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  • 1.
    Audouze, Karine
    et al.
    Université de Paris, T3S, Inserm U1124, Paris, France.
    Zgheib, Elias
    Université de Paris, T3S, Inserm U1124, Paris, France.
    Abass, Khaled
    Thule Institute, University of Arctic, University of Oulu, Oulu, Finland; Department of Pesticides, Menoufia University, Menoufia, Egypt.
    Baig, Asma H.
    Centre for Pollution Research and Policy, Brunel University London, Uxbridge, United Kingdom.
    Forner-Piquer, Isabel
    Centre for Pollution Research and Policy, Brunel University London, Uxbridge, United Kingdom.
    Holbech, Henrik
    Department of Biology, University of Southern Denmark, Odense, Denmark.
    Knapen, Dries
    Zebrafishlab, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium.
    Leonards, Pim E. G.
    Department of Environment and Health, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
    Lupu, Diana I.
    Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden.
    Palaniswamy, Saranya
    Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
    Rautio, Arja
    Thule Institute, University of Arctic, University of Oulu, Oulu, Finland.
    Sapounidou, Maria
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Martin, Olwenn V.
    Centre for Pollution Research and Policy, Brunel University London, Uxbridge, United Kingdom.
    Evidenced-based approaches to support the development of endocrine-mediated adverse outcome pathways: challenges and opportunities2021In: Frontiers in Toxicology, E-ISSN 2673-3080, Vol. 3, article id 787017Article in journal (Refereed)
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  • 2.
    Beausoleil, Claire
    et al.
    French Agency for Food, Environmental and Occupational Health and Safety (Anses), Maisons-Alfort, France.
    Thébault, Anne
    French Agency for Food, Environmental and Occupational Health and Safety (Anses), Maisons-Alfort, France.
    Andersson, Patrik L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Cabaton, Nicolas J.
    INRAE. UMR1331 Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UT3, Toulouse, France.
    Ermler, Sibylle
    Department of Life Sciences, Centre of Genome Engineering and Maintenance, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge, United Kingdom.
    Fromenty, Bernard
    INSERM, Univ Rennes, INRAE, Institut NUMECAN (Nutrition Metabolisms and Cancer) UMR_A 1341, UMR_S 1317, Rennes, France.
    Garoche, Clémentine
    Institut de Recherche en Cancérologie de Montpellier (IRCM), Inserm U1194, Université Montpellier, Institut Régional du Cancer de Montpellier (ICM), Montpellier, France.
    Griffin, Julian L.
    The Rowett Institute, Foresterhill Health Campus, University of Aberdeen, Aberdeen, United Kingdom.
    Hoffmann, Sebastian
    Seh Consulting + Services, Stembergring 15, Paderborn, Germany.
    Kamstra, Jorke H.
    Institute for Risk Assessment Sciences, Department of Population Health Sciences, Utrecht University, Utrecht, Netherlands.
    Kubickova, Barbara
    Radiation, Chemical and Environmental Hazards (RCE), Department of Toxicology, UK Health Security Agency (UKHSA), Harwell Science and Innovation Campus, Oxon, Chilton, United Kingdom.
    Lenters, Virissa
    Institute for Risk Assessment Sciences, Department of Population Health Sciences, Utrecht University, Utrecht, Netherlands.
    Kos, Vesna Munic
    Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
    Poupin, Nathalie
    INRAE. UMR1331 Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UT3, Toulouse, France.
    Remy, Sylvie
    Flemish Institute for Technological Research (VITO), Mol, Belgium.
    Sapounidou, Maria
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Zalko, Daniel
    INRAE. UMR1331 Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UT3, Toulouse, France.
    Legler, Juliette
    Institute for Risk Assessment Sciences, Department of Population Health Sciences, Utrecht University, Utrecht, Netherlands.
    Jacobs, Miriam N.
    Radiation, Chemical and Environmental Hazards (RCE), Department of Toxicology, UK Health Security Agency (UKHSA), Harwell Science and Innovation Campus, Oxon, Chilton, United Kingdom.
    Rousselle, Christophe
    French Agency for Food, Environmental and Occupational Health and Safety (Anses), Maisons-Alfort, France.
    Weight of evidence evaluation of the metabolism disrupting effects of triphenyl phosphate using an expert knowledge elicitation approach2024In: Toxicology and Applied Pharmacology, ISSN 0041-008X, E-ISSN 1096-0333, Vol. 489, article id 116995Article in journal (Refereed)
    Abstract [en]

    Identification of Endocrine-Disrupting Chemicals (EDCs) in a regulatory context requires a high level of evidence. However, lines of evidence (e.g. human, in vivo, in vitro or in silico) are heterogeneous and incomplete for quantifying evidence of the adverse effects and mechanisms involved. To date, for the regulatory appraisal of metabolism-disrupting chemicals (MDCs), no harmonised guidance to assess the weight of evidence has been developed at the EU or international level. To explore how to develop this, we applied a formal Expert Knowledge Elicitation (EKE) approach within the European GOLIATH project. EKE captures expert judgment in a quantitative manner and provides an estimate of uncertainty of the final opinion. As a proof of principle, we selected one suspected MDC -triphenyl phosphate (TPP) - based on its related adverse endpoints (obesity/adipogenicity) relevant to metabolic disruption and a putative Molecular Initiating Event (MIE): activation of peroxisome proliferator activated receptor gamma (PPARγ). We conducted a systematic literature review and assessed the quality of the lines of evidence with two independent groups of experts within GOLIATH, with the objective of categorising the metabolic disruption properties of TPP, by applying an EKE approach. Having followed the entire process separately, both groups arrived at the same conclusion, designating TPP as a “suspected MDC” with an overall quantitative agreement exceeding 85%, indicating robust reproducibility. The EKE method provides to be an important way to bring together scientists with diverse expertise and is recommended for future work in this area.

  • 3.
    Chelcea, Ioana C.
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Vogs, Carolina
    Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
    Hamers, Timo
    Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
    Koekkoek, Jacco
    Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
    Legradi, Jessica
    Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
    Sapounidou, Maria
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Örn, Stefan
    Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Andersson, Patrik L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Physiology-informed toxicokinetic model for the zebrafish embryo test: a case study of bisphenolsManuscript (preprint) (Other academic)
  • 4.
    Chelcea, Ioana C.
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Vogs, Carolina
    Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Box 7028, Uppsala, Sweden; Institute of Environmental Medicine, Karolinska Institutet, Solna, Sweden.
    Hamers, Timo
    Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, HV Amsterdam, Netherlands.
    Koekkoek, Jacco
    Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, HV Amsterdam, Netherlands.
    Legradi, Jessica
    Amsterdam Institute for Life and Environment (A-LIFE), Vrije Universiteit Amsterdam, HV Amsterdam, Netherlands.
    Sapounidou, Maria
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Örn, Stefan
    Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Box 7028, Uppsala, Sweden.
    Andersson, Patrik L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Physiology-informed toxicokinetic model for the zebrafish embryo test developed for bisphenols2023In: Chemosphere, ISSN 0045-6535, E-ISSN 1879-1298, Vol. 345, article id 140399Article in journal (Refereed)
    Abstract [en]

    Zebrafish embryos (ZFE) is a widely used model organism, employed in various research fields including toxicology to assess e.g., developmental toxicity and endocrine disruption. Variation in effects between chemicals are difficult to compare using nominal dose as toxicokinetic properties may vary. Toxicokinetic (TK) modeling is a means to estimate internal exposure concentration or dose at target and to enable extrapolation between experimental conditions and species, thereby improving hazard assessment of potential pollutants. In this study we advance currently existing TK models for ZFE with physiological ZFE parameters and novel experimental bisphenol data, a class of chemicals with suspected endocrine activity. We developed a five-compartment model consisting of water, plastic, chorion, yolk sack and embryo in which surface area and volume changes as well as the processes of biotransformation and blood circulation influence mass fluxes. For model training and validation, we measured internal concentrations in ZFE exposed individually to BPA, bisphenol AF (BPAF) and Z (BPZ). Bayesian inference was applied for parameter calibration based on the training data set of BPZ. The calibrated TK model predicted internal ZFE concentrations of the majority of external test data within a 5-fold error and half of the data within a 2-fold error for bisphenols A, AF, F, and tetrabromo bisphenol A (TBBPA). We used the developed model to rank the hazard of seven bisphenols based on predicted internal concentrations and measured in vitro estrogenicity. This ranking indicated a higher hazard for BPAF, BPZ, bisphenol B and C (BPB, BPC) than for BPA.

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  • 5.
    Sapounidou, Maria
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Andersson, Patrik L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Leemans, Michelle
    UMR 7221, Phyma, CNRS–Muséum National d’Histoire Naturelle, Sorbonne Université, Paris, France.
    Fini, Jean-Baptiste
    UMR 7221, Phyma, CNRS–Muséum National d’Histoire Naturelle, Sorbonne Université, Paris, France.
    Demeneix, Barbara
    UMR 7221, Phyma, CNRS–Muséum National d’Histoire Naturelle, Sorbonne Université, Paris, France.
    Rüegg, Joëlle
    Department of Organismal Biology, Environmental Toxicology, Uppsala University, Uppsala, Sweden.
    Bornehag, Carl-Gustaf
    Faculty of Health, Science and Technology, Department of Health Sciences, Karlstad University, Karlstad, Sweden; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, NY, New York, United States.
    Gennings, Chris
    Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, NY, New York, United States.
    From cohort to cohort: a similar mixture approach (SMACH) to evaluate exposures to a mixture leading to thyroid-mediated neurodevelopmental effects using NHANES data2023In: Toxics, E-ISSN 2305-6304, Vol. 11, no 4, article id 331Article in journal (Refereed)
    Abstract [en]

    Prenatal exposure to a mixture (MIX N) of eight endocrine-disrupting chemicals has been associated with language delay in children in a Swedish pregnancy cohort. A novel approach was proposed linking this epidemiological association with experimental evidence, where the effect of MIX N on thyroid hormone signaling was assessed using the Xenopus eleuthero-embryonic thyroid assay (XETA OECD TG248). From this experimental data, a point of departure (PoD) was derived based on OECD guidance. Our aim in the current study was to use updated toxicokinetic models to compare exposures of women of reproductive age in the US population to MIX N using a Similar Mixture Approach (SMACH). Based on our findings, 66% of women of reproductive age in the US (roughly 38 million women) had exposures sufficiently similar to MIX N. For this subset, a Similar Mixture Risk Index (SMRIHI) was calculated comparing their exposures to the PoD. Women with SMRIHI > 1 represent 1.1 million women of reproductive age. Older women, Mexican American and other/multi race women were less likely to have high SMRIHI values compared to Non-Hispanic White women. These findings indicate that a reference mixture of chemicals identified in a Swedish cohort—and tested in an experimental model for establishment of (PoDs)—is also of health relevance in a US population.

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  • 6.
    Sapounidou, Maria
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Norinder, Ulf
    Department of Computer and Systems Sciences, Stockholm University, Kista, Sweden; MTM Research Centre, School of Science and Technology, Örebro University, Örebro, Sweden; Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
    Andersson, Patrik L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Predicting endocrine disruption using conformal prediction: a prioritization strategy to identify hazardous chemicals with confidence2023In: Chemical Research in Toxicology, ISSN 0893-228X, E-ISSN 1520-5010, Vol. 36, no 1, p. 53-65Article in journal (Refereed)
    Abstract [en]

    Receptor-mediated molecular initiating events (MIEs) and their relevance in endocrine activity (EA) have been highlighted in literature. More than 15 receptors have been associated with neurodevelopmental adversity and metabolic disruption. MIEs describe chemical interactions with defined biological outcomes, a relationship that could be described with quantitative structure-activity relationship (QSAR) models. QSAR uncertainty can be assessed using the conformal prediction (CP) framework, which provides similarity (i.e., nonconformity) scores relative to the defined classes per prediction. CP calibration can indirectly mitigate data imbalance during model development, and the nonconformity scores serve as intrinsic measures of chemical applicability domain assessment during screening. The focus of this work was to propose an in silico predictive strategy for EA. First, 23 QSAR models for MIEs associated with EA were developed using high-throughput data for 14 receptors. To handle the data imbalance, five protocols were compared, and CP provided the most balanced class definition. Second, the developed QSAR models were applied to a large data set (∼55,000 chemicals), comprising chemicals representative of potential risk for human exposure. Using CP, it was possible to assess the uncertainty of the screening results and identify model strengths and out of domain chemicals. Last, two clustering methods, t-distributed stochastic neighbor embedding and Tanimoto similarity, were used to identify compounds with potential EA using known endocrine disruptors as reference. The cluster overlap between methods produced 23 chemicals with suspected or demonstrated EA potential. The presented models could be utilized for first-tier screening and identification of compounds with potential biological activity across the studied MIEs.

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1 - 6 of 6
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