Jean-Lou Dorne

Systems toxicology approaches for understanding the joint effects of environmental chemical mixtures

Environmental mixtures of chemicals constitute a prevalent issue in ecotoxicology and the development of new methods to reduce the uncertainties associated with their ecological risk assessment is a critical research need. Historically, a number of models have been explored to predict the potential combined effects of chemicals on species. These models, especially concentration addition and the independent action, have been applied to a number of mixtures. While often providing a good prediction of joint effect, there are cases where these models can have limitations: notably in cases where there are interactions for which they fail to adequately predict joint effects. To support the better mechanistic understanding of interactions in mixture toxicology a framework to support experimental studies to investigate the basis of observed interactions is proposed. The conceptual framework is derived from the extension of a three stage scheme which has previously been applied to understand chemical bioavailability. The framework considers that interactions in mixtures result from processes related to 1) the speciation, binding and transport of chemicals in the exposure medium (external exposure); 2) the adsorption, distribution, metabolism and excretion of chemicals within the organisms (toxicokinetics); 3) associations governing the binding and toxicity of the chemical(s) at the target site (toxicodynamics). The current state of the art in (eco)toxicology in relation to investigation of the mechanisms of interactions between chemicals is discussed with particular emphasis towards the multi-disciplinary tools and techniques within environmental chemistry; toxicology; biochemistry and systems biology that can be used to address such effects.

Nitrite in feed: From Animal health to human health

Nitrite is widely consumed from the diet by animals and humans. However the largest contribution to exposure results from the in vivo conversion of exogenously derived nitrate to nitrite. Because of its potential to cause to methaemoglobin (MetHb) formation at excessive levels of intake, nitrite is regulated in feed and water as an undesirable substance. Forages and contaminated water have been shown to contain high levels of nitrate and represent the largest contributor to nitrite exposure for food-producing animals. Interspecies differences in sensitivity to nitrite intoxication principally result from physiological and anatomical differences in nitrite handling. In the case of livestock both pigs and cattle are relatively susceptible. With pigs this is due to a combination of low levels of bacterial nitrite reductase and hence potential to reduce nitrite to ammonia as well as reduced capacity to detoxify MetHb back to haemoglobin (Hb) due to intrinsically low levels of MetHb reductase. In cattle the sensitivity is due to the potential for high dietary intake and high levels of rumen conversion of nitrate to nitrite, and an adaptable gut flora which at normal loadings shunts nitrite to ammonia for biosynthesis. However when this escape mechanism gets overloaded, nitrite builds up and can enter the blood stream resulting in methemoglobinemia. Looking at livestock case histories reported in the literature no-observed-effect levels of 3.3mg/kg body weight (b.w.) per day for nitrite in pigs and cattle were estimated and related to the total daily nitrite intake that would result from complete feed at the EU maximum permissible level. This resulted in margins of safety of 9-fold and 5-fold for pigs and cattle, respectively. Recognising that the bulkiness of animal feed limits their consumption, these margins in conjunction with good agricultural practise were considered satisfactory for the protection of livestock health. A human health risk assessment was also carried out taking into account all direct and indirect sources of nitrite from the human diet, including carry-over of nitrite in animal-based products such as milk, eggs and meat products. Human exposure was then compared with the acceptable daily intake (ADI) for nitrite of 0-0.07 mg/kg b.w. per day. Overall, the low levels of nitrite in fresh animal products represented only 2.9% of the total daily dietary exposure and thus were not considered to raise concerns for human health. It is concluded that the potential health risk to animals from the consumption of feed or to man from eating fresh animal products containing nitrite, is very low.

Risk assessment of coccidostatics during feed cross-contamination: Animal and human health aspects

Coccidiosis, an intestinal plasmodium infection, is a major infectious disease in poultry and rabbits. Eleven different coccidiostats are licensed in the EU for the prevention of coccidiosis in these animal species. According to their chemical nature and main biological activity, these compounds can be grouped as ionophoric (monensin, lasalocid sodium, salinomycin, narasin, maduramicin and semduramicin) or non-ionophoric (robenidine, decoquinate, nicarbazin, diclazuril, and halofuginone) substances. Coccidiostats are used as feed additives, mixed upon request into the compounded feed. During the technical process of commercial feed production, cross-contamination of feed batches can result in the exposure of non-target animals and induce adverse health effects in these animals due to a specific sensitivity of mammalian species as compared to poultry. Residue formation in edible tissues of non-target species may result in unexpected human exposure through the consumption of animal products. This review presents recent risk assessments performed by the Scientific Panel on Contaminants in the Food Chain (CONTAM) of the European Food Safety Authority (EFSA). The health risk to non-target species that would result from the consumption of cross-contaminated feed with coccidostats at levels of 2, 5 or 10% was found to be negligible for most animal species with the exception of salinomycin and monensin in horses because of the particular sensitivity for which toxicity may occur when cross-contamination exceeds 2% and 5% respectively. Kinetic data and tissue analyses showed that residues of coccidiostats may occur in the liver and eggs in some cases. However, the level of residues of each coccidiostat in edible animal tissues remained sufficiently low that the aggregate exposure of consumers would not exceed the established acceptable daily intake (ADI) of each coccidiostat. It could be concluded that technical cross-contamination of animal feeds would not be expected to adversely affect the health of consumers.

Toxicokinetic models and related tools in environmental risk assessment of chemicals

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.

Dynamic energy budget models in ecological risk assessment: From principles to applications

In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.

Current EU research activities on combined exposure to multiple chemicals

Humans and wildlife are exposed to an intractably large number of different combinations of chemicals via food, water, air, consumer products, and other media and sources. This raises concerns about their impact on public and environmental health. The risk assessment of chemicals for regulatory purposes mainly relies on the assessment of individual chemicals. If exposure to multiple chemicals is considered in a legislative framework, it is usually limited to chemicals falling within this framework and co-exposure to chemicals that are covered by a different regulatory framework is often neglected. Methodologies and guidance for assessing risks from combined exposure to multiple chemicals have been developed for different regulatory sectors, however, a harmonised, consistent approach for performing mixture risk assessments and management across different regulatory sectors is lacking. At the time of this publication, several EU research projects are running, funded by the current European Research and Innovation Programme Horizon 2020 or the Seventh Framework Programme. They aim at addressing knowledge gaps and developing methodologies to better assess chemical mixtures, by generating and making available internal and external exposure data, developing models for exposure assessment, developing tools for in silico and in vitro effect assessment to be applied in a tiered framework and for grouping of chemicals, as well as developing joint epidemiological-toxicological approaches for mixture risk assessment and for prioritising mixtures of concern. The projects EDC-MixRisk, EuroMix, EUToxRisk, HBM4EU and SOLUTIONS have started an exchange between the consortia, European Commission Services and EU Agencies, in order to identify where new methodologies have become available and where remaining gaps need to be further addressed. This paper maps how the different projects contribute to the data needs and assessment methodologies and identifies remaining challenges to be further addressed for the assessment of chemical mixtures.

Generic physiologically-based toxicokinetic modelling for fish: Integration of environmental factors and species variability

One of the goals of environmental risk assessment is to protect the whole ecosystem from adverse effects resulting from exposure to chemicals. Many research efforts have aimed to improve the quantification of dose-response relationships through the integration of toxicokinetics. For this purpose, physiologically-based toxicokinetic (PBTK) models have been developed to estimate internal doses from external doses in a time-dependent manner. In this study, a generic PBTK model was developed and adapted for rainbow trout (Onchorhynchus mykiss), zebrafish (Danio rerio), fathead minnow (Pimephales promelas), and three-spined stickleback (Gasterosteus aculeatus). New mechanistic approaches were proposed for including the effects of growth and temperature in the model. Physiological parameters and their inter-individual variability were estimated based on the results of extensive literature searches or specific experimental data. The PBTK model was implemented for nine environmental contaminants (with log kow from -0.9 to 6.8) to predict whole-body concentrations and concentrations in various fishs organs. Sensitivity analyses were performed for a lipophilic and a hydrophilic compound to identify which parameters have most impact on the models outputs. Model predictions were compared with experimental data according to dataset-specific exposure scenarios and were accurate: 50% of predictions were within a 3-fold factor for six out of nine chemicals and 75% of predictions were within a 3-fold factor for three of the most lipophilic compounds studied. Our model can be used to assess the influence of physiological and environmental factors on the toxicokinetics of chemicals and provide guidance for assessing the effect of those critical factors in environmental risk assessment.

The Yin–Yang of CYP3A4: a Bayesian meta-analysis to quantify inhibition and induction of CYP3A4 metabolism in humans and refine uncertainty factors for mixture risk assessment

Quantifying differences in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. Cytochrome P450 (CYP) 3A4—the major hepatic and intestinal human CYP—and the P-glycoprotein (Pgp) transporter share a vast range of common substrates for which PK may be modulated through inhibition or induction in the presence of grapefruit juice (GFJ) or St. John’s wort (SJW), respectively. Here, an extensive literature search was performed on PK interactions for CYP3A4 and Pgp substrates after oral co-exposure to GFJ and SJW. Relevant data from 109 publications, extracted for both markers of acute (Cmax) and chronic [clearance and area under the plasma concentration–time curve (AUC)] exposure, were computed into a Bayesian hierarchical meta-analysis model. Bioavailability (F) and substrate fraction metabolised by CYP3A4 (Fm) were identified as the variables exhibiting the highest impact on the magnitude of interaction. The Bayesian meta-regression model developed provided good predictions for magnitudes of inhibition (maximum 5.3-fold with GFJ) and induction (maximum 2.3-fold with SJW). Integration of CYP3A4 variability, F, Fm and magnitude of interaction provided the basis to derive a range of CYP3A4 and Pgp-related UFs. Such CYP3A4 and Pgp-related UFs can be derived in the absence of human data using in vitro TK evidence for CYP3A4/Pgp inhibition or induction as conservative in silico options. The future development of quantitative in vitro–in vivo extrapolation models for mixture risk assessment is discussed with particular attention to integrating human in vitro and in vivo P/TK data on interactions with pathway-related variability.