ArticleToxicological sciences : an official journal of the Society of Toxicology2016
Generalized Concentration Addition Modeling Predicts Mixture Effects of Environmental PPARγ Agonists.
Article in Toxicological sciences : an official journal of the Society of Toxicology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 30 citations in OpenAlex.
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- Chemical mixture that targets the epidermal growth factor pathway impairs human trophoblast cell functions.Toxicology and applied pharmacology · 2024Article
- Equations for estimating binary mixture toxicity: 3-methyl-2-butanone with a series of electrophiles.PloS one · 2024Article
- A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target.The Science of the total environment · 2023Article
- Sensitive image-based chromatin binding assays using inducible ERα to rapidly characterize estrogenic chemicals and mixtures.iScience · 2022Article
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- Predicting the effects of per- and polyfluoroalkyl substance mixtures on peroxisome proliferator-activated receptor alpha activity in vitro.Toxicology · 2022Article
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- PFAS and Potential Adverse Effects on Bone and Adipose Tissue Through Interactions With PPARγ.Endocrinology · 2021Review
- Physiologically based kinetic modelling based prediction of in vivo rat and human acetylcholinesterase (AChE) inhibition upon exposure to diazinon.Archives of toxicology · 2021Article
- Predicting the Activation of the Androgen Receptor by Mixtures of Ligands Using Generalized Concentration Addition.Toxicological sciences : an official journal of the Society of Toxicology · 2020Article
- Generalized concentration addition for ligands that bind to homodimers.Mathematical biosciences · 2019Article
- Assessment of total, ligand-induced peroxisome proliferator activated receptor γ ligand activity in serum.Environmental health : a global access science source · 2019Article
- Generalized Concentration Addition Model Predicts Glucocorticoid Activity Bioassay Responses to Environmentally Detected Receptor-Ligand Mixtures.Toxicological sciences : an official journal of the Society of Toxicology · 2019Article
- Acute toxicity of copper hydroxide and glyphosate mixture in Clarias gariepinus: interaction and prediction using mixture assessment models.Environmental health and toxicology · 2019Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The vast array of potential environmental toxicant combinations necessitates the development of efficient strategies for predicting toxic effects of mixtures. Current practices emphasize the use of concentration addition to predict joint effects of endocrine disrupting chemicals in coexposures. Generalized concentration addition (GCA) is one such method for predicting joint effects of coexposures to chemicals and has the advantage of allowing for mixture components to have differences in efficacy (ie, dose-response curve maxima). Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that plays a central role in regulating lipid homeostasis, insulin sensitivity, and bone quality and is the target of an increasing number of environmental toxicants. Here, we tested the applicability of GCA in predicting mixture effects of therapeutic (rosiglitazone and nonthiazolidinedione partial agonist) and environmental PPARγ ligands (phthalate compounds identified using EPA's ToxCast database). Transcriptional activation of human PPARγ1 by individual compounds and mixtures was assessed using a peroxisome proliferator response element-driven luciferase reporter. Using individual dose-response parameters and GCA, we generated predictions of PPARγ activation by the mixtures, and we compared these predictions with the empirical data. At high concentrations, GCA provided a better estimation of the experimental response compared with 3 alternative models: toxic equivalency factor, effect summation and independent action. These alternatives provided reasonable fits to the data at low concentrations in this system. These experiments support the implementation of GCA in mixtures analysis with endocrine disrupting compounds and establish PPARγ as an important target for further studies of chemical mixtures.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.