Publications : 2016

Rager J, Thompson C, Auerbach S, Fry R. 2016. Integrating genomic and epigenomic data into risk assessment applications through dose response modeling: Case study with prenatal arsenic exposure. Environmental Mutagenesis and Genomics Society, September 25, Kansas City, KS. 


Prenatal and early-life exposure to inorganic arsenic (iAs) is known to adversely impact the health of newborns. Recent investigations have shown that prenatal arsenic exposure influences the expression of genes and proteins, in part through epigenetic mediators, which are in turn associated with adverse outcomes. The doses at which these genomic and epigenomic changes occur, however, have yet to be evaluated. This study set out to estimate arsenic doses that correspond to changes in genomic and epigenomic signatures in human cord blood through benchmark dose (BMD) modeling, and identify which omic responses are the most sensitive to iAs exposure. Genome-wide DNA methylation, microRNA expression, mRNA expression, and protein expression levels in cord blood were modeled against total urinary arsenic (UtAs) levels from humans exposed to varying levels of iAs, primarily through drinking water. Dose-response relationships were modeled in BMDExpress using the Hill, Power, Linear, and Polynomial 2 models. The best fitting models were used to calculate BMD values representing an estimated 10% response level for each molecule. Overall, DNA methylation changes were estimated to have lower BMDs in comparison to other molecular endpoints. Assessment of BMD distributions showed that genomic and epigenomic changes are estimated to occur at low levels of iAs exposure, with ~55% of the BMD estimates at UtAs concentrations less than 50 µg/L. These changes were enriched for organism development and neurotransmitter signaling. Findings from this study bridge genomic and epigenomic research into applications relevant to risk assessment through BMD modeling.