Application of AOPs to assist regulatory assessment of chemical risks - Case studies, needs and recommendations.

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA.

Health Risk Assessment of Ortho-Toluidine Utilising Human Biomonitoring Data of Workers and the General Population.

The aim of this work was to demonstrate how human biomonitoring (HBM) data can be used to assess cancer risks for workers and the general population. Ortho-toluidine, OT (CAS 95-53-4) is an aniline derivative which is an animal and human carcinogen and may cause methemoglobinemia. OT is used as a curing agent in epoxy resins and as intermediate in producing herbicides, dyes, and rubber chemicals. A risk assessment was performed for OT by using existing HBM studies. The urinary mass-balance methodology and generic exposure reconstruction PBPK modelling were both used for the estimation of the external intake levels corresponding to observed urinary levels. The external exposures were subsequently compared to cancer risk levels obtained from the evaluation by the Scientific Committee on Occupational Exposure Limits (SCOEL). It was estimated that workers exposed to OT have a cancer risk of 60 to 90:106 in the worst-case scenario (0.9 mg/L in urine). The exposure levels and cancer risk of OT in the general population were orders of magnitude lower when compared to workers. The difference between the output of urinary mass-balance method and the general PBPK model was approximately 30%. The external exposure levels calculated based on HBM data were below the binding occupational exposure level (0.5 mg/m3) set under the EU Carcinogens and Mutagens Directive.

An exposome connectivity paradigm for the mechanistic assessment of the effects of prenatal and early life exposure to metals on neurodevelopment.

The exposome paradigm through an integrated approach to investigating the impact of perinatal exposure to metals on child neurodevelopment in two cohorts carried out in Slovenia (PHIME cohort) and Greece (HERACLES cohort) respectively, is presented herein. Heavy metals are well-known neurotoxicants with well-established links to impaired neurodevelopment. The links between in utero and early-life exposure to metals, metabolic pathway dysregulation, and neurodevelopmental disorders were drawn through urinary and plasma untargeted metabolomics analysis, followed by the combined application of in silico and biostatistical methods. Heavy metal prenatal and postnatal exposure was evaluated, including parameters indirectly related to exposure and health adversities, such as sociodemographic and anthropometric parameters and dietary factors. The primary outcome of the study was that the identified perturbations related to the TCA cycle are mainly associated with impaired mitochondrial respiration, which is detrimental to cellular homeostasis and functionality; this is further potentiated by the capacity of heavy metals to induce oxidative stress. Insufficient production of energy from the mitochondria during the perinatal period is associated with developmental disorders in children. The HERACLES cohort included more detailed data regarding diet and sociodemographic status of the studied population, allowing the identification of a broader spectrum of effect modifiers, such as the beneficial role of a diet rich in antioxidants such as lycopene and ω-3 fatty acids, the negative effect the consumption of food items such as pork and chicken meat has or the multiple impacts of fish consumption. Beyond diet, several other factors have been proven influential for child neurodevelopment, such as the proximity to pollution sources (e.g., waste treatment site) and the broader living environment, including socioeconomic and demographic characteristics. Overall, our results demonstrate the utility of exposome-wide association studies (EWAS) toward understanding the relationships among the multiple factors that determine human exposure and the underlying biology, reflected as omics markers of effect on neurodevelopment during childhood.

The exposome - a new approach for risk assessment.

Complementing the human genome with an exposome reflects the increasingly obvious impact of environmental exposure, which far exceeds the role of genetics, on human health. Considering the complexity of exposures and, in addition, the reactions of the body to exposures - i.e., the exposome - reverses classical exposure science where the precise measurement of single or few exposures is associated with specific health or environmental effects. The complete description of an individual's exposome is impossible; even less so is that of a population. We can, however, cast a wider net by foregoing some rigor in assessment and compensating with the statistical power of rich datasets. The advent of omics technologies enables a relatively cheap, high-content description of the biological effects of substances, especially in tissues and biofluids. They can be combined with many other rich data-streams, creating big data of exposure and effect. Computational methods increasingly allow data integration, discerning the signal from the noise and formulating hypotheses of exposure-effect relationships. These can be followed up in a targeted way. With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure (interactions) and health/environment effect associations. This may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an expo-sure-driven approach. Technological developments and synergies between approaches, quality assurance (ultimately as Good Exposome Practices), and the integration of mechanistic thinking will advance this approach.

Addressing complexity of health impact assessment in industrially contaminated sites via the exposome paradigm.

BACKGROUND: this paper is based upon work from COST Action ICSHNet. Assessment of the health impacts related to industrially contaminated sites (ICSs) is a major scientific challenge with multiple societal implications. Most studies related to associations between ICSs and public health do not provide established mechanistic links between environmental exposure and disease burden, potentially resulting in suboptimal risk management measures. OBJECTIVES: to assess the potential of the exposome paradigm to overhaul ICS risk assessment and management leading to precision prevention and targeted interventions. METHODS: we selected the second largest waste landfill in Europe and the data collected in the frame of the HERACLES study on the exposome and health and analysed them together with clinical evidence of neurodevelopmental perturbations following the exposome-wide association study paradigm using the exposome analysis tools; briefly, these pertain to refined exposure assessment, internal dosimetry, and human biomonitoring, multi-omics/toxicity pathway analysis and advanced statistical tools for environment-wide association studies. Waste streams and the related contamination of environmental media are not viewed in isolation, but rather as components of the expotype, the vector of exposures an individual is exposed to over time. Thus, a multi-route and multi-pathway exposure estimation can be performed setting a realistic basis for integrated health risk and impact assessment. The study was located in the area around the landfill of Fili, outside Athens (Greece). Since 2012, 325 children were recruited and have been followed using a combination of human biomonitoring, advanced-omics analysis on biosamples, environmental monitoring for metals and organic contaminants, and dietary pattern information. The children were clinically tested for neurodevelopmental perturbations during different developmental stages and the results were analysed according to the exposome-wide association study methodology in conjunction with environmental exposure, but also socioeconomic, dietary, and metabolic determinants of internal exposure and health risk. RESULTS: using the exposome analysis tools, we confirmed that proximity to a landfill and the consequent soil contamination with metals are critical for children neurodevelopment. However, it was found that additional parameters such as parental education level, socioeconomic status, and nutrition contribute either positively or negatively on child neurodevelopment. CONCLUSIONS: the exposome concept comes to overhaul the nature vs. nurture paradigm and embraces a world of dynamic interactions between environmental exposures, endogenous exposures, and genetic expression in humans. In this context, the exposome paradigm provides a novel tool for holistic ICS health risk management. The effectiveness of the exposome approach is demonstrated in the case of Athens, the capital of Greece, where health effects associated to long term exposure to a major waste management facility (landfill) are presented.

A review of exposure assessment methods for epidemiological studies of health effects related to industrially contaminated sites.

BACKGROUND: this paper is based upon work from COST Action ICSHNet. Health risks related to living close to industrially contaminated sites (ICSs) are a public concern. Toxicology-based risk assessment of single contaminants is the main approach to assess health risks, but epidemiological studies which investigate the relationships between exposure and health directly in the affected population have contributed important evidence. Limitations in exposure assessment have substantially contributed to uncertainty about associations found in epidemiological studies. OBJECTIVES: to examine exposure assessment methods that have been used in epidemiological studies on ICSs and to provide recommendations for improved exposure assessment in epidemiological studies by comparing exposure assessment methods in epidemiological studies and risk assessments. METHODS: after defining the multi-media framework of exposure related to ICSs, we discussed selected multi-media models applied in Europe. We provided an overview of exposure assessment in 54 epidemiological studies from a systematic review of hazardous waste sites; a systematic review of 41 epidemiological studies on incinerators and 52 additional studies on ICSs and health identified for this review. RESULTS: we identified 10 multi-media models used in Europe primarily for risk assessment. Recent models incorporated estimation of internal biomarker levels. Predictions of the models differ particularly for the routes 'indoor air inhalation' and 'vegetable consumption'. Virtually all of the 54 hazardous waste studies used proximity indicators of exposure, based on municipality or zip code of residence (28 studies) or distance to a contaminated site (25 studies). One study used human biomonitoring. In virtually all epidemiological studies, actual land use was ignored. In the 52 additional studies on contaminated sites, proximity indicators were applied in 39 studies, air pollution dispersion modelling in 6 studies, and human biomonitoring in 9 studies. Exposure assessment in epidemiological studies on incinerators included indicators (presence of source in municipality and distance to the incinerator) and air dispersion modelling. Environmental multi-media modelling methods were not applied in any of the three groups of studies. CONCLUSIONS: recommendations for refined exposure assessment in epidemiological studies included the use of more sophisticated exposure metrics instead of simple proximity indicators where feasible, as distance from a source results in misclassification of exposure as it ignores key determinants of environmental fate and transport, source characteristics, land use, and human consumption behaviour. More validation studies using personal exposure or human biomonitoring are needed to assess misclassification of exposure. Exposure assessment should take more advantage of the detailed multi-media exposure assessment procedures developed for risk assessment. The use of indicators can be substantially improved by linking definition of zones of exposure to existing knowledge of extent of dispersion. Studies should incorporate more often land use and individual behaviour.

Public health impacts of city policies to reduce climate change: findings from the URGENCHE EU-China project.

BACKGROUND: Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments. METHODS: Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys. RESULTS: There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied. CONCLUSIONS: The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries.

Health impact and monetary cost of exposure to particulate matter emitted from biomass burning in large cities.

The study deals with the assessment of health impact and the respective economic cost attributed to particulate matter (PM) emitted into the atmosphere from biomass burning for space heating, focusing on the differences between the warm and cold seasons in 2011-2012 and 2012-2013 in Thessaloniki (Greece). Health impact was assessed based on estimated exposure levels and the use of established WHO concentration-response functions (CRFs) for all-cause mortality, infant mortality, new chronic bronchitis cases, respiratory and cardiac hospital admissions. Monetary cost was based on the valuation of the willingness-to-pay/accept (WTP/WTA), to avoid or compensate for the loss of welfare associated with illness. Results showed that long term mortality during the 2012-2013 winter increased by 200 excess deaths in a city of almost 900,000 inhabitants or 3540 years of life lost, corresponding to an economic cost of almost 200-250m€. New chronic bronchitis cases dominate morbidity estimates (490 additional new cases corresponding to a monetary cost of 30m€). Estimated health and monetary impacts are more severe during the cold season, despite its smaller duration (4 months). Considering that the increased ambient air concentrations (and the integral of outdoor/indoor exposure) are explained by shifting from oil to biomass for domestic heating purposes, several alternative scenarios were evaluated. Policy scenario analysis revealed that significant public health and monetary benefits (up to 2b€ in avoided mortality and 130m€ in avoided illness) might be obtained by limiting the biomass share in the domestic heat energy mix. Fiscal policy affecting fuels/technologies used for domestic heating needs to be reconsidered urgently, since the net tax loss from avoided oil taxation due to reduced consumption was further compounded by the public health cost of increased mid-term morbidity and mortality.

Measurements of benzene and formaldehyde in a medium sized urban environment. Indoor/outdoor health risk implications on special population groups.

In the present study, the results of a measurement campaign aiming to assess cancer risk among two special groups of population: policemen and laboratory technicians exposed to the toxic substances, benzene and formaldehyde are presented. The exposure is compared to general population risk. The results show that policemen working outdoor (traffic regulation, patrol on foot or in vehicles, etc.) are exposed at a significantly higher benzene concentration (3-5 times) than the general population, while the exposure to carbonyls is in general lower. The laboratory technicians appear to be highly exposed to formaldehyde while no significant variation of benzene exposure in comparison to the general population is recorded. The assessment revealed that laboratory technicians and policemen run a 20% and 1% higher cancer risk respectively compared to the general population. Indoor working place air quality is more significant in assessing cancer risk in these two categories of professionals, due to the higher Inhalation Unit Risk (IUR) of formaldehyde compared to benzene. Since the origin of the danger to laboratory technicians is clear (use of chemicals necessary for the experiments), in policemen the presence of carbonyls in indoor air concentrations due to smoking or used materials constitute a danger equal to the exposure to traffic originated air pollutants.

Bayesian algorithm implementation in a real time exposure assessment model on benzene with calculation of associated cancer risks.

The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK) risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model. Bayesian algorithm was involved in crucial points of both model sub compartments. The application was evaluated in two filling stations (one urban and one rural). Among several algorithms available for the development of the ANN exposure model, Bayesian regularization provided the best results and seemed to be a promising technique for prediction of the exposure pattern of that occupational population group. On assessing the estimated leukemia risk under the scope of providing a distribution curve based on the exposure levels and the different susceptibility of the population, the Bayesian algorithm was a prerequisite of the Monte Carlo approach, which is integrated in the PBPK-based risk model. In conclusion, the modeling system described herein is capable of exploiting the information collected by the environmental sensors in order to estimate in real time the personal exposure and the resulting health risk for employees of gasoline filling stations.