Estimating central tendency from a single spot measure: A closed-form solution for lognormally distributed biomarker data for risk assessment at the individual level

References

• Amann, A., de Lacy Costello, B., Miekisch, W., Schubert, J., Buszewski, B., Pleil, J. D., Ratcliffe, N., and Risby, T. H. 2014. The human volatilome: Volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva. J. Breath Res. 8:034001.
   PubMed Web of Science ®Google Scholar
• Angrish, M. M., Pleil, J. D., Stiegel, M. A., Madden, M. C., Moser, V. C., and Herr, D. W. 2016. Taxonomic applicability of inflammatory cytokines in adverse outcome pathway (AOP) development. J. Environ. Health: A. 26:13.
   Google Scholar
• Aylward, L. L., Kirman, C. R., Adgate, J. L., McKenzie, L. M., and Hays, S. M. 2012. Interpreting variability in population biomonitoring data: Role of elimination kinetics. J. Expos. Sci. Environ. Epidemiol. 22:398–408.
   PubMed Web of Science ®Google Scholar
• Aylward, L. L., Kirman, C. R., Schoeny, R., Portier, C. J., Hays, and S. M. 2013. Evaluation of biomonitoring data from the CDC National Exposure Report in a risk assessment context: Perspectives across chemicals. Environ. Health Perspect. 121:287–294.
   Google Scholar
• Bean, H. D., Pleil, J. D., and Hill, J. E. 2015. Report: New analytical and statistical approaches for interpreting the relationships among environmental stressors and biomarkers. Biomarkers 20:1–4.
   PubMed Web of Science ®Google Scholar
• Centers for Disease Control and Prevention. 2015. National Health and Nutrition Examination Study. http://www.cdc.gov/nchs/nhanes.htm
   Google Scholar
• Crawford‐Brown, D. J. 1997. Theoretical and mathematical foundations of human health risk analysis: Biophysical theory of environmental health science. New York, NY: Kluwer Academic Publishers, Springer US.
   Google Scholar
• Frazzoli, C., Bocca, B., and Mantovani, A. 2015. The one health perspective in trace elements biomonitoring. J. Toxicol. Environ. Health B 18: 344–370.
   PubMed Web of Science ®Google Scholar
• Furusawa, C., Suzuki, T., Kashiwagi, A., Yomo, T., and Kaneko, K. 2005. Ubiquity of log-normal distributions in intra-cellular reaction dynamic. Biophysics 1:25–40.
   Google Scholar
• Halloy, S. R., and Whigham, P. A. 2004. The lognormal as universal descriptor of unconstrained complex systems: A unifying theory for complexity. Proc. 7th Asia-Pacific Complex Systems Conference, pp. 309–320.
   Google Scholar
• Hays, S. M., Becker, R. A., Leung, H. W., Aylward, L. L., and Pyatt, D. W. 2007. Biomonitoring equivalents: a screening approach for interpreting biomonitoring results from a public health risk perspective. Regul. Toxicol. Pharmacol. 47: 96–109.
   PubMed Web of Science ®Google Scholar
• Johnson, C. L., Paulose-Ram, R., Ogden, C. E., Carroll, M. D., Kruszon-Moran, D., Dohrmann, S. M., and Curtin, L. R. 2013. National Health and Nutrition Examination Survey: Analytic guidelines, 1999–2010. Vital and health statistics. Series 2. Data Eval. Methods Res. 161:1–24.
   Google Scholar
• Koch, H. M., Aylward, L. L., Hays, S. M., Smolders, R., Moos, R. K., Cocker, J., Jones, K., Warren, N., Levy, L., and Bevan, R. 2014. Inter- and intra-individual variation in urinary biomarker concentrations over a 6-day sampling period. Part 2: Personal care product ingredients. Toxicol. Lett., 231: 261–269.
   PubMed Web of Science ®Google Scholar
• Kweon, S., Kim, Y., Jang, M. J., Kim, Y., Kim, K., Choi, S., Chun, C., Khang, Y. H., and Oh, K. 2014. Data resource profile: The Korea National Health and Nutrition Examination Survey (KNHANES). Int. J. Epidemiol. 43: 69–77.
   PubMed Web of Science ®Google Scholar
• Li, Z., Romanoff, L. C., Lewin, M. D., Porter, E. N., Trinidad, D. A., Needham, L. L., Patterson, D. G., and Sjödin, A., 2010. Variability of urinary concentrations of polycyclic aromatic hydrocarbon metabolite in general population and comparison of spot, first-morning, and 24-h void sampling. J. Expos. Sci. Environ. Epidemiol. 20: 526535.
   Web of Science ®Google Scholar
• Limpert, E., Stahel, W. A., and Abbt, M, 2001. Lognormal distributions across the sciences: Keys and clues. Bioscience 51: 341352.
   Web of Science ®Google Scholar
• Lindstrom, A. B., and Pleil, J. D. 2002. A review of the USEPA’s single breath canister (SBC) method for exhaled volatile organic biomarkers. Biomarkers 7: 189–208.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D. 2009. Influence of systems biology response and environmental exposure level on between-subject variability in breath and blood biomarkers. Biomarkers 14: 560–571.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D. 2015. Understanding new “exploratory” biomarker data: A first look at observed concentrations and associated detection limits. Biomarkers 20: 168–169.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D. 2016a. Cellular respiration: Recreating in vivo systems biology for in vitro exploration of human exposome and microbiome biomarkers. J. Breath Res., 10:010201.
   Web of Science ®Google Scholar
• Pleil, J. D. 2016b. Comparing biomarker measurements to a normal range: When to use standard error of the mean (SEM) or standard deviation (SD) confidence intervals tests. Biomarkers. doi:10.3109/1354750X.2015.1134666
   PubMed Web of Science ®Google Scholar
• Pleil, J. D., Beauchamp, J. D., Miekisch, W., and Funk, W. E. 2015. Adapting biomarker technologies to adverse outcome pathways (AOPs) research: Current thoughts on using in vivo discovery for developing in vitro target methods. J. Breath Res. 9: 039001.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D., and Sheldon, L. S. 2011. Adapting concepts from systems biology to develop systems exposure event networks for exposure science research. Biomarkers 16: 99–105.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D., Smith, L. B., and Zelnick, S. D. 2000. Personal exposure to JP-8 jet fuel and exhaust at Air Force bases. Environ. Health Perspect. 108: 183–192.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D., and Sobus, J. R., 2013. Estimating lifetime risk from spot biomarker data and intra-class correlation coefficients (ICC). J. Toxicol. Environ. HealthA 76: 747–766.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D., Sobus, J. R., Stiegel, M. A., Hu, D., Oliver, K. D., Olenick, C., Strynar, M. J., Clark, M., Madden, M. C., and Funk, W. E. 2014. Estimating common parameters of log-normally distributed environmental and biomonitoring data: Harmonizing disparate statistics from publications. J. Toxicol. Environ. Health B. 17: 341–368.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D., Stiegel, M. A., Sobus, J. R., Liu, Q., and Madden, M. C. 2011. Observing the human exposome as reflected in breath biomarkers: Heat map data interpretation for environmental and intelligence research. J. Breath Res. 5: 037104.
   PubMed Web of Science ®Google Scholar
• Pleil, J. D., Williams, M., and Sobus, J. R. 2012. Chemical Safety for Sustainability (CSS): Biomonitoring in vivo data for distinguishing among adverse, adaptive, and random responses from in vitro toxicology. Toxicol. Lett. 215: 201–207.
   PubMed Web of Science ®Google Scholar
• Rappaport, S. M. 1991. Assessment of long-term exposure to toxic substances in air. Ann. Occup. Hyg. 35: 61–121.
   PubMed Web of Science ®Google Scholar
• Rappaport, S. M., and Kupper, L. L. 2011. Quantitative exposure assessment. Raleigh, NC: LuLu Press.
   Google Scholar
• Rappaport, S. M., and Smith, M. T. 2010. Environment and disease risk. Science 330: 460–461.
   PubMed Web of Science ®Google Scholar
• Schreinemachers, D. M., Ghio, A. J., Sobus, J. R., and Williams, M. A. 2015. Perchlorate exposure is associated with oxidative stress and indicators of serum iron homeostasis among NHANES 2005–2008 subjects. Biomarker Insights 10: 9–19.
   PubMed Web of Science ®Google Scholar
• Schulz, C., Angerer, J., Ewers, U., and Kolossa-Gehring, M. 2007. The German Human Biomonitoring Commission. Int. J. Hyg. Environ. Health 210: 373–382.
   PubMed Web of Science ®Google Scholar
• Sobus, J. R., Dewoskin, R. S., Tan. Y. M., Pleil, J. D., Phillips, M. B., George, B. J., Christensen, K. Y., Schreinemachers, D. M., Williams, M. A., Cohen-Hubal, E. A., and Edwards, S. W. 2015. Uses of NHANES biomarker data for chemical risk assessment: Trends, challenges and opportunities. Environ. Health Perspect. 123: 919–927.
   PubMed Web of Science ®Google Scholar
• Sobus, J. R., McClean, M. D., Herrick, R. F., Waidyanatha, S., Onyemauwa, F., Kupper, L. L., and Rappaport, S. M. 2009a. Investigation of PAH biomarkers in the urine of workers exposed to hot asphalt. Ann. Occup. Hyg. 53: 551–560.
   PubMed Web of Science ®Google Scholar
• Sobus, J. R., McClean, M. D., Herrick, R. F., Waidyanatha, S., Nylander-French, L. A., Kupper, L. L., and Rappaport, S. M. 2009b. Comparing urinary biomarkers of airborne and dermal exposure to polycyclic aromatic compounds in asphalt-exposed workers. Ann. Occup. Hyg. 53: 561–571.
   PubMed Web of Science ®Google Scholar
• Sobus, J. R., Pleil, J. D., McClean, M. D., Herrick, R. F., and Rappaport, S. M. 2010. Biomarker variance component estimation for exposure surrogate selection and toxicokinetic inference. Toxicol. Lett. 199: 247–253.
   PubMed Web of Science ®Google Scholar
• Sobus, J. R., Tan, Y. M., Pleil, J. D., and Sheldon, L. S. 2011. A biomonitoring framework to support exposure and risk assessments. Sci. Total Environ. 409: 4875–4884.
   PubMed Web of Science ®Google Scholar
• Statistics Canada. 2014. Canadian Health Monitoring Survey. http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=5071
   Google Scholar
• Wild, C. P. 2005. Complementing the genome with an “exposome”: The outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol. Biomarkers Prev. 14: 1847–1850.
   Web of Science ®Google Scholar