Dose addition in mixtures of compounds with dissimilar endocrine modes of action in in vitro receptor activation assays and the zebrafish sexual development test

BACKGROUND

Human exposure to pesticides is being associated with feminisation for which a decrease of the anogenital distance (AGD) is a sensitive endpoint. Dose addition for the cumulative risk assessment of pesticides in food is considered sufficiently conservative for combinations of compounds with both similar and dissimilar modes of action (MoA).

OBJECTIVE

The present study was designed to test the dose addition hypothesis in a binary mixture of endocrine active compounds with a dissimilar mode of action for the endpoint feminisation.

METHODS

Compounds were selected from a list of chemicals of which exposure is related to a decrease of the AGD in rats and completed with reference compounds. These chemicals were characterised using specific in vitro transcriptional activation (TA) assays for estrogenic and androgenic properties, leading to a final selection of dienestrol as an ER-agonist and flutamide, linuron, and deltamethrin as AR-antagonists. These compounds were then tested in an in vivo model, i.e. in zebrafish (Danio rerio), using sex ratio in the population as an endpoint in order to confirm their feminising effect and MoA. Ultimately, the fish model was used to test a binary mixture of flutamide and dienestrol.

RESULTS

Statistical analysis of the binary mixture of flutamide and dienestrol in the fish sexual development tests (FSDT) with zebrafish supported dose addition.

Prenatal dietary exposure to mixtures of chemicals is associated with allergy or respiratory diseases in children in the ELFE nationwide cohort

INTRODUCTION

Prenatal exposure to environmental chemicals may be associated with allergies later in life. We aimed to examine the association between prenatal dietary exposure to mixtures of chemicals and allergic or respiratory diseases up to age 5.5 y.

METHODS

We included 11,638 mother-child pairs from the French "Étude Longitudinale Française depuis l'Enfance" (ELFE) cohort. Maternal dietary exposure during pregnancy to eight mixtures of chemicals was previously assessed. Allergic and respiratory diseases (eczema, food allergy, wheezing and asthma) were reported by parents between birth and age 5.5 years. Associations were evaluated with adjusted logistic regressions. Results are expressed as odds ratio (OR[95%CI]) for a variation of one SD increase in mixture pattern.

RESULTS

Maternal dietary exposure to a mixture composed mainly of trace elements, furans and polycyclic aromatic hydrocarbons (PAHs) was positively associated with the risk of eczema (1.10 [1.05; 1.15]), this association was consistent across sensitivity analyses. Dietary exposure to one mixture of pesticides was positively associated with the risk of food allergy (1.10 [1.02; 1.18]), whereas the exposure to another mixture of pesticides was positively but slightly related to the risk of wheezing (1.05 [1.01; 1.08]). This last association was not found in all sensitivity analyses. Dietary exposure to a mixture composed by perfluoroalkyl acids, PAHs and trace elements was negatively associated with the risk of asthma (0.89 [0.80; 0.99]), this association was consistent across sensitivity analyses, except the complete-case analysis.

CONCLUSION

Whereas few individual chemicals were related to the risk of allergic and respiratory diseases, some consistent associations were found between prenatal dietary exposure to some mixtures of chemicals and the risk of allergic or respiratory diseases. The positive association between trace elements, furans and PAHs and the risk of eczema, and that between pesticides mixtures and food allergy need to be confirmed in other studies. Conversely, the negative association between perfluoroalkyl acids, PAHs and trace elements and the risk of asthma need to be further explored.

Combined chronic dietary exposure to four nephrotoxic metals exceeds tolerable intake levels in the adult population of 10 European countries

A mixture risk assessment (MRA) for four metals relevant to chronic kidney disease (CKD) was performed. Dietary exposure to cadmium or lead alone exceeded the respective reference values in the majority of the 10 European countries included in our study. When the dietary exposure to those metals and inorganic mercury and inorganic arsenic was combined following a classical or personalised modified reference point index (mRPI) approach, not only high exposure (95th percentile) estimates but also the mean exceeded the tolerable intake of the mixture in all countries studied. Cadmium and lead contributed most to the combined exposure, followed by inorganic arsenic and inorganic mercury. The use of conversion factors for inorganic arsenic and inorganic mercury from total arsenic and total mercury concentration data was a source of uncertainty. Other uncertainties were related to the use of different principles to derive reference points. Yet, MRA at the target organ level, as performed in our study, could be used as a way to efficiently prioritise assessment groups for higher-tier MRA. Since the combined exposure to the four metals exceeded the tolerable intake, we recommend a refined MRA based on a common, specific nephrotoxic effect and relative potency factors (RPFs) based on a similar effect size.

Prenatal dietary exposure to chemicals and allergy or respiratory diseases in children in the EDEN mother-child cohort

INTRODUCTION

Maternal exposure to food chemicals may increase the risk of allergy and respiratory disorders in offspring. We aimed to assess the association of prenatal dietary exposure to single chemicals and chemical mixtures with allergy or respiratory events reported before age 8 y in children.

METHODS

We included 1428 mother-child pairs enrolled in the EDEN mother-child cohort. Maternal dietary exposure to 209 chemicals and eight associated mixtures was investigated. Allergic and respiratory diseases (wheezing, asthma, allergic rhinitis, eczema and food allergy) were reported by parents between birth and age 8 y. Associations with the studied outcomes were evaluated with three approaches based on adjusted logistic regression, estimating odds ratios (ORs) and 95 % confidence intervals (CIs). First, food chemicals were considered individually, with correction for multiple testing. Second, chemicals selected by elastic net regression were considered simultaneously in a multiple exposure model. Third, predefined mixtures were introduced in the same adjusted logistic regression. Results are expressed as odds ratio (OR[95 % CI]).

RESULTS

Prenatal single exposure to 74 food chemicals was associated with higher risk of allergic rhinitis. Prenatal single exposure to 11 chemicals was associated with higher risk of wheezing. In the multi-exposure approach, risk of wheezing was associated with the pesticides diazinon and triadimenol, and polycyclic aromatic hydrocarbon 5-methylchrysene. Phytoestrogen resveratrol was negatively associated with lower risk of both wheezing and allergic rhinitis, and mycotoxin monoacetoxyscirpenol was negatively associated with risk of eczema. Finally, a chemical mixture composed mainly of trace elements, furans and polycyclic aromatic hydrocarbons, was associated with higher risk of allergic rhinitis (1.33 [1.02;1.73]).

CONCLUSION

Prenatal dietary exposure to chemicals was associated with risk of allergic rhinitis or wheezing up to age 8 y. A few chemicals were associated with other allergic and respiratory diseases. Larger prospective studies are needed to confirm these findings.

Challenges of studying the dietary exposure to chemical mixtures: Example of the association with mortality risk in the E3N French prospective cohort

Food is contaminated by many chemicals which interact with each other, resulting in additive, synergistic or antagonistic effects. It is thus necessary to study the health effects of dietary exposure to chemical mixtures rather than single contaminants. We aimed to investigate the association between dietary exposure to chemical mixtures and mortality risk in the E3N French prospective cohort. We included 72,585 women from the E3N cohort who completed a food frequency questionnaire in 1993. From 197 chemicals, and using sparse non-negative matrix under-approximation (SNMU), we identified six main chemical mixtures to which these women were chronically exposed through the diet. We estimated the associations between dietary exposure to these mixtures and all-cause or cause-specific mortality using Cox proportional hazard models. During the follow-up (1993-2014), 6441 deaths occurred. We observed no association between dietary exposure to three mixtures and all-cause mortality, and a non-monotonic inverse association for the three other mixtures. These results could be explained by the fact that, despite the different dietary adjustment strategies tested, we did not fully succeed in excluding the residual confounding from the overall effect of the diet. We also questioned the number of chemicals to include in mixtures' studies, as a balance needs to be reached between including a large number of chemicals and the interpretability of the results. Integrating a priori knowledge, such as toxicological data, could lead to the identification of more parsimonious mixtures, thus to more interpretable results. Moreover, as the SNMU is a non-supervised method, which identifies the mixtures only on the basis of the correlations between the exposure variables, and not in relation to the outcome, it would be interesting to test supervised methods. Finally, further studies are needed to identify the most adequate approach to investigate the health effects of dietary exposure to chemical mixtures in observational studies.

A case study of neurodevelopmental risks from combined exposures to lead, methyl-mercury, inorganic arsenic, polychlorinated biphenyls, polybrominated diphenyl ethers and fluoride

We performed a mixture risk assessment (MRA) case study of dietary exposure to the food contaminants lead, methylmercury, inorganic arsenic (iAs), fluoride, non-dioxin-like polychlorinated biphenyls (NDL-PCBs) and polybrominated diphenyl ethers (PBDEs), all substances associated with declines in cognitive abilities measured as IQ loss. Most of these chemicals are frequently measured in human biomonitoring studies. A component-based, personalised modified reference point index (mRPI) approach, in which we expressed the exposures and potencies of our chosen substances as lead equivalent values, was applied to perform a MRA for dietary exposures. We conducted the assessment for four different age groups (toddlers, children, adolescents, and women aged 18-45 years) in nine European countries. Populations in all countries considered exceeded combined tolerable levels at median exposure levels. NDL-PCBs in fish, other seafood and dairy, lead in grains and fruits, methylmercury in fish and other seafoods, and fluoride in water contributed most to the combined exposure. We identified uncertainties for the likelihood of co-exposure, assessment group membership, endpoint-specific reference values (ESRVs) based on epidemiological (lead, methylmercury, iAs, fluoride and NDL-PCBs) and animal data (PBDE), and exposure data. Those uncertainties lead to a complex pattern of under- and overestimations, which would require probabilistic modelling based on expert knowledge elicitation for integration of the identified uncertainties into an overall uncertainty estimate. In addition, the identified uncertainties could be used to refine future MRA for cognitive decline.

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.

Advancing tools for human early lifecourse exposome research and translation (ATHLETE): Project overview

Early life stages are vulnerable to environmental hazards and present important windows of opportunity for lifelong disease prevention. This makes early life a relevant starting point for exposome studies. The Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project aims to develop a toolbox of exposome tools and a Europe-wide exposome cohort that will be used to systematically quantify the effects of a wide range of community- and individual-level environmental risk factors on mental, cardiometabolic, and respiratory health outcomes and associated biological pathways, longitudinally from early pregnancy through to adolescence. Exposome tool and data development include as follows: (1) a findable, accessible, interoperable, reusable (FAIR) data infrastructure for early life exposome cohort data, including 16 prospective birth cohorts in 11 European countries; (2) targeted and nontargeted approaches to measure a wide range of environmental exposures (urban, chemical, physical, behavioral, social); (3) advanced statistical and toxicological strategies to analyze complex multidimensional exposome data; (4) estimation of associations between the exposome and early organ development, health trajectories, and biological (metagenomic, metabolomic, epigenetic, aging, and stress) pathways; (5) intervention strategies to improve early life urban and chemical exposomes, co-produced with local communities; and (6) child health impacts and associated costs related to the exposome. Data, tools, and results will be assembled in an openly accessible toolbox, which will provide great opportunities for researchers, policymakers, and other stakeholders, beyond the duration of the project. ATHLETE's results will help to better understand and prevent health damage from environmental exposures and their mixtures from the earliest parts of the life course onward.

Identification of chemical mixtures to which women are exposed through the diet: Results from the French E3N cohort

Due to the large number of chemical food contaminants, consumers are exposed simultaneously to a wide range of chemicals which can interact and have a negative impact on health. Nevertheless, due to the multitude of possible chemical combinations it is unrealistic to test all combined toxicological effects. It is therefore essential to identify the most relevant mixtures to which the population is exposed through the diet and investigate their impact on heath. The present study aims to identify and describe the main chemical mixtures to which women enrolled in the E3N study, a large French prospective cohort, are chronically exposed through the diet. 74522 women who had answered a validated semi-quantitative food frequency questionnaire in 1993, were included in the present study. Dietary exposure to chemical contaminates was estimated based on the food contamination measured in 186 core food in France collected between 2007 and 2009 by the French agency for food, environment and occupational health, and safety (ANSES) in the framework of the second French total diet study (2TDS). The sparse non-negative matrix under-approximation (SNMU) was used to identify mixtures of chemical substances. A k-means clustering classification of the whole study population was then performed to define clusters with similar co-exposure profiles. Overall, 8 mixtures which explained 83% of the total variance, were retained. The first mixture, entitled "Minerals, inorganic contaminants, and furans", explained the highest proportion of the total variance (38%), and was correlated in particular with the consumption of "Offal" (rho = 0.22), "Vegetables except roots" (rho = 0.20), and "Eggs" (rho = 0.19). The other seven mixtures explained between 17% and 1% of the variance. Finally, 5 clusters were identified based on the adherence to the 8 mixtures. This study, being the largest ever conducted to identify dietary exposure to chemical mixtures, represents a concrete attempt to prioritize mixtures for which it is essential to investigate combined health effects based on exposure.

Mass balance approach to assess the impact of cadmium decrease in mineral phosphate fertilizers on health risk: The case-study of French agricultural soils

Cadmium is a ubiquitous and highly toxic contaminant that can cause serious adverse effects. The European Food Safety Authority (EFSA) and the French Agency for Food, Environmental and Occupational Health & Safety (ANSES) have shown that the risk related to food contamination by cadmium cannot be ruled out in Europe and France. Fertilizing material is one of the main sources of cadmium contamination in the food chain on which regulators can play to reduce cadmium exposure in the population. The aim of this work was to develop a mass-balance approach integrating the various environmental sources of cadmium to estimate the effects of a decrease in cadmium concentrations in crop fertilizers on dietary exposure and on the health risk. This approach led to a predictive model that can be used as a decision-making tool. Representative and protective fertilization scenarios associated with controlled cadmium levels in mineral phosphate fertilizers were simulated and converted into cadmium fluxes. Cadmium inputs from industrial mineral phosphate fertilizers were then compared with cadmium brought by the application of manure, sewage sludge and farm anaerobic digest, at the levels typical of French agricultural practices. Regardless of the fertilizer and scenario used, a flux lower than 2 g Cd.ha^-1.year^-1 reduces both the accumulation in soils and the transfer of cadmium in the food chain. It corresponds to a cadmium content of 20 mg.kg P₂O₅^-1 or less in mineral phosphate fertilizers. Modelling the transfer of cadmium from the soil to consumed food made it possible to propose cadmium limits in fertilizers applied in France. In a global context of ecological transition to promote human health, this research will help risk managers and public authorities in the regulatory decision-making process for the reduction of environmental cadmium contamination and human exposure.

Estimating human exposure to pyrethroids' mixtures from biomonitoring data using physiologically based pharmacokinetic modeling

Human biomonitoring data provide evidence to exposure of environmental chemicals. Physiologically based pharmacokinetic (PBPK) modelling together with an adequate exposure scenario allows to transpose measured concentrations of chemicals or their metabolites into exposure levels, as daily intakes. In France, high levels of urinary pyrethroids metabolites have been measured in populations. Our work aims at estimating the exposure of the French ENNS cohort to mixtures of four pyrethroids (deltamethrin, permethrin, cypermethrin, and cyfluthrin) from the urinary concentrations of five pyrethroids' metabolites commonly measured in biomonitoring studies. We developed a modelling approach based on a global toxicokinetic model that accounts for the cumulative exposure to pyrethroids as some of the metabolites can be shared by several parent compounds and for human inter-individual variability in metabolism. The median of the individual daily intakes was estimated to 8.1 ng/kg bw/day for permethrin, 17.7 ng/kg bw/day for cypermethrin, 20.4 ng/kg bw/day for cyfluthrin and 34.3 ng/kg bw/day for deltamethrin leading to similar weights for the pair permethrin and cypermethrin (36%), cyfluthrin (31%) and deltamethrin (33%) to the cumulative exposure. Accounting for human variability enabled to explain some of the variations in the metabolites' levels within the cohort. The cumulative exposure was then weighted by their toxicities towards three neurotoxic effects to calculate margins of exposure (MOE). Low MOE values were always associated with high measured concentrations of metabolites in urine and the lowest MOEs were observed for the autonomic division. No risks associated with reconstructed mixtures of pyrethroids were expected for the ENNS cohort. Our approach is an asset to analyse the biomarkers of exposure to pyrethroids simultaneously and could be easily adapted to any local or national specificities in pyrethroids' exposure or populations.

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.

Combining data from heterogeneous surveys for aggregate exposure: Application to children exposure to lead in France

To assess human health risks related to the environment, it is necessary to aggregate exposure from multiple sources. The objective of this paper was to propose a relevant approach to combine data from heterogeneous populations and methodologies. Five different methods based on Monte-Carlo simulations were tested and compared. Differences were: taking into account or not stratification variable, timeline to assign exposure factors and concentration and way to account for concentration correlations. The methods were applied to estimate lead exposure from food, dust, soil, air, and tap water or French children aged between six months and three years old. Comparing results' uncertainty, it is recommended to 1) select a reference population representative of the target population, 2) select stratification variables to combine surveys, and 3) simulate a new population by randomly sampling individuals in the reference population and simultaneously assigning human exposure factors and environmental concentrations from other surveys in integrating correlations (MC1S). No difference was observed when taking into account correlations using vectors of determinist data from one survey or rank of correlations with the Iman-Conover method. Regardless the methods used to combine data, dust was the main exposure source, followed by soil and in a less extent by food. Exposures from air and tap water were found to be insignificant for most children.

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.

Linking Probabilistic Exposure and Pharmacokinetic Modeling To Assess the Cumulative Risk from the Bisphenols BPA, BPS, BPF, and BPAF for Europeans

The bisphenols S, F, and AF (BPS, BPF, and BPAF) are used to replace the endocrine disrupting chemical bisphenol A (BPA) while exerting estrogenic effects of comparable potency. We assessed the cumulative risk for the aforementioned BPs in Europe and compared the risk before and after the year 2011, which was when the first BPA restrictions became effective. For this, we probabilistically modeled external exposures from food, personal care products (PCPs), thermal paper, and dust (using the tools MCRA and PACEM for exposures from food and PCPs, respectively). We calculated internal concentrations of unconjugated BPs with substance-specific PBPK models and cumulated these concentrations normalized by estrogenic potency. The resulting mean internal cumulative exposures to unconjugated BPs were 3.8 and 2.1 ng/kg bw/day before and after restrictions, respectively. This decline was mainly caused by the replacement of BPA by BPS in thermal paper and the lower dermal uptake of BPS compared to BPA. However, the decline was not significant: the selected uncertainty intervals overlapped (P2.5-P97.5 uncertainty intervals of 2.7-4.9 and 1.3-6.3 ng/kg bw/day before and after restrictions, respectively). The upper uncertainty bounds for cumulative exposure were higher after restrictions, which reflects the larger uncertainty around exposures to substitutes compared to BPA.

Gender, prick test size and rAra h 2 sIgE level may predict the eliciting dose in patients with peanut allergy: Evidence from the Mirabel survey

BACKGROUND

Peanut allergy management is based on active avoidance and access to emergency treatment including self-injectable adrenaline. Knowing the dose at which a patient is likely to react is crucial for risk assessment and could significantly improve management by integrating a personalized approach.

OBJECTIVE

To develop a threshold dose distribution curve model from routinely collected data.

METHODS

The MIRABEL survey is an observational study of 785 patients with peanut allergy/sensitization conducted in France, Belgium and Luxemburg. The current analysis included the 238 participants for whom medical and oral food challenge data were available. Several statistical models (Kaplan-Meier, Cox model, Weibull and Lognormal with predictive factors, basic Weibull and Lognormal) were compared to select the best model and predictive factor combination associated with the threshold doses. Inferences were made with a Bayesian approach.

RESULTS

Patients were mainly children (mean age: 9 years [IQR: 6-11]; 87% < 16 years) and males (62%). Median Ara h2 s IgE was of 8kUA/L [IQR: 1-55] and median skin prick test size of 10 mm [IQR: 7-13]. OFC was positive in 204 patients (86%). The median threshold dose was of 67 mg of peanut protein [IQR: 16-244]. The dose at which 1% of the patients are likely to react with objective symptoms was 0.26 [0.03; 2.24] mg of peanut protein. Gender, size of the skin prick test (SPT) and Ara h 2 specific IgE level had a significant impact on the threshold dose distribution curve. The Cox model was the most effective to predict threshold doses with this combination of factors. Girls react to lower doses than boys with a beta coefficient associated to the risk and a 95% credible interval of 0.44 [0.04; 0.77]. The higher the size of the SPT and the Ara h 2 specific IgE level are, the higher the risk of reacting to a small amount of peanut, with beta coefficients associated to the risk and 95% credible intervals of 0.05 [0.02; 0.08] and 0.01 [0.01; 0.02], respectively.

CONCLUSION AND CLINICAL RELEVANCE

According to the model, routinely collected data could be used to estimate the threshold dose. The consequences could be the identification of high-risk patients who are susceptible to react to small amounts of peanut and a personalized management of peanut allergy integrating the risk of allergic reaction. Limitations of this study are that assessors of OFC outcome were aware of SPT and Arah2 results, and a further validation study is required to confirm the predictive value of these parameters.

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.

Dietary patterns in the French adult population: a study from the second French national cross-sectional dietary survey (INCA2) (2006-2007)

Identification and characterisation of dietary patterns are needed to define public health policies to promote better food behaviours. The aim of this study was to identify the major dietary patterns in the French adult population and to determine their main demographic, socio-economic, nutritional and environmental characteristics. Dietary patterns were defined from food consumption data collected in the second French national cross-sectional dietary survey (2006-2007). Non-negative-matrix factorisation method, followed by a cluster analysis, was implemented to derive the dietary patterns. Logistic regressions were then used to determine their main demographic and socio-economic characteristics. Finally, nutritional profiles and contaminant exposure levels of dietary patterns were compared using ANOVA. Seven dietary patterns, with specific food consumption behaviours, were identified: 'Small eater', 'Health conscious', 'Mediterranean', 'Sweet and processed', 'Traditional', 'Snacker' and 'Basic consumer'. For instance, the Health-conscious pattern was characterised by a high consumption of low-fat and light products. Individuals belonging to this pattern were likely to be older and to have a better nutritional profile than the overall population, but were more exposed to many contaminants. Conversely, individuals of Snacker pattern were likely to be younger, consumed more highly processed foods, had a nutrient-poor profile but were exposed to a limited number of food contaminants. The study identified main dietary patterns in the French adult population with distinct food behaviours and specific demographic, socio-economic, nutritional and environmental features. Paradoxically, for better dietary patterns, potential health risks cannot be ruled out. Therefore, this study demonstrated the need to conduct a risk-benefit analysis to define efficient public health policies regarding diet.

Identification of the main pesticide residue mixtures to which the French population is exposed

Owing to the intensive use of pesticides and their potential persistence in the environment, various pesticide residues can be found in the diet. Consumers are therefore exposed to complex pesticide mixtures which may have combined adverse effects on human health. By modelling food exposure to multiple pesticides, this paper aims to determine the main mixtures to which the general population is exposed in France. Dietary exposure of 3337 individuals from the INCA2 French national consumption survey was assessed for 79 pesticide residues, based on results of the 2006 French food monitoring programmes. Individuals were divided into groups with similar patterns of co-exposure using the clustering ability of a Bayesian nonparametric model. In the 5 groups of individuals with the highest exposure, mixtures are formed by pairs of pesticides with correlations above 0.7. Seven mixtures of 2-6 pesticides each were characterised. We identified the commodities that contributed the most to exposure. Pesticide mixtures can either be components of a single plant protection product applied together on the same crop or be from separate products that are consumed together during a meal. Of the 25 pesticides forming the mixtures, two--DDT and Dieldrin--are known persistent organic pollutants. The approach developed is generic and can be applied to all types of substances found in the diet in order to characterise the mixtures that should be studied first because of their adverse effects on health.

Population effects and variability

Chemical risk assessment for human health requires a multidisciplinary approach through four steps: hazard identification and characterization, exposure assessment, and risk characterization. Hazard identification and characterization aim to identify the metabolism and elimination of the chemical (toxicokinetics) and the toxicological dose-response (toxicodynamics) and to derive a health-based guidance value for safe levels of exposure. Exposure assessment estimates human exposure as the product of the amount of the chemical in the matrix consumed and the consumption itself. Finally, risk characterization evaluates the risk of the exposure to human health by comparing the latter to with the health-based guidance value. Recently, many research efforts in computational toxicology have been put together to characterize population variability and uncertainty in each of the steps of risk assessment to move towards more quantitative and transparent risk assessment. This chapter focuses specifically on modeling population variability and effects for each step of risk assessment in order to provide an overview of the statistical and computational tools available to toxicologists and risk assessors. Three examples are given to illustrate the applicability of those tools: derivation of pathway-related uncertainty factors based on population variability, exposure to dioxins, dose-response modeling of cadmium.

Development of a hierarchical Bayesian model to estimate the growth parameters of Listeria monocytogenes in minimally processed fresh leafy salads

The optimal growth rate mu(opt) of Listeria monocytogenes in minimally processed (MP) fresh leafy salads was estimated with a hierarchical Bayesian model at (mean+/-standard deviation) 0.33+/-0.16 h(-1). This mu(opt) value was much lower on average than that in nutrient broth, liquid dairy, meat and seafood products (0.7-1.3 h(-1)), and of the same order of magnitude as in cheese. Cardinal temperatures T(min), T(opt) and T(max) were determined at -4.5+/-1.3 degrees C, 37.1+/-1.3 degrees C and 45.4+/-1.2 degrees C respectively. These parameters were determined from 206 growth curves of L. monocytogenes in MP fresh leafy salads (lettuce including iceberg lettuce, broad leaf endive, curly leaf endive, lamb's lettuce, and mixtures of them) selected in the scientific literature and in technical reports. The adequacy of the model was evaluated by comparing observed data (bacterial concentrations at each experimental time for the completion of the 206 growth curves, mean log(10) increase at selected times and temperatures, L. monocytogenes concentrations in naturally contaminated MP iceberg lettuce) with the distribution of the predicted data generated by the model. The sensitivity of the model to assumptions about the prior values also was tested. The observed values mostly fell into the 95% credible interval of the distribution of predicted values. The mu(opt) and its uncertainty determined in this work could be used in quantitative microbial risk assessment for L. monocytogenes in minimally processed fresh leafy salads.

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.

Estimation of microbial contamination of food from prevalence and concentration data: application to Listeria monocytogenes in fresh vegetables

A normal distribution and a mixture model of two normal distributions in a Bayesian approach using prevalence and concentration data were used to establish the distribution of contamination of the food-borne pathogenic bacteria Listeria monocytogenes in unprocessed and minimally processed fresh vegetables. A total of 165 prevalence studies, including 15 studies with concentration data, were taken from the scientific literature and from technical reports and used for statistical analysis. The predicted mean of the normal distribution of the logarithms of viable L. monocytogenes per gram of fresh vegetables was -2.63 log viable L. monocytogenes organisms/g, and its standard deviation was 1.48 log viable L. monocytogenes organisms/g. These values were determined by considering one contaminated sample in prevalence studies in which samples are in fact negative. This deliberate overestimation is necessary to complete calculations. With the mixture model, the predicted mean of the distribution of the logarithm of viable L. monocytogenes per gram of fresh vegetables was -3.38 log viable L. monocytogenes organisms/g and its standard deviation was 1.46 log viable L. monocytogenes organisms/g. The probabilities of fresh unprocessed and minimally processed vegetables being contaminated with concentrations higher than 1, 2, and 3 log viable L. monocytogenes organisms/g were 1.44, 0.63, and 0.17%, respectively. Introducing a sensitivity rate of 80 or 95% in the mixture model had a small effect on the estimation of the contamination. In contrast, introducing a low sensitivity rate (40%) resulted in marked differences, especially for high percentiles. There was a significantly lower estimation of contamination in the papers and reports of 2000 to 2005 than in those of 1988 to 1999 and a lower estimation of contamination of leafy salads than that of sprouts and other vegetables. The interest of the mixture model for the estimation of microbial contamination is discussed.

Management options to reduce exposure to methyl mercury through the consumption of fish and fishery products by the French population

This paper presents an updated assessment of exposure in France to methyl mercury through the consumption of fish and fishery products, and proposes several management scenarios which could reduce this exposure through changes to fish contamination levels or fish consumption patterns. The exposure model was applied in line with previous methodological results [Tressou, J., Crépet, A., Bertail, P., Feinberg, M.H., Leblanc J.Ch., 2004a. Probabilistic exposure assessment to food chemicals based on extreme value theory: application to heavy metals from fish and sea products. Food Chem. Toxicol. 42, 1349-1358; Tressou, J., Leblanc, J.Ch., Feinberg, M., Bertail, P., 2004b. Statistical methodology to evaluate food exposure to a contaminant and influence of sanitary limits: application to ochratoxin A. Regul. Toxicol. Pharmacol. 40, 252-263] so as to obtain a realistic estimate of probability and confidence intervals (95% CI) concerning French consumers exposed to levels exceeding the revised fixed provisional tolerable weekly intake (PTWI) for methyl mercury of 1.6 microg/week/kg of body weight, established by the Joint FAO/WHO Expert Committee on Food Additives in 2003. The results showed that young children aged between 3 and 6 years old or 7 and 10 years old, and women of childbearing age were at the risk groups. With respect to these groups and according to the fish consumers patterns (consumers of predatory fish only or consumers of predatory and nonpredatory fish), the results suggested that strategies to diminish MeHg exposure by reducing the amount of predatory fish consumed would be more efficient in significantly decreasing the probability of exceeding the PTWI than the implementation of international standards.

Probabilistic exposure assessment to food chemicals based on extreme value theory. Application to heavy metals from fish and sea products

This paper presents new statistical methods in the field of exposure assessment. We focus on the estimation of the probability for the exposure to exceed a fixed safe level such as the provisional tolerable weekly intake (PTWI), when both consumption data and contamination data are independently available. Various calculations of exposure are proposed and compared. For many contaminants, PTWI belongs to the exposure tail distribution, which suggests the use of extreme value theory (EVT) to evaluate the risk. Our approach consists in modelling the exposure tail by a Pareto type distribution characterized by a Pareto index which may be seen as a measure of the risk of exceeding the PTWI. Using propositions by EVT specialists, we correct the bias of the usual Hill estimator to accurately estimate this risk index. We compare the results with an empirical plug-in method and show that the Pareto adjustment is relevant and efficient when exposure is low compared to the PTWI while the plug-in method should be used when exposure is higher. To illustrate our approach, we present some exposure assessment for heavy metals (lead, cadmium, mercury) via sea product consumption.