A high-throughput analysis of woman ovarian cycle disruption by mixtures of aromatase inhibitors

Background: Combining computational toxicology with ExpoCast exposure data and ToxCast assay data gives us access to predictions of human health risks stemming from realistic exposures to chemical mixtures. Objectives: To quantify, through mathematical modeling and simulations, the size of potential effects of random mixtures of aromatase inhibitors on the dynamics of women's menstrual cycle. Methods: We simulated random exposures to millions of potential mixtures of up to 256 aromatase inhibitors. A pharmacokinetic model of intake and disposition of the chemicals predicted their internal concentration as a function of time (up to two years). A ToxCast aromatase assay provided concentration-inhibition relationships for each chemical. The resulting total aromatase inhibition was input to a mathematical model of the hormonal hypothalamus-pituitary-ovarian control of ovulation in women. Results: Above 10% inhibition of estradiol synthesis by aromatase inhibitors, noticeable (eventually reversible) effects on ovulation were predicted. Exposures to individual chemicals never led to such effects. Typically, more than 10% of the combined exposures simulated had mild to catastrophic impacts on ovulation. Conclusions: Those results demonstrate the possibility to predict large scale mixture effects for endocrine disrupters with a predictive toxicology approach, suitable for high throughput ranking and risk assessment. The size of the effects predicted is consistent with an increased risk of infertility in women from daily life exposures to our chemical environment.