Integrating endocrine-related health effects into comparative human toxicity characterization

Indigenized Characterization Factors for Health Damage Due to Ambient PM2.5 in Life Cycle Impact Assessment in China

Life cycle assessment (LCA) is a broadly used method for quantifying environmental impacts, and life cycle impact assessment (LCIA) is an important step as well as a major source of uncertainties in LCA. Characterization factors (CFs) are pivotal elements in LCIA models. In China, the health loss due to ambient PM2.5 is an important aspect of LCIA results, which, however, is generally assessed by adopting CFs developed by global models and there remains a need to integrate localized considerations and the latest information for more precise applications in China. In this study, we developed indigenized CFs for LCIA of health damage due to ambient PM2.5 in China by coupling the atmospheric chemical transport model GEOS-Chem, exposure-response model GEMM containing Chinese cohort studies, and the latest local data. Results show that CFs of four major PM2.5 precursors all exhibit significant interregional variation and monthly differences in China. Our results were generally an order of magnitude higher and show disparate spatial distribution compared to CFs currently in use, suggesting that the health damage due to ambient PM2.5 was underestimated in LCIA in China, and indigenized CFs need to be adopted for more accurate results in LCIA and LCA studies.

Probabilistic Reference and 10% Effect Concentrations for Characterizing Inhalation Non-cancer and Developmental/Reproductive Effects for 2,160 Substances

Chemicals assessment and management frameworks rely on regulatory toxicity values, which are based on points of departure (POD) identified following rigorous dose-response assessments. Yet, regulatory PODs and toxicity values for inhalation exposure (i.e., reference concentrations [RfCs]) are available for only ∼200 chemicals. To address this gap, we applied a workflow to determine surrogate inhalation route PODs and corresponding toxicity values, where regulatory assessments are lacking. We curated and selected inhalation in vivo data from the U.S. EPA's ToxValDB and adjusted reported effect values to chronic human equivalent benchmark concentrations (BMCh) following the WHO/IPCS framework. Using ToxValDB chemicals with existing PODs associated with regulatory toxicity values, we found that the 25th %-ile of a chemical's BMCh distribution (POD p 25 BMC h ) could serve as a suitable surrogate for regulatory PODs (Q2 ≥ 0.76, RSE ≤ 0.82 log10 units). We applied this approach to derive POD p 25 BMC h for 2,095 substances with general non-cancer toxicity effects and 638 substances with reproductive/developmental toxicity effects, yielding a total coverage of 2,160 substances. From these POD p 25 BMC h , we derived probabilistic RfCs and human population effect concentrations. With this work, we have expanded the number of chemicals with toxicity values available, thereby enabling a much broader coverage for inhalation risk and impact assessment.

Deep eutectic solvents for the determination of endocrine disrupting chemicals

The harmful effects of endocrine disrupting chemicals (EDCs) to humans and other organisms in the environment have been well established over the years, and more studies are ongoing to classify other chemicals that have the potential to alter or disrupt the regular function of the endocrine system. In addition to toxicological studies, analytical detection systems are progressively being improved to facilitate accurate determination of EDCs in biological, environmental and food samples. Recent microextraction methods have focused on the use of green chemicals that are safe for analytical applications, and present very low or no toxicity upon disposal. Deep eutectic solvents (DESs) have emerged as one of the viable alternatives to the conventional hazardous solvents, and their unique properties make them very useful in different applications. Notably, the use of renewable sources to prepare DESs leads to highly biodegradable products that mitigate negative ecological impacts. This review presents an overview of both organic and inorganic EDCs and their ramifications on human health. It also presents the fundamental principles of liquid phase and solid phase microextraction methods, and gives a comprehensive account of the use of DESs for the determination of EDCs in various samples.

Application of the Key Characteristics Framework to Identify Potential Breast Carcinogens Using Publicly Available in Vivo, in Vitro, and in Silico Data

BACKGROUND

Chemicals that induce mammary tumors in rodents or activate estrogen or progesterone signaling are likely to increase breast cancer (BC) risk. Identifying chemicals with these activities can prompt steps to protect human health.

OBJECTIVES

We compiled data on rodent tumors, endocrine activity, and genotoxicity to assess the key characteristics (KCs) of rodent mammary carcinogens (MCs), and to identify other chemicals that exhibit these effects and may therefore increase BC risk.

METHODS

Using authoritative databases, including International Agency for Research on Cancer (IARC) Monographs and the US Environmental Protection's (EPA) ToxCast, we selected chemicals that induce mammary tumors in rodents, stimulate estradiol or progesterone synthesis, or activate the estrogen receptor (ER) in vitro. We classified these chemicals by their genotoxicity and strength of endocrine activity and calculated the overrepresentation (enrichment) of these KCs among MCs. Finally, we evaluated whether these KCs predict whether a chemical is likely to induce mammary tumors.

RESULTS

We identified 279 MCs and an additional 642 chemicals that stimulate estrogen or progesterone signaling. MCs were significantly enriched for steroidogenicity, ER agonism, and genotoxicity, supporting the use of these KCs to predict whether a chemical is likely to induce rodent mammary tumors and, by inference, increase BC risk. More MCs were steroidogens than ER agonists, and many increased both estradiol and progesterone. Enrichment among MCs was greater for strong endocrine activity vs. weak or inactive, with a significant trend.

DISCUSSION

We identified hundreds of compounds that have biological activities that could increase BC risk and demonstrated that these activities are enriched among MCs. We argue that many of these should not be considered low hazard without investigating their ability to affect the breast, and chemicals with the strongest evidence can be targeted for exposure reduction. We describe ways to strengthen hazard identification, including improved assessments for mammary effects, developing assays for more KCs, and more comprehensive chemical testing. https://doi.org/10.1289/EHP13233.

Probabilistic Points of Departure and Reference Doses for Characterizing Human Noncancer and Developmental/Reproductive Effects for 10,145 Chemicals

BACKGROUND

Regulatory toxicity values used to assess and manage chemical risks rely on the determination of the point of departure (POD) for a critical effect, which results from a comprehensive and systematic assessment of available toxicity studies. However, regulatory assessments are only available for a small fraction of chemicals.

OBJECTIVES

Using in vivo experimental animal data from the U.S. Environmental Protection Agency's Toxicity Value Database, we developed a semiautomated approach to determine surrogate oral route PODs, and corresponding toxicity values where regulatory assessments are unavailable.

METHODS

We developed a curated data set restricted to effect levels, exposure routes, study designs, and species relevant for deriving toxicity values. Effect levels were adjusted to chronic human equivalent benchmark doses (BMDh). We hypothesized that a quantile of the BMDh distribution could serve as a surrogate POD and determined the appropriate quantile by calibration to regulatory PODs. Finally, we characterized uncertainties around the surrogate PODs from intra- and interstudy variability and derived probabilistic toxicity values using a standardized workflow.

RESULTS

The BMDh distribution for each chemical was adequately fit by a lognormal distribution, and the 25th percentile best predicted the available regulatory PODs [R2≥0.78, residual standard error (RSE)≤0.53 log10 units]. We derived surrogate PODs for 10,145 chemicals from the curated data set, differentiating between general noncancer and reproductive/developmental effects, with typical uncertainties (at 95% confidence) of a factor of 10 and 12, respectively. From these PODs, probabilistic reference doses (1% incidence at 95% confidence), as well as human population effect doses (10% incidence), were derived.

DISCUSSION

In providing surrogate PODs calibrated to regulatory values and deriving corresponding toxicity values, we have substantially expanded the coverage of chemicals from 744 to 8,023 for general noncancer effects, and from 41 to 6,697 for reproductive/developmental effects. These results can be used across various risk assessment and risk management contexts, from hazardous site and life cycle impact assessments to chemical prioritization and substitution. https://doi.org/10.1289/EHP11524.

Enhancing the use of exposure science across EU chemical policies as part of the European Exposure Science Strategy 2020-2030

BACKGROUND

A scientific framework on exposure science will boost the multiuse of exposure knowledge across EU chemicals-related policies and improve risk assessment, risk management and communication across EU safety, security and sustainability domains.

OBJECTIVE

To stimulate public and private actors to align and strengthen the cross-policy adoption of exposure assessment data, methods and tools across EU legislation.

METHODS

By mapping and analysing the EU regulatory landscape making use of exposure information, policy and research challenges and key areas of action are identified and translated into opportunities enhancing policy and scientific efficiency.

RESULTS

Identified key areas of actions are to develop a common scientific exposure assessment framework, supported by baseline acceptance criteria and a shared knowledge base enhancing exchangeability and acceptability of exposure knowledge within and across EU chemicals-related policies. Furthermore, such framework will improve communication and management across EU chemical safety, security and sustainability policies comprising sourcing, manufacturing and global trade of goods and waste management. In support of building such a common framework and its effective use in policy and industry, exposure science innovation needs to be better embedded along the whole policymaking cycle, and be integrated into companies' safety and sustainability management systems. This will help to systemically improve regulatory risk management practices.

SIGNIFICANCE

This paper constitutes an important step towards the implementation of the EU Green Deal and its underlying policy strategies, such as the Chemicals Strategy for Sustainability.

Towards a more comprehensive life cycle assessment framework for assessing toxicity-related impacts for livestock products: The case of Danish pork

In life cycle assessments of livestock systems, toxicity-related impacts are not commonly considered or only specific aspects (such as pesticides, manufacturing of inputs) are assessed. In this context, the aim of this study was to define a framework for assessing toxicity-related impacts and to characterize human toxicity and freshwater ecotoxicity for a livestock product based on applying the state-of-the-art models PestLCI Consensus and USEtox. Furthermore, methodological gaps were discussed and ways forward were suggested. The case study focused on Danish pork production and the toxicity results were reported per kg 'meat' (the parts of pig used for human consumption) leaving the slaughterhouse. The assessment framework included the use of pesticides and heavy metals in feed production, the use of veterinary pharmaceuticals in pig production, and the manufacturing of inputs. The use of cleaning agents could not be assessed with the currently available methods. New characterization factors were calculated for 35 chemicals not available in USEtox. For Danish pork production, feed production was the main contributor to the analyzed toxicity impacts. The use of pesticides was the main driver for organic substances while heavy metal emissions related to the application of pig manure to fields were the hotspot for metal-based substances. The use of veterinary pharmaceuticals contributed only to freshwater ecotoxicity by 3%. PestLCI Consensus estimates were compared with different approaches. The impact of metabolites of pesticides and veterinary pharmaceuticals was assessed and discussed. Methodological gaps and research needs were identified regarding the assessment of pesticides, veterinary pharmaceuticals, metal-based substances, inorganic substances, and combined exposure to multiple chemicals. Better data related to the use and chemical properties of substances are needed to reduce uncertainty in toxicity modeling.

Machine Learning Models for Predicting Liver Toxicity

Liver toxicity is a major adverse drug reaction that accounts for drug failure in clinical trials and withdrawal from the market. Therefore, predicting potential liver toxicity at an early stage in drug discovery is crucial to reduce costs and the potential for drug failure. However, current in vivo animal toxicity testing is very expensive and time consuming. As an alternative approach, various machine learning models have been developed to predict potential liver toxicity in humans. This chapter reviews current advances in the development and application of machine learning models for prediction of potential liver toxicity in humans and discusses possible improvements to liver toxicity prediction.

A Life Cycle Assessment of an Energy-Biochar Chain Involving a Gasification Plant in Italy

Life cycle assessment (LCA) is a fundamental tool for evaluating the environmental and energy load of a production cycle. Its application to renewable energy production systems offers the possibility of identifying the environmental benefits of such processes—especially those related to the by-products of production processes (i.e., digestion or biochar). Biochar has received worldwide interest because of its potential uses in bioenergy production, due to its coproducts (bio-oil and syngas), as well as in global warming mitigation, sustainable agriculture, pollutant removal, and other uses. Biochar production and use of soil is a strategy for carbon sequestration that could contribute to the reduction of emissions, providing simultaneous benefits to soil and opportunities for bioenergy generation. However, to confirm all of biochar’s benefits, it is necessary to characterize the environmental and energy loads of the production cycle. In this work, soil carbon sequestration, nitrous oxide emissions, use of fertilizers, and use of water for irrigation have been considered in the biochar’s LCA, where the latter is used as a soil conditioner. Primary data taken from experiments and prior studies, as well as open-source available databases, were combined to evaluate the environmental impacts of energy production from biomass, as well as the biochar life cycle, including pre- and post-conversion processes. From the found results, it can be deduced that the use of gasification production of energy and biochar is an attractive strategy for mitigating the environmental impacts analyzed here—especially climate change, with a net decrease of about −8.3 × 103 kg CO2 eq. Finally, this study highlighted strategic research developments that combine the specific characteristics of biochar and soil that need to be amended.

Utilizing High-Throughput Screening Data, Integrative Toxicological Prioritization Index Score, and Exposure-Activity Ratios for Chemical Prioritization: A Case Study of Endocrine-Active Pesticides in Food Crops

Endocrine-active chemicals can directly act on nuclear receptors and trigger the disturbances of metabolism and a homeostatic system, which are important risk factors for complicating chronic diseases in humans. The endocrine-active potentials of pesticides acting on estrogen, androgen, and thyroid hormone receptors have been extensively evaluated for pesticides; however, the effects on other receptors are less understood. This study aims to comprehensively characterize and prioritize the endocrine-active pesticides using an exposure-activity ratio (EAR) method and toxicological prioritization index (ToxPi). The aggregate exposure assessment of pesticides was performed using a computational exposure model [stochastic human exposure and dose simulation high-throughput model (SHEDS-HT)]. Minimum in vitro point of departure values were converted to human oral equivalent doses via in vitro-to-in vivo extrapolation. The overall endocrine-disrupting potentials of pesticides were evaluated via 76 assays, representing 11 nuclear receptors. EARs and ToxPi scores were then derived to prioritize 79 pesticides in food. This case study demonstrates that EAR profiling can inform the regulatory agencies for a relevant chemical prioritization, which would direct in-depth health risk assessments in the future.