Reconstructing human exposures using biomarkers and other "clues"

Biomonitoring is the process by which biomarkers are measured in human tissues and specimens to evaluate exposures. Given the growing number of population-based biomonitoring surveys, there is now an escalated interest in using biomarker data to reconstruct exposures for supporting risk assessment and risk management. While detection of biomarkers is de facto evidence of exposure and absorption, biomarker data cannot be used to reconstruct exposure unless other information is available to establish the external exposure-biomarker concentration relationship. In this review, the process of using biomarker data and other information to reconstruct human exposures is examined. Information that is essential to the exposure reconstruction process includes (1) the type of biomarker based on its origin (e.g., endogenous vs. exogenous), (2) the purpose/design of the biomonitoring study (e.g., occupational monitoring), (3) exposure information (including product/chemical use scenarios and reasons for expected contact, the physicochemical properties of the chemical and nature of the residues, and likely exposure scenarios), and (4) an understanding of the biological system and mechanisms of clearance. This review also presents the use of exposure modeling, pharmacokinetic modeling, and molecular modeling to assist in integrating these various types of information.

Exploring chemical space in non-targeted analysis: a proposed ChemSpace tool

Non-targeted analysis (NTA) using high-resolution mass spectrometry allows scientists to detect and identify a broad range of compounds in diverse matrices for monitoring exposure and toxicological evaluation without a priori chemical knowledge. NTA methods present an opportunity to describe the constituents of a sample across a multidimensional swath of chemical properties, referred to as "chemical space." Understanding and communicating which region of chemical space is extractable and detectable by an NTA workflow, however, remains challenging and non-standardized. For example, many sample processing and data analysis steps influence the types of chemicals that can be detected and identified. Accordingly, it is challenging to assess whether analyte non-detection in an NTA study indicates true absence in a sample (above a detection limit) or is a false negative driven by workflow limitations. Here, we describe the need for accessible approaches that enable chemical space mapping in NTA studies, propose a tool to address this need, and highlight the different ways in which it could be implemented in NTA workflows. We identify a suite of existing predictive and analytical tools that can be used in combination to generate scores that describe the likelihood a compound will be detected and identified by a given NTA workflow based on the predicted chemical space of that workflow. Higher scores correspond to a higher likelihood of compound detection and identification in a given workflow (based on sample extraction, data acquisition, and data analysis parameters). Lower scores indicate a lower probability of detection, even if the compound is truly present in the samples of interest. Understanding the constraints of NTA workflows can be useful for stakeholders when results from NTA studies are used in real-world applications and for NTA researchers working to improve their workflow performance. The hypothetical ChemSpaceTool suggested herein could be used in both a prospective and retrospective sense. Prospectively, the tool can be used to further curate screening libraries and set identification thresholds. Retrospectively, false detections can be filtered by the plausibility of the compound identification by the selected NTA method, increasing the confidence of unknown identifications. Lastly, this work highlights the chemometric needs to make such a tool robust and usable across a wide range of NTA disciplines and invites others who are working on various models to participate in the development of the ChemSpaceTool. Ultimately, the development of a chemical space mapping tool strives to enable further standardization of NTA by improving method transparency and communication around false detection rates, thus allowing for more direct method comparisons between studies and improved reproducibility. This, in turn, is expected to promote further widespread applications of NTA beyond research-oriented settings.

Microbiota alter metabolism and mediate neurodevelopmental toxicity of 17β-estradiol

Estrogenic chemicals are widespread environmental contaminants associated with diverse health and ecological effects. During early vertebrate development, estrogen receptor signaling is critical for many different physiologic responses, including nervous system function. Recently, host-associated microbiota have been shown to influence neurodevelopment. Here, we hypothesized that microbiota may biotransform exogenous 17-βestradiol (E2) and modify E2 effects on swimming behavior. Colonized zebrafish were continuously exposed to non-teratogenic E2 concentrations from 1 to 10 days post-fertilization (dpf). Changes in microbial composition and predicted metagenomic function were evaluated. Locomotor activity was assessed in colonized and axenic (microbe-free) zebrafish exposed to E2 using a standard light/dark behavioral assay. Zebrafish tissue was collected for chemistry analyses. While E2 exposure did not alter microbial composition or putative function, colonized E2-exposed larvae showed reduced locomotor activity in the light, in contrast to axenic E2-exposed larvae, which exhibited normal behavior. Measured E2 concentrations were significantly higher in axenic relative to colonized zebrafish. Integrated peak area for putative sulfonated and glucuronidated E2 metabolites showed a similar trend. These data demonstrate that E2 locomotor effects in the light phase are dependent on the presence of microbiota and suggest that microbiota influence chemical E2 toxicokinetics. More broadly, this work supports the concept that microbial colonization status may influence chemical toxicity.

Predictors of Urinary 3-Phenoxybenzoic Acid Levels in 50 North Carolina Adults

Limited data are available on the non-chemical stressors that impact adult exposures to pyrethroid insecticides based on urinary biomonitoring. The urinary metabolite, 3-phenoxybenzoic acid (3-PBA), is commonly used to assess human exposure to a number of pyrethroids. In a further analysis of published study data, we quantified urinary 3-PBA levels of 50 adults over a single, 24-h sampling period and examined the associations between the biomarker measurements and selected non-chemical stressors (demographic, lifestyle, and dietary factors). A convenience sample of 50 adults was recruited in North Carolina in 2009-2011. Participants collected individual urine voids (up to 11) and filled out activity, food, and pesticide use diaries over a 24-h sampling period. Urine voids (n = 326) were analyzed for 3-PBA concentrations using high-performance liquid chromatography-tandem mass spectrometry. 3-PBA was detected in 98% of the 24-h composited urine samples. The geometric mean urinary 3-PBA level was 1.68 ng/mL in adults. Time spent outside (p = 0.0006) was a highly significant predictor of natural log-transformed (ln) urinary 3-PBA levels, while consumption of coffee (p = 0.007) and breads (p = 0.019) and ln creatinine levels (p = 0.037) were significant predictors of urinary 3-PBA levels. In conclusion, we identified specific factors that substantially increased adult exposures to pyrethroids in their everyday environments.

How do cancer-sniffing dogs sort biological samples? Exploring case-control samples with non-targeted LC-Orbitrap, GC-MS, and immunochemistry methods

Early identification of disease onset is regarded as an important factor for successful medical intervention. However, cancer and other long-term latency diseases are rare and may take years to manifest clinically. As such, there are no gold standards with which to immediately validate proposed preclinical screening methodologies. There is evidence that dogs can sort samples reproducibly into yes/no categories based on case-control training, but the basis of their decisions is unknown. Because dogs are sniffing air, the distinguishing chemicals must be either in the gas-phase or attached to aerosols and/or airborne particles. Recent biomonitoring research has shown how to extract and analyze semi- and non-volatile compounds from human breath in exhaled condensates and aerosols. Further research has shown that exhaled aerosols can be directly collected on standard hospital-style olefin polypropylene masks and that these masks can be used as a simple sampling scheme for canine screening. In this article, detailed liquid chromatography-high resolution mass spectrometry (LC-HR-MS) with Orbitrap instrumentation and gas chromatography-mass spectrometry (GC-MS) analyses were performed on two sets of masks sorted by consensus of a four-dog cohort as either cancer or control. Specifically, after sorting by the dogs, sample masks were cut into multiple sections and extracted for LC-MS and GC-MS non-targeted analyses. Extracts were also analyzed for human cytokines, confirming the presence of human aerosol content above levels in blank masks. In preliminary evaluations, 345 and 44 high quality chemical features were detected by LC-MS and GC-MS analyses, respectively. These features were used to develop provisional orthogonal projection to latent structures-discriminant analysis (OPLS-DA) models to determine if the samples classified as cancer (case) or non-cancer (control) by the dogs could be separated into the same groups using analytical instrumentation. While the OPLS-DA model for the LC-HR-MS data was able to separate the two groups with statistical significance, although weak explanatory power, the GC-MS model was not found to be significant. These results suggest that the dogs may rely on the less volatile compounds from breath aerosol that were analyzed by LC-HR-MS than the more volatile compounds observed by GC-MS to sort mask samples into groups. These results provide justification for more expansive studies in the future that aim to characterize specific chemical features, and the role(s) of these features in maintaining homeostatic biological processes.

Exposure science in an age of rapidly changing climate: challenges and opportunities

Climate change is anticipated to alter the production, use, release, and fate of environmental chemicals, likely leading to increased uncertainty in exposure and human health risk predictions. Exposure science provides a key connection between changes in climate and associated health outcomes. The theme of the 2015 Annual Meeting of the International Society of Exposure Science-Exposures in an Evolving Environment-brought this issue to the fore. By directing attention to questions that may affect society in profound ways, exposure scientists have an opportunity to conduct "consequential science"-doing science that matters, using our tools for the greater good and to answer key policy questions, and identifying causes leading to implementation of solutions. Understanding the implications of changing exposures on public health may be one of the most consequential areas of study in which exposure scientists could currently be engaged. In this paper, we use a series of case studies to identify exposure data gaps and research paths that will enable us to capture the information necessary for understanding climate change-related human exposures and consequent health impacts. We hope that paper will focus attention on under-developed areas of exposure science that will likely have broad implications for public health.

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.

Rapid identification and analysis of airborne plutonium using a combination of alpha spectroscopy and inductively coupled plasma mass spectrometry

Recent wildland fires near two U.S. nuclear facilities point to a need to rapidly identify the presence of airborne plutonium during incidents involving the potential release of radioactive materials. Laboratory turn-around times also need to be shortened for critical samples collected in the earliest stages of radiological emergencies. This note discusses preliminary investigations designed to address both these problems. The methods under review are same day high-resolution alpha spectroscopy to screen air filter samples for the presence of plutonium and inductively coupled plasma mass spectrometry to perform sensitive plutonium analyses. Thus far, using modified alpha spectroscopy techniques, it has been possible to reliably identify the approximately 5.2 MeV emission of 239Pu on surrogate samples (air filters artificially spiked with plutonium after collection) even though the primary alpha-particle emissions of plutonium are, as expected, superimposed against a natural alpha radiation background dominated by short-lived radon and thoron progeny (approximately 6-9 MeV). Several processing methods were tested to prepare samples for analysis and shorten laboratory turn-around time. The most promising technique was acid-leaching of air filter samples using a commercial open-vessel microwave digestion system. Samples prepared in this way were analyzed by both alpha spectroscopy (as a thin-layer iron hydroxide co-precipitate) and inductively coupled plasma mass spectrometry. The detection levels achieved for 239Pu--approximately 1 mBq m(-3) for alpha spectroscopy screening, and, < 0.1 mBq m(-3) for inductively coupled plasma mass spectrometry analysis--are consistent with derived emergency response levels based on EPA's Protective Action Guides, and samples can be evaluated in 36 to 72 h. Further, if samples can be returned to a fixed-laboratory and processed immediately, results from mass spectrometry could be available in as little as 24 h. When fully implemented, these techniques have the potential to provide useful information and improved operational flexibility to emergency planners and first-responders during radiological emergencies.

Combined screening and retroactive data mining for emerging perfluoroethers in wildlife and pets in the Cape Fear region of North Carolina

The recent application of non-targeted analysis (NTA) techniques in environmental monitoring has revealed numerous novel fluorinated species in surface water, wildlife, and humans in the Cape Fear River (CFR) region of North Carolina. In this study, we have re-examined archived alligator, striped bass, horse, and dog serum as well as archived seabird tissue data from previously reported exposure studies in order to extend the panel of detected novel PFAS. In this study, the compounds CF3-(OCF2)x-COOH, x = 6, 7, 8 (Abbreviated PFO6TeDA, PFO7HxDA, PFO8OcDA, respectively), and 6H-Perfluoro-3-oxa,4-methylhexanesulfonic acid (Nafion byproduct 6) were detected for the first time in environmental tissues even though these analytes were not previously detected in the CFR. Analytical standards were available for PFO6TeDA and Nafion Byproduct 6, and therefore, were quantitated in investigated tissues. PFO7HxDA and PFO8OcDA had no available standards and were semi-quantitated using NTA techniques. Of note, PFO6TeDA, PFO7HxDA, and PFO8OcDA were observed in alligator, bass, and seabird but not horse and dog. PFO6TeDA was detected at the highest frequency in all investigated tissues with PFO7HxDA and PFO8OcDA detected at lower frequencies. No Nafion Byproduct 6 values are reported in serum due to poor analytical reproducibility of the measurements. Seabird tissue to blood ratios suggests PFO6TeDA is highest in the heart, kidney, and liver and lowest in the brain. Overall, additional studies are needed to fully understand the potential impact of these additional novel PFAS on both wildlife and humans in the CFR region.