Title: A systems-based computational model for dose-response comparisons of two mode of action hypotheses for ethanol-induced neurodevelopmental toxicity.

Authors: Gohlke, J M; Griffith, W C; Faustman, E M

Published In Toxicol Sci, (2005 Aug)

Abstract: Investigations into the potential mechanisms for ethanol-induced developmental toxicity have been ongoing for over 30 years since Fetal Alcohol Syndrome (FAS) was first described. Neurodevelopmental endpoints are particularly sensitive to in utero exposure to alcohol as suggested by the more prevalent alcohol-related neurodevelopmental disorder (ARND). The inhibition of proliferation during neurogenesis and the induction of apoptosis during the period of synaptogenesis have been identified as potentially important mechanisms for ARND. However, it is unclear how these two mechanisms quantitatively relate to the dose and timing of exposure. We have extended our model of neocortical neurogenesis to evaluate apoptosis during synaptogenesis. This model construct allows quantitative evaluation of the relative impacts on neuronal proliferation versus apoptosis during neocortical development. Ethanol-induced lengthening of the cell cycle of neural progenitor cells during rat neocortical neurogenesis (G13-G19) is used to compute the number of neurons lost after exposure during neurogenesis. Ethanol-induced dose-dependent increases in cell death rates are applied to our apoptosis model during rat synaptogenesis (P0-P14), when programmed cell death plays a major role in shaping the future neocortex. At a human blood ethanol concentration that occurs after 3-5 drinks ( approximately 150 mg/dl), our model predicts a 20-30% neuronal deficit due to inhibition of proliferation during neurogenesis, while a similar exposure during synaptogenesis suggests a 7-9% neuronal loss through induction of cell death. Experimental in vitro and in vivo dose-response research and stereological research on long-term neuronal loss after developmental exposure to ethanol is compared to our model predictions. Our computational model allows for quantitative, systems-level comparisons of mechanistic hypotheses for perturbations during specific neurodevelopmental periods.

PubMed ID: 15917484

MeSH Terms: No MeSH terms associated with this publication