Attitudes of pregnant women towards collection of biological specimens during pregnancy and at birth

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90568/1/j.1365-3016.2012.01265.x.pd

ExO: An Ontology for Exposure Science

An ontology is a formal representation of knowledge within a domain and typically consists of classes, the properties of those classes, and the relationships between them. Ontologies are critically important for specifying data of interest in a consistent manner, thereby enabling data aggregation, analysis and exchange. An exposure ontology, consistent with those being used in toxicology and other health sciences, is required to formally represent exposure concepts, the relationships between these concepts and most important, the relationships between exposure, susceptibility, and toxicology information. A successful exposure ontology must facilitate the semantic retrieval of exposure data in the context of environmental health science, medical surveillance, disease control, health tracking, risk assessment, and other public health and environmental science endeavors. To address this need, an Exposure Ontology, ExO, was designed and a prototype developed to provide the foundation for exposure data centralization and integration. The root classes forming the basis for the ontology are 'exposure event’ ‘exposure stressor', 'exposure receptor', and 'exposure outcome'. Although the initial development of ExO was focused on human exposure to chemicals, the ultimate intent is to provide domains that can be extended to address exposures to the full suite of environmental stressors

Measuring Potential Dermal Transfer of a Pesticide to Children in a Child Care Center

Currently, the major determinants of children’s exposure to pesticides are not fully understood, and approaches for measuring and assessing dermal exposure in a residential setting have not been sufficiently evaluated. In one approach, dermal exposure is estimated using empirically derived transfer coefficients. To assess the feasibility of using this approach for assessing children’s exposure to pesticides, we conducted a study was conducted in a child care center that had a preexisting contract with a pest control service for regular monthly pesticide applications. Children in the selected child care center were monitored using full-body cotton garments to measure dermal loading. Pesticide residues on classroom surfaces were measured in the areas where the children spent time. Measured surface-wipe loadings ranged from 0.47 to 120 ng/cm(2), and total garment loadings ranged from 0.5 to 660 pg/cm(2). The garment and surface loading measurements were used to calculate dermal-transfer coefficients for use in assessing children’s residential exposure to pesticides. Dermal-transfer coefficients calculated using these data range from approximately 10 to 6,000 cm(2)/hr. The wide range in these values demonstrates the importance of developing standard surface-measurement protocols if this approach is to be used to assess dermal exposure in a residential environment. The upper-range values resulting from this study were found to be similar to the default value used by the U.S. Environmental Protection Agency to assess children’s dermal exposures resulting from contact with indoor surfaces

Polybrominated Diphenyl Ethers: A Case Study for Using Biomonitoring Data to Address Risk Assessment Questions

The use of biomonitoring data holds promise for characterizing exposure and informing risk assessment. Biomonitoring data have been used successfully to track population trends, identify susceptible populations, and provide indications of emerging environmental health issues. However, there remain challenges associated with interpreting biomonitoring data for risk assessment. An international biomonitoring workshop was convened in September 2004 to explore the use of biomonitoring data in the context of risk assessment. Six compounds were examined as case studies for this workshop, including polybrominated diphenyl ethers (PBDEs). The PBDE case study was developed to provide an example of a persistent compound for which relatively few data are available for human exposure, biomonitoring, and health outcomes. PBDEs are used in hard plastics, electronics, textiles, and polyurethane foam products. The congener pattern downstream of production facilities often resembles the commercial mixture. However, because these compounds persist in the environment and in biota, the patterns of congeners evolve. PBDEs partition into body lipids, and direct measurement of bromodiphenyl ether congeners in biologic specimens provides a good marker of exposure. Data indicate significant variability (> 100-fold range) in lipid-adjusted levels for PBDEs in the general population. It is hypothesized that both exposure and pharmacokinetics may play a role in observed congener profiles. Significant gaps in our ability to interpret PBDE biomonitoring data to address public health and risk assessment questions include limited knowledge of environmental fate and transport of PBDE congeners, limited population-based data for adults, and lack of data for potentially vulnerable populations such as children

Providing the Missing Link: the Exposure Science Ontology ExO

Environmental health information resources lack exposure data required to translate molecular insights, elucidate environmental contributions to diseases, and assess human health and ecological risks. We report development of an Exposure Ontology, ExO, designed to address this information gap by facilitating centralization and integration of exposure data. Major concepts were defined and the ontology drafted and evaluated by a working group of exposure scientists and other ontology and database experts. The resulting major concepts forming the basis for the ontology are exposure stressor , exposure receptor , exposure event , and exposure outcome . Although design of the first version of ExO focused on human exposure to chemicals, we anticipate expansion by the scientific community to address exposures of human and ecological receptors to the full suite of environmental stressors. Like other widely used ontologies, ExO is intended to link exposure science and diverse environmental health disciplines including toxicology, epidemiology, disease surveillance, and epigenetics

Mechanistic Indicators of Childhood Asthma (MICA) Study: piloting an integrative design for evaluating environmental health

BACKGROUND: Asthma is a common complex disease responsible for considerable morbidity and mortality, particularly in urban minority populations. The Mechanistic Indicators of Childhood Asthma study was designed to pilot an integrative approach in children's health research. The study incorporates exposure metrics, internal dose measures, and clinical indicators to decipher the biological complexity inherent in diseases such as asthma and cardiovascular disease with etiology related to gene-environment interactions. METHODS/DESIGN: 205 non-asthmatic and asthmatic children, (9-12 years of age) from Detroit, Michigan were recruited. The study includes environmental measures (indoor and outdoor air, vacuum dust), biomarkers of exposure (cotinine, metals, total and allergen specific Immunoglobulin E, polycyclic aromatic hydrocarbons, volatile organic carbon metabolites) and clinical indicators of health outcome (immunological, cardiovascular and respiratory). In addition, blood gene expression and candidate SNP analyses were conducted. DISCUSSION: Based on an integrative design, the MICA study provides an opportunity to evaluate complex relationships between environmental factors, physiological biomarkers, genetic susceptibility and health outcomes. PROJECT APPROVAL: IRB Number 05-EPA-2637: The human subjects' research protocol was reviewed by the Institutional Review Board (IRB) of the University of North Carolina; the IRB of Westat, Inc., the IRB of the Henry Ford Health System; and EPA's Human Subjects' Research Review Official

Informing Selection of Nanomaterial Concentrations for ToxCast in Vitro Testing Based on Occupational Exposure Potential

Background: Little justification is generally provided for selection of in vitro assay testing concentrations for engineered nanomaterials (ENMs). Selection of concentration levels for hazard evaluation based on real-world exposure scenarios is desirable

Using Biomarkers to Inform Cumulative Risk Assessment

BACKGROUND: Biomarkers are considered the method of choice for determining exposure to environmental contaminants and relating such exposures to health outcomes. However, the association between many biomarkers and outcome is not direct because of variability in sensitivity and susceptibility in the individual. OBJECTIVES: We explore the relationship between environmental exposures and health outcomes as mitigated by differential susceptibility in individuals or populations and address the question “Can biomarkers enable us to understand and quantify better the population burden of disease and health effects attributable to environmental exposures?” METHODS: We use a case–study approach to develop the thesis that biomarkers offer a pathway to disaggregation of health effects into specific, if multiple, risk factors. We offer the point of view that a series or array of biomarkers, including biomarkers of exposure, biomarkers of susceptibility, and biomarkers of effect, used in concert offer the best means by which to effect this disaggregation. We commence our discussion by developing the characteristics of an ideal biomarker, then give some examples of commonly used biomarkers to show the strengths and weaknesses of current usage. We follow this by more detailed case-study assessment outlining the state-of-the-science in specific cases. We complete our work with recommendations regarding the future use of biomarkers and areas for continued development. CONCLUSIONS: The case studies provide examples of when and how biomarkers can be used to infer the source and magnitude of exposure among a set of competing sources and pathways. The answer to this question is chemical specific and relates to how well the biomarker matches the characteristics of an “ideal” biomarker–in particular ease of collection and persistence. The use of biomarkers in combination provides a better opportunity to disaggregate both source and pathway contributions