The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA)--i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on "augmentation" of weight of evidence--using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards "integration" of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for "expansion" of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual "reorientation" of QRA towards approaches that more directly link environmental exposures to human outcomes.
Keywords: ATSDR; Agency for Toxic Substances and Disease Registry; BMD; Biomarkers; DNA–protein crosslinks; DPX; Dose–response assessment; EPA; Environmental Protection Agency; GO; GST; HT/HC; HuGE; Human Genome Epidemiology; IQ; IRIS; Integrate Risk Information System; LOAEL; MOA; Molecular epidemiology; NCCT; NOAEL; NOTEL; NRC; National Center for Computational Toxicology; National Research Council; POD; QRA; RfC; RfD; Risk assessment; Toxicogenomics; benchmark dose; gene ontology; glutathione-S-transferase; high throughput/high content; intelligence quotient; lowest observed adverse effect level; mode of action; no observed adverse effect level; no observed transcriptional effect level; point of departure; quantitative risk assessment; reference concentration; reference dose.
Published by Elsevier Inc.