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Risk Assessment of Exposure to Trihalomethanes: Use of Biomonitoring Equivalents and Biomonitoring Data from NHANES Lesa L. AylwardRichard A. Becker Sean.

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Presentation on theme: "Risk Assessment of Exposure to Trihalomethanes: Use of Biomonitoring Equivalents and Biomonitoring Data from NHANES Lesa L. AylwardRichard A. Becker Sean."— Presentation transcript:

1 Risk Assessment of Exposure to Trihalomethanes: Use of Biomonitoring Equivalents and Biomonitoring Data from NHANES Lesa L. AylwardRichard A. Becker Sean M. Hays Chris R. KirmanAmerican Chemistry Council

2 Purpose and Approach  Conduct an internal dose-based risk assessment of potential non-cancer risks from population THM exposures  Use internal dose measures for both Dose-response – Biomonitoring Equivalents (BEs) Exposure metrics – NHANES blood THM data  Use IPCS Tier 1 approach (assumption of dose addition) for screening THM mixtures in blood

3 “Biomonitoring Equivalent” Concentration of biomarker that is consistent with existing exposure guidance or reference values such as RfDs, TDIs, etc. Rat Dose NOAEL/LOAEL “Safe” Human Dose – RfD BE RfD Human Blood Level 3

4 THMs Non-Cancer Critical Effects (USEPA 2001, 2005)  Critical effect: Risk of fatty liver degeneration in rats and dogs Quantal measure: yes/no Point of Departure: BMDL 10  Non-alcoholic fatty liver disease prevalent in adult US population (~10%)  PBPK models available for humans and experimental species

5 BE Derivation for THMs BMDL 1 0

6 Low-Dose Extrapolation: 2 Approaches

7 NHANES 2003-2004 Blood THM Data  Population representative sampling  Allows assessment of simultaneous internal blood concentrations of all four THMs on an individual-by-individual basis  Highly transient biomarkers

8 Hazard Quotient/Hazard Index  Compare estimated dose to RfD to estimate a “Hazard Quotient” (HQ):  Compare measured biomarker concentration to BE RfD :  Sum across THMs (IPCS Tier 1 approach): 8

9 Hazard Indices and Quotients Across Individuals Based on NHANES Data 0 0 0 0

10 Estimated Percentiles: Risk of Fatty Liver

11 Issues in Interpretation  Highly transient biomarker: comparison to steady-state avg. blood conc. (BE POD, BE RfD ) How representative are spot blood samples of long term avg. conc.? Is this better/worse/complementary to external exposure-based assessments?  POD: quantal risk of fatty liver (y/n) vs. background prevalence of fatty liver and pre- fatty liver changes Continuous metric for POD (e.g., severity, liver enzyme changes) might allow evaluation of risks to “sensitive” or at-risk populations

12 Issues in Interpretation (cont’d)  Low-dose extrapolation procedure: How does MOA for hepatic fatty liver occurrence inform selection? MOA: Cytotoxicity due to reactive metabolite production Related to peak, or elevated, metabolism rates rather than low-level production of metabolites? Interaction of this mechanism with underlying pre-pathologic conditions in humans?


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