Epigenetics and Transcriptomics to Detect Adverse Drug Effects in Model Systems of Human Development

Abstract

Prenatal exposure to environmental chemicals or drugs has been associated with functional or structural deficits and the development of diseases in later life. For example, developmental neurotoxicity (DNT) is triggered by lead, and this compound may predispose to neurodegenerative diseases in later life. The molecular memory for such late consequences of early exposure is not known, but epigenetic mechanisms (modification of the chromatin structure) could take this role. Examples and underlying mechanisms have been compiled here for the field of DNT. Moreover, we addressed the question as to what readout is suitable for addressing drug memory effects. We summarize how complex developmental processes can be modelled in vitro by using the differentiation of human stem cells. Although cellular models can never replicate the final human DNT phenotype, they can model the adverse effect that a chemical has on key biological processes essential for organ formation and function. Highly information-rich transcriptomics data may inform on these changes and form the bridge from in vitro models to human prediction. We compiled data showing that transcriptome analysis can indicate toxicity patterns of drugs. A crucial question to be answered in our systems is when and how transcriptome changes indicate adversity (as opposed to transient adaptive responses), and how drug-induced changes are perpetuated over time even after washout of the drug. We present evidence for the hypothesis that changes in the histone methylation pattern could represent the persistence detector of an early insult that is transformed to an adverse effect at later time-points in life.

Functional AdoMet Isosteres Resistant to Classical AdoMet Degradation Pathways

“…5–15 Consistent with this, alterations in methylation-dependent processes are associated with cancer, 16 neurodegenerative/neuropsychiatric disorders, 17–19 inflammation, 20,21 metabolic disorders, 22 fundamental development/regenerative medicine, 23,24 susceptibility to disease/adverse drug response, 25,26 and drug resistance. 13–15,27,28 While there have been great advances in methylation-dependent bioinformatics and disease-associated biomarkers, 29–31 the study of intracellular MT spatial/temporal resolution, specificity, and/or function remains a challenge.…”

Reference compounds for alternative test methods to indicate developmental neurotoxicity (DNT) potential of chemicals: Example lists and criteria for their selection and use_suppl

“…In vitro toxicity testing is the major focus of the "biomarkers-of-toxicity" concept, which concerns the identification of measurable and predictive endpoints that can be applied to model systems. For the purpose of compound selection for DNT in vitro assays, the concept of "toxicity endophenotypes" contributes a useful perspective (Kadereit et al, 2012;Balmer and Leist, 2014;Bal-Price et al, 2015a) (Fig. 2).…”

Animal use for science in Europe

“…Besides the development of new technologies (Leist et al, 2012b), such as metabolomics (Ramirez et al, 2013;Bouhifd et al, 2015), high-content imaging (van Vliet et al, 2014) or epigenetic profiling (Balmer et al, 2012Balmer and Leist, 2014), the most important new developments in the field are high throughput assays (Judson et al, 2014) of 3D models (Alepee et al, 2014) and of stem cell-derived human non-transformed cells. Concerning the evaluation of toxicological data, two major scientific principles are being developed (Daston et al, 2015;Gocht et al, 2015): i) the improvement of readacross and rational toxicant grouping to incorporate biological data in addition to (or even instead of) chemical structure data (Kleinstreuer et al, 2014;Patlewicz et al, 2014); and ii) systems toxicology approaches that are rather qualitative, such as adverse outcome pathways (AOP), or that try to use more quantitative systems biology information, like pathways of toxicity (Hartung, 2012;Rovida et al, 2015;Sauer et al, 2015;Bouhifd et al, 2013Bouhifd et al, , 2014Bouhifd et al, , 2015Kleensang et al, 2014;Whelan and Andersen, 2013;Sturla and Hollenberg, 2014).…”