Occupational exposure to potentially toxic elements alters gene expression profiles in formal and informal Brazilian workers.

Chemical elements, such as toxic metals, have previously demonstrated their ability to alter gene expression in humans and other species. In this study, microarray analysis was used to compare the gene expression profiles of different occupational exposure populations: a) informal workers who perform soldering of jewelry inside their houses (n = 22) in São Paulo (SP) State; and b) formal workers from a steel company (n = 10) in Rio de Janeiro (RJ) state, Brazil. Control participants were recruited from the same neighborhoods without occupational chemical exposure (n = 19 in SP and n = 8 in RJ). A total of 68 blood samples were collected and RNA was extracted and hybridized using an Agilent microarray platform. Data pre-processing, statistical and pathway analysis were performed using GeneSpring software. Different expression was detected by fold-change analysis resulting in 16 up- and 33 down-regulated genes in informal workers compared to the control group. Pathway analysis revealed genes enriched in MAPK, Toll-like receptor, and NF-kappa B signaling pathways, involved in inflammatory and immune responses. In formal workers, 20 up- and 50 down-regulated genes were found related to antimicrobial peptides, defensins, neutrophil degranulation, Fc-gamma receptor-dependent phagocytosis, and pathways associated with atherosclerosis development, which is one of the main factors involved in the progression of cardiovascular diseases. The gene IFI27 was the only one commonly differentially expressed between informal and formal workers and is known to be associated with various types of cancer. In conclusion, differences in gene expression related to occupational exposure are mainly associated with inflammation and immune response. Previous research has identified a link between inflammation and immune responses and the development of chronic diseases, suggesting that prolonged occupational exposures to potentially toxic elements in Brazilian metal workers could lead to negative health outcomes. Further analysis should be carried out to investigate its direct effects and to validate causal associations.

Integrated assessment of personal monitor applications for evaluating exposure to urban stressors: A scoping review.

Urban stressors pose a health risk, and individual-level assessments provide necessary and fine-grained insight into exposure. An ever-increasing amount of research literature on individual-level exposure to urban stressors using data collected with personal monitors, has called for an integrated assessment approach to identify trends, gaps and needs, and provide recommendations for future research. To this end, a scoping review of the respective literature was performed, as part of the H2020 URBANOME project. Moreover, three specific aims were identified: (i) determine current state of research, (ii) analyse literature according with a waterfall methodological framework and identify gaps and needs, and (iii) provide recommendations for more integrated, inclusive and robust approaches. Knowledge and gaps were extracted based on a systematic approach, e.g., data extraction questionnaires, as well as through the expertise of the researchers performing the review. The findings were assessed through a waterfall methodology of delineating projects into four phases. Studies described in the papers vary in their scope, with most assessing exposure in a single macro domain, though a trend of moving towards multi-domain assessment is evident. Simultaneous measurements of multiple stressors are not common, and papers predominantly assess exposure to air pollution. As urban environments become more diverse, stakeholders from different groups are included in the study designs. Most frequently (per the quadruple helix model), civil society/NGO groups are involved, followed by government and policymakers, while business or private sector stakeholders are less frequently represented. Participants in general function as data collectors and are rarely involved in other phases of the research. While more active involvement is not necessary, more collaborative approaches show higher engagement and motivation of participants to alter their lifestyles based on the research results. The identified trends, gaps and needs can aid future exposure research and provide recommendations on addressing different urban communities and stakeholders.

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.

Empowering Participatory Research in Urban Health: Wearable Biometric and Environmental Sensors for Activity Recognition.

Participatory exposure research, which tracks behaviour and assesses exposure to stressors like air pollution, traditionally relies on time-activity diaries. This study introduces a novel approach, employing machine learning (ML) to empower laypersons in human activity recognition (HAR), aiming to reduce dependence on manual recording by leveraging data from wearable sensors. Recognising complex activities such as smoking and cooking presents unique challenges due to specific environmental conditions. In this research, we combined wearable environment/ambient and wrist-worn activity/biometric sensors for complex activity recognition in an urban stressor exposure study, measuring parameters like particulate matter concentrations, temperature, and humidity. Two groups, Group H (88 individuals) and Group M (18 individuals), wore the devices and manually logged their activities hourly and minutely, respectively. Prioritising accessibility and inclusivity, we selected three classification algorithms: k-nearest neighbours (IBk), decision trees (J48), and random forests (RF), based on: (1) proven efficacy in existing literature, (2) understandability and transparency for laypersons, (3) availability on user-friendly platforms like WEKA, and (4) efficiency on basic devices such as office laptops or smartphones. Accuracy improved with finer temporal resolution and detailed activity categories. However, when compared to other published human activity recognition research, our accuracy rates, particularly for less complex activities, were not as competitive. Misclassifications were higher for vague activities (resting, playing), while well-defined activities (smoking, cooking, running) had few errors. Including environmental sensor data increased accuracy for all activities, especially playing, smoking, and running. Future work should consider exploring other explainable algorithms available on diverse tools and platforms. Our findings underscore ML's potential in exposure studies, emphasising its adaptability and significance for laypersons while also highlighting areas for improvement.

Assessment of Individual-Level Exposure to Airborne Particulate Matter during Periods of Atmospheric Thermal Inversion.

Air pollution exposure is harmful to human health and reducing it at the level of an individual requires measurements and assessments that capture the spatiotemporal variability of different microenvironments and the influence of specific activities. In this paper, activity-specific and general indoor and outdoor exposure during and after a period of high concentrations of particulate matter (PM), e.g., an atmospheric thermal inversion (ATI) in the Ljubljana subalpine basin, Slovenia, was assessed. To this end, personal particulate matter monitors (PPM) were used, worn by participants of the H2020 ICARUS sampling campaigns in spring 2019 who also recorded their hourly activities. ATI period(s) were determined based on data collected from two meteorological stations managed by the Slovenian Environmental Agency (SEA). Results showed that indoor and outdoor exposure to PM was significantly higher during the ATI period, and that the difference between mean indoor and outdoor exposure to PM was much higher during the ATI period (23.0 µg/m3) than after (6.5 µg/m3). Indoor activities generally were associated with smaller differences, with cooking and cleaning even having higher values in the post-ATI period. On the other hand, all outdoor activities had higher PM values during the ATI than after, with larger differences, mostly >30.0 µg/m3. Overall, this work demonstrated that an individual-level approach can provide better spatiotemporal resolution and evaluate the relative importance of specific high-exposure events, and in this way provide an ancillary tool for exposure assessments.

Assessing personal exposure using Agent Based Modelling informed by sensors technology.

Technology innovations create possibilities to capture exposure-related data at a great depth and breadth. Considering, though, the substantial hurdles involved in collecting individual data for whole populations, this study introduces a first approach of simulating human movement and interaction behaviour, using Agent Based Modelling (ABM). A city scale ABM was developed for urban Thessaloniki, Greece that feeds into population-based exposure assessment without imposing prior bias, basing its estimations onto emerging properties of the behaviour of the computerised autonomous decision makers (agents) that compose the city-system. Population statistics, road and buildings networks data were transformed into human, road and building agents, respectively. Survey outputs with time-use patterns were associated with human agent rules, aiming to model representative to real-world behaviours. Moreover, time-geography of exposure data, derived from a local sensors campaign, was used to inform and enhance the model. As a prevalence of an agent-specific decision-making, virtual individuals of different sociodemographic backgrounds express different spatiotemporal behaviours and their trajectories are coupled with spatially resolved pollution levels. Personal exposure was evaluated by assigning PM concentrations to human agents based on coordinates, type of location and intensity of encountered activities. Study results indicated that PM2.5 inhalation adjusted exposure between housemates can differ by 56.5% whereas exposure between two neighbours can vary by as much as 87%, due to the prevalence of different behaviours. This study provides details of a new methodology that permits the cost-effective construction of refined time-activity diaries and daily exposure profiles, taking into account different microenvironments and sociodemographic characteristics. The proposed method leads to a refined exposure assessment model, addressing effectively vulnerable subgroups of population. It can be used for evaluating the probable impacts of different public health policies prior to implementation reducing, therefore, the time and expense required to identify efficient measures.

Cardioprotective effects of hesperidin on carbon monoxide poisoned in rats.

Carbon monoxide (CO) poisoning causes cardiotoxicity and so far, no definite antidote has been proposed to overcome CO-induced adverse outcomes. Hesperidin, a citrus flavonoid, has shown cardio-protective effects in cardiac ischemia/reperfusion models. This study investigated the protective effects of hesperidin against CO-induced cardiac injury. To induce CO poisoning, rats were exposed to CO at 3000 ppm for 60 min. On the exposure day and the four following days, hesperidin (at three different doses of 25, 50, and 100 mg/kg/day) was administered intraperitoneally. A group of animals received normal saline and served as the control group. The electrocardiogram (ECG) was recorded and evaluated with special focus on S-T segment changes (depression or elevation), T-wave alterations, AV block and ventricular and supraventricular arrhythmias. On day 6 (i.e., the day after the last injection day), the animals were sacrificed and the hearts were harvested and evaluated for necrosis using hematoxylin and eosin staining. In addition, Akt protein expression levels and BAX/BCL2 ratio were determined by western blotting. Our results showed that hesperidin decreased cardiac necrosis. In animals treated with hesperidin 100 mg/kg, Akt protein expression was increased, while the BAX/BCL2 ratio was significantly decreased. ECG changes were reversed in all groups 2 h following CO exposure, regardless of hesperidin administration. Overall, hesperidin decreased the deleterious cardiac effects of CO poisoning in rats.

Development of a generic lifelong physiologically based biokinetic model for exposome studies.

The current study within the frame of the HEALS project aims at the development of a lifelong physiologically based biokinetic (PBBK) model for exposome studies. The aim was to deliver a comprehensive modelling framework for addressing a large chemical space. Towards this aim, the delivered model can easily adapt parameters from existing ad-hoc models or complete the missing compound specific parameters using advanced quantitative structure activity relationship (QSAR). All major human organs are included, as well as arterial, venous, and portal blood compartments. Xenobiotics and their metabolites are linked through the metabolizing tissues. This is mainly the liver, but also other sites of metabolism might be considered (intestine, brain, skin, placenta) based on the presence or not of the enzymes involved in the metabolism of the compound of interest. Each tissue is described by three mass balance equations for (a) red blood cells, (b) plasma and interstitial tissue and (c) cells respectively. The anthropometric parameters of the models are time dependent, so as to provide a lifetime internal dose assessment, as well as to describe the continuously changing physiology of the mother and the developing fetus. An additional component of flexibility is that the biokinetic processes that relate to metabolism are related with either Michaelis-Menten kinetics, as well as intrinsic clearance kinetics. The capability of the model is demonstrated in the assessment of internal exposure and the prediction of expected biomonitored levels in urine for three major compounds within the HEALS project, namely bisphenol A (BPA), Bis(2-ethylhexyl) phthalate (DEHP) and cadmium (Cd). The results indicated that the predicted urinary levels fit very well with the ones from human biomonitoring (HBM) studies; internal exposure to plasticizers is very low (in the range of ng/L), while internal exposure to Cd is in the range of µg/L.

Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data.

Low-cost sensors can be used to improve the temporal and spatial resolution of an individual's particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6-22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.

Urinary bisphenol A in children, mothers and fathers from Slovenia: Overall results and determinants of exposure.

In the present study, urinary bisphenol A (BPA) levels were reported for the first time in the Slovenian general population and were evaluated with regard to dietary and non-dietary exposure sources, and compared according to age, gender and area of residence. First morning urine was collected from children (6-11 years), their mothers (30-52 years) and fathers (30-53 years), living in urban and rural areas of Slovenia. Besides basic questionnaire data on general population characteristics, socio-economic status and dietary habits, BPA-specific data was also collected, including consumption of food and beverages from plastic and canned containers, presence of white dental fillings, the use of specific consumer products and hormonal treatments. Urine samples were analysed for both free and conjugated BPA using GC-MS/MS. The urinary levels of total BPA in children, mothers and fathers were low, with geometric means of 1.51, 0.79, and 0.20 µg/g creatinine, respectively. The levels were comparable with the levels reported for other European countries and were all below the current health-based guidance values. In line with large-scale surveys, the data revealed age-dependant BPA urinary levels, with the highest levels in the youngest age group. In mothers, urinary levels of BPA were determined by hormonal interactions more than dietary sources, while a positive association between urinary BPA and diet was apparent in children (canned food/drink and food from plastic material) and fathers (canned food/drink). The study clearly shows that physiological and behavioural differences account for differences in levels of urinary BPA among study groups, a finding that sets the priorities for future research.

Risk characterization of bisphenol-A in the Slovenian population starting from human biomonitoring data.

The current study aims to characterize exposure and risk associated to bisphenol-A (BPA) exposure in Slovenia, starting from biomonitoring data. Based on the urinary data, daily intake for the individuals was back-calculated using a physiology based biokinetic (PBBK) model properly parameterized for BPA, coupled with an exposure reconstruction algorithm. Re-running the PBBK model in forward mode allowed the estimation of biologically effective dose (free plasma BPA) and the respective daily area under the curve (AUC). Finally, risk characterization ratio was derived using both external and internal dose metrics. The urinary BPA levels were found low, with GM of 0.79, 1.51 and 0.20 µg/g creatinine for mothers, children and fathers respectively, similar to the levels of other European countries. Based on the above and accounting for the dynamics of exposure and biokinetics, daily intake was estimated, median exposure levels have been estimated equal to 0.019, 0.035 and 0.005 µg/kg_bw/d for mothers, fathers and children respectively. The highest estimated intake level was found in a child, equal to 0.87 µg/kg_bw/d, while the maximum intake for mothers and fathers were 0.7 and 0.8 µg/kg_bw/d respectively. The respective RCR levels using the EFSA t-TDI of 4 µg/kg_bw/d were 2 magnitudes of order lower below 1, independently of the selected method. It has to be noted that had daily intake been estimated solely based on the urinary concentrations mass balance, the estimated intake would be lower, as a result of the oversimplification on exposure and elimination time dynamics. This highlights the importance for using PBBK modelling based exposure reconstruction schemes for rapidly metabolized and excreted compounds such as BPA, as well as the study design of efficient sampling for rapidly metabolized compounds.

A dual mixture of persistent organic pollutants modifies carbohydrate metabolism in the human hepatic cell line HepaRG.

Individuals as well as entire ecosystems are exposed to mixtures of Persistent Organic Pollutants (POPs). Previously, we showed, by a non-targeted approach, that the expression of several genes involved in carbohydrate metabolism was almost completely inhibited in the human hepatic cell line HepaRG following exposure to a mixture of the organochlorine insecticide alpha-endosulfan and 2,3,7,8 tetrachlorodibenzo-p-dioxin. In this European HEALS project, which studies the effects of the exposome on human health, we used a Physiologically Based BioKinetic model to compare the concentrations previously used in vitro with in vivo exposures for humans. We investigated the effects of these POPs on the levels of proteins, on glycogen content, glucose production and the oxidation of glucose into CO2 and correlated them to the expression of genes involved in carbohydrate metabolism as measured by RT-qPCR. Exposure to individual POPs and the mixture decreased the expression of the proteins investigated as well as glucose output (up to 82%), glucose oxidation (up to 29%) and glycogen content (up to 48%). siRNAs that specifically inhibit the expression of several xenobiotic receptors were used to assess receptor involvement in the effects of the POPs. In the HepaRG model, we demonstrate that the effects are mediated by the aryl hydrocarbon receptor and the estrogen receptor alpha, but not the pregnane X receptor or the constitutive androstane receptor. These results provide evidence that exposure to combinations of POPs, acting through different signaling pathways, may affect, more profoundly than single pollutants alone, metabolic pathways such as carbohydrate/energy metabolism and play a potential role in pollutant associated metabolic disorders.

A model for estimating the lifelong exposure to PM2.5 and NO2 and the application to population studies.

Numerous epidemiological studies have confirmed the negative influences of air pollutants on human health, where fine particles (PM2.5) and nitrogen dioxide (NO2) cause the highest health risks. However, the traditional studies have only involved the ambient concentration for a short to medium time period, which ignores the influence of indoor sources, the individual time-activity pattern, and the fact that the health status is impacted by the long-term accumulated exposure. The aim of this paper is to develop a methodology to simulate the lifelong exposure (rather than outdoor concentration) to PM2.5 and NO2 for individuals in Europe. This method is realized by developing a probabilistic model that integrates an outdoor air quality model, a model estimating indoor air pollution, an exposure model, and a life course trajectory model for predicting retrospectively the employment status. This approach has been applied to samples of two population studies in the frame of the European Commission FP7-ENVIRONMENT research project HEALS (Health and Environment-wide Associations based on Large Population Surveys), where socioeconomic data of the participants have been collected. Results show that the simulated exposures to both pollutants for the samples are influenced by socio-demographic characteristics, including age, gender, residential location, employment status and smoking habits. Both outdoor concentrations and indoor sources play an important role in the total exposure. Moreover, large variances have been observed among countries and cities. The application of this methodology provides valuable insights for the exposure modelling, as well as important input data for exploring the correlation between exposure and health impacts.

Lifelong exposure to multiple stressors through different environmental pathways for European populations.

Traditional exposure studies provide valuable insights for epidemiology, toxicology, and risk assessment. Throughout their lives, individuals are exposed to thousands of stressors in the environment which are not static, but influenced by environmental, temporal, spatial, and even socio-demographic factors. Existing exposure studies have usually focused on specific stressors for a constrained period of time. In response, the concept of the exposome has been raised, which is defined as the totality of exposure experienced from conception until death. The EU FP7-ENVIRONMENT research project HEALS was launched with the aim of incorporating a series of novel technologies, data analysis, and modelling tools to efficiently support exposome studies in Europe. The authors have developed a framework of modelling tools for estimating the long-term external exposure of selected population groups to multiple stressors through different pathways. As the starting point, the stressors, including electromagnetic fields (EMF) and ultraviolet light (UV) through dermal uptake, phthalates (DEHP, DIDP, and DINP) through inhalation, as well as chromium, mercury, and lead through food intake, have been selected. The simulation for multiple stressors has been realised by developing a probabilistic model that integrates the micro-environment approach, time-activity patterns, and a life course trajectory model. The methodology has been applied to a selected sample of subjects enrolled in the Italian Twin Registry (ITR). The results show that long-term exposures to multiple stressors are affected by factors including age, gender, geographical location, and education level. The methods developed in this paper extended the temporal and spatial scales of exposure modelling in Europe. Moreover, the application of our methods provided a novel approach and crucial input data for future work on environment-wide association studies.

Physiology-based toxicokinetic modelling in the frame of the European Human Biomonitoring Initiative.

Given the opportunities provided by internal dosimetry modelling in the interpretation of human biomonitoring (HBM) data, the assessment of the links between exposure to chemicals and observed HBM data can be effectively supported by PBTK modelling. This paper gives a comprehensive review of available human PBTK models for compounds selected as a priority by the European Human Biomonitoring Initiative (HBM4EU). We highlight their advantages and deficiencies and suggest steps for advanced internal dose modelling. The review of the available PBTK models highlighted the conceptual differences between older models compared to the ones developed recently, reflecting commensurate differences in research questions. Due to the lack of coordinated strategies for deriving useful biomonitoring data for toxicokinetic properties, significant problems in model parameterisation still remain; these are further increased by the lack of human toxicokinetic data due to ethics issues. Finally, questions arise as well as to the extent they are really representative of interindividual variability. QSARs for toxicokinetic properties is a complementary approach for PBTK model parameterisation, especially for data poor chemicals. This approach could be expanded to model chemico-biological interactions such as intestinal absorption and renal clearance; this could serve the development of more complex generic PBTK models that could be applied to newly derived chemicals. Another gap identified is the framework for mixture interaction terms among compounds that could eventually interact in metabolism. From the review it was concluded that efforts should be shifted toward the development of generic multi-compartmental and multi-route models, supported by targeted biomonitoring coupled with parameterisation by both QSAR approach and experimental (in-vivo and in-vitro) data for newly developed and data poor compounds.

Critical assessment and integration of separate lines of evidence for risk assessment of chemical mixtures.

Humans are exposed to multiple chemicals on a daily basis instead of to just a single chemical, yet the majority of existing toxicity data comes from single-chemical exposure. Multiple factors must be considered such as the route, concentration, duration, and the timing of exposure when determining toxicity to the organism. The need for adequate model systems (in vivo, in vitro, in silico and mathematical) is paramount for better understanding of chemical mixture toxicity. Currently, shortcomings plague each model system as investigators struggle to find the appropriate balance of rigor, reproducibility and appropriateness in mixture toxicity studies. Significant questions exist when comparing single-to mixture-chemical toxicity concerning additivity, synergism, potentiation, or antagonism. Dose/concentration relevance is a major consideration and should be subthreshold for better accuracy in toxicity assessment. Previous work was limited by the technology and methodology of the time, but recent advances have resulted in significant progress in the study of mixture toxicology. Novel technologies have added insight to data obtained from in vivo studies for predictive toxicity testing. These include new in vitro models: omics-related tools, organs-on-a-chip and 3D cell culture, and in silico methods. Taken together, all these modern methodologies improve the understanding of the multiple toxicity pathways associated with adverse outcomes (e.g., adverse outcome pathways), thus allowing investigators to better predict risks linked to exposure to chemical mixtures. As technology and knowledge advance, our ability to harness and integrate separate streams of evidence regarding outcomes associated with chemical mixture exposure improves. As many national and international organizations are currently stressing, studies on chemical mixture toxicity are of primary importance.

Biomarkers of exposure in environment-wide association studies - Opportunities to decode the exposome using human biomonitoring data.

BACKGROUND: The European Union's 7th Framework Programme (EU's FP7) project HEALS - Health and Environment-wide Associations based on Large Population Surveys - aims a refinement of the methodology to elucidate the human exposome. Human biomonitoring (HBM) provides a valuable tool for understanding the magnitude of human exposure from all pathways and sources. However, availability of specific biomarkers of exposure (BoE) is limited. OBJECTIVES: The objective was to summarize the availability of BoEs for a broad range of environmental stressors and exposure determinants and corresponding reference and exposure limit values and biomonitoring equivalents useful for unraveling the exposome using the framework of environment-wide association studies (EWAS). METHODS: In a face-to-face group discussion, scope, content, and structure of the HEALS deliverable "Guidelines for appropriate BoE selection for EWAS studies" were determined. An expert-driven, distributed, narrative review process involving around 30 individuals of the HEALS consortium made it possible to include extensive information targeted towards the specific characteristics of various environmental stressors and exposure determinants. From the resulting 265 page report, targeted information about BoE, corresponding reference values (e.g., 95th percentile or measures of central tendency), exposure limit values (e.g., the German HBM I and II values) and biomonitoring equivalents (BEs) were summarized and updated. RESULTS: 64 individual biological, chemical, physical, psychological and social environmental stressors or exposure determinants were included to fulfil the requirements of EWAS. The list of available BoEs is extensive with a number of 135; however, 12 of the stressors and exposure determinants considered do not leave any measurable specific substance in accessible body specimens. Opportunities to estimate the internal exposure stressors not (yet) detectable in human specimens were discussed. CONCLUSIONS: Data about internal exposures are useful to decode the exposome. The paper provides extensive information for EWAS. Information included serves as a guideline - snapshot in time without any claim to comprehensiveness - to interpret HBM data and offers opportunities to collect information about the internal exposure of stressors if no specific BoE is available.

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.

Human biomonitoring data analysis for metals in an Italian adolescents cohort: An exposome approach.

The first Italian human biomonitoring survey (PROBE - PROgramme for Biomonitoring general population Exposure) considered a reference population of adolescents, aged 13-15 years, living in urban and rural areas and investigated their exposure to metals. The study was expanded up to 453 adolescents living in the same areas of Latium Region (Italy) and blood samples were analyzed for 19 metals (As, Be, Cd, Co, Cr, Hg, Ir, Mn, Mo, Ni, Pb, Pd, Pt, Rh, Sb, Sn, Tl, V, and W) by sector field inductively coupled plasma mass spectrometry. The exposure assessment was contextualized following an exposome approach that considered several determinants related to the subjects, available environmental parameters and geo-coding of residence address. To assess the influence of exposure determinants and modifiers on children biomarkers levels we used two independent methodologies. The first makes use of the so-called Environment-Wide Association Study (EWAS) methodology while the second was based on the application of a Generalized Liner Model (GLM) capturing co-exposures to pairs of key determinants. Based on our analysis, Hg and As were positively associated with dietary pathways (primarily linked to fish and to a lesser extent to milk consumption) while Cr showed a more complex interaction between co-exposure to different dietary pathways (milk and fish) coupled to proximity of residence to industrial activities. In addition to diet, socio-economic status of the mother revealed robust statistical associations with Cd, Ni and W biomonitoring levels in the respective children.