How can epidemiological data be used to better support mechanistic hypotheses in risk assessment?
Epidemiology uses observational data to assess the distribution of diseases across populations, usually with the aim of revealing possible disease causes. Associations noted between biomarkers of exposure and human health effects are commonly presumed to be causal but need to be carefully examined to eliminate confounding factors that may contribute to the observed association. Natural variation in physiology in different life stages or disease states may themselves affect pharmacokinetics. These changes could produce observed associations of biomarkers with disease or health outcomes. These association would not be causal but would suffer from pharmacokinetic bias.
Understanding the role of pharmacokinetic bias, also called reverse casualty, in observed association between biomarkers and health effects is essential from a public health policy perspective. ScitoVation and LRI have championed the development of a statistical framework for assessing the probability of various causal hypotheses for the relationship between biomarkers of exposure and health effects. Using these new methodologies, ACC has supported the development several case studies to investigate the role of pharmacokinetic bias in accounting for observed association of perfluoroalkyl substances with several reproductive effects and the association of polychlorinated biphenyls with diabetes.
Dzierlenga MW, Yoon M, Wania F, Ward PL, Armitage JM, Wood SA, Clewell HJ, Longnecker MP. (2019) Quantitative bias analysis of the association of type 2 diabetes mellitus with 2,2′,4,4′,5,5′-hexachlorobiphenyl (PCB-153). Environ Int. 125:291-299.
Ruark CD, Song G, Yoon M, Verner MA, Andersen ME, Clewell HJ, Longnecker MP. (2017) Quantitative bias analysis for epidemiological associations of perfluoroalkyl substance serum concentrations and early onset of menopause. Environ Int. 99:245-254.
Song G, Peoples CR, Yoon M, Wu H, Verner MA, Andersen ME, Clewell H, Longnecker MP. (2016) Pharmacokinetic bias analysis of the epidemiological associations between serum polybrominated diphenyl ether (BDE-47) and timing of menarche, Environ Res, 150, 541-548.
Wu H, Yoon M, Verner MA, Xue J, Luo M, Andersen ME, Longnecker MP, Clewell HJ. (2015) Can the observed association between serum perfluoroalkyl substances and delayed menarche be explained on the basis of puberty-related changes in physiology and pharmacokinetics? Environ. Int., 2015, 82: 61-68.