Integrating Selection and Risk Assessment of Chemical Mixtures: A Novel Approach Applied to a Breast Milk Survey.

BACKGROUND: One of the main challenges of modern risk assessment is to account for combined exposure to the multitude of various substances present in food and the environment. OBJECTIVE: The present work proposes a methodological approach to perform chemical risk assessment of contaminant mixtures across regulatory silos regarding an extensive range of substances and to do so when comprehensive relevant data concerning the specific effects and modes of action of the mixture components are not available. METHODS: We developed a complete step-by-step approach using statistical methods to prioritize substances involved in combined exposure, and we used a component-based approach to cumulate the risk using dose additivity. The most relevant toxicological end point and the associated reference point were selected from the literature to construct a toxicological threshold for each substance. DISCUSSION: By applying the proposed method to contaminants in breast milk, we observed that among the 19 substances comprising the selected mixture, ∑DDT, ∑PCBi, and arsenic were main joint contributors to the risk of neurodevelopmental and thyroid effects for infants. In addition, ∑PCCD/F contributed to the thyroid effect and ∑aldrin-dieldrin to the neurodevelopmental effect. Our case study on contaminants in breast milk demonstrated the importance of crossing regulatory silos when studying mixtures and the importance of identifying risk drivers to regulate the risk related to environmental contamination. Applying this method to another set of data, such as human biomonitoring or in ecotoxicology, will reinforce its relevance for risk assessment. https://doi.org/10.1289/EHP8262.

Guidance Document on Scientific criteria for grouping chemicals into assessment groups for human risk assessment of combined exposure to multiple chemicals.

This guidance document provides harmonised and flexible methodologies to apply scientific criteria and prioritisation methods for grouping chemicals into assessment groups for human risk assessment of combined exposure to multiple chemicals. In the context of EFSA's risk assessments, the problem formulation step defines the chemicals to be assessed in the terms of reference usually through regulatory criteria often set by risk managers based on legislative requirements. Scientific criteria such as hazard-driven criteria can be used to group these chemicals into assessment groups. In this guidance document, a framework is proposed to apply hazard-driven criteria for grouping of chemicals into assessment groups using mechanistic information on toxicity as the gold standard where available (i.e. common mode of action or adverse outcome pathway) through a structured weight of evidence approach. However, when such mechanistic data are not available, grouping may be performed using a common adverse outcome. Toxicokinetic data can also be useful for grouping, particularly when metabolism information is available for a class of compounds and common toxicologically relevant metabolites are shared. In addition, prioritisation methods provide means to identify low-priority chemicals and reduce the number of chemicals in an assessment group. Prioritisation methods include combined risk-based approaches, risk-based approaches for single chemicals and exposure-driven approaches. Case studies have been provided to illustrate the practical application of hazard-driven criteria and the use of prioritisation methods for grouping of chemicals in assessment groups. Recommendations for future work are discussed.

Aggregate and cumulative chronic risk assessment for pyrethroids in the French adult population.

Pyrethroids are commonly used as insecticides in households, in agriculture or in veterinary and medicinal products. This study aimed to assess cumulative aggregate exposure to cyfluthrin, cypermethrin, deltamethrin and permethrin in adults in France and the associated health risk, and to identify major contributions of exposure sources and routes. External chronic exposures were estimated from dietary and several environmental sources for the oral, inhalation and dermal routes. Internal concentrations of five associated metabolites were simulated with a physiologically-based pharmacokinetic model. The predicted urinary concentrations were in same order of magnitude as those of the French ENNS biomonitoring survey. Dietary exposure, especially from cereals and animal products, was the major source of exposure. For the 1% of adults most highly exposed, dermal exposure to permethrin through medicinal and veterinary products was an important source of exposure. Considering alterations of motor, sensory and autonomic division, all individual margins of exposure were higher than 100, suggesting that no neurotoxic risk associated with the cumulative aggregate exposure to these four pyrethroids is expected for the French adult population.

Cumulative dietary risk assessment overarching different regulatory silos using a margin of exposure approach: A case study with three chemical silos.

Risk assessment of chemicals occurring in our diet is commonly performed for single chemicals without considering exposure to other chemicals. We performed a case study on risk assessment of combined dietary exposure to chemicals from different regulatory silos, i.e. pesticides (PPRs), persistent organic pollutants (POPs) and food additives (FAs). Chemicals were grouped into the cumulative assessment group (CAG) liver steatosis using a component-based approach. Based on literature, the CAG included 144 PPRs, 49 POPS and 7 FAs for which concentration data were available. For each silo, chronic combined dietary exposure was assessed for adults and children of nine European countries following the most commonly used exposure methodologies in Europe and by using a relative potency factor approach. For risk characterization, a Margin of Exposure (MOE) was calculated. To overarch the risk across silos, a normalised combined margin of exposure (nMOET) approach was proposed. This case study demonstrated that risk assessment of combined exposure to chemicals can be performed within regulatory silos. It also highlighted important differences in the conservatism of exposure scenarios, the derivation of point of departures and the subsequent acceptable MOEs between the silos. To overarch the risk despite these differences, a nMOET approach can be used.

The MCRA toolbox of models and data to support chemical mixture risk assessment.

A model and data toolbox is presented to assess risks from combined exposure to multiple chemicals using probabilistic methods. The Monte Carlo Risk Assessment (MCRA) toolbox, also known as the EuroMix toolbox, has more than 40 modules addressing all areas of risk assessment, and includes a data repository with data collected in the EuroMix project. This paper gives an introduction to the toolbox and illustrates its use with examples from the EuroMix project. The toolbox can be used for hazard identification, hazard characterisation, exposure assessment and risk characterisation. Examples for hazard identification are selection of substances relevant for a specific adverse outcome based on adverse outcome pathways and QSAR models. Examples for hazard characterisation are calculation of benchmark doses and relative potency factors with uncertainty from dose response data, and use of kinetic models to perform in vitro to in vivo extrapolation. Examples for exposure assessment are assessing cumulative exposure at external or internal level, where the latter option is needed when dietary and non-dietary routes have to be aggregated. Finally, risk characterisation is illustrated by calculation and display of the margin of exposure for single substances and for the cumulation, including uncertainties derived from exposure and hazard characterisation estimates.

Frequentist and Bayesian approaches for food allergen risk assessment: risk outcome and uncertainty comparisons.

Peer-reviewed probabilistic methods already predict the probability of an allergic reaction resulting from an accidental exposure to food allergens, however, the methods calculate it in different ways. The available methods utilize the same three major input parameters in the risk model: the risk is estimated from the amount of food consumed, the concentration of allergen in the contaminated product and the distribution of thresholds among allergic persons. However, consensus is lacking about the optimal method to estimate the risk of allergic reaction and the associated uncertainty. This study aims to compare estimation of the risk of allergic reaction and associated uncertainty using different methods and suggest improvements. Four cases were developed based on the previous publications and the risk estimations were compared. The risk estimation was found to agree within 0.5% with the different simulation cases. Finally, an uncertainty analysis method is also presented in order to evaluate the uncertainty propagation from the input parameters to the risk.

Sensitivity analysis to derive a food consumption point estimate for deterministic food allergy risk assessment.

One of the input parameters in food allergy risk assessment is the amount of a given food consumed at an eating occasion. There is no consensus on how to use food consumption data when assessing the risk from unintended allergen presence in food products. A sensitivity analysis was performed to establish the optimal food consumption estimate for a deterministic food allergy risk assessment. Exposure was calculated for consumption percentiles (50th percentile, P50 to maximum) using the iFAAM consumption database in conjunction with an allergen concentration range from 1 to 1000 ppm. The resulting allergen intakes were compared to the allergic population reference doses proposed by Taylor et al. (2014) for 10 major allergenic foods. Optimal consumption percentiles were defined as those which predicted an intake below the relevant reference dose and met the defined acceptable risk level confirmed by probabilistic risk assessments. Analysis showed that, for 99% of the food groups, the P50 consumption met our criteria, while the P75 did so for 100% of the food groups. We suggest that the P75 is the optimal point estimate for use in deterministic food allergy risk assessment. It meets the safety objective and is adequately conservative for a public health context.

Food groups for allergen risk assessment: Combining food consumption data from different countries in Europe.

To prevent allergic reactions, food producers have to be able to make a knowledge based decision on whether to label their products with precautionary labelling. As many manufactured food products are sold in different countries across Europe, the allergen risk assessment should be estimated at the European levels. As currently, there are no pan-European food data suitable for food allergy risk assessment. The aim of this paper is to investigate if consumption data, at a meal level, from National Food Consumption Surveys, can be combined to form a common Food Consumption database. In this first attempt we developed a procedure to investigate, if national food consumption data can be combined and grouped using data from Netherlands, France and Denmark. The homogeneity of consumption patterns and the relevance of difference in risk of allergic reaction were compared, using a fixed framework of allergen concentration levels and threshold distribution. Thus, the relevance of using common consumption data across countries was verified. The food groups formed were subsequently evaluated and adjusted based on practical considerations. It resulted in designing 61 food groups that can be used for allergen risk assessment. The summary statistics and descriptive names for each food group are included.

An integrative risk assessment approach for persistent chemicals: a case study on dioxins, furans and dioxin-like PCBs in France.

For persistent chemicals slowly eliminated from the body, the accumulated concentration (body burden), rather than the daily exposure, is considered the proper starting point for the risk assessment. This work introduces an integrative approach for persistent chemical risk assessment by means of a dynamic body burden approach. To reach this goal a Kinetic Dietary Exposure Model (KDEM) was extended with the long term time trend in the exposure (historic exposure) and the comparison of bioaccumulation with body burden references for toxicity. The usefulness of the model was illustrated on the dietary exposure to PolyChlorinatedDibenzo-p-Dioxins (PCDDs), PolyChlorinatedDibenzoFurans (PCDFs) and PolyChlorinated Biphenyls (PCBs) in France. Firstly the dietary exposure to these compounds was determined in 2009 and combined with its long term time trend. In order to take differences between the kinetics of PCDD/F and dl-PCBs into account, three groups of congeners were considered i.e. PCDD/Fs, PCB 126 and remaining dl-PCBs. The body burden was compared with reference body burdens corresponding to reproductive, hepatic and thyroid toxicity. In the case of thyroid toxicity this comparison indicated that in 2009 the probability of the body burden to exceed its reference ranged from 2.8% (95% CI: 1.5-4.9%) up to 3.9% (95% CI: 2.7-7.1%) (18-29 vs. 60-79year olds). Notwithstanding the decreasing long-term time trend of the dietary dioxin exposure in France, this probability still is expected to be 1.5% (95% CI: 0.3-2.5%) in 2030 in 60-79 olds. In the case of reproductive toxicity the probability of the 2009 body burden to exceed its reference ranged from 3.1% (95% CI: 1.4-5.0%) (18-29year olds) to 3.5% (95% CI: 2.2-5.2%) (30-44year olds). In 2030 this probability is negligible in 18-29year olds, however small though significant in 30-44year olds (0.7%, 95% CI: 0-1.6%). In the case of hepatic toxicity the probability in 2009 even in 60-79year olds already was negligible. In conclusion this approach indicates that in France dioxin levels in food form a declining, though still present, future health risk with respect to thyroid and reproductive toxicity.

New approach for the assessment of cluster diets.

Dietary risk assessment is a major public health concern, positioned in the context of establishing overall food safety policy. It requires some understanding of population food choices although geographical location and social-cultural environment are variable. Several years ago, a cluster analysis based on FAO consumption data, ranging from 1990 to 1994, was at the origin of the 13, so called, GEMS/Food cluster diets. This analysis required the initial identification of 19 food markers based on geographical and cultural differences. This paper proposes a new modelling of FAO food consumption database in order to define new cluster diets based on updated consumption data from 2002 to 2007 and better adapted statistical methods. Two statistical methods were combined to extract, consumption systems that generate a substructure from the initial food consumption database and then by deriving a clustering of countries according to their consumption system profiles. The clustering resulted in 17 cluster diets composed of 2 up to 30 countries. The few discrepancies between these new clusters and former ones may be due to more recent data, and to the fact that the new approach is based on another mathematical modelling which does not require any initial identification of food markers.

Quantitative risk assessment relating to adventitious presence of allergens in food: a probabilistic model applied to peanut in chocolate.

Peanut allergy is a public health concern, owing to the high prevalence in France and the severity of the reactions. Despite peanut-containing product avoidance diets, a risk may exist due to the adventitious presence of peanut allergens in a wide range of food products. Peanut is not mentioned in their ingredients list, but precautionary labeling is often present. A method of quantifying the risk of allergic reactions following the consumption of such products is developed, taking the example of peanut in chocolate tablets. The occurrence of adventitious peanut proteins in chocolate and the dose-response relationship are estimated with a Bayesian approach using available published data. The consumption pattern is described by the French individual consumption survey INCA2. Risk simulations are performed using second-order Monte Carlo simulations, which separately propagates variability and uncertainty of the model input variables. Peanut allergens occur in approximately 36% of the chocolates, leading to a mean exposure level of 0.2 mg of peanut proteins per eating occasion. The estimated risk of reaction averages 0.57% per eating occasion for peanut-allergic adults. The 95% values of the risk stand between 0 and 3.61%, which illustrates the risk variability. The uncertainty, represented by the 95% credible intervals, is concentrated around these risk estimates. Children have similar results. The conclusion is that adventitious peanut allergens induce a risk of reaction for a part of the French peanut-allergic population. The method developed can be generalized to assess the risk due to the consumption of every foodstuff potentially contaminated by allergens.

Using empirical likelihood to combine data: application to food risk assessment.

This article introduces an original methodology based on empirical likelihood, which aims at combining different food contamination and consumption surveys to provide risk managers with a risk measure, taking into account all the available information. This risk index is defined as the probability that exposure to a contaminant exceeds a safe dose. It is naturally expressed as a nonlinear functional of the different consumption and contamination distributions, more precisely as a generalized U-statistic. This nonlinearity and the huge size of the data sets make direct computation of the problem unfeasible. Using linearization techniques and incomplete versions of the U-statistic, a tractable "approximated" empirical likelihood program is solved yielding asymptotic confidence intervals for the risk index. An alternative "Euclidean likelihood program" is also considered, replacing the Kullback-Leibler distance involved in the empirical likelihood by the Euclidean distance. Both methodologies are tested on simulated data and applied to assess the risk due to the presence of methyl mercury in fish and other seafood.