspects of the application, use and selection of biomarkers. For future biomonitoring studies, a more comprehensive approach is discussed to broaden the selection of compounds.

A state-of-the-science review and guide for measuring environmental exposure biomarkers in dried blood spots

BACKGROUND

Dried blood spot (DBS) sampling is a simple, cost-effective, and minimally invasive alternative to venipuncture for measuring exposure biomarkers in public health and epidemiological research. DBS sampling provides advantages in field-based studies conducted in low-resource settings and in studies involving infants and children. In addition, DBS samples are routinely collected from newborns after birth (i.e., newborn dried blood spots, NDBS), with many states in the United States permitting access to archived NDBS samples for research purposes.

OBJECTIVES

We review the state of the science for analyzing exposure biomarkers in DBS samples, both archived and newly collected, and provide guidance on sample collection, storage, and blood volume requirements associated with individual DBS assays. We discuss recent progress regarding analytical methods, analytical sensitivity, and specificity, sample volume requirements, contamination considerations, estimating extracted blood volumes, assessing stability and analyte recovery, and hematocrit effects.

METHODS

A systematic search of PubMed (MEDLINE), Embase (Elsevier), and CINAHL (EBSCO) was conducted in March 2022. DBS method development and application studies were divided into three main chemical classes: environmental tobacco smoke, trace elements (including lead, mercury, cadmium, and arsenic), and industrial chemicals (including endocrine-disrupting chemicals and persistent organic pollutants). DBS method development and validation studies were scored on key quality-control and performance parameters by two members of the review team.

RESULTS

Our search identified 47 published reports related to measuring environmental exposure biomarkers in human DBS samples. A total of 28 reports (37 total studies) were on methods development and validation and 19 reports were primarily the application of previously developed DBS assays. High-performing DBS methods have been developed, validated, and applied for detecting environmental exposures to tobacco smoke, trace elements, and several important endocrine-disrupting chemicals and persistent organic pollutants. Additional work is needed for measuring cadmium, arsenic, inorganic mercury, and bisphenol A in DBS and NDBS samples.

SIGNIFICANCE

We present an inventory and critical review of available assays for measuring environmental exposure biomarkers in DBS and NDBS samples to help facilitate this sampling medium as an emerging tool for public health (e.g., screening programs, temporal biomonitoring) and environmental epidemiology (e.g., field-based studies).

Using optimal subset regression to identify factors associated with insulin resistance and construct predictive models in the US adult population

BACKGROUND

In recent decades, with the development of the global economy and the improvement of living standards, insulin resistance (IR) has become a common phenomenon. Current studies have shown that IR varies between races. Therefore, it is necessary to develop individual prediction models for each country. The purpose of this study was to develop a predictive model of IR applicable to the US population.

METHOD

In total, 11 cycles of data from the NHANES database were selected for this study. Of these, participants from 1999 to 2010 (n = 14931) were used to establish the model, and participants from 2011 to 2020 (n = 13,646) were used to validate the model. Univariate and multivariable logistic regression was used to analyze the factors associated with IR. Optimal subset regression was used to filter the best modeling variables. ROC curves, calibration curves, and decision curve analysis were used to determine the strengths and weaknesses of the model.

RESULTS

After screening the variables by optimal subset regression, variables with covariance were excluded, and a total of seven factors (including HDL, LDL, ALB, GLB, GLU, BMI, and waist) were finally included to establish the prediction model. The AUCs were 0.851 and 0.857 in the training and validation sets, respectively, and the Brier value of the calibration curve was 0.153.

CONCLUSION

The optimal subset predictive model proposed in this study has a great performance in predicting IR, and the decision curve analysis shows that it has a high net clinical benefit, which can help clinicians and epidemiologists easily detect IR and take appropriate interventions as early as possible.

Environmental Phenol and Paraben Exposure Risks and Their Potential Influence on the Gene Expression Involved in the Prognosis of Prostate Cancer

Prostate cancer (PCa) is one of the leading malignant tumors in US men. The lack of understanding of the molecular pathology on the risk of food supply chain exposures of environmental phenol (EP) and paraben (PB) chemicals limits the prevention, diagnosis, and treatment options. This research aims to utilize a risk assessment approach to demonstrate the association of EP and PB exposures detected in the urine samples along with PCa in US men (NHANES data 2005−2015). Further, we employ integrated bioinformatics to examine how EP and PB exposure influences the molecular pathways associated with the progression of PCa. The odds ratio, multiple regression model, and Pearson coefficients were used to evaluate goodness-of-fit analyses. The results demonstrated associations of EPs, PBs, and their metabolites, qualitative and quantitative variables, with PCa. The genes responsive to EP and PB exposures were identified using the Comparative Toxicogenomic Database (CTD). DAVID.6.8, GO, and KEGG enrichment analyses were used to delineate their roles in prostate carcinogenesis. The plug-in CytoHubba and MCODE completed identification of the hub genes in Cytoscape software for their roles in the PCa prognosis. It was then validated by using the UALCAN database by evaluating the expression levels and predictive values of the identified hub genes in prostate cancer prognosis using TCGA data. We demonstrate a significant association of higher levels of EPs and PBs in the urine samples, categorical and numerical confounders, with self-reported PCa cases. The higher expression levels of the hub genes (BUB1B, TOP2A, UBE2C, RRM2, and CENPF) in the aggressive stages (Gleason score > 8) of PCa tissues indicate their potential role(s) in the carcinogenic pathways. Our results present an innovative approach to extrapolate and validate hub genes responsive to the EPs and PBs, which may contribute to the severity of the disease prognosis, especially in the older population of US men.

Quantitative non-targeted analysis: Bridging the gap between contaminant discovery and risk characterization

Chemical risk assessments follow a long-standing paradigm that integrates hazard, dose-response, and exposure information to facilitate quantitative risk characterization. Targeted analytical measurement data directly support risk assessment activities, as well as downstream risk management and compliance monitoring efforts. Yet, targeted methods have struggled to keep pace with the demands for data regarding the vast, and growing, number of known chemicals. Many contemporary monitoring studies therefore utilize non-targeted analysis (NTA) methods to screen for known chemicals with limited risk information. Qualitative NTA data has enabled identification of previously unknown compounds and characterization of data-poor compounds in support of hazard identification and exposure assessment efforts. In spite of this, NTA data have seen limited use in risk-based decision making due to uncertainties surrounding their quantitative interpretation. Significant efforts have been made in recent years to bridge this quantitative gap. Based on these advancements, quantitative NTA data, when coupled with other high-throughput data streams and predictive models, are poised to directly support 21st-century risk-based decisions. This article highlights components of the chemical risk assessment process that are influenced by NTA data, surveys the existing literature for approaches to derive quantitative estimates of chemicals from NTA measurements, and presents a conceptual framework for incorporating NTA data into contemporary risk assessment frameworks.

Analysis of polycyclic aromatic hydrocarbon intake in the US adult population from NHANES 2005-2014 identifies vulnerable subpopulations, suggests interaction between tobacco smoke exposure and sociodemographic factors

Polycyclic aromatic hydrocarbons (PAHs) are a toxic and ubiquitous class of environmental chemicals, products of fuel combustion from human and natural sources. The objective of this study was to identify vulnerable populations for high PAH exposure and variability, to better understand where to target PAH exposure reduction initiatives. Urinary metabolite data were collected from 9517 individuals from the U.S. CDC National Health and Nutrition Examination Survey years 2005-2014 for four parental PAHs naphthalene, fluorene, phenanthrene, and pyrene. We utilized these urinary biomarkers to estimate PAH intake, and regression models were fit for multiple demographic and lifestyle variables, to determine variable effects, interactions, odds of high versus low PAH intake. Smoking and secondhand smoke exposure accounted for the largest PAH intake rate variability (25.62%), and there were strongest interactions between race/ethnicity and smoking or SHS exposure, reflected in a much greater contribution of smoking to PAH intake in non-Hispanic Whites as compared to other races/ethnicities. Increased odds of high PAH intake were seen in older age groups, obese persons, college graduates, midrange incomes, smokers, and those who were SHS exposed. Among the non-smoking population, effects of other demographic factors lessened, suggesting a highly interactive nature. Our results suggest that there are demographic subpopulations with high PAH intake as a result of different smoking behaviors and potentially other exposures. This has human health, environmental justice, and regulatory implications wherein smoking cessation programs, SHS exposure regulations, and public health initiatives could be better targeted towards vulnerable subpopulations to meaningfully reduce PAH exposures.

The association of minerals intake in three meals with cancer and all-cause mortality: the U.S. National Health and Nutrition Examination Survey, 2003-2014

BACKGROUND

Intake time of diet has recently been demonstrated to be associated with the internal clock and circadian pattern. However, whether and how the intake time of minerals would influence the natural course of cancer was largely unknown.

METHODS

This study aimed to assess the association of mineral intake at different periods with cancer and all-cause mortality. A total of 27,455 participants aged 18-85 years old in the National Health and Nutrition Examination Survey were recruited. The main exposures were the mineral intakes in the morning, afternoon and evening, which were categorized into quintiles, respectively. The main outcomes were mortality of cancer and all causes.

RESULTS

During the 178,182 person-years of follow-up, 2680 deaths, including 601 deaths due to cancer, were documented. After adjusting for potential confounders, compared to the participants who were in the lowest quintile(quintile-1) of mineral intakes at dinner, the participants in the highest quintile intake(quintile-5) of dietary potassium, calcium and magnesium had lower mortality risks of cancer (HRpotassium = 0.72, 95% CI:0.55-0.94, P for trend = 0.023; HRcalcium = 0.74, 95% CI:0.57-0.98, P for trend = 0.05; HRmagnesium = 0.75, 95% CI:0.56-0.99, P for trend = 0.037) and all-cause (HRpotassium = 0.83, 95% CI:0.73-0.94, P for trend = 0.012; HRcalcium = 0.87, 95% CI:0.76-0.99, P for trend = 0.025; HRmagnesium = 0.85, 95% CI:0.74-0.97, P for trend = 0.011; HRcopper = 0.80, 95%CI: 0.68-0.94, P for trend = 0.012). Further, equivalently replacing 10% of dietary potassium, calcium and magnesium consumed in the morning with those in the evening were associated with lower mortality risk of cancer (HRpotassium = 0.94, 95%CI:0.91-0.97; HRcalcium = 0.95, 95%CI:0.92-0.98; HRmagnesium = 0.95, 95%CI: 0.92-0.98).

CONCLUSIONS

This study demonstrated that the optimal intake time of potassium, calcium and magnesium for reducing the risk of cancer and all-cause mortality was in the evening.

Utilizing a Biology-Driven Approach to Map the Exposome in Health and Disease: An Essential Investment to Drive the Next Generation of Environmental Discovery

BACKGROUND

Recent developments in technologies have offered opportunities to measure the exposome with unprecedented accuracy and scale. However, because most investigations have targeted only a few exposures at a time, it is hypothesized that the majority of the environmental determinants of chronic diseases remain unknown.

OBJECTIVES

We describe a functional exposome concept and explain how it can leverage existing bioassays and high-resolution mass spectrometry for exploratory study. We discuss how such an approach can address well-known barriers to interpret exposures and present a vision of next-generation exposomics.

DISCUSSION

The exposome is vast. Instead of trying to capture all exposures, we can reduce the complexity by measuring the functional exposome-the totality of the biologically active exposures relevant to disease development-through coupling biochemical receptor-binding assays with affinity purification-mass spectrometry. We claim the idea of capturing exposures with functional biomolecules opens new opportunities to solve critical problems in exposomics, including low-dose detection, unknown annotations, and complex mixtures of exposures. Although novel, biology-based measurement can make use of the existing data processing and bioinformatics pipelines. The functional exposome concept also complements conventional targeted and untargeted approaches for understanding exposure-disease relationships.

CONCLUSIONS

Although measurement technology has advanced, critical technological, analytical, and inferential barriers impede the detection of many environmental exposures relevant to chronic-disease etiology. Through biology-driven exposomics, it is possible to simultaneously scale up discovery of these causal environmental factors. https://doi.org/10.1289/EHP8327.

High-throughput PBTK models for in vitro to in vivo extrapolation

INTRODUCTION

Toxicity data are unavailable for many thousands of chemicals in commerce and the environment. Therefore, risk assessors need to rapidly screen these chemicals for potential risk to public health. High-throughput screening (HTS) for in vitro bioactivity, when used with high-throughput toxicokinetic (HTTK) data and models, allows characterization of these thousands of chemicals.

AREAS COVERED

This review covers generic physiologically based toxicokinetic (PBTK) models and high-throughput PBTK modeling for in vitro-in vivo extrapolation (IVIVE) of HTS data. We focus on 'httk', a public, open-source set of computational modeling tools and in vitro toxicokinetic (TK) data.

EXPERT OPINION

HTTK benefits chemical risk assessors with its ability to support rapid chemical screening/prioritization, perform IVIVE, and provide provisional TK modeling for large numbers of chemicals using only limited chemical-specific data. Although generic TK model design can increase prediction uncertainty, these models provide offsetting benefits by increasing model implementation accuracy. Also, public distribution of the models and data enhances reproducibility. For the httk package, the modular and open-source design can enable the tool to be used and continuously improved by a broad user community in support of the critical need for high-throughput chemical prioritization and rapid dose estimation to facilitate rapid hazard assessments.

Independent and combined associations of urinary heavy metals exposure and serum sex hormones among adults in NHANES 2013-2016

Accumulating evidences indicated that heavy metals may disrupt human sex hormones. However, the combined effects of heavy metals on sex hormones remain to be clarified. To explore the independent and combined associations between heavy metal exposure and serum sex hormones among adults, data of 2728 adults from the National Health and Nutrition Examination Survey (NHANES) was applied. We examined independent and combined associations of fourteen urinary heavy metals and three serum sex steroid hormones (total testosterone (TT), estradiol (E2) and sex hormone-binding globulin (SHBG)). Multivariate linear regression was used to evaluate the independent associations between metal exposure and sex hormone alterations. Principle component analysis -weighted quantile sum regression (PCA-WQSR) model was performed to estimate the combined associations in our individuals. In the co-exposure model, we determined that weighted quantile sum (WQS) index of industrial pollutants was negatively associated with E2 in females (WQS Percent change_8-metal = -20.6%; 95% CI: -30.1%, -9.96%), while in males WQS index of water pollutants was negatively related to SHBG (WQS Percent change_8-metal = -5.35%; 95% CI: -9.88%, -0.598%). Cadmium (Cd), tin (Sn) and lead (Pb) were the dominating metals of female E2-negative association while Ba was the leading contributor related to male SHBG reduction, which was consistent with the results of multivariate linear regression. Additionally, in postmenopausal women, the associations of E2 decrease with heavy metal co-exposure remained significant while Cd and monomethylarsonic acid (MMA) were identified as hazardous metals in the mixture. We concluded that the exposure to heavy metals was associated with human sex hormone alterations in independent or combined manners. Considering the design of NHANES study, further studies from other national-representative surveys are necessary.

Cohort profile: China National Human Biomonitoring (CNHBM)-A nationally representative, prospective cohort in Chinese population

OBJECTIVE

Globally, developed countries such as the United States, Canada, Germany, Korea, have carried out long-term and systematic biomonitoring programs for environmental chemicals in their populations. The China National Human Biomonitoring (CNHBM) was to document the extent of human exposure to a wide array of environmental chemicals, to understand exposure profiles, magnitude and ongoing trends in exposure in the general Chinese population, and to establish a national biorepository.

METHODS

CNHBM adopted three-stage sampling method to obtain a nationally representative sample of the population. A total of 21,888 participants who were permanent residents in 31 provinces were designed to interviewed in this national biomonitoring (152 monitoring sites × 3 survey units × 2 sexes × 6 age groups × 4 persons = 21,888 persons) in 2017-2018. Unlike the US National Health and Nutrition Examination Survey, the CNHBM will follow the same participants in subsequent cycles allowing for dynamic, longitudinal data sets for epidemiologic follow-up. Each survey cycle of CNHBM will last 2 years and each subsequent cycle will occur 3 years after the prior cycle's completion.

RESULTS

In 2017-2018, the CNHBM created a large cohort of Chinese citizens that included districts/counties questionnaire, community questionnaire collecting information on villages/communities, individual questionnaire, household questionnaire, comprehensive medical examination, and collection of blood and urine samples for measurement of clinical and exposure biomarkers. A total of 21,746 participants were finally included in CNHBM, accounting for 99.4% of the designed sample size; and 152 PSUs questionnaires, 454 community questionnaires, 21,619 family questionnaires, 21,712 cases of medical examinations, 21,700 individual questionnaires, 21,701 blood samples and 21,704 urine samples were collected, respectively. Planned analyses of blood and urine samples were to measure both inorganic and organic chemicals, including 13 heavy metals and metalloids, 18 poly- and per-fluorinated alkyl substances, 12 phthalate metabolites, 9 polycyclic aromatic hydrocarbons metabolites, 4 environmental alkylated phenols, and 2 benzene metabolites.

CONCLUSIONS

CNHBM established the first nationally representative, prospective cohort in the Chinese population to understand the baseline and trend of internal exposure of environmental chemicals in general population, and to understand environmental toxicity.

A Phased Approach for preparation and organization of human biomonitoring studies

BACKGROUND

Human biomonitoring (HBM) studies like other epidemiological studies are costly and time-consuming. They require the administration of questionnaires and collection of biological samples, putting substantial burden on the participants which may result in low participation rates. The growing importance of HBM studies in epidemiology, exposure assessment and risk assessment underline the importance of optimizing study planning, designing and implementation thus minimizing the above-mentioned difficulties.

METHODS

Based on frameworks from survey design and fieldwork preparation of the European Joint Program HBM4EU, the German Environment Surveys and the COPHES/DEMOCOPHES twin projects combined with elements of project management strategies, a Phased Approach has been developed, introducing a step-by-step guideline for the development of epidemiological studies.

RESULTS

The Phased Approach splits the process of developing a study into six phases: Phase 0 (Scoping and Planning): All aspects that are necessary to conduct a study are compiled and put on the agenda for decision-making. Phase 1 (Preparation and Testing): Instruments (e.g. questionnaires), materials (e.g. guidelines, information), and ethics and data management issues, needing thorough preparation and testing before a study can start. Phase 2 (Initiation): Organization and acquisition of necessary equipment and engaging and training personnel. Phase 3 (Implementation): All procedures that require temporal proximity to the start date of fieldwork, such as obtaining contact information of invitees. Phase 4 (Fieldwork and Analysis): Involvement of participants and chemical analysis of the collected samples. Phase 5 (Results and Evaluation): Final procedures leading to closure of the project, such as providing and communicating results.

CONCLUSIONS

The separation of the planning and conduct of human biomonitoring studies into different phases creates the basis for a structured procedure and facilitates a step-by-step approach reducing costs, warranting high participation rates and increasing quality of conduct. Emphasis is put on a comprehensive scoping phase ensuring high quality of the study design, which is indispensable for reliable results.

Is It Realistic to Propose Determination of a Lifetime Internal Exposome?

Biomonitoring of xenobiotics has been performed for many years in occupational and environmental medicine. It has revealed hidden exposures and the exposure of workers could be reduced. Although most of the toxic effects of chemicals on humans were discovered in workers, the scientific community has more recently focused on environmental samples. In several countries, urinary and blood samples have been collected and analyzed for xenobiotics. Health, biochemical, and clinical parameters were measured in the biomonitoring program of the Unites States. The data were collected and evaluated as group values, comparing races, ages, and gender. The term exposome was created in order to relate chemical exposure to health effects together with the terms genome, proteome, and transcriptome. Internal exposures were mostly established with snapshot measurements, which can lead to an obvious misclassification of the individual exposures. Albumin and hemoglobin adducts of xenobiotics reflect the exposure of a larger time frame, up to 120 days. It is likely that only a small fraction of xenobiotics form such adducts. In addition, adduct analyses are more work intensive than the measurement of xenobiotics and metabolites in urine and/or blood. New technology, such as high-resolution mass spectrometry, will enable the discovery of new compounds that have been overlooked in the past, since over 300,000 chemicals are commercially available and most likely also present in the environment. Yet, quantification will be challenging, as it was for the older methods. At this stage, determination of a lifetime internal exposome is very unrealistic. Instead of an experimental approach with a large number of people, which is economically and scientifically not feasible, in silico methods should be developed further to predict exposure, toxicity, and potential health effects of mixtures. The computer models will help to focus internal exposure investigations on smaller groups of people and smaller number of chemicals.

Enhancing life cycle chemical exposure assessment through ontology modeling

In its 2014 report, A Framework Guide for the Selection of Chemical Alternatives, the National Academy of Sciences placed increased emphasis on comparative exposure assessment throughout the life cycle (i.e., from manufacturing to end-of-life) of a chemical. The inclusion of the full life cycle greatly increases the data demands for exposure assessments, including both the quantity and type of data. High throughput tools for exposure estimation add to this challenge by requiring rapid accessibility to data. In this work, ontology modeling was used to bridge the domains of exposure modeling and life cycle inventory modeling to facilitate data sharing and integration. The exposure ontology, ExO, is extended to describe human exposure to consumer products, while an inventory modeling ontology, LciO, is formulated to support automated data mining. The core ontology pieces are connected using a bridging ontology and discussed through a theoretical example to demonstrate how data from LCA can be leveraged to support rapid exposure modeling within a life cycle context.

Multiple metal concentrations and gestational diabetes mellitus in Taiyuan, China

BACKGROUND

The association between multiple metal concentrations and gestational diabetes mellitus (GDM) is poorly understood.

METHODS

A total of 776 women with GDM and an equal number of controls were included in the study. Concentrations of metals in participants' blood (nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), thallium (Tl), mercury (Hg), lead (Pb)) were measured using inductively coupled plasma-mass. We used unconditional logistical regression models to estimate the associations between metals and GDM. We also employed weighted quantile sum (WQS) regression and principal components analysis (PCA) to examine metal mixtures in relation to GDM.

RESULTS

An increased risk of GDM was associated with As (OR = 1.49, 95% CI: 1.11, 2.01 for the 2nd tertile vs. the 1st tertile) and Hg (OR = 1.43, 95% CI: 1.09, 1.88 for the 3rd tertile vs. the 1st tertile). In WQS analysis, the WQS index was significantly associated with GDM (OR = 1.20, 95% CI: 1.02, 1.41). The major contributor to the metal mixture index was Hg (69.2%), followed by Pb (12.8%), and As (11.3%). Based on PCA, the second principal component, which was characterized by Hg, Ni, and Pb, was associated with an increased risk of GDM (OR = 1.46, 95% CI: 1.02, 2.08 for the highest quartile vs. the lowest quartile).

CONCLUSIONS

Our study results suggest that high metal levels are associated with an increased risk of GDM, and this increased risk is mainly driven by Hg and, to a lesser extent, by Ni, Pb, and As.

A comparative assessment of dilution correction methods for spot urinary analyte concentrations in a UK population exposed to arsenic in drinking water

Spot urinary concentrations of environmental exposure biomarkers require correction for dilution. There is no consensus on the most appropriate method, with creatinine used by default despite lacking theoretical robustness. We comparatively assessed the efficacy of creatinine; specific gravity (SG); osmolality and modifications of all three for dilution correcting urinary arsenic. For 202 participants with urinary arsenic, creatinine, osmolality and SG measurements paired to drinking water As, we compared the performance corrections against two independent criteria: primarily, (A) correlations of corrected urinary As and the dilution measurements used to correct them - weak correlations indicating good performance and (B) correlations of corrected urinary As and drinking water As - strong correlations indicating good performance. More than a third of variation in spot urinary As concentrations was attributable to dilution. Conventional SG and osmolality correction removed significant dilution variation from As concentrations, whereas conventional creatinine over-corrected, and modifications of all three removed measurable dilution variation. Modified creatinine and both methods of SG and osmolality generated stronger correlations of urinary and drinking water As concentrations than conventional creatinine, which gave weaker correlations than uncorrected values. A disparity in optima between performance criteria was observed, with much smaller improvements possible for Criterion B relative to A. Conventional corrections - particularly creatinine - limit the utility spot urine samples, whereas a modified technique outlined here may allow substantial improvement and can be readily retrospectively applied to existing datasets. More studies are needed to optimize urinary dilution correction methods. Covariates of urinary dilution measurements still warrant consideration.

Generating the Blood Exposome Database Using a Comprehensive Text Mining and Database Fusion Approach

BACKGROUND

Blood chemicals are routinely measured in clinical or preclinical research studies to diagnose diseases, assess risks in epidemiological research, or use metabolomic phenotyping in response to treatments. A vast volume of blood-related literature is available via the PubMed database for data mining.

OBJECTIVES

We aimed to generate a comprehensive blood exposome database of endogenous and exogenous chemicals associated with the mammalian circulating system through text mining and database fusion.

METHODS

Using NCBI resources, we retrieved PubMed abstracts, PubChem chemical synonyms, and PMC supplementary tables. We then employed text mining and PubChem crowdsourcing to associate phrases relating to blood with PubChem chemicals. False positives were removed by a phrase pattern and a compound exclusion list.

RESULTS

A query to identify blood-related publications in the PubMed database yielded 1.1 million papers. Matching a total of 15 million synonyms from 6.5 million relevant PubChem chemicals against all blood-related publications yielded 37,514 chemicals and 851,999 publications records. Mapping PubChem compound identifiers to the PubMed database yielded 49,940 unique chemicals linked to 676,643 papers. Analysis of open-access metabolomics papers related to blood phrases in the PMC database yielded 4,039 unique compounds and 204 papers. Consolidating these three approaches summed up to a total of 41,474 achiral structures that were linked to 65,957 PubChem CIDs and to over 878,966 PubMed articles. We mapped these compounds to 50 databases such as those covering metabolites and pathways, governmental and toxicological databases, pharmacology resources, and bioassay repositories. In comparison, HMDB, the Human Metabolome Database, links 1,075 compounds to blood-related primary publications.

CONCLUSION

This new Blood Exposome Database can be used for prioritizing chemicals for systematic reviews, developing target assays in exposome research, identifying compounds in untargeted mass spectrometry, and biological interpretation in metabolomics data. The database is available at http://bloodexposome.org. https://doi.org/10.1289/EHP4713.

New Approach Methodologies for Exposure Science

Chemical risk assessment relies on knowledge of hazard, the dose-response relationship, and exposure to characterize potential risks to public health and the environment. A chemical with minimal toxicity might pose a risk if exposures are extensive, repeated, and/or occurring during critical windows across the human life span. Exposure assessment involves understanding human activity, and this activity is confounded by interindividual variability that is both biological and behavioral. Exposures further vary between the general population and susceptible or occupationally exposed populations. Recent computational exposure efforts have tackled these problems through the creation of new tools and predictive models. These tools include machine learning to draw inferences from existing data and computer-enhanced screening analyses to generate new data. Mathematical models provide frameworks describing chemical exposure processes. These models can be statistically evaluated to establish rigorous confidence in their predictions. The computational exposure tools reviewed here are oriented toward 'high-throughput' application, that is, they are suitable for dealing with the thousands of chemicals in commerce with limited sources of chemical exposure information. These new tools and models are moving chemical exposure and risk assessment forward in the 21st century.

Overview of known plastic packaging-associated chemicals and their hazards

Global plastics production has reached 380 million metric tons in 2015, with around 40% used for packaging. Plastic packaging is diverse and made of multiple polymers and numerous additives, along with other components, such as adhesives or coatings. Further, packaging can contain residues from substances used during manufacturing, such as solvents, along with non-intentionally added substances (NIAS), such as impurities, oligomers, or degradation products. To characterize risks from chemicals potentially released during manufacturing, use, disposal, and/or recycling of packaging, comprehensive information on all chemicals involved is needed. Here, we present a database of Chemicals associated with Plastic Packaging (CPPdb), which includes chemicals used during manufacturing and/or present in final packaging articles. The CPPdb lists 906 chemicals likely associated with plastic packaging and 3377 substances that are possibly associated. Of the 906 chemicals likely associated with plastic packaging, 63 rank highest for human health hazards and 68 for environmental hazards according to the harmonized hazard classifications assigned by the European Chemicals Agency within the Classification, Labeling and Packaging (CLP) regulation implementing the United Nations' Globally Harmonized System (GHS). Further, 7 of the 906 substances are classified in the European Union as persistent, bioaccumulative, and toxic (PBT), or very persistent, very bioaccumulative (vPvB), and 15 as endocrine disrupting chemicals (EDC). Thirty-four of the 906 chemicals are also recognized as EDC or potential EDC in the recent EDC report by the United Nations Environment Programme. The identified hazardous chemicals are used in plastics as monomers, intermediates, solvents, surfactants, plasticizers, stabilizers, biocides, flame retardants, accelerators, and colorants, among other functions. Our work was challenged by a lack of transparency and incompleteness of publicly available information on both the use and toxicity of numerous substances. The most hazardous chemicals identified here should be assessed in detail as potential candidates for substitution.

Using prepared mixtures of ToxCast chemicals to evaluate non-targeted analysis (NTA) method performance

Non-targeted analysis (NTA) methods are increasingly used to discover contaminants of emerging concern (CECs), but the extent to which these methods can support exposure and health studies remains to be determined. EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) was launched in 2016 to address this need. As part of ENTACT, 1269 unique substances from EPA's ToxCast library were combined to make ten synthetic mixtures, with each mixture containing between 95 and 365 substances. As a participant in the trial, we first performed blinded NTA on each mixture using liquid chromatography (LC) coupled with high-resolution mass spectrometry (HRMS). We then performed an unblinded evaluation to identify limitations of our NTA method. Overall, at least 60% of spiked substances could be observed using selected methods. Discounting spiked isomers, true positive rates from the blinded and unblinded analyses reached a maximum of 46% and 65%, respectively. An overall reproducibility rate of 75% was observed for substances spiked into more than one mixture and observed at least once. Considerable discordance in substance identification was observed when comparing a subset of our results derived from two separate reversed-phase chromatography methods. We conclude that a single NTA method, even when optimized, can likely characterize only a subset of ToxCast substances (and, by extension, other CECs). Rigorous quality control and self-evaluation practices should be required of labs generating NTA data to support exposure and health studies. Accurate and transparent communication of performance results will best enable meaningful interpretations and defensible use of NTA data. Graphical abstract ᅟ.

Epidemiology: a foundation of environmental decision making

Many epidemiologic studies are designed so they can be drawn upon to provide scientific evidence for evaluating hazards of environmental exposures, conducting quantitative assessments of risk, and informing decisions designed to reduce or eliminate harmful exposures. However, experimental animal studies are often relied upon for environmental and public health policy making despite the expanding body of observational epidemiologic studies that could inform the relationship between actual, as opposed to controlled, exposures and health effects. This paper provides historical examples of how epidemiology has informed decisions at the U.S. Environmental Protection Agency, discusses some challenges with using epidemiology to inform decision making, and highlights advances in the field that may help address these challenges and further the use of epidemiologic studies moving forward.

Leveraging the Canadian Health Measures Survey for environmental health research

Since 2007, the nationally representative, cross-sectional Canadian Health Measures Survey (CHMS) has collected detailed health and exposure data from more than 25,000 Canadians, including a wide range of chemical biomarkers analyzed in blood, urine, and environmental media. This article highlights the extent to which the CHMS dataset has been used in the peer-reviewed environmental health literature and opportunities for further expanding usage of the dataset. A literature search (2007-2018) was performed to identify peer-reviewed studies that have made substantive use of the CHMS dataset. Studies were analyzed according to the study type, data usage, populations studied, environmental health themes, citation/publication data, and institutional collaborations. A total of 51 environmental-health related CHMS studies were identified, including studies related to indoor and outdoor air quality, the built environment, and chemical and environmental tobacco smoke exposures. Health indicator data are being increasingly exploited, as is the ability to combine cycle datasets over time. Although these studies covered a range of environmental exposures, many CHMS variables remain underutilized. The CHMS dataset provides a valuable portrait of chemical exposures in Canadians of all ages, linked to a wide variety of health indicators. Many opportunities remain to exploit and expand both the use of the dataset and collaborations between Canadian agencies and domestic and international research institutions.

Assessing Cancer Risk Associated with Aquatic Polycyclic Aromatic Hydrocarbon Pollution Reveals Dietary Routes of Exposure and Vulnerable Populations

Polycyclic aromatic hydrocarbon (PAH) exposure is widespread, and many PAHs are considered carcinogenic. The PAH-contaminated AWI Superfund site in Virginia provides a model for studying a complex PAH mixture and its extrapolation to cancer risk and PAH exposure in the general population. We examined cancer risk at the Superfund site due to sediment-derived PAHs and then evaluated PAH sources in the general population and potentially vulnerable subpopulations upon PAH mixture exposure. The PAH mixture was assessed for potential carcinogenicity using the US EPA's OncoLogic™ ranking tool and the US EPA list of priority PAHs. Cancer risk due to PAH exposure was calculated for Superfund site users and compared to the US EPA assessment. Human intake and health endpoints of PAHs within the mixture were extracted from USEtox® chemical fate database, while mean intake exposure was calculated for U.S. adults for select PAHs using NHANES database urinary biomarkers. Eleven PAH compounds within the mixture were of carcinogenic concern, and seven PAHs conveyed significant excess cancer risk at the Superfund site and in the general population, wherein PAH-contaminated seafood ingestion was a main contributor. Other dietary sources of PAHs derived from PAH-contaminated soil or water could also play a role in total exposure. Vulnerable populations to PAH exposure and coinciding increased cancer risk may include, in addition to smokers, children and non-Hispanic blacks, which is a public health concern.

Exposure to Bisphenol A, Bisphenol F, and Bisphenol S in U.S. Adults and Children: The National Health and Nutrition Examination Survey 2013-2014

Bisphenol F (BPF) and bisphenol S (BPS) are replacing bisphenol A (BPA) in the manufacturing of products containing polycarbonates and epoxy resins. Data on current human exposure levels of these substitutes are needed to aid in the assessment of their human health risks. This study analyzed urinary bisphenol levels in adults (N = 1808) and children (N = 868) participating in the National Health and Nutrition Examination Survey (NHANES) 2013-2014 and investigated demographic and lifestyle factors associated with urinary levels of bisphenols. BPA, BPS, and BPF were detected in 95.7, 89.4, and 66.5% of randomly selected urine samples analyzed as part of NHANES 2013-2014, respectively. Median levels of BPA in U.S. adult were higher (1.24 μg/L) than BPF and BPS levels (0.35 and 0.37 μg/L, respectively). For children, median BPA levels were also higher (1.25 μg/L) than BPF and BPS levels (0.32 and 0.29 μg/L, respectively). The limits of detection for BPA, BPF, and BPS were 0.2, 0.2, and 0.1 μg/L, respectively. Urinary levels showed associations with gender, race/ethnicity, family income, physical activity, smoking, and/or alcohol intake that depended on the specific bisphenol. The results of this study indicate that exposure of the general U.S. population to BPA substitutes is almost ubiquitous. Because exposures differ across the U.S. population, further studies of environmental, consumer, and lifestyle factors affecting BPF and BPS exposures are warranted.

Diagnosis, monitoring and prevention of exposure-related non-communicable diseases in the living and working environment: DiMoPEx-project is designed to determine the impacts of environmental exposure on human health

The WHO has ranked environmental hazardous exposures in the living and working environment among the top risk factors for chronic disease mortality. Worldwide, about 40 million people die each year from noncommunicable diseases (NCDs) including cancer, diabetes, and chronic cardiovascular, neurological and lung diseases. The exposure to ambient pollution in the living and working environment is exacerbated by individual susceptibilities and lifestyle-driven factors to produce complex and complicated NCD etiologies. Research addressing the links between environmental exposure and disease prevalence is key for prevention of the pandemic increase in NCD morbidity and mortality. However, the long latency, the chronic course of some diseases and the necessity to address cumulative exposures over very long periods does mean that it is often difficult to identify causal environmental exposures. EU-funded COST Action DiMoPEx is developing new concepts for a better understanding of health-environment (including gene-environment) interactions in the etiology of NCDs. The overarching idea is to teach and train scientists and physicians to learn how to include efficient and valid exposure assessments in their research and in their clinical practice in current and future cooperative projects. DiMoPEx partners have identified some of the emerging research needs, which include the lack of evidence-based exposure data and the need for human-equivalent animal models mirroring human lifespan and low-dose cumulative exposures. Utilizing an interdisciplinary approach incorporating seven working groups, DiMoPEx will focus on aspects of air pollution with particulate matter including dust and fibers and on exposure to low doses of solvents and sensitizing agents. Biomarkers of early exposure and their associated effects as indicators of disease-derived information will be tested and standardized within individual projects. Risks arising from some NCDs, like pneumoconioses, cancers and allergies, are predictable and preventable. Consequently, preventative action could lead to decreasing disease morbidity and mortality for many of the NCDs that are of major public concern. DiMoPEx plans to catalyze and stimulate interaction of scientists with policy-makers in attacking these exposure-related diseases.

Human biomarker interpretation: the importance of intra-class correlation coefficients (ICC) and their calculations based on mixed models, ANOVA, and variance estimates

Human biomonitoring is the foundation of environmental toxicology, community public health evaluation, preclinical health effects assessments, pharmacological drug development and testing, and medical diagnostics. Within this framework, the intra-class correlation coefficient (ICC) serves as an important tool for gaining insight into human variability and responses and for developing risk-based assessments in the face of sparse or highly complex measurement data. The analytical procedures that provide data for clinical and public health efforts are continually evolving to expand our knowledge base of the many thousands of environmental and biomarker chemicals that define human systems biology. These chemicals range from the smallest molecules from energy metabolism (i.e., the metabolome), through larger molecules including enzymes, proteins, RNA, DNA, and adducts. In additiona, the human body contains exogenous environmental chemicals and contributions from the microbiome from gastrointestinal, pulmonary, urogenital, naso-pharyngeal, and skin sources. This complex mixture of biomarker chemicals from environmental, human, and microbiotic sources comprise the human exposome and generally accessed through sampling of blood, breath, and urine. One of the most difficult problems in biomarker assessment is assigning probative value to any given set of measurements as there are generally insufficient data to distinguish among sources of chemicals such as environmental, microbiotic, or human metabolism and also deciding which measurements are remarkable from those that are within normal human variability. The implementation of longitudinal (repeat) measurement strategies has provided new statistical approaches for interpreting such complexities, and use of descriptive statistics based upon intra-class correlation coefficients (ICC) has become a powerful tool in these efforts. This review has two parts; the first focuses on the history of repeat measures of human biomarkers starting with occupational toxicology of the early 1950s through modern applications in interpretation of the human exposome and metabolic adverse outcome pathways (AOPs). The second part reviews different methods for calculating the ICC and explores the strategies and applications in light of different data structures.

Estimating Methylmercury Intake for the General Population of South Korea Using Physiologically Based Pharmacokinetic Modeling

The Korean National Environmental Health Survey (KoNEHS 2009-2011) tracks levels of environmental pollutants in biological samples from the adult Korean population (age 19-88). Recent survey results for blood mercury (Hg) suggest some exceedance above existing blood Hg reference levels. Because total blood Hg represents both organic and inorganic forms, and methylmercury (MeHg) has been specifically linked to several adverse health outcomes, a need exists to quantify MeHg intake for this population. Gender, age, and frequency of fish consumption were first identified as important predictors of KoNEHS blood Hg levels using generalized linear models. Stratified distributions of total blood Hg were then used to estimate distributions of blood MeHg using fractions of MeHg to total Hg from the literature. Next, a published physiologically based pharmacokinetic (PBPK) model was used to predict distributions of blood MeHg as a function of MeHg intake; ratios of MeHg intake to model-predicted blood MeHg were then combined with KoNEHS-based blood MeHg values to produce MeHg intake estimates. These intake estimates were ultimately compared with the Reference Dose (RfD) for MeHg (0.1 µg/kg/day) and reported as margin of exposure (MOE) estimates for specific KoNEHS subgroups. The derived MOEs across all subgroups, based on estimated geometric mean intake, ranged from 1.6 to 4.1. These results suggest MeHg exposures approaching the RfD for several subgroups of the Korean population, and not just for specific subgroups (eg, those who eat fish very frequently).

A Method for Identifying Prevalent Chemical Combinations in the U.S. Population

BACKGROUND

Through the food and water they ingest, the air they breathe, and the consumer products with which they interact at home and at work, humans are exposed to tens of thousands of chemicals, many of which have not been evaluated to determine their potential toxicities. Furthermore, while current chemical testing tends to focus on individual chemicals, the exposures that people actually experience involve mixtures of chemicals. Unfortunately, the number of mixtures that can be formed from the thousands of environmental chemicals is enormous, and testing all of them would be impossible.

OBJECTIVES

We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans.

METHODS

We applied frequent itemset mining, a technique traditionally used for market basket analysis, to biomonitoring data from the 2009-2010 cycle of the continuous National Health and Nutrition Examination Survey (NHANES) to identify combinations of chemicals that frequently co-occur in people.

RESULTS

We identified 90 chemical combinations consisting of relatively few chemicals that occur in at least 30% of the U.S. population, as well as three supercombinations consisting of relatively many chemicals that occur in a small but nonnegligible proportion of the U.S. population.

CONCLUSIONS

We demonstrated how FIM can be used in conjunction with biomonitoring data to narrow a large number of possible chemical combinations down to a smaller set of prevalent chemical combinations. https://doi.org/10.1289/EHP1265.