title: Predictive models of prenatal developmental toxicity from ToxCast high-throughput screening data.
abstract: Environmental Protection Agency's ToxCast project is profiling the in vitro bioactivity of chemicals to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesized that developmental toxicity in guideline animal studies captured in the ToxRefDB database would correlate with cell-based and cell-free in vitro high-throughput screening (HTS) data to reveal meaningful mechanistic relationships and provide models identifying chemicals with the potential to cause developmental toxicity. To test this hypothesis, we built statistical associations based on HTS and in vivo developmental toxicity data from ToxRefDB. Univariate associations were used to filter HTS assays based on statistical correlation with distinct in vivo endpoint. This revealed 423 total associations with distinctly different patterns for rat (301 associations) and rabbit (122 associations) across multiple HTS assay platforms. From these associations, linear discriminant analysis with cross-validation was used to build the models. Species-specific models of predicted developmental toxicity revealed strong balanced accuracy (> 70%) and unique correlations between assay targets such as transforming growth factor beta, retinoic acid receptor, and G-protein-coupled receptor signaling in the rat and inflammatory signals, such as interleukins (IL) (IL1a and IL8) and chemokines (CCL2), in the rabbit. Species-specific toxicity endpoints were associated with one another through common Gene Ontology biological processes, such as cleft palate to urogenital defects through placenta and embryonic development. This work indicates the utility of HTS assays for developing pathway-level models predictive of developmental toxicity.
authors.affiliation: National Center for Computational Toxicology, Office of Research & Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA. sipes.nisha@epa.gov
authors.forename: Nisha S
authors.initials: NS
authors.lastname: Sipes
authors.forename: Matthew T
authors.initials: MT
authors.lastname: Martin
authors.forename: David M
authors.initials: DM
authors.lastname: Reif
authors.forename: Nicole C
authors.initials: NC
authors.lastname: Kleinstreuer
authors.forename: Richard S
authors.initials: RS
authors.lastname: Judson
authors.forename: Amar V
authors.initials: AV
authors.lastname: Singh
authors.forename: Kelly J
authors.initials: KJ
authors.lastname: Chandler
authors.forename: David J
authors.initials: DJ
authors.lastname: Dix
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Kavlock
authors.forename: Thomas B
authors.initials: TB
authors.lastname: Knudsen
mesh_terms: D000818:Animals; D000013:Congenital Abnormalities / Q000209:etiology*; D016208:Databases, Factual; D047108:Embryonic Development / Q000187:drug effects; D023381:Endpoint Determination; D004785:Environmental Pollutants / Q000145:classification / Q000633:toxicity*; D047109:Fetal Development / Q000187:drug effects; D057166:High-Throughput Screening Assays; D008954:Models, Biological; D011817:Rabbits; D051381:Rats; D013045:Species Specificity; D013723:Teratogens / Q000145:classification / Q000633:toxicity*; D014481:United States; D014484:United States Environmental Protection Agency
chemical_list: D004785:Environmental Pollutants; D013723:Teratogens