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.European Union’s Horizon 2020 research and innovation programme under grant agreement number 874583—the Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project. The author Mousumi Chatterjee is grateful for a Daphne Jackson Trust (UK) fellowship. The authors would like to thank EFSA providing the food consumption databases, data owners for giving permission to use the data, and Gerda van Donkersgoed and Matthijs Sam (RIVM) for organising the food consumption data and chemical concentration data

Harmonized human biomonitoring in European children, teenagers and adults: EU-wide exposure data of 11 chemical substance groups from the HBM4EU Aligned Studies (2014-2021)

As one of the core elements of the European Human Biomonitoring Initiative (HBM4EU) a human biomonitoring (HBM) survey was conducted in 23 countries to generate EU-wide comparable HBM data. This survey has built on existing HBM capacity in Europe by aligning national or regional HBM studies, referred to as the HBM4EU Aligned Studies. The HBM4EU Aligned Studies included a total of 10,795 participants of three age groups: (i) 3,576 children aged 6-12 years, (ii) 3,117 teenagers aged 12-18 years and (iii) 4,102 young adults aged 20-39 years. The participants were recruited between 2014 and 2021 in 11-12 countries per age group, geographically distributed across Europe. Depending on the age group, internal exposure to phthalates and the substitute DINCH, halogenated and organophosphorus flame retardants, per- and polyfluoroalkyl substances (PFASs), cadmium, bisphenols, polycyclic aromatic hydrocarbons (PAHs), arsenic species, acrylamide, mycotoxins (deoxynivalenol (total DON)), benzophenones and selected pesticides was assessed by measuring substance specific biomarkers subjected to stringent quality control programs for chemical analysis. For substance groups analyzed in different age groups higher average exposure levels were observed in the youngest age group, i.e., phthalates/DINCH in children versus teenagers, acrylamide and pesticides in children versus adults, benzophenones in teenagers versus adults. Many biomarkers in teenagers and adults varied significantly according to educational attainment, with higher exposure levels of bisphenols, phthalates, benzophenones, PAHs and acrylamide in participants (from households) with lower educational attainment, while teenagers from households with higher educational attainment have higher exposure levels for PFASs and arsenic. In children, a social gradient was only observed for the non-specific pyrethroid metabolite 3-PBA and di-isodecyl phthalate (DiDP), with higher levels in children from households with higher educational attainment. Geographical variations were seen for all exposure biomarkers. For 15 biomarkers, the available health-based HBM guidance values were exceeded with highest exceedance rates for toxicologically relevant arsenic in teenagers (40%), 3-PBA in children (36%), and between 11 and 14% for total DON, Sigma (PFOA + PFNA + PFHxS + PFOS), bisphenol S and cadmium. The infrastructure and harmonized approach succeeded in obtaining comparable European wide internal exposure data for a prioritized set of 11 chemical groups. These data serve as a reference for comparison at the global level, provide a baseline to compare the efficacy of the European Commission's chemical strategy for sustainability and will give leverage to national policy makers for the implementation of targeted measures

Harmonized human biomonitoring in European children, teenagers and adults: EU-wide exposure data of 11 chemical substance groups from the HBM4EU Aligned Studies (2014–2021)

As one of the core elements of the European Human Biomonitoring Initiative (HBM4EU) a human biomonitoring (HBM) survey was conducted in 23 countries to generate EU-wide comparable HBM data. This survey has built on existing HBM capacity in Europe by aligning national or regional HBM studies, referred to as the HBM4EU Aligned Studies. The HBM4EU Aligned Studies included a total of 10,795 participants of three age groups: (i) 3,576 children aged 6–12 years, (ii) 3,117 teenagers aged 12–18 years and (iii) 4,102 young adults aged 20–39 years. The participants were recruited between 2014 and 2021 in 11–12 countries per age group, geographically distributed across Europe. Depending on the age group, internal exposure to phthalates and the substitute DINCH, halogenated and organophosphorus flame retardants, per- and polyfluoroalkyl substances (PFASs), cadmium, bisphenols, polycyclic aromatic hydrocarbons (PAHs), arsenic species, acrylamide, mycotoxins (deoxynivalenol (total DON)), benzophenones and selected pesticides was assessed by measuring substance specific biomarkers subjected to stringent quality control programs for chemical analysis. For substance groups analyzed in different age groups higher average exposure levels were observed in the youngest age group, i.e., phthalates/DINCH in children versus teenagers, acrylamide and pesticides in children versus adults, benzophenones in teenagers versus adults. Many biomarkers in teenagers and adults varied significantly according to educational attainment, with higher exposure levels of bisphenols, phthalates, benzophenones, PAHs and acrylamide in participants (from households) with lower educational attainment, while teenagers from households with higher educational attainment have higher exposure levels for PFASs and arsenic. In children, a social gradient was only observed for the non-specific pyrethroid metabolite 3-PBA and di-isodecyl phthalate (DiDP), with higher levels in children from households with higher educational attainment. Geographical variations were seen for all exposure biomarkers. For 15 biomarkers, the available health-based HBM guidance values were exceeded with highest exceedance rates for toxicologically relevant arsenic in teenagers (40%), 3-PBA in children (36%), and between 11 and 14% for total DON, Σ (PFOA + PFNA + PFHxS + PFOS), bisphenol S and cadmium. The infrastructure and harmonized approach succeeded in obtaining comparable European wide internal exposure data for a prioritized set of 11 chemical groups. These data serve as a reference for comparison at the global level, provide a baseline to compare the efficacy of the European Commission's chemical strategy for sustainability and will give leverage to national policy makers for the implementation of targeted measures

HBM4EU - Deliverable Report D 5.5: Human biomonitoring in risk assessment: 2nd set of examples on the use of HBM in risk assessments of HBM4EU priority chemicals

Co-authors: Henriqueta Louro, Bruno Costa Gomes, Maria João Silva, Ricardo Assunção, Carla Martins, Paula Alvito (INSA)The aim of this work was to exemplify the inclusion of human biomonitoring (HBM) data in risk assessment (RA) and health impact assessment (HIA) strategies. RA was performed for six compound groups on HBM4EU’s first list of priority substances: anilines, cadmium/chromium, flame retardants, PAHs, PFAS and phthalates. In addition, burden of disease (BoD) calculations were made for cadmium. The general approach used included: 1) identification of an existing RA for the substance, 2) identification of possible existing biological limit or guidance values or biological equivalents (BEs), or if lacking, existing health based limit values for external exposure, 3) identification of relevant biomonitoring data to be used in the RA, 4) in case no existing biological limit or guidance values or BEs existed, identification of approaches for reverse/forward calculation, including the use of PBPK modelling or calculation of BE values based on one-compartment modelling, 5) RA or BoD calculation based on HBM data, 6) analysing the benefits and challenges of using HBM data in RA compared to the use of external exposure data. The overall result of the work was that HBM can be included in RA even when relatively few data are available, and its inclusion generally benefits the RA. Several methods exist, and a tiered approach is suggested, based on the amount and quality of data available. The recommended 1st tier method is a one-compartment modelling based derivation of BE values or reverse calculation of external exposure based on biomarker levels. This approach is simple and rough, and uses only very basic parameters. However, in many cases this approach can be considered sufficient, especially when conservative assumptions have been used for the FUE, and the calculated RCRs remain well below 1, indicating a low risk. Also, in cases in which risk assessment using this approach supports the RA made based on external exposure estimates, it is often a sufficient approach. Nevertheless, in some cases e.g. where the RCR is close to 1, a more detailed approach may be needed to refine the RA. For the 2nd tier, PBPK modelling is recommended. For the most robust, 3rd tier approach, measured data on correlations between external exposure and internal doses from well controlled studies would be needed. Certain cases were identified where inclusion of HBM would be particularly important for performing RA: for compounds, for which several exposure routes may contribute to the body burden and the health effects, as HBM reflects the total body burden, and cumulative compounds. For cumulative compounds, HBM could also be useful for hazard assessment in addition to exposure assessment. One of the major challenges for the inclusion of HBM into RA is the often limited data available on toxicokinetics. In addition, in some cases, there is an urgent need for more specific biomarkers or more sensitive analytic methods than currently available. It should be noted that these risk assessments were performed purely to determine how HBM data can contribute to the risk assessment of chemicals, and they have no regulatory implications. Overall for the substances on the HBM4EU’s first list of priority substances, more HBM data are needed. This work is ongoing in WP8, and the RAs presented here will be updated when new data become available.HORIZON2020 Programme Contract No. 733032 HBM4EUinfo:eu-repo/semantics/publishedVersio