Integration of biomonitoring data and reverse dosimetry modeling to assess population risks of arsenic-induced chronic kidney disease and urinary cancer

Abstract

Chronic exposure to inorganic arsenic (iAs) is associated with chronic kidney disease (CKD) and urinary cancer, but the risks are poorly understood. Human biomonitoring can serve as a tool to better quantify human exposure and to conduct risk assessment. We aimed to assess the population risks of CKD and urinary cancer due to iAs intake based on the blood arsenic concentrations of 601 participants in Taiwan. A physiologically based pharmacokinetic modeling-based reverse dosimetry was conducted to estimate the daily intakes of iAs (DIiAs). We performed the benchmark dose (BMD) modeling for CKD using participants’ estimated glomerular filtration rate (eGFR) and the estimated DIiAs to derive a point of departure (POD). Margin of exposure (MOE) was used to characterize the risks. The population with eGFR values of <60 mL/min/1.73 m2 had significantly higher DIiAs (median: 3.20 μg/kg/day, 2.5th–97.5th percentiles: 2.35–4.67 μg/kg/day) than those with normal renal function (1.99, 1.22–3.42 μg/kg/day). The POD for CKD was 1.557 μg/kg/day, which could serve as a possible reference value for CKD risk assessment. The MOEs indicated that the CKD risk due to iAs intake may potentially be a cause for high concern for the population with reduced renal function. The iAs-induced urinary cancer risk may be a cause for moderate-to-high concern.