Estimating lifetime risk from spot biomarker data and intraclass correlation coefficients (ICC)

Biomonitoring Equivalents for ethylene thiourea

Ethylene thiourea, or ETU, is used in the rubber industry and is a degradation product and impurity in some fungicides. The general public may be exposed to low concentrations of residues of ETU in a variety of ways, including food treated with ethylene bis-dithiocarbamate (EBDC) fungicides or migration from rubber products. Biomonitoring of ETU in urine is useful for an assessment of integrated exposures to ETU across different sources and routes of exposure. In this evaluation, we review available health-based risk assessments and toxicological reference values (TRVs) for ETU and derive Biomonitoring Equivalent (BE) values for interpretation of population biomonitoring data. BEs were derived based on existing TRVs derived by Health Canada, yielding a BE of 27 μg of total ETU/L in urine associated with the Acceptable Daily Intake (ADI) and 6.7 μg/L associated with a 1e-6 cancer risk. These BEs are based on an analytical method that involves a digestion step to liberate conjugated ETU, thus producing 'total' ETU in urine. The BE values derived in this manuscript can serve as a guide to help public health officials and regulators interpret population based ETU biomonitoring data in a public health risk context.

A Comparison of In Vitro Points of Departure with Human Blood Levels for Per- and Polyfluoroalkyl Substances (PFAS)

Per- and polyfluoroalkyl substances (PFAS) are widely used, and their fluorinated state contributes to unique uses and stability but also long half-lives in the environment and humans. PFAS have been shown to be toxic, leading to immunosuppression, cancer, and other adverse health outcomes. Only a small fraction of the PFAS in commerce have been evaluated for toxicity using in vivo tests, which leads to a need to prioritize which compounds to examine further. Here, we demonstrate a prioritization approach that combines human biomonitoring data (blood concentrations) with bioactivity data (concentrations at which bioactivity is observed in vitro) for 31 PFAS. The in vitro data are taken from a battery of cell-based assays, mostly run on human cells. The result is a Bioactive Concentration to Blood Concentration Ratio (BCBCR), similar to a margin of exposure (MoE). Chemicals with low BCBCR values could then be prioritized for further risk assessment. Using this method, two of the PFAS, PFOA (Perfluorooctanoic Acid) and PFOS (Perfluorooctane Sulfonic Acid), have BCBCR values < 1 for some populations. An additional 9 PFAS have BCBCR values < 100 for some populations. This study shows a promising approach to screening level risk assessments of compounds such as PFAS that are long-lived in humans and other species.

Biomonitoring Equivalents for glyphosate

One of the most widely used herbicides worldwide, glyphosate is registered for use in many agricultural and non-agricultural settings. Accordingly, regulatory authorities develop toxicology reference values (TRVs) to conduct risk assessments for potential exposures. Exposures to glyphosate are typically biomonitored via measures of glyphosate in urine. However, measured concentrations of glyphosate in urine, with units mg/L urine, cannot be directly interpreted using the available TRVs as they are presented in terms of daily intake levels (e.g. mg/kg-bw per day). In this evaluation, we review available health-based risk assessments and TRVs for glyphosate and derive Biomonitoring Equivalent (BE) values for interpretation of population biomonitoring data. Biomonitoring Equivalents (BEs) are defined as the concentration or range of concentrations of a chemical or its metabolite in a biological medium (blood, urine, human milk, etc.) that is consistent with an existing health-based TRVs such as a reference dose (RfD) or tolerable daily intake (TDI). The BE values derived in this manuscript are screening values that can help public health officials and regulators interpret glyphosate biomonitoring data.

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.

Reviewing the variability in urinary concentrations of non-persistent organic chemicals: evaluation across classes, sampling strategies and dilution corrections

Various biomonitoring studies have been carried out to investigate the exposure of populations by measuring non-persistent organic chemicals in urine. To accurately assess the exposure, study designs should be carefully developed to maximise reproducibility and achieve good characterization of the temporal variability. To test these parameters, the intraclass correlation coefficients (ICCs) are calculated from repeated measurements and range from poor (<0.4) to excellent (≥0.75). Several studies have reported ICCs based on diverse study designs, but an overview, including recommendations for future studies, was lacking. Therefore, this review aimed to collect studies describing ICCs of non-persistent organic chemicals, discuss variations due to study design and formulate recommendations for future studies. More than 60 studies were selected, considering various chemical classes: bisphenols, pyrethroids, parabens, phthalates, alternative plasticizers and phosphate flame retardants. The variation in ICCs for an individual chemical was high (e.g. ICC of propyl paraben = 0.28-0.91), showing the large impact of the study design and of the specific exposure sources. The highest ICCs were reported for parabens (median = 0.52), while lowest ICCs were for 3-phenoxybenzoic acid (median = 0.08) and bisphenol A (median = 0.20). Overall, chemicals that had an exposure source with high variation, such as the diet, showed lower ICCs than those with more stable exposure sources, such as indoor materials. Urine correction by specific gravity had an overall positive effect on reducing the variability of ICCs. However, this effect was mostly seen in the adult population, while specific compounds showed less variation with creatinine correction. Single samples might not accurately capture the exposure to most non-persistent organic chemicals, especially when small populations are sampled. Future studies that examine compounds with low ICCs should take adequate measures to improve accuracy, such as correcting dilution with specific gravity or collecting multiple samples for one participant.

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.

Reproducibility of the Blood and Urine Exposome: A Systematic Literature Review and Meta-Analysis

Endogenous and exogenous metabolite concentrations may be susceptible to variation over time. This variability can lead to misclassification of exposure levels and in turn to biased results. To assess the reproducibility of metabolites, the intraclass correlation coefficient (ICC) is computed. A literature search in three databases from 2000 to May 2021 was conducted to identify studies reporting ICCs for blood and urine metabolites. This review includes 192 studies, of which 31 studies are included in the meta-analyses. The ICCs of 359 single metabolites are reported, and the ICCs of 10 metabolites were meta-analyzed. The reproducibility of the single metabolites ranges from poor to excellent and is highly compound-dependent. The reproducibility of bisphenol A (BPA), mono-ethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-2-ethylhexyl phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-benzyl phthalate (MBzP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), methylparaben, and propylparaben is poor to moderate (ICC median: 0.32; range: 0.15-0.49), and for 25-hydroxyvitamin D [25(OH)D], it is excellent (ICC: 0.95; 95% CI, 0.90-0.99). Pharmacokinetics, mainly the half-life of elimination and exposure patterns, can explain reproducibility. This review describes the reproducibility of the blood and urine exposome, provides a vast dataset of ICC estimates, and hence constitutes a valuable resource for future reproducibility and clinical epidemiologic studies.

Quo vadis blood protein adductomics?

Chemicals are measured regularly in air, food, the environment, and the workplace. Biomonitoring of chemicals in biological fluids is a tool to determine the individual exposure. Blood protein adducts of xenobiotics are a marker of both exposure and the biologically effective dose. Urinary metabolites and blood metabolites are short term exposure markers. Stable hemoglobin adducts are exposure markers of up to 120 days. Blood protein adducts are formed with many xenobiotics at different sites of the blood proteins. Newer methods apply the techniques developed in the field of proteomics. Larger adducted peptides with 20 amino acids are used for quantitation. Unfortunately, at present the methods do not reach the limits of detection obtained with the methods looking at single amino acid adducts or at chemically cleaved adducts. Therefore, to progress in the field new approaches are needed.

The quality assessment of intraabdominal infection guidelines/consensuses in 2 decades - which are better and any changes?

BACKGROUND AND AIM

Intraabdominal infection (IAI) is a common and important disease worldwide. An increasing number of related guidelines/consensuses have been published in recent years, the quality evaluation for these guidelines/consensuses is necessary to identify lower-quality documents and explore the quality distribution in different time range and areas in this field.

METHODS

The Appraisal of Guidelines for Research & Evaluation Instrument tool was adopted to assess the quality of IAI guidelines/consensuses by 3 researchers independently. Intraclass correlation coefficients (ICCs) among the researchers were retrieved to reflect reliability. The quality differences of these guidelines/consensuses issued before and after May 2009, both international and non-international, were compared by a Mann-Whitney U test.

RESULTS

Fourteen IAI guidelines/consensuses published in English were obtained following a literature search. The ICCs among the researchers were all above 0.75, indicating satisfactory reliability. This outcome showed that the overall quality of these guidelines/consensuses was mediocre and considered acceptable in all items. A few guidelines/consensuses were better in their scientific and methodological characteristics than the others. Moreover, there were no significant differences in the scores between the guidelines/consensuses issued before and after May 2009 or between international vs regional guidelines/consensuses.

CONCLUSIONS

Overall, the quality of the IAI guidelines/consensuses was generally acceptable and applicable, with a few deficiencies. Therefore, continuous improvement is essential. The guideline assessment tools should be applied in guideline/consensus development both widely and strictly to improve the methodological quality.

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.

Variations of phthalate exposure and metabolism over three trimesters

Maternal exposure to phthalates may cause some adverse health effects on both mother and fetus, but variations of phthalate exposure and metabolism during pregnancy have not been thoroughly characterized. A total of 946 participants were selected from a cohort study conducted in Wuhan between 2014 and 2015 through which they had provided a complete set of urine samples at three trimesters. Eight phthalate metabolites were analyzed in 2838 urine samples. Based on urinary concentrations, various parameters (i.e. phthalate metabolite concentrations, ratios of metabolites of bis(2-ethylhexyl) phthalate (DEHP) in DEHP, and percentages of individual metabolites in total phthalates) were compared over three visits. We observed that levels of phthalate metabolites showed a U-shaped trend across three trimesters. The significant variations in the ratios of DEHP metabolites indicated that the efficiency in metabolizing DEHP declined during pregnancy and less recent exposure occurred in mid-pregnancy. The changes of percentages of individual compound in total phthalates suggested the inconsistent pattern over trimesters. This longitudinal study found that the exposure pattern, exposure timing and metabolic susceptibility varied by trimesters, which suggests that urine samples should be collected at multiple time points and mothers should be especially careful in the early pregnancy.

Detection and analysis of endogenous polar volatile organic compounds (PVOCs) in urine for human exposome research

Background: The human exposome, defined as '…everything that is not the genome', comprises all chemicals in the body interacting with life processes. The exposome drives genes x environment (GxE) interactions that can cause long-term latency and chronic diseases. The exposome constantly changes in response to external exposures and internal metabolism. Different types of compounds are found in different biological media. Objective: Measure polar volatile organic compounds (PVOCs) excreted in urine to document endogenous metabolites and exogenous compounds from environmental exposures. Methods: Use headspace collection and sorbent tube thermal desorption coupled with bench-top gas chromatography-mass spectrometry (GC-MS) for targeted and non-targeted approaches. Identify and categorize PVOCs that may distinguish among healthy and affected individuals. Results: Method is successfully demonstrated to tabulate a series of 28 PVOCs detected in human urine across 120 samples from 28 human subjects. Median concentrations range from below detect to 165 ng/mL. Certain PVOCs have potential health implications. Conclusions: Headspace collection with sorbent tubes is an effective method for documenting PVOCs in urine that are otherwise difficult to measure. This methodology can provide probative information regarding biochemical processes and adverse outcome pathways (AOPs) for toxicity testing.

Variability of urinary concentrations of non-persistent chemicals in pregnant women and school-aged children

BACKGROUND

Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions.

OBJECTIVES

We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children.

METHODS

154 pregnant women and 152 children from six European countries were enrolled in 2014-2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80.

RESULTS

All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40-0.59) to good (0.60-0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15-20 urines each would be necessary to obtain an ICC above 0.80.

CONCLUSIONS

This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months.

Biomarkers of exposure in environment-wide association studies - Opportunities to decode the exposome using human biomonitoring data

BACKGROUND

The European Union's 7th Framework Programme (EU's FP7) project HEALS - Health and Environment-wide Associations based on Large Population Surveys - aims a refinement of the methodology to elucidate the human exposome. Human biomonitoring (HBM) provides a valuable tool for understanding the magnitude of human exposure from all pathways and sources. However, availability of specific biomarkers of exposure (BoE) is limited.

OBJECTIVES

The objective was to summarize the availability of BoEs for a broad range of environmental stressors and exposure determinants and corresponding reference and exposure limit values and biomonitoring equivalents useful for unraveling the exposome using the framework of environment-wide association studies (EWAS).

METHODS

In a face-to-face group discussion, scope, content, and structure of the HEALS deliverable "Guidelines for appropriate BoE selection for EWAS studies" were determined. An expert-driven, distributed, narrative review process involving around 30 individuals of the HEALS consortium made it possible to include extensive information targeted towards the specific characteristics of various environmental stressors and exposure determinants. From the resulting 265 page report, targeted information about BoE, corresponding reference values (e.g., 95th percentile or measures of central tendency), exposure limit values (e.g., the German HBM I and II values) and biomonitoring equivalents (BEs) were summarized and updated.

RESULTS

64 individual biological, chemical, physical, psychological and social environmental stressors or exposure determinants were included to fulfil the requirements of EWAS. The list of available BoEs is extensive with a number of 135; however, 12 of the stressors and exposure determinants considered do not leave any measurable specific substance in accessible body specimens. Opportunities to estimate the internal exposure stressors not (yet) detectable in human specimens were discussed.

CONCLUSIONS

Data about internal exposures are useful to decode the exposome. The paper provides extensive information for EWAS. Information included serves as a guideline - snapshot in time without any claim to comprehensiveness - to interpret HBM data and offers opportunities to collect information about the internal exposure of stressors if no specific BoE is available.

An analysis of cumulative risks based on biomonitoring data for six phthalates using the Maximum Cumulative Ratio

The Maximum Cumulative Ratio (MCR) quantifies the degree to which a single chemical drives the cumulative risk of an individual exposed to multiple chemicals. Phthalates are a class of chemicals with ubiquitous exposures in the general population that have the potential to cause adverse health effects in humans. This work used the MCR to evaluate coexposures to six phthalates as measured in biomonitoring data from the most recent cycle (2013-2014) of the National Health and Nutrition Examination Survey (NHANES). The values of MCR, Hazard Index (HI), and phthalate-specific Hazard Quotients (HQs) were determined for 2663 NHANES participants aged six years and older by using reverse dosimetry techniques to calculate steady-state doses consistent with concentrations of metabolites of six phthalates in urine and using Tolerable Daily Intake values. There were 21 participants (0.8% of the NHANES sample) with HI>1. Of those, 43% (9/21) would have been missed by chemical-by-chemical assessments (i.e. all HQs were less than one). The mean MCR value in the 21 participants was 2.1. HI and MCR values were negatively correlated (p<0.001) indicating that most participants, especially those with elevated HI values, had their cumulative risks driven by relatively large doses of a single phthalate rather than doses of multiple phthalates. The dominate phthalate varied across participants. Children (aged 6-17years) had a higher HI values (p<0.01) than adults (18+ years). However, the probability of having HI>1 was not driven by age, gender, or ethnicity. The cumulative exposures of concern largely originated from a subset of three of the fifteen possible pairs of the six phthalates. These findings suggest that cumulative exposures were a potential concern for a small portion of the surveyed participants involving a subset of the phthalates explored. The largest risks tended to occur in individuals whose exposures were dominated by a single phthalate.

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.

Variation in urinary spot sample, 24 h samples, and longer-term average urinary concentrations of short-lived environmental chemicals: implications for exposure assessment and reverse dosimetry

Population biomonitoring data sets such as the Canadian Health Measures Survey (CHMS) and the United States National Health and Nutrition Examination Survey (NHANES) collect and analyze spot urine samples for analysis for biomarkers of exposure to non-persistent chemicals. Estimation of population intakes using such data sets in a risk-assessment context requires consideration of intra- and inter-individual variability to understand the relationship between variation in the biomarker concentrations and variation in the underlying daily and longer-term intakes. Two intensive data sets with a total of 16 individuals with collection and measurement of serial urine voids over multiple days were used to examine these relationships using methyl paraben, triclosan, bisphenol A (BPA), monoethyl phthalate (MEP), and mono-2-ethylhexyl hydroxyl phthalate (MEHHP) as example compounds. Composited 24 h voids were constructed mathematically from the individual collected voids, and concentrations for each 24 h period and average multiday concentrations were calculated for each individual in the data sets. Geometric mean and 95th percentiles were compared to assess the relationship between distributions in spot sample concentrations and the 24 h and multiday collection averages. In these data sets, spot sample concentrations at the 95th percentile were similar to or slightly higher than the 95th percentile of the distribution of all 24 h composite void concentrations, but tended to overestimate the maximum of the multiday concentration averages for most analytes (usually by less than a factor of 2). These observations can assist in the interpretation of population distributions of spot samples for frequently detected analytes with relatively short elimination half-lives.

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).

Comparison of gaseous polycyclic aromatic hydrocarbon metabolites according to their specificity as biomarkers of occupational exposure: Selection of 2-hydroxyfluorene and 2-hydroxyphenanthrene

Exposure to Polycyclic Aromatic Hydrocarbons (PAHs) occurs by respiratory, digestive and dermal absorption. Biomonitoring takes all pathways into account but sensitive and specific biomarkers are required. Different gaseous PAHs metabolites were used due to their abundance in the atmospheric mixtures but none of them were selected as better biomarker than the others. To identify the best candidates for assessing occupational airborne exposure, relation between atmospheric levels of Naphtalene, Fluorene and Phenanthrene and urinary metabolites concentrations was studied in a carbon electrode workers group. Linear mixed effects models were built to select explanatory variables and estimate variance component. Urinary creatinine was a predictor of metabolites levels confirming the importance of diuresis for interpreting results. High significance of pre-shift sampling time combined with positive coefficients of post-shift indicated that urine should be sampled at the end of the workday in association with pre-shift urine to avoid misinterpretations. Among the 10 metabolites studied, urinary 2-hydroxyfluorene and 2-hydroxyphenanthrene showed the highest increase of variance explained by models after inclusion of individual atmospheric levels as explanatory variable. Priority could be given to 2-hydroxyfluorene due to higher excretion levels than 2-hydroxyphenanthrene.

Estimation of iodine nutrition and thyroid function status in late-gestation pregnant women in the United States: Development and application of a population-based pregnancy model

Previously, a deterministic biologically-based dose-response (BBDR) pregnancy model was developed to evaluate moderate thyroid axis disturbances with and without thyroid-active chemical exposure in a near-term pregnant woman and fetus. In the current study, the existing BBDR model was adapted to include a wider functional range of iodine nutrition, including more severe iodine deficiency conditions, and to incorporate empirically the effects of homeostatic mechanisms. The extended model was further developed into a population-based model and was constructed using a Monte Carlo-based probabilistic framework. In order to characterize total (T4) and free (fT4) thyroxine levels for a given iodine status at the population-level, the distribution of iodine intake for late-gestation pregnant women in the U.S was reconstructed using various reverse dosimetry methods and available biomonitoring data. The range of median (mean) iodine intake values resulting from three different methods of reverse dosimetry tested was 196.5-219.9μg of iodine/day (228.2-392.9μg of iodine/day). There was minimal variation in model-predicted maternal serum T4 and ft4 thyroxine levels from use of the three reconstructed distributions of iodine intake; the range of geometric mean for T4 and fT4, was 138-151.7nmol/L and 7.9-8.7pmol/L, respectively. The average value of the ratio of the 97.5th percentile to the 2.5th percentile equaled 3.1 and agreed well with similar estimates from recent observations in third-trimester pregnant women in the U.S. In addition, the reconstructed distributions of iodine intake allowed us to estimate nutrient inadequacy for late-gestation pregnant women in the U.S. via the probability approach. The prevalence of iodine inadequacy for third-trimester pregnant women in the U.S. was estimated to be between 21% and 44%. Taken together, the current work provides an improved tool for evaluating iodine nutritional status and the corresponding thyroid function status in pregnant women in the U.S. This model enables future assessments of the relevant risk of thyroid hormone level perturbations due to exposure to thyroid-active chemicals at the population-level.

Taxonomic applicability of inflammatory cytokines in adverse outcome pathway (AOP) development

Cytokines, low-molecular-weight messenger proteins that act as intercellular immunomodulatory signals, have become a mainstream preclinical marker for assessing the systemic inflammatory response to external stressors. The challenge is to quantitate from healthy subjects cytokine levels that are below or at baseline and relate those dynamic and complex cytokine signatures of exposures with the inflammatory and repair pathways. Thus, highly sensitive, specific, and precise analytical and statistical methods are critically important. Investigators at the U.S. Environmental Protection Agency (EPA) have implemented advanced technologies and developed statistics for evaluating panels of inflammatory cytokines in human blood, exhaled breath condensate, urine samples, and murine biological media. Advanced multiplex, bead-based, and automated analytical platforms provided sufficient sensitivity, precision, and accuracy over the traditional enzyme-linked immunosorbent assay (ELISA). Thus, baseline cytokine levels can be quantified from healthy human subjects and animals and compared to an in vivo exposure response from an environmental chemical. Specifically, patterns of cytokine responses in humans exposed to environmental levels of ozone and diesel exhaust, and in rodents exposed to selected pesticides (such as fipronil and carbaryl), were used as case studies to generally assess the taxonomic applicability of cytokine responses. The findings in this study may aid in the application of measureable cytokine markers in future adverse outcome pathway (AOP)-based toxicity testing. Data from human and animal studies were coalesced and the possibility of using cytokines as key events (KE) to bridge species responses to external stressors in an AOP-based framework was explored.

Estimating central tendency from a single spot measure: A closed-form solution for lognormally distributed biomarker data for risk assessment at the individual level

Exposure-based risk assessment employs large cross-sectional data sets of environmental and biomarker measurements to predict population statistics for adverse health outcomes. The underlying assumption is that long-term (many years) latency health problems including cancer, autoimmune and cardiovascular disease, diabetes, and asthma are triggered by lifetime exposures to environmental stressors that interact with the genome. The aim of this study was to develop a specific predictive method that provides the statistical parameters for chronic exposure at the individual level based upon a single spot measurement and knowledge of global summary statistics as derived from large data sets. This is a profound shift in exposure and health statistics in that it begins to answer the question "How large is my personal risk?" rather than just providing an overall population-based estimate. This approach also holds value for interpreting exposure-based risks for small groups of individuals within a community in comparison to random individuals from the general population.

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

BACKGROUND

Each year, the U.S. NHANES measures hundreds of chemical biomarkers in samples from thousands of study participants. These biomarker measurements are used to establish population reference ranges, track exposure trends, identify population subsets with elevated exposures, and prioritize research needs. There is now interest in further utilizing the NHANES data to inform chemical risk assessments.

OBJECTIVES

This article highlights a) the extent to which U.S. NHANES chemical biomarker data have been evaluated, b) groups of chemicals that have been studied, c) data analysis approaches and challenges, and d) opportunities for using these data to inform risk assessments.

METHODS

A literature search (1999-2013) was performed to identify publications in which U.S. NHANES data were reported. Manual curation identified only the subset of publications that clearly utilized chemical biomarker data. This subset was evaluated for chemical groupings, data analysis approaches, and overall trends.

RESULTS

A small percentage of the sampled NHANES-related publications reported on chemical biomarkers (8% yearly average). Of 11 chemical groups, metals/metalloids were most frequently evaluated (49%), followed by pesticides (9%) and environmental phenols (7%). Studies of multiple chemical groups were also common (8%). Publications linking chemical biomarkers to health metrics have increased dramatically in recent years. New studies are addressing challenges related to NHANES data interpretation in health risk contexts.

CONCLUSIONS

This article demonstrates growing use of NHANES chemical biomarker data in studies that can impact risk assessments. Best practices for analysis and interpretation must be defined and adopted to allow the full potential of NHANES to be realized.

Variation in urinary flow rates according to demographic characteristics and body mass index in NHANES: potential confounding of associations between health outcomes and urinary biomarker concentrations

BACKGROUND

Urinary analyte concentrations are affected both by exposure level and by urinary flow rate (UFR). Systematic variations in UFR with demographic characteristics or body mass index (BMI) could confound assessment of associations between health outcomes and biomarker concentrations.

OBJECTIVES

We assessed patterns of UFR (milliliters per hour) and body weight-adjusted UFR (UFRBW; milliliters per kilogram per hour) across age, sex, race/ethnicity, and BMI category in the NHANES (National Health and Nutrition Examination Survey) 2009-2012 data sets.

METHODS

Geometric mean (GM) UFR and UFRBW were compared across age-stratified (6-11, 12-19, 20-39, 40-59, and ≥ 60 years) subgroups (sex, race/ethnicity, and BMI category). Patterns of analyte urinary concentration or mass excretion rates (nanograms per hour and nanograms per kilogram per hour BW) were assessed in sample age groups for case study chemicals bisphenol A and 2,5-dichlorophenol.

RESULTS

UFR increased from ages 6 to 60 years and then declined with increasing age. UFRBW varied inversely with age. UFR, but not UFRBW, differed significantly by sex (males > females after age 12 years). Differences in both metrics were observed among categories of race/ethnicity. UFRBW, but not UFR, varied inversely with BMI category and waist circumference in all age groups. Urinary osmolality increased with increasing BMI. Case studies demonstrated different exposure-outcome relationships depending on exposure metric. Conventional hydration status adjustments did not fully address the effect of flow rate variations.

CONCLUSIONS

UFR and UFRBW exhibit systematic variations with age, sex, race/ethnicity, and BMI category. These variations can confound assessments of potential exposure-health outcome associations based on urinary concentration. Analyte excretion rates are valuable exposure metrics in such assessments.

Analysis of inflammatory cytokines in human blood, breath condensate, and urine using a multiplex immunoassay platform

A change in the expression of cytokines in human biological media indicates an inflammatory response to external stressors and reflects an early step along the adverse outcome pathway (AOP) for various health endpoints. To characterize and interpret this inflammatory response, methodology was developed for measuring a suite of 10 different cytokines in human blood, exhaled breath condensate (EBC), and urine using an electrochemiluminescent multiplex Th1/Th2 cytokine immunoassay platform. Measurement distributions and correlations for eight interleukins (IL) (1β, 2, 4, 5, 8, 10, 12p70 and 13), interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α) were evaluated using 90 blood plasma, 77 EBC, and 400 urine samples collected from nominally healthy adults subjects in North Carolina in 2008-2012. The in vivo results show that there is sufficient sensitivity for characterizing all 10 cytokines at levels of 0.05-0.10 ρg/ml with a dynamic range up to 100 ng/ml across all three of these biological media. The measured in vivo results also show that the duplicate analysis of blood, EBC and urine samples have average estimated fold ranges of 2.21, 3.49, and 2.50, respectively, which are similar to the mean estimated fold range (2.88) for the lowest concentration (0.610 ρg/ml) from a series of spiked control samples; the cytokine method can be used for all three biological media. Nine out of the 10 cytokines measured in EBC were highly correlated within one another with Spearman ρ coefficients ranging from 0.679 to 0.852, while the cytokines measured in blood had a mix of negative and positive correlations, ranging from -0.620 to 0.836. Almost all correlations between EBC and blood were positive. This work also represents the first successful within- and between-person evaluation of ultra trace-level inflammatory markers in blood, EBC, and urine.

Changes in epidemiologic associations with different exposure metrics: a case study of phthalate exposure associations with body mass index and waist circumference

The use of human biomonitoring data to characterize exposure to environmental contaminants in epidemiology studies has expanded greatly in recent years. Substantial variability in effect measures may arise when using different exposure metrics for a given contaminant, and it is often not clear which metric is the best surrogate for the 'causal' or 'true' exposure. Here we evaluated variability and potential bias in epidemiologic associations resulting from the use of different phthalate exposure metrics in the 2009-2010 National Health and Nutrition Examination Survey (NHANES). We examined associations between urinary phthalate metabolites and the outcomes of body mass index (BMI) and waist circumference (WC). We examined each of the following NHANES-derived exposure metrics for metabolites of individual phthalates: molar excretion rate (nmol/min), molar amount (nmol), molar concentration (nmol/mL, with and without additional model adjustment for creatinine), creatinine corrected molar concentration (nmol/g creatinine), and reconstructed daily phthalate intake (nmol/kg/day). In order to investigate potential biasing effect of each metric, we first assumed that daily intake of the parent phthalate is the causal exposure. We then constructed a simulated population based on the 2009-2010 NHANES, and randomly assigned each individual a di-2-ethylhexyl phthalate (DEHP) intake dose based on a published distribution, but independent of any other factor. Accordingly, all associations between these randomly assigned intake doses and individuals' BMI and WC should be null. Next, demographic data in the NHANES were incorporated into a pharmacokinetic model to predict urinary molar excretions of five DEHP metabolites based on the randomly assigned DEHP intake. The predicted molar excretions were then used to calculate the same exposure metrics listed above. Three exposure metrics (randomly generated intake, excretion rate, urine concentration) showed no significant associations with BMI, which supports the null hypothesis stated above. In contrast, metrics adjusted for creatinine showed a significant negative correlation, and reconstructed daily intake showed a significant positive correlation, indicating the introduction of bias away from the true (i.e., null) association. Interestingly, trends in the simulation analysis were similar to those seen in the observed NHANES data. Our findings show that, at least in this example case, the choice of exposure metric can introduce significant bias of varying magnitude and direction into the calculation of epidemiologic associations.

A proposal for assessing study quality: Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument

The quality of exposure assessment is a major determinant of the overall quality of any environmental epidemiology study. The use of biomonitoring as a tool for assessing exposure to ubiquitous chemicals with short physiologic half-lives began relatively recently. These chemicals present several challenges, including their presence in analytical laboratories and sampling equipment, difficulty in establishing temporal order in cross-sectional studies, short- and long-term variability in exposures and biomarker concentrations, and a paucity of information on the number of measurements required for proper exposure classification. To date, the scientific community has not developed a set of systematic guidelines for designing, implementing and interpreting studies of short-lived chemicals that use biomonitoring as the exposure metric or for evaluating the quality of this type of research for WOE assessments or for peer review of grants or publications. We describe key issues that affect epidemiology studies using biomonitoring data on short-lived chemicals and propose a systematic instrument--the Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument--for evaluating the quality of research proposals and studies that incorporate biomonitoring data on short-lived chemicals. Quality criteria for three areas considered fundamental to the evaluation of epidemiology studies that include biological measurements of short-lived chemicals are described: 1) biomarker selection and measurement, 2) study design and execution, and 3) general epidemiological study design considerations. We recognize that the development of an evaluative tool such as BEES-C is neither simple nor non-controversial. We hope and anticipate that the instrument will initiate further discussion/debate on this topic.

Population variation in biomonitoring data for persistent organic pollutants (POPs): an examination of multiple population-based datasets for application to Australian pooled biomonitoring data

BACKGROUND

Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population.

METHODS

Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2',4,4' tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS).

RESULTS

Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data.

CONCLUSIONS

Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.

A new method for generating distributions of biomonitoring equivalents to support exposure assessment and prioritization

Biomonitoring data are now available for hundreds of chemicals through state and national health surveys. Exposure guidance values also exist for many of these chemicals. Several methods are frequently used to evaluate biomarker data with respect to a guidance value. The "biomonitoring equivalent" (BE) approach estimates a single biomarker concentration (called the BE) that corresponds to a guidance value (e.g., Maximum Contaminant Level, Reference Dose, etc.), which can then be compared with measured biomarker data. The resulting "hazard quotient" estimates (HQ=biomarker concentration/BE) can then be used to prioritize chemicals for follow-up examinations. This approach is used exclusively for population-level assessments, and works best when the central tendency of measurement data is considered. Complementary approaches are therefore needed for assessing individual biomarker levels, particularly those that fall within the upper percentiles of measurement distributions. In this case study, probabilistic models were first used to generate distributions of BEs for perchlorate based on the point-of-departure (POD) of 7μg/kg/day. These distributions reflect possible biomarker concentrations in a hypothetical population where all individuals are exposed at the POD. A statistical analysis was then performed to evaluate urinary perchlorate measurements from adults in the 2001 to 2002 National Health and Nutrition Examination Survey (NHANES). Each NHANES adult was assumed to have experienced repeated exposure at the POD, and their biomarker concentration was interpreted probabilistically with respect to a BE distribution. The HQ based on the geometric mean (GM) urinary perchlorate concentration was estimated to be much lower than unity (HQ≈0.07). This result suggests that the average NHANES adult was exposed to perchlorate at a level well below the POD. Regarding individuals, at least a 99.8% probability was calculated for all but two NHANES adults that a higher biomarker concentration would have been observed compared to what was actually measured if the daily dietary exposure had been at the POD. This is strong evidence that individual perchlorate exposures in the 2001-2002 NHANES adult population were likely well below the POD. This case study demonstrates that the "stochastic BE approach" provides useful quantitative metrics, in addition to HQ estimates, for comparison across chemicals. This methodology should be considered when evaluating biomarker measurements against exposure guidance values, and when examining chemicals that have been identified as needing follow-up investigation based on existing HQ estimates.

Estimating common parameters of lognormally distributed environmental and biomonitoring data: harmonizing disparate statistics from publications

The progression of science is driven by the accumulation of knowledge and builds upon published work of others. Another important feature is to place current results into the context of previous observations. The published literature, however, often does not provide sufficient direct information for the reader to interpret the results beyond the scope of that particular article. Authors tend to provide only summary statistics in various forms, such as means and standard deviations, median and range, quartiles, 95% confidence intervals, and so on, rather than providing measurement data. Second, essentially all environmental and biomonitoring measurements have an underlying lognormal distribution, so certain published statistical characterizations may be inappropriate for comparisons. The aim of this study was to review and develop direct conversions of different descriptions of data into a standard format comprised of the geometric mean (GM) and the geometric standard deviation (GSD) and then demonstrate how, under the assumption of lognormal distribution, these parameters are used to answer questions of confidence intervals, exceedance levels, and statistical differences among distributions. A wide variety of real-world measurement data sets was reviewed, and it was demonstrated that these data sets are indeed of lognormal character, thus making them amenable to these methods. Potential errors incurred from making retrospective estimates from disparate summary statistics are described. In addition to providing tools to interpret "other people's data," this review should also be seen as a cautionary tale for publishing one's own data to make it as useful as possible for other researchers.