Combined exposure to endocrine disrupting pesticides impairs parturition, causes pup mortality and affects sexual differentiation in rats

Abstract

Risk assessment is currently based on the no observed adverse effect levels (NOAELs) for single compounds. Humans are exposed to a mixture of chemicals and recent studies in our laboratory have shown that combined exposure to endocrine disrupters can cause adverse effects on male sexual development, even though the doses of the single compounds are below their individual NOAELs for anti-androgenic effects. Consequently, we have initiated a large project where the purpose is to study mixture effects of endocrine disrupting pesticides at low doses. In the initial range-finding mixture studies, rats were gavaged during gestation and lactation with five doses of a mixture of the fungicides procymidone, mancozeb, epoxyconazole, tebuconazole and prochloraz. The mixture ratio was chosen according to the doses of each individual pesticide that produced no observable effects on pregnancy length and pup survival in our laboratory and the dose levels used ranged from 25 to 100% of this mixture. All dose levels caused increased gestation length and dose levels above 25% caused impaired parturition leading to markedly decreased number of live born offspring and high pup perinatal mortality. The sexual differentiation of the pups was affected at 25% and higher as anogenital distance was affected in both male and female offspring at birth and the male offspring exhibited malformations of the genital tubercle, increased nipple retention, and decreased prostate and epididymis weights at pup day 13. The results show that doses of endocrine disrupting pesticides, which appear to induce no effects on gestation length, parturition and pup mortality when judged on their own, induced marked adverse effects on these endpoints in concert with other pesticides. In addition, the sexual differentiation of the offspring was affected. This as well as the predictability of the combination effects based on dose-additivity modelling will be studied further in a large dose-response study.