Identification of Real-Life Mixtures Using Human Biomonitoring Data: A Proof of Concept Study.

Human health risk assessment of chemical mixtures is complex due to the almost infinite number of possible combinations of chemicals to which people are exposed to on a daily basis. Human biomonitoring (HBM) approaches can provide inter alia information on the chemicals that are in our body at one point in time. Network analysis applied to such data may provide insight into real-life mixtures by visualizing chemical exposure patterns. The identification of groups of more densely correlated biomarkers, so-called "communities", within these networks highlights which combination of substances should be considered in terms of real-life mixtures to which a population is exposed. We applied network analyses to HBM datasets from Belgium, Czech Republic, Germany, and Spain, with the aim to explore its added value for exposure and risk assessment. The datasets varied in study population, study design, and chemicals analysed. Sensitivity analysis was performed to address the influence of different approaches to standardise for creatinine content of urine. Our approach demonstrates that network analysis applied to HBM data of highly varying origin provides useful information with regards to the existence of groups of biomarkers that are densely correlated. This information is relevant for regulatory risk assessment, as well as for the design of relevant mixture exposure experiments.

Mixture risk assessment and human biomonitoring: Lessons learnt from HBM4EU.

Unintentional chemical mixtures that are present in the environment are of societal concern as the (environmental) chemicals contained therein, either singly or in combination, may possess properties that are hazardous (toxic) for human health. The current regulatory practice, however, is still largely based on evaluating single chemical substances one-by-one. Over the years various research efforts have delivered tools and approaches for risk assessment of chemical mixtures, but many of these were not considered sufficiently mature for regulatory implementation. This is (partly) due to mixture risk assessment (MRA) being very complex because of the large number of chemicals present in the environment. A key element in risk assessment is information on actual exposures in the population of interest. To date, information on actual personal (internal) mixture exposures is largely absent, severely limiting MRA. The use of human biomonitoring data may improve this situation. Therefore, we investigated within the European Human Biomonitoring Initiative (HBM4EU) various approaches to assess combined exposures and MRA. Based on the insights and lessons learnt in the context of the HBM4EU project, conclusions as well as recommendations for policy development regarding chemical mixtures and for further research were drafted. These conclusions and recommendations relate to both exposure and adverse health effects in humans. The recommendations were discussed with stakeholders in a workshop held in October 2021. There was considerable support and agreement with the spirit, scope and intention of the draft recommendations. Here we describe the lessons learnt on mixture risk assessment through the HBM4EU project and present the final recommendations. Overall, HBM4EU results demonstrated the potential of human biomonitoring as an instrument to obtain insight into the real-life mixtures the human population is exposed to. Also, HBM4EU results demonstrated that chemical mixtures are of public health concern. In the majority of the cases, it was possible to identify risk drivers, i.e. chemicals that contribute more strongly than others to the health risk. The novel approaches to identify co-occurrence patterns demonstrated clusters of co-occurring chemicals; chemicals in these mixture clusters are regulated independently under different legislative frameworks. Moreover, HBM4EU data and expertise can support a science-based derivation of a Mixture Assessment Factor and gauge potential impacts on the population's exposure to chemicals. While further expansion is needed on various aspects of the mixture activities carried out in the context of HBM4EU, application of available methodologies for mixture risk assessment should already be implemented to the degree possible.

Effects of pesticide exposure on oxidative stress and DNA methylation urinary biomarkers in Czech adults and children from the CELSPAC-SPECIMEn cohort.

Current-use pesticide (CUP) exposure occurs mainly through diet and environmental application in both agricultural and urban settings. While pesticide exposure has been associated with many adverse health outcomes, the intermediary molecular mechanisms are still not completely elucidated. Among others, their roles in epigenetics (DNA methylation) and DNA damage due to oxidative stress are presumed. Scientific evidence on urinary biomarkers of such body response in general population is limited, especially in children. A total of 440 urine samples (n = 110 parent-child pairs) were collected during the winter and summer seasons in order to describe levels of overall DNA methylation (5-mC, 5-mdC, 5-hmdC, 7-mG, 3-mA) and oxidative stress (8-OHdG) biomarkers and investigate their possible associations with metabolites of pyrethroids (3-PBA, t/c-DCCA), chlorpyrifos (TCPY), and tebuconazole (TEB-OH). Linear mixed-effects models accounting for intraindividual and intrahousehold correlations were utilized. We applied false discovery rate procedure to account for multiplicity and adjusted for potential confounding variables. Higher urinary levels of most biological response biomarkers were measured in winter samples. In adjusted repeated measures models, interquartile range (IQR) increases in pyrethroid metabolites were associated with higher oxidative stress. t/c-DCCA and TCPY were associated with higher urinary levels of cytosine methylation biomarkers (5-mC and/or 5-mdC). The most robust association was observed for tebuconazole metabolite with 3-mA (-15.1% change per IQR increase, 95% CI = -23.6, -5.69) suggesting a role of this pesticide in reduced demethylation processes through possible DNA glycosylase inhibition. Our results indicate an urgent need to extend the range of analyzed environmental chemicals such as azole pesticides (e.g. prothioconazole) in human biomonitoring studies. This is the first study to report urinary DNA methylation biomarkers in children and associations between CUP metabolites and a comprehensive set of biomarkers including methylated and oxidized DNA alterations. Observed associations warrant further large-scale research of these biomarkers and environmental pollutants including CUPs.

Assessment of exposure to pesticide mixtures in five European countries by a harmonized urinary suspect screening approach.

Humans are exposed to a mixture of pesticides through diet as well as through the environment. We conducted a suspect-screening based study to describe the probability of (concomitant) exposure to a set of pesticide profiles in five European countries (Latvia, Hungary, Czech Republic, Spain and the Netherlands). We explored whether living in an agricultural area (compared to living in a peri-urban area), being a a child (compared to being an adult), and the season in which the urine sample was collected had an impact on the probability of detection of pesticides (-metabolites). In total 2088 urine samples were collected from 1050 participants (525 parent-child pairs) and analyzed through harmonized suspect screening by five different laboratories. Fourty pesticide biomarkers (either pesticide metabolites or the parent pesticides as such) relating to 29 pesticides were identified at high levels of confidence in samples across all study sites. Most frequently detected were biomarkers related to the parent pesticides acetamiprid and chlorpropham. Other biomarkers with high detection rates in at least four countries related to the parent pesticides boscalid, fludioxonil, pirimiphos-methyl, pyrimethanil, clothianidin, fluazifop and propamocarb. In 84% of the samples at least two different pesticides were detected. The median number of detected pesticides in the urine samples was 3, and the maximum was 13 pesticides detected in a single sample. The most frequently co-occurring substances were acetamiprid with chlorpropham (in 62 urine samples), and acetamiprid with tebuconazole (30 samples). Some variation in the probability of detection of pesticides (-metabolites) was observed with living in an agricultural area or season of urine sampling, though no consistent patterns were observed. We did observe differences in the probability of detection of a pesticide (metabolite) among children compared to adults, suggesting a different exposure and/or elimination patterns between adults and children. This survey demonstrates the feasibility of conducting a harmonized pan-European sample collection, combined with suspect screening to provide insight in the presence of exposure to pesticide mixtures in the European population, including agricultural areas. Future improvements could come from improved (harmonized) quantification of pesticide levels.

A Tiered Approach for Assessing Individual and Combined Risk of Pyrethroids Using Human Biomonitoring Data.

Pyrethroids are a major insecticide class, suitable for biomonitoring in humans. Due to similarities in structure and metabolic pathways, urinary metabolites are common to various active substances. A tiered approach is proposed for risk assessment. Tier I was a conservative screening for overall pyrethroid exposure, based on phenoxybenzoic acid metabolites. Subsequently, probabilistic approaches and more specific metabolites were used for refining the risk estimates. Exposure was based on 95th percentiles from HBM4EU aligned studies (2014-2021) covering children in Belgium, Cyprus, France, Israel, Slovenia, and The Netherlands and adults in France, Germany, Israel, and Switzerland. In all children populations, the 95th percentiles for 3-phenoxybenzoic acid (3-PBA) exceeded the screening value. The probabilistic refinement quantified the risk level of the most exposed population (Belgium) at 2% or between 1-0.1% depending on the assumptions. In the substance specific assessments, the 95th percentiles of urinary concentrations in the aligned studies were well below the respective human biomonitoring guidance values (HBM-GVs). Both information sets were combined for refining the combined risk. Overall, the HBM data suggest a low health concern, at population level, related to pyrethroid exposure for the populations covered by the studies, even though a potential risk for highly exposed children cannot be completely excluded. The proposed tiered approach, including a screening step and several refinement options, seems to be a promising tool of scientific and regulatory value in future.

A large scale multi-laboratory suspect screening of pesticide metabolites in human biomonitoring: From tentative annotations to verified occurrences.

Within the Human Biomonitoring for Europe initiative (HBM4EU), a study to determine new biomarkers of exposure to pesticides and to assess exposure patterns was conducted. Human urine samples (N = 2,088) were collected from five European regions in two different seasons. The objective of the study was to identify pesticides and their metabolites in collected urine samples with a harmonized suspect screening approach based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) applied in five laboratories. A combined data processing workflow included comprehensive data reduction, correction of mass error and retention time (RT) drifts, isotopic pattern analysis, adduct and elemental composition annotation, finalized by a mining of the elemental compositions for possible annotations of pesticide metabolites. The obtained tentative annotations (n = 498) were used for acquiring representative data-dependent tandem mass spectra (MS2) and verified by spectral comparison to reference spectra generated from commercially available reference standards or produced through human liver S9 in vitro incubation experiments. 14 parent pesticides and 71 metabolites (including 16 glucuronide and 11 sulfate conjugates) were detected. Collectively these related to 46 unique pesticides. For the remaining tentative annotations either (i) no data-dependent MS2 spectra could be acquired, (ii) the spectral purity was too low for sufficient matching, or (iii) RTs indicated a wrong annotation, leaving potential for more pesticides and/or their metabolites being confirmed in further studies. Thus, the reported results are reflecting only a part of the possible pesticide exposure.

Pesticide exposure among Czech adults and children from the CELSPAC-SPECIMEn cohort: Urinary biomarker levels and associated health risks.

Current-use pesticides (CUP) are extensively applied in both agricultural and urban settings. Exposure occurs mainly via the dietary pathway; however, other pathways such as inhalation or skin contact are also important. In this study, urinary levels of 12 CUP metabolites were investigated among 110 parent-child pairs during two seasons of 2020. Metabolites of pyrethroids (3-PBA, t/c-DCCA), chlorpyrifos (TCPY), and tebuconazole (TEB-OH) were detected in more than 60% of the samples. Chlorpyrifos metabolite was found at the highest concentration and tebuconazole was detected in almost all samples. CUP urinary metabolite levels were significantly higher in children in comparison to adults, except for tebuconazole, which was similar in both groups. In children, winter samples had significantly higher concentrations of pyrethroid and chlorpyrifos metabolites in comparison to the summer samples, but in adults, only chlorpyrifos metabolite concentrations were higher in the winter. No association between CUP urinary metabolite levels and proximity/surface of agricultural areas around residences was observed. Based on our findings, we suspect that CUP exposure is mainly driven by diet and that the effect of environmental exposure is less significant. Daily Intakes were estimated with three possible scenarios considering the amount of the metabolite excreted in urine and were compared to Acceptable Daily Intake values. Using a realistic scenario, exposure to chlorpyrifos exhibited the highest health risk, but still within a safe level. The Acceptable Daily Intake was exceeded only in one child in the case of cypermethrin. The cumulative risk assessment of pesticide mixtures having an effect on the nervous system, based on the total margin of exposure calculations, did not indicate any risk. The overall risk associated with pesticide exposure in the observed population was low. However, the risk observed using the worst-case scenario suggests the need for continuous evaluation of human exposure to such compounds, especially in children.

Network Analysis to Identify Communities Among Multiple Exposure Biomarkers Measured at Birth in Three Flemish General Population Samples.

Introduction: Humans are exposed to multiple environmental chemicals via different sources resulting in complex real-life exposure patterns. Insight into these patterns is important for applications such as linkage to health effects and (mixture) risk assessment. By providing internal exposure levels of (metabolites of) chemicals, biomonitoring studies can provide snapshots of exposure patterns and factors that drive them. Presentation of biomonitoring data in networks facilitates the detection of such exposure patterns and allows for the systematic comparison of observed exposure patterns between datasets and strata within datasets. Methods: We demonstrate the use of network techniques in human biomonitoring data from cord blood samples collected in three campaigns of the Flemish Environment and Health Studies (FLEHS) (sampling years resp. 2002-2004, 2008-2009, and 2013-2014). Measured biomarkers were multiple organochlorine compounds, PFAS and metals. Comparative network analysis (CNA) was conducted to systematically compare networks between sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Results: Network techniques offered an intuitive approach to visualize complex correlation structures within human biomonitoring data. The identification of groups of highly connected biomarkers, "communities," within these networks highlighted which biomarkers should be considered collectively in the analysis and interpretation of epidemiological studies or in the design of toxicological mixture studies. Network analyses demonstrated in our example to which extent biomarker networks and its communities changed across the sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Conclusion: Network analysis is a data-driven and intuitive screening method when dealing with multiple exposure biomarkers, which can easily be upscaled to high dimensional HBM datasets, and can inform mixture risk assessment approaches.

Assessment of Determinants of Emission Potentially Affecting the Concentration of Airborne Nano-Objects and Their Agglomerates and Aggregates.

Background: Nano-specific inhalation exposure models could potentially be effective tools to assess and control worker exposure to nano-objects, and their aggregates and agglomerates (NOAA). However, due to the lack of reliable and consistent collected NOAA exposure data, the scientific basis for validation of the existing NOAA exposure models is missing or limited. The main objective of this study was to gain more insight into the effect of various determinants underlying the potential on the concentration of airborne NOAA close to the source with the purpose of providing a scientific basis for existing and future exposure inhalation models. Method: Four experimental studies were conducted to investigate the effect of 11 determinants of emission on the concentration airborne NOAA close to the source during dumping of ~100% nanopowders. Determinants under study were: nanomaterial, particle size, dump mass, height, rate, ventilation rate, mixing speed, containment, particle surface coating, moisture content of the powder, and receiving surface. The experiments were conducted in an experimental room (19.5 m3) with well-controlled environmental and ventilation conditions. Particle number concentration and size distribution were measured using real-time measurement devices. Results: Dumping of nanopowders resulted in a higher number concentration and larger particles than dumping their reference microsized powder (P < 0.05). Statistically significant more and larger particles were also found during dumping of SiO2 nanopowder compared to TiO2/Al2O3 nanopowders. Particle surface coating did not affect the number concentration but on average larger particles were found during dumping of coated nanopowders. An increase of the powder's moisture content resulted in less and smaller particles in the air. Furthermore, the results indicate that particle number concentration increases with increasing dump height, rate, and mass and decreases when ventilation is turned on. Discussion: These results give an indication of the direction and magnitude of the effect of the studied determinants on concentrations close to the source and provide a scientific basis for (further) development of existing and future NOAA inhalation exposure models.