2-Mercaptobenzothiazole in urine of children and adolescents in Germany – Human biomonitoring results of the German Environmental Survey 2014–2017 (GerES V)

Exploring the Occurrence of Organic Contaminants in Human Semen through an Innovative LC-HRMS-Based Methodology Suitable for Target and Nontarget Analysis

Understanding the potential impact of organic contaminants on male fertility is crucial, yet limited studies have examined these chemicals in semen, with most focusing on urine and blood. To address this gap, we developed and validated a robust LC-HRMS methodology for semen analysis, with a focus on polar and semipolar chemicals. Our methodology enables the quantitative (or semiquantitative) analysis of >2000 chemicals being compatible with suspect and nontarget strategies and providing unprecedented insights into the occurrence and potential bioaccumulation of diverse contaminants in this matrix. We comprehensively analyzed exogenous organic chemicals and associated metabolites in ten semen samples from Spanish participants collected in an area with a large presence of the chemical industry included in the LED-FERTYL Spanish study cohort. This investigation revealed the presence of various contaminants in semen, including plastic additives, PFAS, flame retardants, surfactants, and insecticides. Notably, prevalent plastic additives such as phthalic acid esters and bisphenols were identified, indicating potential health risks. Additionally, we uncovered previously understudied chemicals like the tire additive 2-mercaptobenzothiazole and specific organophosphate flame retardants. This study showcases the potential of our methodology as a valuable tool for large-scale cohort studies, providing insights into the association between contaminant exposure and the risk of male fertility impairments.

A revised concept for deriving reference values for internal exposures to chemical substances and its application to population-representative biomonitoring data in German children and adolescents 2014-2017 (GerES V)

HBM reference values, in contrast to toxicologically derived values, are statistically derived values that provide information on the exposure of the population. The exceedance frequency (if applicable for individual population groups) is often a first assessment standard for the local exposure situation for municipalities. More than 25 years have passed since the German Human Biomonitoring Commission (HBMC) formulated the first recommendations for the derivation of population-based reference values (HBM reference values, RV95) for substance concentrations based on HBM studies. A fundamental revision is timely, for several reasons. There have been considerable advances in relevant statistical methods, which meant that previously time-consuming and inaccessible procedures and calculations are now widely available. Furthermore, not all steps for the derivation of HBM reference values were clearly elaborated in the first recommendations. With this revision we intended to achieve a rigorous standardization of the entire process of deriving HBM reference values, also to realise a higher degree of transparency. In accordance with established international practice, it is recommended to use the 95th percentile of the reference distribution as the HBM reference value. To this end, the empirical 95th percentile of a suitable sample should be rounded, ensuring that the rounded value is within the two-sided 95% confidence interval of the percentile. All estimates should be based on distribution-free methods, and the confidence interval should be estimated using a bootstrap approach, if possible, according to the BCa ("bias-corrected and accelerated bootstrap"). A minimum sample size of 80 observations is considered necessary. The entire procedure ensures that the derived HBM reference value is robust against at least two extreme values and can also be used for underlying mixed distributions. If it is known in advance that certain subgroups (different age groups, smokers, etc.) show differing internal exposures, it is recommended that group-specific HBM reference values should be derived. Especially when the sample sizes for individual subgroups are too small, individual datasets with potential outliers can be excluded in advance to homogenize the reference value population. In the second part, new HBM reference values based on data of the German Environmental Survey for Children and Adolescents (GerES V, 2014-2017) were derived in accordance with the revised recommendations. The GerES V is the most recent population-representative monitoring of human exposure to pollutants in Germany on children and adolescents aged 3-17 years (N = 2294). RV95 for GerES V are reported for four subgroups (males/females and 3-11/12-17 years) for 108 different substances including phthalates and alternative plasticisers, metals, organochlorine pesticides, polychlorinated biphenyls (PCB), per- and polyfluoroalkyl substances (PFAS), parabens, aprotic solvents, chlorophenols, polycyclic aromatic hydrocarbons (PAH) and UV filter, in total 135 biomarkers. Algorithms implemented in R were used for the statistics and the determination of the HBM reference values. To facilitate a quality control of the study data, the corresponding R source code is given, together with graphical representations of results. The HBM reference values listed in this article replace earlier RV95 values derived by the HBMC for children and adolescents from data of precedent GerES studies (e.g. published in Apel et al., 2017).

Monitoring the exposure to ethoxyquin between 2000 and 2021 in urine samples from the German Environmental Specimen Bank

Human Biomonitoring (HBM) of emerging chemicals gained increasing attention within the EU in recent years. After evaluating the metabolism, we established a new HBM method for ethoxyquin (EQ), a feed additive, which was banned in 2017 due to concerns regarding the possible exposure of the general population to it and its highly toxic precursor p-phenetidine. The method was applied to 250 urine samples from the Environmental Specimen Bank collected between 2000 and 2021. The major metabolite EQI was quantified in the majority of the study samples illustrating the ubiquitous exposure of the non-occupationally exposed population. A rather constant exposure was observed until 2016 with a significant decline from 2016 to 2021. This drop falls within the EU wide ban of the chemical as a feed additive from June 2017 which led to a gradual removal until its complete suspension in June 2020. The daily intake (DI) was evaluated with respect to the reported derived no-effect level (DNEL) to estimate the potential health risks from EQ exposure. The median DI of 0.0181 µg/kg bw/d corresponds to only 0.01 % of the DNEL. Even the observed maxima up to 13.1 µg/kg bw/d only accounted for 10 % of the DNEL. Nevertheless, the values suggest a general exposure with the risk of higher burden in a low fraction of the population. In regard to the EQ associated intake of the carcinogen and suspected mutagen p-phenetidine, this level of exposure cannot be evaluated as safe. The recent decrease and the broad exposure substantiate the need for future HBM campaigns in population representative studies to further investigate the observed reductions, potentially find highly exposed subgroups and clarify the impact of the ban as feed additive on EQ exposure.

Promotion of Bladder Cancer Cell Metastasis by 2-Mercaptobenzothiazole via Its Activation of Aryl Hydrocarbon Receptor Transcription: Molecular Dynamics Simulations, Cell-Based Assays, and Machine Learning-Driven Prediction

2-Mercaptobenzothiazole (MBT) is an industrial chemical widely used for rubber products, corrosion inhibitors, and polymer materials with multiple environmental and exposure pathways. A growing body of evidence suggests its potential bladder cancer (BC) risk as a public health concern; however, the molecular mechanism remains poorly understood. Herein, we demonstrate the activation of the aryl hydrocarbon receptor (AhR) by MBT and reveal key events in carcinogenesis associated with BC. MBT alters conformational changes of AhR ligand binding domain (LBD) as revealed by 500 ns molecular dynamics simulations and activates AhR transcription with upregulation of AhR-target genes CYP1A1 and CYP1B1 to approximately 1.5-fold. MBT upregulates the expression of MMP1, the cancer cell metastasis biomarker, to 3.2-fold and promotes BC cell invasion through an AhR-mediated manner. MBT is further revealed to induce differentially expressed genes (DEGs) most enriched in cancer pathways by transcriptome profiling. The exposure of MBT at environmentally relevant concentrations induces BC risk via AhR signaling disruption, transcriptome aberration, and malignant cell metastasis. A machine learning-based model with an AUC value of 0.881 is constructed to successfully predict 31 MBT analogues. Overall, we provide molecular insight into the BC risk of MBT and develop an effective tool for rapid screening of AhR agonists.

The German Environmental Survey for Children and Adolescents 2014-2017 (GerES V) - Study population, response rates and representativeness

The German Environmental Survey (GerES) is a population-representative, cross-sectional study on environmental exposures of the general population of Germany. GerES has repeatedly been conducted since 1985 by the German Environment Agency (UBA) in close collaboration with the Health Interview and Examination Surveys of the Robert Koch Institute (RKI). In the German Environmental Survey for Children and adolescents 2014-2017 (GerES V) pollutants and other environmental stressors were measured in human samples as well as in the homes of 3- to 17-year-old children and adolescents. Interviews were conducted about health-related behaviors and living conditions. The GerES V basic program encompassed examinations of whole blood, blood plasma, morning urine and drinking water samples, measurements of ultrafine particles and noise levels, comprehensive standardized interviews, and self-administrated questionnaires. Additional modules on volatile organic compounds and aldehydes, particulate matter (PM_2.5) in indoor air, organic compounds in drinking water and pollutants in house dust were conducted in subsamples. Potential GerES V participants were identified and attained by the RKI from those participants who were examined and interviewed for the cross-sectional component of the second follow-up to the German Health Interview and Examination Survey for Children and Adolescents (KiGGS Wave 2). The gross sample of GerES V comprised 3031 children and adolescents of which 2294 finally took part in the survey. This equals a total response rate of 75.7 %. Response rates varied, depending on region, type of municipality, age and sex, from 66.0 % to 78.3 %. By calculating individual case weights, discrepancies due to sample design and non-response between the GerES V sample and the whole population could be considered in statistical analysis. Therefore, the representativeness of the GerES V results with regard to age, sex, community size and region was assured.

Machine Learning-Enabled Renal Cell Carcinoma Status Prediction Using Multiplatform Urine-Based Metabolomics

Renal cell carcinoma (RCC) is diagnosed through expensive cross-sectional imaging, frequently followed by renal mass biopsy, which is not only invasive but also prone to sampling errors. Hence, there is a critical need for a noninvasive diagnostic assay. RCC exhibits altered cellular metabolism combined with the close proximity of the tumor(s) to the urine in the kidney, suggesting that urine metabolomic profiling is an excellent choice for assay development. Here, we acquired liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) data followed by the use of machine learning (ML) to discover candidate metabolomic panels for RCC. The study cohort consisted of 105 RCC patients and 179 controls separated into two subcohorts: the model cohort and the test cohort. Univariate, wrapper, and embedded methods were used to select discriminatory features using the model cohort. Three ML techniques, each with different induction biases, were used for training and hyperparameter tuning. Assessment of RCC status prediction was evaluated using the test cohort with the selected biomarkers and the optimally tuned ML algorithms. A seven-metabolite panel predicted RCC in the test cohort with 88% accuracy, 94% sensitivity, 85% specificity, and 0.98 AUC. Metabolomics Workbench Study IDs are ST001705 and ST001706.

Cohort profile: China National Human Biomonitoring (CNHBM)-A nationally representative, prospective cohort in Chinese population

OBJECTIVE

Globally, developed countries such as the United States, Canada, Germany, Korea, have carried out long-term and systematic biomonitoring programs for environmental chemicals in their populations. The China National Human Biomonitoring (CNHBM) was to document the extent of human exposure to a wide array of environmental chemicals, to understand exposure profiles, magnitude and ongoing trends in exposure in the general Chinese population, and to establish a national biorepository.

METHODS

CNHBM adopted three-stage sampling method to obtain a nationally representative sample of the population. A total of 21,888 participants who were permanent residents in 31 provinces were designed to interviewed in this national biomonitoring (152 monitoring sites × 3 survey units × 2 sexes × 6 age groups × 4 persons = 21,888 persons) in 2017-2018. Unlike the US National Health and Nutrition Examination Survey, the CNHBM will follow the same participants in subsequent cycles allowing for dynamic, longitudinal data sets for epidemiologic follow-up. Each survey cycle of CNHBM will last 2 years and each subsequent cycle will occur 3 years after the prior cycle's completion.

RESULTS

In 2017-2018, the CNHBM created a large cohort of Chinese citizens that included districts/counties questionnaire, community questionnaire collecting information on villages/communities, individual questionnaire, household questionnaire, comprehensive medical examination, and collection of blood and urine samples for measurement of clinical and exposure biomarkers. A total of 21,746 participants were finally included in CNHBM, accounting for 99.4% of the designed sample size; and 152 PSUs questionnaires, 454 community questionnaires, 21,619 family questionnaires, 21,712 cases of medical examinations, 21,700 individual questionnaires, 21,701 blood samples and 21,704 urine samples were collected, respectively. Planned analyses of blood and urine samples were to measure both inorganic and organic chemicals, including 13 heavy metals and metalloids, 18 poly- and per-fluorinated alkyl substances, 12 phthalate metabolites, 9 polycyclic aromatic hydrocarbons metabolites, 4 environmental alkylated phenols, and 2 benzene metabolites.

CONCLUSIONS

CNHBM established the first nationally representative, prospective cohort in the Chinese population to understand the baseline and trend of internal exposure of environmental chemicals in general population, and to understand environmental toxicity.