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Application of benchmark dose modeling to protein expression data in the development and analysis of mode of action/adverse outcome pathways for testicular toxicity
Author(s) -
Chepelev Nikolai L.,
Meek M. E. Bette,
Yauk Carole Lyn
Publication year - 2014
Publication title -
journal of applied toxicology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.784
H-Index - 87
eISSN - 1099-1263
pISSN - 0260-437X
DOI - 10.1002/jat.3071
Subject(s) - adverse outcome pathway , toxicant , mode of action , adverse effect , concordance , risk assessment , pharmacology , toxicity , bioinformatics , computational biology , toxicogenomics , biology , toxicology , medicine , gene expression , computer science , gene , genetics , computer security
Reliable quantification of gene and protein expression has potential to contribute significantly to the characterization of hypothesized modes of action (MOA) or adverse outcome pathways for critical effects of toxicants. Quantitative analysis of gene expression by benchmark dose (BMD) modeling has been facilitated by the development of effective software tools. In contrast, protein expression is still generally quantified by a less robust effect level (no or lowest [adverse] effect levels) approach, which minimizes its potential utility in the consideration of dose–response and temporal concordance for key events in hypothesized MOAs. BMD modeling is applied here to toxicological data on testicular toxicity to investigate its potential utility in analyzing protein expression relevant to the proposed MOA to inform human health risk assessment. The results illustrate how the BMD analysis of protein expression in animal tissues in response to toxicant exposure: (1) complements other toxicity data, and (2) contributes to consideration of the empirical concordance of dose–response relationships, as part of the weight of evidence for hypothesized MOAs to facilitate consideration and application in regulatory risk assessment. Lack of BMD analysis in proteomics has likely limited its use for these purposes. This paper illustrates the added value of BMD modeling to support and strengthen hypothetical MOAs as a basis to facilitate the translation and uptake of the results of proteomic research into risk assessment. Copyright © 2014 Her Majesty the Queen in Right of Canada. Journal of Applied Toxicology © 2014 John Wiley & Sons, Ltd.