Final Report: Integrating Innovative Biomarkers of Environmentally Induced Disease for Children in Agricultural Communities

EPA Grant Number: R832733
Title: Integrating Innovative Biomarkers of Environmentally Induced Disease for Children in Agricultural Communities
Investigators: Faustman, Elaine , Griffith, William C. , Yu, Xiaozhong
Institution: University of Washington , University of Washington - Seattle
EPA Project Officer: Callan, Richard
Project Period: October 1, 2005 through September 30, 2008 (Extended to September 30, 2010)
Project Amount: $749,997
RFA: Early Indicators of Environmentally Induced Disease (2004) RFA Text |  Recipients Lists
Research Category: Human Health , Health , Biology/Life Sciences , Children's Health , Health Effects

Objective:

The purpose of this U.S. Environmental Protection Agency (EPA) Science to Achieve Results (STAR) award (RD832733) was to develop an integrative tool for evaluating genomic biomarkers of susceptibility and early response for public health. Our hypothesis was that an understanding of these biomarkers and their relationship could allow us to identify the potential for pesticide exposure and effect and to design effective intervention and prevention approaches. The integrative tool was designed for identifying and characterizing the potential for exposure and response relationships in adults and children in agricultural and non-agricultural communities using the public health biomarker paradigm.

We collaborated with the Community Based Participatory Research (CBPR) project in the Yakima Valley, which is part of the Center for Child Environmental Health Risks Research (CHC) funded by the U.S. Environmental Protection Agency (EPA) and the National Institute of Environmental Health Sciences (NIEHS). Of particular utility was the availability of a biorepository from their study of farmworker and non-farmworker families. The biorepository included samples of blood, urine, and dust collected from households and families of Hispanic farmworkers (N = 100) and their children (N=100) and Hispanic non-farmworkers (N = 100) and their children (N = 100). Samples were taken frequently over the agricultural season including samples over a 5-day period during times of pesticide application (thinning season) and non-application (non-spray season). Organophosphate (OP) pesticides present in the biospecimens were characterized. The biospecimens were collected with informed consent in accordance with the Fred Hutchinson Cancer Research Center (FHCRC) Institutional Review Board (IRB) #5946, and access to the samples is governed by the University of Washington (UW) Human Subjects protocol #27533. The biospecimens were de-identified. We evaluated the potential for exposures using the following biomarkers:

Integrated Tool:  The models used in this study are linked through the study design by the collection of environmental and biological samples from adult/child pairs living in the same household, and the collection of samples from these households across seasons. These samples then were analyzed in multiple assays so that it was possible to link measurements to households and seasons. To better understand the potential for OP exposures to affect neurodevelopment, these exposures were linked to studies in laboratory animals. We used biologically based dose response models to understand the dynamics of response in laboratory animals to estimate the potential for human responses. Acetylcholinesterase inhibitioni was used as a common biomarker of effect linking potential for animal and humal responses to OP exposure. This allowed for cross species comparisons for biomarkers of early biological response.

The four types of models used were:

Environmental and Exposure biomarkers:  We modeled six urinary dialkyl phosphate (DAP) metabolites (dimethylphosphate [DMP], dimethylthiophosphate [DMTP], dimethyldithiophosphate [DMDTP], diethylphosphate [DEP], diethylthiophosphate [DETP] and diethyldithiophosphate [DEDTP]). We also measured several parent compounds of OP in blood, including chlorpyrifos (CP) and azinphos-methyl (AZ) in blood. We characterized environmental sources of exposure by measuring six parent compounds in home and vehicle dust (AZ, phosmet, malathion, methyl-parathion, CP, and diazinon).

Biomarkers of Early Biological Response:  We evaluated activities for two cholinesterase (ChE) enzymes from blood samples collected from farmworkers and non-farmworkers, acetylcholinesterase (AChE) and butylcholinesterase (BuChE). We explored the feasibility of using buccal swabs to examine gene-expression analyses.

Biomarkers of Susceptibility:  We modeled the following three classes of biomarkers of susceptibility for OP to characterize the potential for individual differences in response to OP exposure: 1) genotype of CYP450 metabolism genes; 2) geno/phenotype for paraoxonase 1 (PON1); and 3) genotype for oxidative response pathways.

Biomarkers of Effect Showing Altered Function:  To evaluate biomarkers of effect showing altered function we also developed models from CHC studies using laboratory animals, mice, exposed during pregnancy to CP. This system-based GO-Quant approach identified a diversity of functional gene pathways known to be disrupted by CP and highlighted possible additional consequences of CP neurotoxicity, such as disturbance of the ubiquitin proteasome system.

Summary/Accomplishments (Outputs/Outcomes):

We have developed an integrative tool that is organized around the Public Health paradigm “V- diagram,” which models the occurrence of disease in response to original sources of exposure (see Figure below). The diagram identifies intermediate processes (which may be subject to public health intervention) and conditions (which may be observable for public health monitoring and hypothesis testing) along the pathway from exposure source to health effect. While the CBPR Project focused on identifying the potential for a take-home pathway of OP transfer we focused on modeling biomarkers of exposure, susceptibility, and effect as shown in the figure below.

Integrative tool containing models we developed in boxes A-G organized around the Public Health paradigm “V‐diagram.”

Environmental and Exposure biomarkers:  We have developed Bayesian-based mixed effects Markov Chain Monte Carlo (MCMC) methodologies to model the potential for exposure to OPs in farmworkers and their children during the thinning, harvest and non-spray seasons. The MCMC methods allowed us to develop methods for treating the many observations below the limit of detection as censored observations. Our findings demonstrated that the day-to-day variability within an individual is frequently larger than between individuals. Thus, our multiple sampling methods allowed us to more accurately estimate the exposures within study groups by accounting for between and within person variability. Urine from farmworker adults and children had considerably higher concentrations of OP metabolites, particularly DMTP, during the thinning season compared to non-farmworkers and to nation-wide estimates from the National Health and Nutrition Examination Survey IV (NHANES IV). Furthermore, farmworker adults and children had significant correlations with house dust residues and with each other’'s DMTP concentration indicating the importance of the take-home pathway. DMTP was the OP metabolite with the highest concentration in the urine of the farmworkers and their children. We observed that during the thinning season, about half of farmworkers had detectable levels of AZ in blood whereas no one in the non-farmworkers group had levels above the limit of detection. In contrast, farmworkers' samples did not have detectable levels of AZ during the non-spray season, whereas only one non-farmworker had detectable levels of AZ. We observed a significant correlation between the levels of AZ in blood and concentrations of urinary metabolites, suggesting that AZ is a significant source of these metabolites.

Biomarkers of Early Biological Response:  We observed a higher number of farmworkers compared to non-farmworkers having > 20% inhibition (the action level for monitoring worker exposure under the Washington State Department of Labor and Industry) for both AChE and BuChE. We observed statistically significant associations between biomarkers of exposure AZ and dimethyl DAPs and ChE inhibition indicating a direct link between pesticide exposure and these biomarkers of response. In order to characterize buccal gene expression patterns, we optimized a ribonucleic acid (RNA) isolation protocol and began exploring reverse transcription polymerase chain reaction (RT-PCR) and microarray assays.

Biomarkers of Susceptibility:  We observed that polymorphism of the genes encoding cytochrome P450s (CYP450s) impacts the production of oxon, which is the active metabolite that causes AChE inhibition. For example, participants who had the A-allele in the CYP3A5 position 6986 had lower AChE inhibition than those with the G-allele. This suggests that these two groups differ in their ability to metabolize OP and may indicate different susceptibility for developing OP-related effects. Our findings suggest that PON1 status does not modify the relationship between the biomarkers of exposure and effect in our populations. This is in agreement with the idea that AZ, the most frequently detected OP among study participants, is not a substrate for PON1. We currently are evaluating the oxidative response pathways. Preliminary results show marginally significant associations between glutathione S-transferase (GST) genotype and AChE inhibition. More analysis is in progress to determine the impact of genetic variation in these oxidative response pathways.

Biomarkers of Effect Showing Altered FunctionTo evaluate biomarkers of effect showing altered function we also developed models from CHC studies using laboratory animals, mice, exposed during pregnancy to multiple doses of CP. We have applied a GO-Quant approach to examine the toxicogenomic responses in mice after in utero exposure to CP. This system-based GO-Quant approach identified a diversity of functional gene pathways known to be disrupted by CP and highlighted possible additional consequences of CP neurotoxicity, such as disturbance of the ubiquitin proteasome system. We explored dose-dependent alterations in toxicogenomic response in the fetal and maternal C57BL/6 mouse brain after daily gestational exposure (days 6 to 17) to CP (2, 4, 10, 12 or 15 mg/kg by subcutaneous injection to the dam). The dose-–effect relationship of CP on gene expression, both at the gene and pathway levels was non-monotonic and had a different pattern than brain AChE inhibition. In the maternal brain, lower doses (4 mg/kg) influenced gene ontology (GO) categories and pathways such as cell adhesion, behavior, lipid metabolism, long-term potentiation, nervous system development, neurogenesis, and synaptic transmission. In the fetal brain, lower doses (2 and/or 4 mg/kg) significantly altered gene responses in pathways for cell division, translation, transmission of nerve impulse, chromatin modification, and long-term potentiation. In addition, some genes involved in nervous system development and signaling were shown to be specifically influenced by these lower CP doses. Other genes were shown to be mainly affected at 10 mg/kg indicating that the genes in the brain with altered function depend upon the dose of CP. We demonstrated that toxicogenomic changes in gene expression showing altered function were more sensitive than the early biological response of AChE inhibition in demonstrating the effect of CP in the fetal brain. The altered gene expression analyzed with the GO-Quant tool reflected the diversity of responses known to be disrupted by CP and highlighted possible additional consequences of CP neurotoxicity.

The models used to link biomarkers of exposure to biomarkers of effect in our integrated tool provided links to describe the “cascade of events” that are part of the “continuum” from exposure to adverse outcome described in the Computational Toxicology Research Program of EPA. Because our models used observations in a farmworker population occupationally exposed to OPs it was possible to directly link many of the events along the continuum. For example, we showed direct links between biomarkers of exposure and biomarkers of early biological response and biomarkers of susceptibility in the farmworkers and their children. We have begun the process of filling in these steps by developing PBPK models incorporating genotypes of polymorphisms of metabolizing genes for OPs. As additional data become available to provide details about these steps, it will be possible to more accurately predict effects of pesticide exposures using the models in our integrated tool.

Conclusions:

We have conceptualized and developed an integrative tool that allowed us to pose and answer important questions along stages of the pathway from exposure to disease. We determined that farmworkers and their children are exposed to OPs to a greater degree than non-farmworkers. We have identified a critical path of take-home exposure for both adults and children living in an agricultural region and we have demonstrated that we can decrease these exposures by using a public health intervention model (see Presentations Vigoren, et al., 2009). We also have identified that exposed farmworkers and non-farmworkers have differential susceptibility based on differences in genotype for metabolizing enzymes. We have shown using laboratory animal studies that at the lowest doses tested, we could observe changes in function measured by gene expression pathways in the fetal brain even when we could not detect changes in AChE inhibition, a biomarker of early biological response. Thus, the public health implications of these findings suggest the need for looking at additional ways to decrease exposure, addressing the take-home exposure by implementing evidence-based interventions and further investigating other sources of exposure for workers in the field, additional characterization of susceptibility markers, and development of screening tools to identify at risk individuals.


Journal Articles on this Report : 26 Displayed | Download in RIS Format

Other project views: All 107 publications 31 publications in selected types All 26 journal articles
Type Citation Project Document Sources
Journal Article Bekris LM, Shephard C, Janer M, Graham J, McNeney B, Shin J, Zarghami M, Griffith W, Farin F, Kavanagh TJ, Lernmark A. Glutamate cysteine ligase catalytic subunit promoter polymorphisms and associations with type 1 diabetes age-at-onset and GAD65 autoantibody levels. Experimental and Clinical Endocrinology and Diabetes 2007;115(4):221-228. R832733 (2007)
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  • Journal Article Coronado GD, Vigoren EM, Thompson B, Griffith WC, Faustman EM. Organophosphate pesticide exposure and work in pome fruit:evidence for the take-home pesticide pathway. Environmental Health Perspectives 2006;114(7):999-1006. R832733 (Final)
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  • Journal Article Coronado GD, Vigoren EM, Griffith WC, Faustman EM, Thompson B. Organophosphate pesticide exposure among pome and non-pome farmworkers:a subgroup analysis of a community randomized trial. Journal of Occupational and Environmental Medicine 2009;51(4):500-509. R832733 (Final)
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  • Journal Article Coronado GD, Griffith WC, Vigoren EM, Faustman EM, Thompson B. Where's the dust? Characterizing locations of azinphos-methyl residues in house and vehicle dust among farmworkers with young children. Journal of Occupational and Environmental Hygiene 2010;7(12):663-671. R832733 (Final)
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  • Journal Article Coronado GD, Holte S, Vigoren E, Griffith WC, Faustman E, Thompson B. Organophosphate pesticide exposure and residential proximity to nearby fields:evidence for the drift pathway. Journal of Occupational and Environmental Medicine 2011;53(8):884-891. R832733 (Final)
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  • Journal Article Cullen AC, Corrales MA, Kramer CB, Faustman EM. The application of genetic information for regulatory standard setting under the clean air act:a decision-analytic approach. Risk Analysis 2008;28(4):877-890. R832733 (Final)
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  • Journal Article Garry MR, Kavanagh TJ, Faustman EM, Sidhu JS, Liao R, Ware C, Vliet P, Deeb S. Sensitivity of mouse lung fibroblasts heterozygous for GPx4 to oxidative stress. Free Radical Biology and Medicine 2008;44(6):1075-1087. R832733 (Final)
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  • Journal Article Gohlke JM, Griffith WC, Faustman EM. Computational models of neocortical neuronogenesis and programmed cell death in the developing mouse, monkey, and human. Cerebral Cortex 2007;17(10):2433-2442. R832733 (Final)
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  • Journal Article Gohlke JM, Griffith WC, Faustman EM. Computational models of ethanol-induced neurodevelopmental toxicity across species:implications for risk assessment. Birth Defects Research Part B. Developmental and Reproductive Toxicology 2008;83(1):1-11. R832733 (Final)
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  • Journal Article Griffith W, Curl CL, Fenske RA, Lu CA, Vigoren EM, Faustman EM. Organophosphate pesticide metabolite levels in pre-school children in an agricultural community:within-and between-child variability in a longitudinal study. Environmental Research 2011;111(6):751-756. R832733 (Final)
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  • Journal Article Moreira EG, Yu X., Robinson JF, Griffith W, Hong SW, Beyer RP, Bammler TK, Faustman EM. Toxicogenomic profiling in maternal and fetal rodent brains following gestational exposure to chlorpyrifos. Toxicology and Applied Pharmacology 2010;245(3):310-325. R832733 (Final)
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  • Journal Article Ramaprasad J, Tsai MG, Fenske RA, Faustman EM, Griffith WC, Felsot AS, Elgethun K, Weppner S, Yost MG. Children's inhalation exposure to methamidophos from sprayed potato fields in Washington State:exploring the use of probabilistic modeling of meteorological data in exposure assessment. Journal of Exposure Science and Environmental Epidemiology 2009;19(6):613-623. R832733 (Final)
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  • Journal Article Robinson JF, Yu X, Hong S, Griffith WC, Beyer R, Kim E, Faustman EM. Cadmium-induced differential toxicogenomic response in resistant and sensitive mouse strains undergoing neurulation. Toxicological Sciences 2009;107(1):206-219. R832733 (Final)
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  • Journal Article Robinson JF, Guerrette Z, Yu X, Hong S, Faustman EM. A systems-based approach to investigate dose-and time-dependent methylmercury-induced gene expression response in C57BL/6 mouse embryos undergoing neurulation. Birth Defects Research. Part B: Developmental and Reproductive Toxicology 2010;89(3):188-200. R832733 (Final)
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  • Journal Article Robinson JF, Yu X, Hong S, Zhou C, Kim N, DeMasi D, Faustman EM. Embryonic toxicokinetic and dynamic differences underlying strain sensitivity to cadmium during neurulation. Reproductive Toxicology 2010;29(3):279-285. R832733 (Final)
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  • Journal Article Robinson JF, Port JA, Yu X, Faustman EM. Integrating genetic and toxicogenomic information for determining underlying susceptibility to developmental disorders. Birth Defects Research. Part A--Clinical and Molecular Teratology 2010;88(10):920-930. R832733 (Final)
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  • Journal Article Robinson JF, Griffith WC, Yu X, Hong S, Kim E, Faustman EM. Methylmercury induced toxicogenomic response in C57 and SWV mouse embryos undergoing neural tube closure. Reproductive Toxicology 2010;30(2):284-291. R832733 (Final)
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  • Journal Article Robinson JF, Yu X, Moreira EG, Hong S, Faustman EM. Arsenic-and cadmium-induced toxicogenomic response in mouse embryos undergoing neurulation. Toxicology and Applied Pharmacology 2011;250(2):117-129. R832733 (Final)
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  • Journal Article Sidhu JS, Ponce RA, Vredevoogd MA, Yu X, Gribble E, Hong S-W, Schneider E, Faustman EM. Cell cycle inhibition by sodium arsenite in primary embryonic rat midbrain neuroepithelial cells. Toxicological Sciences 2006;89(2):475-484. R832733 (Final)
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  • Journal Article Thompson B, Coronado GD, Vigoren EM, Griffith WC, Fenske RA, Kissel JC, Shirai JH, Faustman EM. Para ninos saludables: a community intervention trial to reduce organophosphate pesticide exposure in children of farmworkers. Environmental Health Perspectives 2008;116(5):687-694. R832733 (Final)
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  • Journal Article Yu X, Griffith WC, Hanspers K, Dillman III JF, Ong H, Vredevoogd MA, Faustman EM. A system-based approach to interpret dose-and time-dependent microarray data:quantitative integration of gene ontology analysis for risk assessment. Toxicological Sciences 2006;92(2):560-577. R832733 (2007)
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  • Journal Article Yu X, Hong S, Faustman EM. Cadmium-induced activation of stress signaling pathways, disruption of ubiquitin-dependent protein degradation and apoptosis in primary rat Sertoli cell-gonocyte cocultures. Toxicological Sciences 2008;104(2):385-396. R832733 (Final)
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  • Journal Article Yu X, Robinson JF, Gribble E, Hong SW, Sidhu JS, Faustman EM. Gene expression profiling analysis reveals arsenic-induced cell cycle arrest and apoptosis in p53-proficient and p53-deficient cells through differential gene pathways. Toxicology and Applied Pharmacology 2008;233(3):389-403. R832733 (Final)
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  • Journal Article Yu X, Hong S, Moreira EG, Faustman EM. Improving in vitro Sertoli cell/gonocyte co-culture model for assessing male reproductive toxicity:lessons learned from comparisons of cytotoxicity versus genomic responses to phthalates. Toxicology and Applied Pharmacology 2009;239(3):325-336. R832733 (Final)
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  • Journal Article Yu X, Robinson JF, Sidhu JS, Hong S, Faustman EM. A system-based comparison of gene expression reveals alterations in oxidative stress, disruption of ubiquitin-proteasome system and altered cell cycle regulation after exposure to cadmium and ethylmercury in mouse embryonic fibroblast. Toxicological Sciences 2010;114(2):356-377. R832733 (Final)
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  • Journal Article Yu X, Sidhu JS, Hong S, Robinson JF, Ponce RA, Faustman EM. Cadmium induced p53-dependent activation of stress signaling, accumulation of ubiquitinated proteins, and apoptosis in mouse embryonic fibroblast cells. Toxicological Sciences 2011;120(2):403-412. R832733 (Final)
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  • Supplemental Keywords:

    Organophosphate pesticides, cholinesterase inhibition, genomic biomarkers, biomonitoring, farmworkers, children;, RFA, Health, Scientific Discipline, ENVIRONMENTAL MANAGEMENT, Health Risk Assessment, Biochemistry, Children's Health, Risk Assessment, pesticide exposure, Human Health Risk Assessment, assessment of exposure, children's vulnerablity, susceptibility, children's environmental health, biological markers, agricultural community, disease

    Progress and Final Reports:

    Original Abstract
  • 2006 Progress Report
  • 2007 Progress Report
  • 2008
  • 2009 Progress Report