Interindividual Variation in Source-Specific Doses is a Determinant of Health Impacts of Combined Chemical Exposures

Multi-source exposure and health risks of phthalates among university students in Northeastern China

The endocrine disruptor phthalates (PAEs) are widely used as important chemical additives in a variety of areas around the globe. PAEs are toxic to reproduction and development and may adversely affect the health of adolescents. Risk assessments of exposure to PAEs from different sources are more reflective of actual exposure than single-source assessments. We used personal exposure parameters to estimate the dose of PAEs to 107 university students from six media (including dormitory dust, dormitory air, clothing, food, disposable food containers, and personal care products (PCPs)) and three exposure routes (including ingestion, inhalation, and dermal absorption). Individual factors and lifestyles may affect PAE exposure to varying degrees. Based on a positive matrix factorization (PMF) model, the results indicated that the main sources of PAEs in dust were indoor building materials and plastics, while PCPs and adhesives were the major sources of airborne PAEs. The relative contribution of each source to PAE exposure showed that food and air were the primary sources of dimethyl phthalate (DMP) and dibutyl phthalate (DBP). Air source contributed the most to diethyl phthalate (DEP) exposure, followed by PCPs. Food was the most significant source of diisobutyl phthalate (DiBP), benzyl butyl phthalate (BBP), and bis(2-ethylhexyl) phthalate (DEHP) exposure. Additionally, the exposure of DEHP to dust was not negligible. The ingestion pathway was the most dominant among the three exposure pathways, followed by dermal absorption. The non-carcinogenic risk of PAEs from the six sources was within acceptable limits. DEHP exhibits a low carcinogenic risk. We suggest university students maintain good hygienic and living habits to minimize exposure to PAEs.

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

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

Opportunities and challenges related to saturation of toxicokinetic processes: Implications for risk assessment

Top dose selection for repeated dose animal studies has generally focused on identification of apical endpoints, use of the limit dose, or determination of a maximum tolerated dose (MTD). The intent is to optimize the ability of toxicity tests performed in a small number of animals to detect effects for hazard identification. An alternative approach, the kinetically derived maximum dose (KMD), has been proposed as a mechanism to integrate toxicokinetic (TK) data into the dose selection process. The approach refers to the dose above which the systemic exposures depart from being proportional to external doses. This non-linear external-internal dose relationship arises from saturation or limitation of TK process(es), such as absorption or metabolism. The importance of TK information is widely acknowledged when assessing human health risks arising from exposures to environmental chemicals, as TK determines the amount of chemical at potential sites of toxicological responses. However, there have been differing opinions and interpretations within the scientific and regulatory communities related to the validity and application of the KMD concept. A multi-stakeholder working group, led by the Health and Environmental Sciences Institute (HESI), was formed to provide an opportunity for impacted stakeholders to address commonly raised scientific and technical issues related to this topic and, more specifically, a weight of evidence approach is recommended to inform design and dose selection for repeated dose animal studies. Commonly raised challenges related to the use of TK data for dose selection are discussed, recommendations are provided, and illustrative case examples are provided to address these challenges or refute misconceptions.