Abstract |
Current efforts to assess human health response to chemicals based on high-throughput in vitro assay data on intra-cellular changes have been hindered for some illnesses by lack of information on higher-level extracellular, inter-organ, and organism-level interactions. However, a dose-response function (DRF), informed by various levels of information including apical health response, can represent a template for convergent top-down, bottom-up analysis. In this paper, a general DRF for chronic chemical and other health stressors and mixtures is derived based on a general first-order model previously derived and demonstrated for illness progression. The derivation accounts for essential autocorrelation among initiating event magnitudes along a toxicological mode of action, typical of complex processes in general, and reveals the inverse relationship between the minimum illness-inducing dose, and the illness severity per unit dose (both variable across a population). The resulting emergent DRF is theoretically scale-inclusive and amenable to low-dose extrapolation. The two-parameter single-toxicant version can be monotonic or sigmoidal, and is demonstrated preferable to traditional models (multistage, lognormal, generalized linear) for the published cancer and non- cancer datasets analyzed: chloroform (induced liver necrosis in female mice); bromate (induced dysplastic focia in male inbred rats); and 2-acetylaminofluorene (induced liver neoplasms and bladder carcinomas in 20,328 female mice). Common- and dissimilar-mode mixture models are demonstrated versus orthogonal data on toluene/ benzene mixtures (mortality in Japanese medaka, Oryzias latipes, following embryonic exposure). Findings support previous empirical demonstration, and also reveal how a chemical with a typical monotonically-increasing DRF can display a J-shaped DRF when a second, antagonistic common-mode chemical is present. Overall, the general DRF derived here based on an autocorrelated first-order model appears to provide both a strong theoretical/biological basis for, as well as an accurate statistical description of, a diverse, albeit small, sample of observed dose-response data. The further generalizability of this conclusion can be tested in future analyses comparing with traditional modeling approaches across a broader range of datasets.
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Authors | James D Englehardt, Weihsueh A Chiu |
Journal | PloS one
(PLoS One)
Vol. 14
Issue 2
Pg. e0211780
( 2019)
ISSN: 1932-6203 [Electronic] United States |
PMID | 30768598
(Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, U.S. Gov't, Non-P.H.S.)
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Chemical References |
- Bromates
- Toluene
- Chloroform
- 2-Acetylaminofluorene
- Benzene
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Topics |
- 2-Acetylaminofluorene
(adverse effects, pharmacology)
- Animals
- Benzene
(adverse effects, pharmacology)
- Bromates
(adverse effects, pharmacology)
- Chloroform
(adverse effects, pharmacology)
- Dose-Response Relationship, Drug
- Mice
- Models, Biological
- Oryzias
- Rats
- Toluene
(adverse effects, pharmacology)
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