New thesis on novel approaches to identify endocrine disruptors
Welcome to Linus Wiklunds presentation of his thesis ”Advancing assessments of endocrine disruptors using adverse outcome pathways and novel methodologies”.
Time: October 17 at 13.00
Location: Inghesalen, Tomtebodavägen 18a and online
Supervisor: Anna Beronius, Associate Professor, Institute of Environmental Medicine (IMM)
Opponent: George Kass, Professor, University of Galway, College of Medicine, Nursing and Health Sciences
Zoom: https://ki-se.zoom.us/j/69541953684?pwd=Kqbb0mHd8mNqdxaibFaEIaNIcbaiga.1
Three questions to Linus
What is the thesis about?
In my thesis, I develop and explore novel methodologies for health risk assessment of chemicals, aiming to increase the use of data from in silico, in chemico and in vitro methods to identify endocrine disruptors (EDs). The included studies explore how mechanistic data from these types of methods can be linked to adverse health effects in humans, and ultimately how these data can be used to predict adversity without the need for animal testing. To do this, we used Adverse Outcome Pathways (AOPs) to structure and connect different types of data. An AOP is a conceptual framework that describes a chain of biological events, connecting early molecular and cellular events to an adverse health effect.
Can you tell us about some interesting results?
In the second study of my thesis, we investigated whether perfluorooctane sulfonic acid (PFOS) can be identified as an ED, and to what extent the ED assessment could be conducted without using toxicity data from animal studies. First, using animal data, we concluded that PFOS can be considered an ED. Then, for the ‘animal-free’ assessment, we anchored data from in silico, in chemico and in vitro methods to relevant AOPs, linking these early mechanistic data to adverse effects. While this approach clearly showed that PFOS can disturb endocrine signalling, we could not provide evidence of an adverse health effect. A major limitation was the lack of quantitative information in the AOPs, which prevented us from predicting if the effects on the early mechanistic events would lead to a downstream adverse effect on an organism.
Therefore, in the fourth study, we developed a method to quantify part of an AOP. We then used this method to quantify the relationship between an endocrine mechanism (decreased testosterone levels) and an adverse health effect (decreased sperm count). The resulting statistical model can be used to predict decreases in sperm count based on decreased circulating testosterone levels, which can support ‘animal-free’ ED assessments like the one described above.
What further research is needed in the area?
It is important to evaluate how the novel methodologies that were developed perform when investigating different types of compounds, for example chemicals with very little data. It would also be interesting to see how well the methodologies can distinguish between well-known EDs and chemicals without any endocrine activity, or how the inclusion of human data can support the assessments.
We also need to further develop our understanding of the endocrine system and develop more non-animal methods to measure disturbances on this system, to have enough information and (reliable) data for non-animal ED assessments in the future.