IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v17y1997i5p649-656.html
   My bibliography  Save this article

Variability in PAH‐DNA Adduct Measurements in Peripheral Mononuclear Cells: Implications for Quantitative Cancer Risk Assessment

Author

Listed:
  • Christopher Dickey
  • Regina M. Santella
  • Dale Hattis
  • Deliang Tang
  • Yanzhi Hsu
  • Tom Cooper
  • Tie‐Lan Young
  • Frederica P. Perera

Abstract

Biomarkers such as DNA adducts have significant potential to improve quantitative risk assessment by characterizing individual differences in metabolism of genotoxins and DNA repair and accounting for some of the factors that could affect interindividual variation in cancer risk. Inherent uncertainty in laboratory measurements and within‐person variability of DNA adduct levels over time are putatively unrelated to cancer risk and should be subtracted from observed variation to better estimate interindividual variability of response to carcinogen exposure. A total of 41 volunteers, both smokers and nonsmokers, were asked to provide a peripheral blood sample every 3 weeks for several months in order to specifically assess intraindividual variability of polycyclic aromatic hydrocarbon (PAH)‐DNA adduct levels. The intraindividual variance in PAH‐DNA adduct levels, together with measurement uncertainty (laboratory variability and unaccounted for differences in exposure), constituted roughly 30% of the overall variance. An estimated 70% of the total variance was contributed by interindividual variability and is probably representative of the true biologic variability of response to carcinogenic exposure in lymphocytes. The estimated interindividual variability in DNA damage after subtracting intraindividual variability and measurement uncertainty was 24‐fold. Inter‐individual variance was higher (52‐fold) in persons who constitutively lack the Glutathione S‐Transferase M1 (GSTM1) gene which is important in the detoxification pathway of PAH. Risk assessment models that do not consider the variability of susceptibility to DNA damage following carcinogen exposure may underestimate risks to the general population, especially for those people who are most vulnerable.

Suggested Citation

  • Christopher Dickey & Regina M. Santella & Dale Hattis & Deliang Tang & Yanzhi Hsu & Tom Cooper & Tie‐Lan Young & Frederica P. Perera, 1997. "Variability in PAH‐DNA Adduct Measurements in Peripheral Mononuclear Cells: Implications for Quantitative Cancer Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 17(5), pages 649-656, October.
    • Handle: RePEc:wly:riskan:v:17:y:1997:i:5:p:649-656
    DOI: 10.1111/j.1539-6924.1997.tb00905.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.1997.tb00905.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1539-6924.1997.tb00905.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kimberly M. Thompson & David E. Burmaster & Edmund A.C. Crouch3, 1992. "Monte Carlo Techniques for Quantitative Uncertainty Analysis in Public Health Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 12(1), pages 53-63, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. A. E. Ades & Karl Claxton & Mark Sculpher, 2006. "Evidence synthesis, parameter correlation and probabilistic sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 373-381, April.
    2. Brent Finley & Deborah Proctor & Paul Scott & Natalie Harrington & Dennis Paustenbach & Paul Price, 1994. "Recommended Distributions for Exposure Factors Frequently Used in Health Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 533-553, August.
    3. Maged M. Hamed & Philip B. Bedient, 1997. "On the Effect of Probability Distributions of Input Variables in Public Health Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 17(1), pages 97-105, February.
    4. Hou, Tianfeng & Nuyens, Dirk & Roels, Staf & Janssen, Hans, 2019. "Quasi-Monte Carlo based uncertainty analysis: Sampling efficiency and error estimation in engineering applications," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    5. Frédéric Dor & Pascal Empereur‐Bissonnet & Denis Zmirou & Vincent Nedellec & Jean‐Marie Haguenoer & Frans Jongeneelen & Alain Person & William Dab & Colin Ferguson, 2003. "Validation of Multimedia Models Assessing Exposure to PAHs—The SOLEX Study," Risk Analysis, John Wiley & Sons, vol. 23(5), pages 1047-1057, October.
    6. K. Claxton & P. J. Neumannn & S. S. Araki & M. C. Weinstein, "undated". "Bayesian Value-of-Information Analysis: An Application to a Policy Model of Alzheimer's Disease," Discussion Papers 00/39, Department of Economics, University of York.
    7. Alan H. Stern, 1993. "Re‐evaluation of the Reference Dose for Methylmercury and Assessment of Current Exposure Levels," Risk Analysis, John Wiley & Sons, vol. 13(3), pages 355-364, June.
    8. Julia J. Pet‐Armacost & Jose Sepulveda & Milton Sakude, 1999. "Monte Carlo Sensitivity Analysis of Unknown Parameters in Hazardous Materials Transportation Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 19(6), pages 1173-1184, December.
    9. Wout Slob, 1994. "Uncertainty Analysis in Multiplicative Models," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 571-576, August.
    10. Alison C. Cullen, 1994. "Measures of Compounding Conservatism in Probabilistic Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 389-393, August.
    11. Michael Greenberg & Charles Haas & Anthony Cox & Karen Lowrie & Katherine McComas & Warner North, 2012. "Ten Most Important Accomplishments in Risk Analysis, 1980–2010," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 771-781, May.
    12. Bas Groot Koerkamp & Theo Stijnen & Milton C. Weinstein & M. G. Myriam Hunink, 2011. "The Combined Analysis of Uncertainty and Patient Heterogeneity in Medical Decision Models," Medical Decision Making, , vol. 31(4), pages 650-661, July.
    13. A. E. Ades & S. Cliffe, 2002. "Markov Chain Monte Carlo Estimation of a Multiparameter Decision Model: Consistency of Evidence and the Accurate Assessment of Uncertainty," Medical Decision Making, , vol. 22(4), pages 359-371, August.
    14. Ana P. Johnson-Masotti & Purushottam W. Laud & Raymond G. Hoffmann & Matthew J. Hayat & Steven D. Pinkerton, 2004. "A Bayesian Approach to Net Health Benefits: An Illustration and Application to Modeling HIV Prevention," Medical Decision Making, , vol. 24(6), pages 634-653, November.
    15. Michael R. Adams & Cynthia A. Hanna & Janet A. Mayernik & William M. Mendez, 1994. "Probabilistic Health Risk Assessment for Exposures to Estuary Sediments and Biota Contaminated with Polychlorinated Biphenyls, Polychlorinated Terphenyls and Other Toxic Substances," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 577-594, August.
    16. Paul S. Price & Cynthia L. Curry & Philip E. Goodrum & Michael N. Gray & Jane I. McCrodden & Natalie W. Harrington & Heather Carlson‐Lynch & Russell E. Keenan, 1996. "Monte Carlo Modeling of Time‐Dependent Exposures Using a Microexposure Event Approach," Risk Analysis, John Wiley & Sons, vol. 16(3), pages 339-348, June.
    17. John Bukowski & Leo Korn & Daniel Wartenberg, 1995. "Correlated Inputs in Quantitative Risk Assessment: The Effects of Distributional Shape," Risk Analysis, John Wiley & Sons, vol. 15(2), pages 215-219, April.
    18. Cynthia B. Van Landingham & Greg A Lawrence & Annette M Shipp, 2004. "Estimates of Lifetime‐Absorbed Daily Doses from the Use of Personal‐Care Products Containing Polyacrylamide: A Monte Carlo Analysis," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 603-619, June.
    19. Victor R. Vasquez & Wallace B. Whiting, 2005. "Accounting for Both Random Errors and Systematic Errors in Uncertainty Propagation Analysis of Computer Models Involving Experimental Measurements with Monte Carlo Methods," Risk Analysis, John Wiley & Sons, vol. 25(6), pages 1669-1681, December.
    20. Maged M. Hamed, 1997. "First‐Order Reliability Analysis of Public Health Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 17(2), pages 177-185, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:17:y:1997:i:5:p:649-656. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.