Introduction to Biomonitoring

Transcription

1 Introduction to Biomonitoring Interpretation of biomonitoring data using physiologically based pharmacokinetic modeling Centers for Human Health Assessment September 25-29, 2006

2 Definition of Biomonitoring Biomonitoring is defined as a method for assessing human exposure to chemicals by measuring the chemicals or their metabolites in human tissues or specimens, such as blood or urine (CDC 2005). (NRC, 2006)

3 Exposure-Effect Continuum for Environmental Chemicals (Angerer et al. 2006)

4 Stages of a Biomonitoring Study (NRC, 2006)

5 CDC s National Report on Human Exposure to Environmental Chemicals An assessment of the U. S. population s exposure to environmental chemicals using biomonitoring data.

6 NHANES National Health and Nutrition Examination Survey (administered by CDC NCHS) Stratified, multistage, national probability sample of the civilian, noninstitutionalized population Data released every 2 years 27 chemicals (1st Report), chemicals (2nd Report), chemicals (3rd Report), localities via mobile trailers Data collected Extensive questionnaire on demographics and health behaviors Physical exam Medical and nutritional lab tests Drinking water sampled

7 CDC s National Report on Human Exposure to Environmental Chemicals Reported Chemicals Metals Polychlorinated biphenyls, dioxins and furans Organochlorine pesticides Carbamate pesticides Organophosphorous pesticides Pyrethroid pesticides Herbicides Polycyclic aromatic hydrocarbons Phthalates Phytoestrogens Pest repellants Cotinine Starting in 2003: Perfluorinated chemicals BFRs VOCs Perchlorate Acrylamide

8 CDC s National Report on Human Exposure to Environmental Chemicals Individual Specimens Urine Specimens: Ages 6 Blood Specimens: Ages 12 Exceptions: Pb, Cd, Hg 1 year Cotinine 3 years + Pooled Specimens BFRs/PCBs/Persistent Pesticides PCDDs/PCDFs/cPCBs Total Lipids Perfluorinatedchemicals

9 CDC s National Report on Human Exposure to Environmental Chemicals CDC Caveats: Cannot provide estimates for: States, cities, special localities Groups with special exposures Analysis of trends for many chemicals awaits future data The presence of a chemical does not imply disease

10 National Research Council Study Human Biomonitoring for Environmental Chemicals The ability to generate new biomonitoring data often exceeds our ability to evaluate whether and how a chemical measured in an individual or population causes a health risk or to evaluate its sources and pathways for exposure (NRC, 2006)

11 Interpretation of Biomonitoring Data Can be informative CDC study finds dramatic drop in levels of lead in American bodies U.S. bodies have less dangerous chemicals CDC calls 2nd-hand smoke a problem for kids, blacks. Sweeping study looks at chemical exposure.

12 Interpretation of Biomonitoring Data Can be informative or not 'Watershed event' finds human body awash in pesticides, solvents, metals CDC report says everybody's contaminated CDC results are in: We're full of contaminants Dozens of Chemicals Found in Most Americans' Bodies

13 Interpretation of Biomonitoring Data Depends on Nature of Data and Purpose Type of Biomonitoring Data Biomarker of internal dose (e.g., pg/ml in blood) Biomarker of interaction (e.g., adduct level) Biomarker of biological effect (e.g., AChE inhibition) Concern Exposure characterization (extent, trends) Risk characterization (potential for health effects) Risk management (reduction of exposure)

14 Interpretation of Biomonitoring Data Biomonitoring data may be interpreted with either descriptive or risk-based approaches Descriptive approaches present a statistical review of the data (e.g., 10th, 25th, 50th, 75th, and 90 th percentiles) Risk-based approaches use toxicologic, epidemiologic, or pharmacokinetic modeling data to relate biomonitoring data to other measures of toxicity in an effort to evaluate the risk associated with the amount of chemical in the body (NRC, 2006)

15 Interpretation of Biomonitoring Data Possible with Descriptive Approaches: Determine which chemicals get into members of the general population and at what concentrations Determine if exposure levels are higher in some groups than in others Track temporal trends in levels of exposure Assess the effectiveness of public health efforts to reduce exposure Establish reference ranges Requires Risk-Based Approaches: Determine the prevalence of people with levels above known toxicity levels Set priorities for research on human health effects (CDC, 2005)

16 Interpretation of Biomonitoring Data Minimum Information Requirements Exposure characterization (extent, trends) Biomarker of exposure Risk management (reduction of exposure) Biomarker of exposure Exposure pathway characterization Risk characterization (potential for health effects) Biomarker of exposure Exposure pathway characterization Pharmacokinetic Information Toxicity dose-response

17 Chemicals from 3 rd National Exposure Report for which Health-Based Values are Available (CDC 2005) 25 5 No known toxicity values Established Biological Exposure Indicies Established toxicity values 118 CDC s Third National Report on Human Exposure to Environmental Chemicals (2005)

18 Interpretation of Biomonitoring Data Alternative Approaches (NRC, 2006)

19 Interpretation of Biomonitoring Data Determining Trends in Population Exposure Cotinine: Nicotine metabolite that tracks exposure to tobacco smoke For nonsmokers, tracks exposure to secondhand smoke

20 Interpretation of Biomonitoring Data Determining Trends in Population Exposure

21 Interpretation of Biomonitoring Data Determining Trends in Population Exposure Environmental tobacco smoke exposure monitored as serum cotinine Comparing NHANES III ( ) to NHANES 99-02, median levels in non-smokers have fallen: 68% in children 69% in adolescents About 75% in adults Higher in non-hispanic blacks than Mexican Americans or non-hispanic whites

22 Interpretation of Biomonitoring Data Determining Trends in Population Exposure

23 Interpretation of Biomonitoring Data Monitoring Effectiveness of Interventions

24 Interpretation of Biomonitoring Data Monitoring Effectiveness of Interventions

25 Interpretation of Biomonitoring Data Monitoring Effectiveness of Interventions

26 Interpretation of Biomonitoring Data Evaluate Potential for Health Risks (CDC, 2005)

27 Interpretation of Biomonitoring Data Evaluate Potential for Health Risks (USEPA 2006)

28 Example of Risk Characterization Using Biomonitoring Data: CDC Evaluation of Mercury in Blood blood Hg levels in young children and women of childbearing age usually are below levels of concern. However, approximately 6% of childbearing-aged women had levels at or above a reference dose, an estimated level assumed to be without appreciable harm (>5.8 µg/l). -- CDC MMWR (NHANES )

29 Interpretation of Biomonitoring Data Alternative Risk-Based Approach 1 Biomonitoring-based risk assessment Most straightforward approach Epidemiologic studies have developed exposureresponse relationships based on biomarker measurements of hair, blood, urine, or other matrices The relationships can be applied directly to new biomonitoring data to determine where on the exposure-response curve any person is Few chemicals are in this data-rich category (e.g., lead and mercury). (NRC, 2006)

30 Interpretation of Biomonitoring Data Alternative Risk-Based Approach 2 Using existing risk assessment for interpreting biomonitoring data Interpretation of biomonitoring results can be enhanced by existing risk assessments of a specific chemical Traditional risk assessment calculates the dose associated with various exposure pathways, cumulates the pathways into a total dose, and then compares the total dose with the RfD or uses it to estimate cancer risk A comprehensive exposure and risk assessment for the general population, if available, can be a useful starting point for putting the biomonitoring data into perspective Example: permethrin (NRC, 2006)

31 Interpretation of Biomonitoring Data Alternative Risk-Based Approach 3 Biomonitoring-led risk assessment Biomonitoring-led risk assessment is needed when biomonitoring and toxicology databases are robust but there are no epidemiologic data on the relationship between the biomarker and the effect and the exposure sources and routes are not known Pharmacokinetic modeling techniques are applied to convert the biomonitoring data into a format that may be used as exposure information in risk assessments Examples include dioxin, PFOA, and phthalates. (NRC, 2006)

32 Example of Biomonitoring-Led Risk Assessment Perfluoro-octanoic Acid (PFOA) PFOA (ppm) PFOA in Human Blood (ng/ml) Benchmark Blood Concentrations (BMDLs) at NOAELs in Toxicity Studies (ng/ml) Male Monkey Liver Weight 23 Rat Post-natal Effects 29 Male Monkey Body Weight 60 Male Rat Leydig Cell Tumors Boys Girls Adult Males Adult Females Elderly Males Elderly Females MOE = lowest BMDL / 95 th %ile of human blood concentrations: 1600 (Butenhoff et al. 2004)

33 Example of Biomonitoring-Led Risk Assessment Perfluoro-octanoic Acid (PFOA) Approach: Compared 95% upper bound blood of concentrations measured in humans with 95% lower bound of blood concentrations at lowest animal NOAEL to obtain a Margin of Exposure (MOE) Relied on measurements of blood concentrations in toxicity studies or pharmacokinetic data/modeling to predict blood concentrations from administered doses Complication: uncertain relationship of internal biomarker to toxicity (target tissue dose) Issue: how to determine adequacy of MOE

34 NRC Framework for Characterizing Biomarkers From Report on Human Biomonitoring for Environmental Chemicals (NRC( 2006)

35 National Research Council Study on Human Biomonitoring for Environmental Chemicals Recommendations for Interpretation of Biomarkers Development of the application of biomarkers in epidemiology is needed, including increasing the number of biosamples collected and stored to provide for future research opportunities Animal toxicologic-study designs need to include collection of relevant biomarker data to facilitate development of biomarker-response relationships for extrapolating biomonitoring results to humans Pharmacokinetic models are needed to help to assess the influence of such factors as metabolism and sampling time Exposure assessment should be a component of population-based biomonitoring studies (NRC, 2006)

36 Biomonitoring in Epidemiology Studies Confirmation that exposure has occurred Quantifiable exposure data that can be used to: assess dose-response relationships in health effects studies develop background normative values identify population sub-groups more highly exposed evaluate intervention strategies to reduce exposure assess inter-individual variations in factors such as use of PPE, personal hygiene, toxicokinetics or genetic susceptibility

37 Biomonitoring in Epidemiology Studies Identification of chemical agents in mixtures Integration of exposure from all routes Identify unexpected or accidental exposures not identified in records or questionnaire Movement towards validated questions Indication of exposure measurement error - direction and magnitude

38 Biomarkers in Animal Studies Human biomonitoring data described in units of internal dose (e.g., blood and/or urine concentration) Animal toxicity studies reported in units of external dose (mg/kg/day or ppm) Dosimetry of current toxicity tests provides no direct context for interpreting human biomonitoring data e.g., NOAEL and LOAEL values not linked to blood and/or urine concentrations

39 Biomarkers in Animal Studies Obtain data for biomarker of internal under the same conditions (or in the same studies) in which toxicity data used for risk assessment are collected Advances in analytical technologies facilitate sensitive and rapid quantitation of parent and/or metabolite levels Reduce uncertainty in human risk assessments by developing Margin of Exposure (MOE) comparisons based on ratio of internal dose in animal (e.g., at NOAEL) to internal dose in human population

40 Exposure Assessment Approaches Questionnaire/Historical Information (includes GIS + video) Environmental monitoring (Air, Water, Food, Soil) Biomonitoring Environmental / Biological Modeling

41 (USEPA 2006)

42 (USEPA 2006)