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2007 CompTox Forum

Abstract - A Physiologically Based Computational Model of the BPG Axis in Fathead Minnows: Predicting Effects of Endocrine Disrupting Chemical Exposure on Reproductive Endpoints

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Karen Watanabe[a], Zhenhong Li[a], Kevin Kroll[b], Natalia Reyero[b], Nancy Szabo[b], Marisol Sepúlveda[c], Edward Orlando[d], Daniel Villeneuve[e], Michael Breen[f], Gerald Ankley[e] and Nancy Denslow[b]

Karen H. Watanabe, Ph.D. (presenting author)
Assistant Professor
Department of Environmental and Biomolecular Systems
Oregon Health & Science University
20000 NW Walker Road, Beaverton, OR 97006
Phone: 503-748-1217
E-mail: watanabe@ebs.ogi.edu

Some endocrine active compounds (EACs) have been shown to cause adverse reproductive effects in wildlife and humans when exposures occur at high doses or at inappropriate times in the life cycle. To further our understanding of how EACs affect reproduction in a small fish species, the fathead minnow (FHM, Pimephales promelas), a physiologically based computational model has been developed. Our model simulates the brain-pituitary-gonadal (BPG) axis and other endpoints important in reproduction such as concentrations of sex steroid hormones, 17β-estradiol (E2), testosterone (T), 11-ketotestosterone (11-KT), and vitellogenin (Vtg), a precursor to the major egg yolk protein. Additionally, our model simulates the pharmacokinetics of an environmentally relevant estrogenic EAC, 17α-ethynylestradiol (EE2). The model was calibrated with data from: (i) unexposed FHM collected by scientists from the Mid-Continent Ecology Division, U.S. Environmental Protection Agency; and, (ii) FHM exposed to 50 ng EE2/L for 48 hours under 24-hour static replacement conditions at the University of Florida. Markov Chain Monte Carlo simulations were used to estimate unknown model parameters including kinetic rate constants for certain steroid hormone reactions and the elimination of EE2. Two thousand parameter sets (the last 500 parameter sets from each of four Markov chains) were obtained through model calibration. The parameter sets and model were then used to predict values of endpoints measured in unexposed FHM that were not used in the model calibration phase. In general, we found good agreement between our model predictions of E2, 11-KT, and Vtg, though the variance of the model predictions is smaller than the variance observed in the data from unexposed FHM. The model predicted values of T were about a factor of 3 lower than measurements of T in unexposed FHM. We conclude that this model provides a reasonable representation of the BPG axis in FHM, and that additional experimental data are needed to validate some of the other endpoints predicted by the model.

  1. Oregon Health & Science University, Department of Environmental and Biomolecular Systems
  2. University of Florida, Department of Physiological Sciences
  3. Purdue University, Department of Forestry & Natural Resources
  4. Florida Atlantic University, Department of Biological Sciences
  5. U.S. EPA/ORD/NHEERL/Mid-Continent Ecology Division
  6. U.S. EPA/ORD/National Center for Computational Toxicology

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