The European Human Biomonitoring Initiative (HBM4EU): Human biomonitoring guidance values (HBM-GVs) for the aprotic solvents N-methyl-2-pyrrolidone (NMP) and N-ethyl-2-pyrrolidone (NEP)

Toxicity Weighting for Human Biomonitoring Mixture Risk Assessment: A Proof of Concept

Chemical mixture risk assessment has, in the past, primarily focused on exposures quantified in the external environment. Assessing health risks using human biomonitoring (HBM) data provides information on the internal concentration, from which a dose can be derived, of chemicals to which human populations are exposed. This study describes a proof of concept for conducting mixture risk assessment with HBM data, using the population-representative German Environmental Survey (GerES) V as a case study. We first attempted to identify groups of correlated biomarkers (also known as 'communities', reflecting co-occurrence patterns of chemicals) using a network analysis approach (n = 515 individuals) on 51 chemical substances in urine. The underlying question is whether the combined body burden of multiple chemicals is of potential health concern. If so, subsequent questions are which chemicals and which co-occurrence patterns are driving the potential health risks. To address this, a biomonitoring hazard index was developed by summing over hazard quotients, where each biomarker concentration was weighted (divided) by the associated HBM health-based guidance value (HBM-HBGV, HBM value or equivalent). Altogether, for 17 out of the 51 substances, health-based guidance values were available. If the hazard index was higher than 1, then the community was considered of potential health concern and should be evaluated further. Overall, seven communities were identified in the GerES V data. Of the five mixture communities where a hazard index was calculated, the highest hazard community contained N-Acetyl-S-(2-carbamoyl-ethyl)cysteine (AAMA), but this was the only biomarker for which a guidance value was available. Of the other four communities, one included the phthalate metabolites mono-isobutyl phthalate (MiBP) and mono-n-butyl phthalate (MnBP) with high hazard quotients, which led to hazard indices that exceed the value of one in 5.8% of the participants included in the GerES V study. This biological index method can put forward communities of co-occurrence patterns of chemicals on a population level that need further assessment in toxicology or health effects studies. Future mixture risk assessment using HBM data will benefit from additional HBM health-based guidance values based on population studies. Additionally, accounting for different biomonitoring matrices would provide a wider range of exposures. Future hazard index analyses could also take a common mode of action approach, rather than the more agnostic and non-specific approach we have taken in this proof of concept.

How to use human biomonitoring in chemical risk assessment: Methodological aspects, recommendations, and lessons learned from HBM4EU

One of the aims of the European Human Biomonitoring Initiative, HBM4EU, was to provide examples of and good practices for the effective use of human biomonitoring (HBM) data in human health risk assessment (RA). The need for such information is pressing, as previous research has indicated that regulatory risk assessors generally lack knowledge and experience of the use of HBM data in RA. By recognising this gap in expertise, as well as the added value of incorporating HBM data into RA, this paper aims to support the integration of HBM into regulatory RA. Based on the work of the HBM4EU, we provide examples of different approaches to including HBM in RA and in estimations of the environmental burden of disease (EBoD), the benefits and pitfalls involved, information on the important methodological aspects to consider, and recommendations on how to overcome obstacles. The examples are derived from RAs or EBoD estimations made under the HBM4EU for the following HBM4EU priority substances: acrylamide, o-toluidine of the aniline family, aprotic solvents, arsenic, bisphenols, cadmium, diisocyanates, flame retardants, hexavalent chromium [Cr(VI)], lead, mercury, mixture of per-/poly-fluorinated compounds, mixture of pesticides, mixture of phthalates, mycotoxins, polycyclic aromatic hydrocarbons (PAHs), and the UV-filter benzophenone-3. Although the RA and EBoD work presented here is not intended to have direct regulatory implications, the results can be useful for raising awareness of possibly needed policy actions, as newly generated HBM data from HBM4EU on the current exposure of the EU population has been used in many RAs and EBoD estimations.

Human biomonitoring guidance values (HBM-GVs) for priority substances under the HBM4EU initiative - New values derivation for deltamethrin and cyfluthrin and overall results

The European Initiative HBM4EU aimed to further establish human biomonitoring across Europe as an important tool for determining population exposure to chemicals and as part of health-related risk assessments, thus making it applicable for policy advice. Not only should analytical methods and survey design be harmonized and quality assured, but also the evaluation of human biomonitoring data. For the health-related interpretation of the data within HBM4EU, a strategy for deriving health-based human biomonitoring guidance values (HBM-GVs) for both the general population and workers was agreed on. On this basis, HBM-GVs for exposure biomarkers of 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH), phthalates (diethyl hexyl phthalate (DEHP), di-n-butyl phthalate (DnBP), diisobutyl phthalate (DiBP), butyl benzyl phthalate (BBzP), and bis-(2-propylheptyl) phthalate (DPHP)), bisphenols A and S, pyrethroids (deltamethrin and cyfluthrin), solvents (1-methyl-2-pyrrolidone (NMP), 1-ethylpyrrolidin-2-one (NEP), N-dimethylformamide (DMF), N,N-dimethylacetamide (DMAC)), the heavy metal cadmium and the mycotoxin deoxynivalenol (DON) were developed and assigned a level of confidence. The approach to HBM-GV derivations, results, and limitations in data interpretation with special focus on the pyrethroids are presented in this paper.

Prioritization of mixtures of neurotoxic chemicals for biomonitoring using high-throughput toxicokinetics and mixture toxicity modeling

Modern society continues to pollute the environment with larger quantities of chemicals that have also become more structurally and functionally diverse. Risk assessment of chemicals can hardly keep up with the sheer numbers that lead to complex mixtures of increasing chemical diversity including new chemicals, substitution products on top of still abundant legacy compounds. Fortunately, over the last years computational tools have helped us to identify and prioritize chemicals of concern. These include toxicokinetic models to predict exposure to chemicals as well as new approach methodologies such as in-vitro bioassays to address toxicodynamic effects. Combined, they allow for a prediction of mixtures and their respective effects and help overcome the lack of data we face for many chemicals. In this study we propose a high-throughput approach using experimental and predicted exposure, toxicokinetic and toxicodynamic data to simulate mixtures, to which a virtual population is exposed to and predict their mixture effects. The general workflow is adaptable for any type of toxicity, but we demonstrated its applicability with a case study on neurotoxicity. If no experimental data for neurotoxicity were available, we used baseline toxicity predictions as a surrogate. Baseline toxicity is the minimal toxicity any chemical has and might underestimate the true contribution to the mixture effect but many neurotoxicants are not by orders of magnitude more potent than baseline toxicity. Therefore, including baseline-toxic effects in mixture simulations yields a more realistic picture than excluding them in mixture simulations. This workflow did not only correctly identify and prioritize known chemicals of concern like benzothiazoles, organochlorine pesticides and plasticizers but we were also able to identify new potential neurotoxicants that we recommend to include in future biomonitoring studies and if found in humans, to also include in neurotoxicity screening.

[Human Biomonitoring for Europe (HBM4EU)-first insights into the results of the initiative]

Beim Human-Biomonitoring wird die innere Schadstoffbelastung des Menschen aus verschiedenen Quellen wie Nahrung, Alltagsgegenständen oder Atemluft erfasst, indem z. B. Blut und Urin analysiert werden. Um das Human-Biomonitoring in Europa zu fördern und zu koordinieren, wurde 2017 das Projekt „Human-Biomonitoring für Europa“ (HBM4EU) begonnen, an dem sich 30 Länder, die Europäische Umweltagentur und die Europäische Kommission beteiligt haben. Im Juni 2022 wurde das Projekt abgeschlossen.

Vergleichbare und zuverlässige Belastungsdaten konnten für eine breite Palette von Umweltchemikalien erfasst und einheitlich bewertet werden. Weitere wichtige Erfolge der Initiative waren die Etablierung eines Kontrollprogramms zur Qualitätssicherung, ein Konzept zur Vereinheitlichung zukünftiger HBM-Studien, eine gemeinsame Strategie zur Ableitung von gesundheitsbezogenen Beurteilungswerten (HBM Guidance Values – HBM-GVs) und die Einrichtung nationaler Gremien. Die gewonnenen Belastungsdaten sind über die Informationsplattform für die Überwachung von Chemikalien (IPCHEM) und das EU HBM-Dashboard zugänglich. Publikationen sind über die HBM4EU-Onlinebibliothek frei verfügbar.

Insgesamt zeigen die Ergebnisse, dass die Belastungen der EU-Bevölkerung für viele Chemikalien wie etwa Phthalate und perfluorierte Alkylsubstanzen (PFAS) zu hoch sind und weiterhin Handlungsbedarf seitens der Politik besteht. Das im Projekt HBM4EU generierte Wissen kann die politischen Entscheidungsträger:innen bei der Verbesserung der Chemikalien‑, Umwelt- und Gesundheitspolitik unterstützen.

Human Biomonitoring Initiative (HBM4EU): Human Biomonitoring Guidance Values Derived for Dimethylformamide

Within the European Joint Program on Human Biomonitoring HBM4EU, human biomonitoring guidance values (HBM-GVs) for the general population (HBM-GV_GenPop) or for occupationally exposed adults (HBM-GV_Worker) are derived for prioritized substances including dimethylformamide (DMF). The methodology to derive these values that was agreed upon within the HBM4EU project was applied. A large database on DMF exposure from studies conducted at workplaces provided dose–response relationships between biomarker concentrations and health effects. The hepatotoxicity of DMF has been identified as having the most sensitive effect, with increased liver enzyme concentrations serving as biomarkers of the effect. Out of the available biomarkers of DMF exposure studied in this paper, the following were selected to derive HBM-GV_Worker: total N-methylformamide (tNMF) (sum of N-hydroxymethyl-N-methylformamide and NMF) and N-acetyl-S-(N-methylcarbamoyl)cysteine (AMCC) in urine. The proposed HBM-GV_Worker is 10 mg·L⁻¹ or 10 mg·g⁻¹ creatinine for both biomarkers. Due to their different half-lives, tNMF (representative of the exposure of the day) and AMCC (representative of the preceding days’ exposure) are complementary for the biological monitoring of workers exposed to DMF. The levels of confidence for these HBM-GV_Worker are set to “high” for tNMF and “medium-low” for AMCC. Therefore, further investigations are required for the consolidation of the health-based HBM-GV for AMCC in urine.

Chemical Mixtures in the EU Population: Composition and Potential Risks

Regulating chemical mixtures is a complex scientific and policy task. The aim of this study was to investigate typical mixtures and their potential risks based on internal exposure levels in the European population. Based on human biomonitoring (HBM) data made available via the HBM4EU project, we derived generic mixtures representative of a median (P50) and a worst-case scenario (P95) for adults and children. We performed a mixture risk assessment based on HBM concentrations, health-based guidance values (HBGVs) as internal thresholds of concern, and the conservative assumption of concentration addition applied across different toxicological endpoints. Maximum cumulative ratios (MCRs) were calculated to characterize the mixture risk. The mixtures comprise 136 biomarkers for adults and 84 for children, although concentration levels could be quantified only for a fraction of these. Due to limited availability of HBGVs, the mixture risk was assessed for a subset of 20 substance-biomarker pairs for adults and 17 for children. The mixture hazard index ranged from 2.8 (P50, children) to 9.2 (P95, adults). Six to seven substances contributed to over 95% of the total risk. MCR values ranged between 2.6 and 5.5, which is in a similar range as in previous studies based on human external exposures assessments. The limited coverage of substances included in the calculations and the application of a hazard index across toxicological endpoints argue for caution in the interpretation of the results. Nonetheless the analyses of MCR and MAF_ceiling can help inform a possible mixture assessment factor (MAF) applicable to single substance risk assessment to account for exposure to unintentional mixtures.