LAUSR

BACKGROUND Acrylamide toxicity involves several metabolic pathways. Thus, a panel of blood and urinary biomarkers for the evaluation of acrylamide exposure was deemed appropriate. OBJECTIVE The study was designed to evaluate daily acrylamide exposure in US adults via hemoglobin adducts and urinary metabolites using a pharmacokinetic framework. METHODS A cohort of 2798 subjects aged 20-79 was selected from the National Health and Nutrition Examination Survey (NHANES, 2013-2016) for analysis. Three acrylamide biomarkers including hemoglobin adducts of acrylamide in blood and two urine metabolites, N-Acetyl-S-(2-carbamoylethyl)cysteine (AAMA) and N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-l-cysteine (GAMA) were used to estimate daily acrylamide exposure using validated pharmacokinetic prediction models. Multivariate regression models were also used to examine key factors in determining estimated acrylamide intake. RESULTS The estimated daily acrylamide exposure varied across the sampled population. Estimated acrylamide daily exposure was comparable among the three different biomarkers (median: 0.4-0.7 μg/kg/d). Cigarette smoking emerged as the leading contributor to the acquired acrylamide dose. Smokers had the highest estimated acrylamide intake (1.20-1.49 μg/kg/d) followed by passive smokers (0.47-0.61) and non-smokers (0.45-0.59). Several covariates, particularly, body mass index and race/ethnicity, played roles in determining estimated exposures. DISCUSSION Estimated daily acrylamide exposures among US adults using multiple acrylamide biomarkers were similar to populations reported elsewhere providing additional support for using the current approach in assessing acrylamide exposure. This analysis assumes that the biomarkers used indicate intake of acrylamide into the body, which is consistent with the substantial known exposures due to diet and smoking. Although this study did not explicitly evaluate background exposure arising from analytical or internal biochemical factors, these findings suggest that the use of multiple biomarkers may reduce uncertainties regarding the ability of any single biomarker to accurately represent actual systemic exposures to the agent. This study also highlights the value of integrating a pharmacokinetic approach into exposure assessments.