Mixture risk assessment of pesticides with acute neurotoxic effects: a novel approach based on urinary exposure biomarkers.

Abstract

Pesticides showing neurotoxic effects, including organophosphates, pyrethroids, and N-methyl carbamates, are widely used in agriculture. Human biomonitoring (HBM) integrates exposure from multiple sources and routes by measuring pesticide levels in human biological samples. This study applied a novel MRA methodology using urinary biomarkers, focusing on two cumulative assessment groups (CAGs) of pesticides with acute neurotoxic effects, as previously established by the European Food Safety Authority (EFSA), namely, CAG-NAN on brain and/or erythrocyte acetylcholinesterase inhibition; and CAG-NAM on functional alterations of the motor, sensory and autonomic division. Available urinary pesticide metabolites were assigned to potential parent compounds within these CAGs and were converted to external exposure levels, expressed as estimated daily intakes (EDI), using reverse dosimetry. Toxicological reference points, i.e., no observed adverse effect levels (NOAEL) were obtained from EFSA report. For each parent compound, the ratio of the NOAEL to the EDI was calculated, and these ratios were used to determine the total margin of exposure (MOET). This approach was applied as a proof-of-concept to children and adults from 10 HBM studies across seven European countries. For CAG-NAN, median MOET ranged between 27 and 2485 across datasets with percentage of individuals below a threshold of 100 from 2.8 to 97%. For CAG-NAM median MOET values ranged from 34 to 220 000 and in one scenario the percentage of individuals below the threshold was between 24% for children and up to 93% for adults. Azinphos-ethyl, triazophos, omethoate, and chlorpyrifos were identified as risk drivers. This study highlights the need for improved MRA methodologies based on HBM data, including the development of pesticide-specific exposure biomarkers, and the establishment of human biomonitoring-guidance values (HBM-GVs). Incorporating HBM data strengthens human health MRA by reducing uncertainty surrounding non-dietary exposure and generating valuable evidence to inform future pesticide monitoring and regulatory strategies.