Sastry S. Isukapalli

Reconstructing population exposures to environmental chemicals from biomarkers: Challenges and opportunities

A conceptual/computational framework for exposure reconstruction from biomarker data combined with auxiliary exposure-related data is presented, evaluated with example applications, and examined in the context of future needs and opportunities. This framework employs physiologically based toxicokinetic (PBTK) modeling in conjunction with numerical “inversion” techniques. To quantify the value of different types of exposure data “accompanying” biomarker data, a study was conducted focusing on reconstructing exposures to chlorpyrifos, from measurements of its metabolite levels in urine. The study employed biomarker data as well as supporting exposure-related information from the National Human Exposure Assessment Survey (NHEXAS), Maryland, while the MENTOR-3P system (Modeling ENvironment for TOtal Risk with Physiologically based Pharmacokinetic modeling for Populations) was used for PBTK modeling. Recently proposed, simple numerical reconstruction methods were applied in this study, in conjunction with PBTK models. Two types of reconstructions were studied using (a) just the available biomarker and supporting exposure data and (b) synthetic data developed via augmenting available observations. Reconstruction using only available data resulted in a wide range of variation in estimated exposures. Reconstruction using synthetic data facilitated evaluation of numerical inversion methods and characterization of the value of additional information, such as study-specific data that can be collected in conjunction with the biomarker data. Although the NHEXAS data set provides a significant amount of supporting exposure-related information, especially when compared to national studies such as the National Health and Nutrition Examination Survey (NHANES), this information is still not adequate for detailed reconstruction of exposures under several conditions, as demonstrated here. The analysis presented here provides a starting point for introducing improved designs for future biomonitoring studies, from the perspective of exposure reconstruction; identifies specific limitations in existing exposure reconstruction methods that can be applied to population biomarker data; and suggests potential approaches for addressing exposure reconstruction from such data.

Urinary mycoestrogens, body size and breast development in New Jersey girls.

BACKGROUND Despite extensive research and interest in endocrine disruptors, there are essentially no epidemiologic studies of estrogenic mycotoxins, such as zeranol and zearalenone (ZEA). ZEA mycoestrogens are present in grains and other plant foods through fungal contamination, and in animal products (e.g., meat, eggs, dairy products) through deliberate introduction of zeranol into livestock to enhance meat production, or by indirect contamination of animals through consumption of contaminated feedstuff. Zeranol is banned for use in animal husbandry in the European Union and other countries, but is still widely used in the US. Surprisingly, little is known about the health effects of these mycoestrogens, including their impact on puberty in girls, a period highly sensitive to estrogenic stimulation. OBJECTIVES AND METHODS We conducted a cross-sectional analysis among 163 girls, aged 9 and 10 years, participating in the Jersey Girl Study to measure urinary mycoestrogens and their possible relationship to body size and development. RESULTS We found that mycoestrogens were detectable in urine in 78.5% of the girls, and that urinary levels were predominantly associated with beef and popcorn intake. Furthermore, girls with detectable urinary ZEA mycoestrogen levels tended to be shorter and less likely to have reached the onset of breast development. CONCLUSIONS Our findings suggest that ZEA mycoestrogens may exert anti-estrogenic effects similar to those reported for isoflavones. To our knowledge, this was the first evaluation of urinary mycoestrogens and their potential health effects in healthy girls. However, our findings need replication in larger studies with more heterogeneous populations, using a longitudinal approach.

Differential gene expression profiling of mouse skin after sulfur mustard exposure: Extended time response and inhibitor effect

Sulfur mustard (HD, SM), is a chemical warfare agent that within hours causes extensive blistering at the dermal-epidermal junction of skin. To better understand the progression of SM-induced blistering, gene expression profiling for mouse skin was performed after a single high dose of SM exposure. Punch biopsies of mouse ears were collected at both early and late time periods following SM exposure (previous studies only considered early time periods). The biopsies were examined for pathological disturbances and the samples further assayed for gene expression profiling using the Affymetrix microarray analysis system. Principal component analysis and hierarchical cluster analysis of the differently expressed genes, performed with ArrayTrack showed clear separation of the various groups. Pathway analysis employing the KEGG library and Ingenuity Pathway Analysis (IPA) indicated that cytokine-cytokine receptor interaction, cell adhesion molecules (CAMs), and hematopoietic cell lineage are common pathways affected at different time points. Gene ontology analysis identified the most significantly altered biological processes as the immune response, inflammatory response, and chemotaxis; these findings are consistent with other reported results for shorter time periods. Selected genes were chosen for RT-PCR verification and showed correlations in the general trends for the microarrays. Interleukin 1 beta was checked for biological analysis to confirm the presence of protein correlated to the corresponding microarray data. The impact of a matrix metalloproteinase inhibitor, MMP-2/MMP-9 inhibitor I, against SM exposure was assessed. These results can help in understanding the molecular mechanism of SM-induced blistering, as well as to test the efficacy of different inhibitors.

A personal exposure study employing scripted activities and paths in conjunction with atmospheric releases of perfluorocarbon tracers in Manhattan, New York

A personal exposure study was conducted in New York City as part of the Urban Dispersion Program (UDP). It examined the contact of individuals with four harmless perflourocarbon tracers (PFT) released in Midtown Manhattan with approval by city agencies at separate locations, during two types of experiments, completed during each release period. Two continuous 1 h release periods separated by a 1.5 h ventilation time were completed on 3 October 2005. Stationary site and personal exposure measurements were taken during each period, and the first half hour after the release ended. Two types of scripted exposure activities are reported: Outdoor Source Scale, and Outdoor Neighborhood Scale; requiring 1- and 10-min duration samples, respectively. The results showed that exposures were influenced by the surface winds, the urban terrain, and the movements of people and vehicles typical in urban centers. The source scale exposure data indicated that local conditions significantly affected the distribution of each tracer, and consequently the exposures. The highest PFT exposures resulted from interaction of the scripted activities with local surface conditions. The range measured for 1- min exposures were large with measured values exceeding 5000 ppqv (parts per quadrillion by volume). The neighborhood scale measurements quantified exposures at distances up to seven blocks away from the release points. Generally, but not always, the PFT levels returned quickly to zero indicating that after cessation of the emissions the concentrations decrease rapidly, and reduce the intensity of local exposures. The near source and neighborhood personal exposure route results provided information to establish a baseline for determining how a release could affect both the general public and emergency responders, and evaluate the adequacy of re-entry or exit strategies from a local area. Finally, the data also show that local characteristics can produce “hot spots”.

Mechanistic modeling of emergency events: Assessing the impact of hypothetical releases of anthrax

A modular system for source-to-dose-to-effect modeling analysis has been developed based on the modeling environment for total risk studies (MENTOR),((1)) and applied to study the impacts of hypothetical atmospheric releases of anthrax spores. The system, MENTOR-2E (MENTOR for Emergency Events), provides mechanistically consistent analysis of inhalation exposures for various release scenarios, while allowing consideration of specific susceptible subpopulations (such as the elderly) at the resolution of individual census tracts. The MENTOR-2E application presented here includes atmospheric dispersion modeling, statistically representative samples of individuals along with corresponding activity patterns, and population-based dosimetry modeling that accounts for activity and physiological variability. Two hypothetical release scenarios were simulated: a 100 g release of weaponized B. anthracis over a period of (a) one hour and (b) 10 hours, and the impact of these releases on population in the State of New Jersey was studied. Results were compared with those from simplified modeling of population dynamics (location, activities, etc.), and atmospheric dispersion of anthrax spores. The comparisons showed that in the two release scenarios simulated, each major approximation resulted in an overestimation of the number of probable infections by a factor of 5 to 10; these overestimations can have significant public health implications when preparing for and responding effectively to an actual release. This is in addition to uncertainties in dose-response modeling, which result in an additional factor of 5 to 10 variation in estimated casualties. The MENTOR-2E system has been developed in a modular fashion so that improvements in individual modules can be readily made without impacting the other modules, and provides a first step toward the development of models that can be used in supporting real-time decision making.

Physiologically-Based Toxicokinetic Modeling of Zearalenone and Its Metabolites: Application to the Jersey Girl Study

Zearalenone (ZEA), a fungal mycotoxin, and its metabolite zeranol (ZAL) are known estrogen agonists in mammals, and are found as contaminants in food. Zeranol, which is more potent than ZEA and comparable in potency to estradiol, is also added as a growth additive in beef in the US and Canada. This article presents the development and application of a Physiologically-Based Toxicokinetic (PBTK) model for ZEA and ZAL and their primary metabolites, zearalenol, zearalanone, and their conjugated glucuronides, for rats and for human subjects. The PBTK modeling study explicitly simulates critical metabolic pathways in the gastrointestinal and hepatic systems. Metabolic events such as dehydrogenation and glucuronidation of the chemicals, which have direct effects on the accumulation and elimination of the toxic compounds, have been quantified. The PBTK model considers urinary and fecal excretion and biliary recirculation and compares the predicted biomarkers of blood, urinary and fecal concentrations with published in vivo measurements in rats and human subjects. Additionally, the toxicokinetic model has been coupled with a novel probabilistic dietary exposure model and applied to the Jersey Girl Study (JGS), which involved measurement of mycoestrogens as urinary biomarkers, in a cohort of young girls in New Jersey, USA. A probabilistic exposure characterization for the study population has been conducted and the predicted urinary concentrations have been compared to measurements considering inter-individual physiological and dietary variability. The in vivo measurements from the JGS fall within the high and low predicted distributions of biomarker values corresponding to dietary exposure estimates calculated by the probabilistic modeling system. The work described here is the first of its kind to present a comprehensive framework developing estimates of potential exposures to mycotoxins and linking them with biologically relevant doses and biomarker measurements, including a systematic characterization of uncertainties in exposure and dose estimation for a vulnerable population.

Using national and local extant data to characterize environmental exposures in the national children's study: Queens County, New York.

Objective The National Children’s Study is a long-term epidemiologic study of 100,000 children from 105 locations across the United States. It will require information on a large number of environmental variables to address its core hypotheses. The resources available to collect actual home and personal exposure samples are limited, with most of the home sampling completed on periodic visits and the personal sampling generally limited to biomonitoring. To fill major data gaps, extant data will be required for each study location. The Queens Vanguard Center has examined the extent of those needs and the types of data that are generally and possibly locally available. Data In this review we identify three levels of data—national, state and county—and local data and information sets (levels 1–3, respectively), each with different degrees of availability and completeness, that can be used as a starting point for the extant data collection in each study location over time. We present an example on the use of this tiered approach, to tailor the data needs for Queens County and to provide general guidance for application to other NCS locations. Conclusions Preexisting and continually evolving databases are available for use in the NCS to characterize exposure. The three levels of data we identified will be used to test a method for developing exposure indices for segments and homes during the pilot phase of NCS, as outlined in this article.

Studying permethrin exposure in flight attendants using a physiologically based pharmacokinetic model

Assessment of potential health risks to flight attendants from exposure to pyrethroid insecticides, used for aircraft disinsection, is limited because of (a) lack of information on exposures to these insecticides, and (b) lack of tools for linking these exposures to biomarker data. We developed and evaluated a physiologically based pharmacokinetic (PBPK) model to assess the exposure of flight attendants to the pyrethroid insecticide permethrin attributable to aircraft disinsection. The permethrin PBPK model was developed by adapting previous models for pyrethroids, and was parameterized using currently available metabolic parameters for permethrin. The human permethrin model was first evaluated with data from published human studies. Then, it was used to estimate urinary metabolite concentrations of permethrin in flight attendants who worked in aircrafts, which underwent residual and pre-flight spray treatments. The human model was also applied to analyze the toxicokinetics following permethrin exposures attributable to other aircraft disinsection scenarios. Predicted levels of urinary 3-phenoxybenzoic acid (3-PBA), a metabolite of permethrin, following residual disinsection treatment were comparable to the measurements made for flight attendants. Simulations showed that the median contributions of the dermal, oral and inhalation routes to permethrin exposure in flight attendants were 83.5%, 16.1% and 0.4% under residual treatment scenario, respectively, and were 5.3%, 5.0% and 89.7% under pre-flight spray scenario, respectively. The PBPK model provides the capability to simulate the toxicokinetic profiles of permethrin, and can be used in the studies on human exposure to permethrin.

Chapter 44 – Modeling and Predicting Pesticide Exposures

Publisher Summary Models provide a means for representing a real system in an understandable way. Conceptual models help to identify the major influences on where a chemical is likely to be found in the environment, and as such, need to be developed to help target sources of data needed to assess an environmental problem. This chapter appraises the available models for predicting exposure to pesticide. In general, developing a model requires two main steps. First, a model of the domain and the processes being studied must be defined. Then, a model of the boundary conditions is especially needed to represent the environment surrounding the study domain. Research scientists often develop physical or dynamic models to estimate the location where a chemical would be expected to move under controlled conditions, only on a much smaller scale. Isolated systems are usually encountered only in highly controlled reactors, so are important in modeling pesticide formulation and manufacturing but are not directly pertinent to pesticide exposure modeling. Pesticide transport and fate models can be statistical (stochastic) and/or deterministic. Statistical models include the pollutant dispersion models, such as the Lagrangian models, which follow the movement of a control volume starting from the source to the receptor locations. Deterministic models are used when the physical, chemical, and other processes are sufficiently understood so as to be incorporated to reflect the movement and fate of chemicals. More comprehensive models provide realistic descriptions of the underlying processes and are invaluable for performing detailed analysis. Thus, the evolution of models will allow for more realistic scenarios, especially regarding personal exposures to pesticides.

Modelling of aerosol processes in plumes

A modelling platform for studying photochemical gaseous and aerosol phase processes from localized (e.g., point) sources has been presented. The current approach employs a reactive plume model which extends the regulatory model RPM-IV by incorporating aerosol processes and heterogeneous chemistry. The physics and chemistry of elemental carbon, organic carbon, sulfate, nitrate, ammonium material of aerosols are treated and attributed to the PM size distribution. A modified version of the carbon bond IV chemical mechanism is included to model the formation of organic aerosol. Aerosol dynamics modeled include mechanisms of nucleation, condensation, dry deposition and gas/particle partitioning of organic matter. The model is first applied to a number of case studies involving emissions from point sources and sulfate particle formation in plumes. Model calculations show that homogeneous nucleation is an efficient process for new particle formation in plumes, in agreement with previous field studies and theoretical predictions. In addition, the model is compared with field data from power plant plumes with satisfactory predictions against gaseous species and total sulphate mass measurements. Finally, the plume model is applied to study secondary organic matter formation due to various emission categories such as vehicles and the oil production sector.