ERGO: Breaking Down the Wall between Human Health and Environmental Testing of Endocrine Disrupters.
Henrik HolbechPeter MatthiessenMartin HansenGerrit SchüürmannDries KnapenMarieke ReuverFrédéric FlamantLaurent M SachsWerner KloasKlara HilscherovaMarc LeonardJürgen ArningVolker StraussTaisen IguchiLisa BaumannPublished in: International journal of molecular sciences (2020)
ERGO (EndocRine Guideline Optimization) is the acronym of a European Union-funded research and innovation action, that aims to break down the wall between mammalian and non-mammalian vertebrate regulatory testing of endocrine disruptors (EDs), by identifying, developing and aligning thyroid-related biomarkers and endpoints (B/E) for the linkage of effects between vertebrate classes. To achieve this, an adverse outcome pathway (AOP) network covering various modes of thyroid hormone disruption (THD) in multiple vertebrate classes will be developed. The AOP development will be based on existing and new data from in vitro and in vivo experiments with fish, amphibians and mammals, using a battery of different THDs. This will provide the scientifically plausible and evidence-based foundation for the selection of B/E and assays in lower vertebrates, predictive of human health outcomes. These assays will be prioritized for validation at OECD (Organization for Economic Cooperation and Development) level. ERGO will re-think ED testing strategies from in silico methods to in vivo testing and develop, optimize and validate existing in vivo and early life-stage OECD guidelines, as well as new in vitro protocols for THD. This strategy will reduce requirements for animal testing by preventing duplication of testing in mammals and non-mammalian vertebrates and increase the screening capacity to enable more chemicals to be tested for ED properties.
Keyphrases
- human health
- emergency department
- risk assessment
- early life
- high throughput
- climate change
- transcription factor
- molecular docking
- electronic health record
- dna methylation
- machine learning
- genome wide
- human immunodeficiency virus
- hiv testing
- molecular dynamics simulations
- hiv infected
- single cell
- data analysis
- solid state