Rats exposed to Alternaria toxins in vivo exhibit altered liver activity highlighted by disruptions in riboflavin and acylcarnitine metabolism.

Natural toxins produced by Alternaria fungi include the mycotoxins alternariol, tenuazonic acid and altertoxins I and II. Several of these toxins have shown high toxicity even at low levels including genotoxic, mutagenic, and estrogenic effects. However, the metabolic effects of toxin exposure from Alternaria are understudied, especially in the liver as a key target. To gain insight into the impact of Alternaria toxin exposure on the liver metabolome, rats (n = 21) were exposed to either (1) a complex culture extract with defined toxin profiles from Alternaria alternata (50 mg/kg body weight), (2) the isolated, highly genotoxic altertoxin-II (ATX-II) (0.7 mg/kg of body weight) or (3) a solvent control. The complex mixture contained a spectrum of Alternaria toxins including a controlled dose of ATX-II, matching the concentration of the isolated ATX-II. Liver samples were collected after 24 h and analyzed via liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Authentic reference standards (> 100) were used to identify endogenous metabolites and exogenous compounds from the administered exposures in tandem with SWATH-acquired MS/MS data which was used for non-targeted analysis/screening. Screening for metabolites produced by Alternaria revealed several compounds solely isolated in the liver of rats exposed to the complex culture, confirming results from a previously performed targeted biomonitoring study. This included the altersetin and altercrasin A that were tentatively identified. An untargeted metabolomics analysis found upregulation of acylcarnitines in rats receiving the complex Alternaria extract as well as downregulation of riboflavin in rats exposed to both ATX-II and the complex mixture. Taken together, this work provides a mechanistic view of Alternari toxin exposure and new suspect screening insights into hardly characterized Alternaria toxins.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage.

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Bridging Targeted (Zeno MRM-HR) and Untargeted (SWATH) LC-HRMS in a Single Run for Sensitive Exposomics.

Traditionally, chemical exposure has been assessed by low-resolution mass spectrometry via targeted approaches due to the typically extremely low concentration of such compounds in biological samples. Nevertheless, untargeted approaches are now becoming a promising tool for a broader investigation of the exposome, covering additional compounds, their biotransformation products, and possible metabolic alterations (metabolomics). However, despite broad compound coverage, untargeted metabolomics still underperforms in ultratrace biomonitoring analysis. To overcome these analytical limitations, we present the development of the first combined targeted/untargeted LC-MS method, merging MRM-HR and SWATH experiments in one analytical run, making use of Zeno technology for improved sensitivity. Multiple reaction monitoring transitions were optimized for 135 highly diverse toxicants including mycotoxins, plasticizers, PFAS, personal care products ingredients, and industrial side products as well as potentially beneficial xenobiotics such as phytohormones. As a proof of concept, standard reference materials of human plasma (SRM 1950) and serum (SRM 1958) were analyzed with both Zeno MRM-HR + SWATH and SWATH-only methodologies. Results demonstrated a significant increase in sensitivity represented by the detection of lower concentration levels in spiked SRM materials (mean value: 2.2 and 3 times lower concentrations for SRMs 1950 and 1958, respectively). Overall, the detection frequency was increased by 68% (19 to 32 positive detections) in the MRM-HR + SWATH mode compared to the SWATH-only. This work presents a promising avenue for addressing the outstanding key challenge in the small-molecule omics field: finding a balance between high sensitivity and broad chemical coverage. It was demonstrated for exposomic applications but might be transferred to lipidomics and metabolomics workflows.

Network analysis reveals age- and virus-specific circuits in nasal epithelial cells of extremely premature infants.

BACKGROUND AND OBJECTIVES: Viral respiratory infections significantly affect young children, particularly extremely premature infants, resulting in high hospitalization rates and increased health-care burdens. Nasal epithelial cells, the primary defense against respiratory infections, are vital for understanding nasal immune responses and serve as a promising target for uncovering underlying molecular and cellular mechanisms. METHODS: Using a trans-well pseudostratified nasal epithelial cell system, we examined age-dependent developmental differences and antiviral responses to influenza A and respiratory syncytial virus through systems biology approaches. RESULTS: Our studies revealed differences in innate-receptor repertoires, distinct developmental pathways, and differentially connected antiviral network circuits between neonatal and adult nasal epithelial cells. Consensus network analysis identified unique and shared cellular-viral networks, emphasizing highly relevant virus-specific pathways, independent of viral replication kinetics. CONCLUSION: This research highlights the importance of nasal epithelial cells in innate antiviral immune responses and offers crucial insights that allow for a deeper understanding of age-related differences in nasal epithelial cell immunity following respiratory virus infections.

Scaling up a targeted exposome LC-MS/MS biomonitoring method by incorporating veterinary drugs and pesticides.

Humans are exposed to a cocktail of food-related and environmental contaminants, potentially contributing to the etiology of chronic diseases. Better characterizing the "exposome" is a challenging task and requires broad human biomonitoring (HBM). Veterinary drugs (VDs)/antibiotics, widely used and regulated in food and animal production, however, are typically not yet included in exposomics workflows. Therefore, in this work, a previously established multianalyte liquid chromatography-tandem mass spectrometry (LC-MS/MS) method covering >80 diverse xenobiotics was expanded by >40 VDs/antibiotics and pesticides. It was investigated if the generic workflow allowed for the successful integration of a high number of new analytes in a proof-of-principle study. The expanded method was successfully in-house validated and specificity, matrix effects, linearity, intra- and inter-day precision, accuracy, limits of quantification, and detection were evaluated. The optimized method demonstrated satisfactory recovery (81-120%) for most of the added analytes with acceptable RSDs (<20%) at three spiking levels. The majority of VDs/antibiotics and pesticides (69%) showed matrix effects within a range of 50-140%. Moreover, sensitivity was excellent with median LODs and LOQs of 0.10 ng/mL and 0.31 ng/mL, respectively. In total, the expanded method can be used to detect and quantify more than 120 highly diverse analytes in a single analytical run. To the best of the authors' knowledge, this work represents the first targeted biomonitoring method integrating VDs with various other classes of pollutants including plasticizers, PFAS, bisphenols, mycotoxins, and personal care products. It demonstrates the potential to expand targeted multianalyte methods towards additional groups of potentially toxic chemicals.

Insights into the early-life chemical exposome of Nigerian infants and potential correlations with the developing gut microbiome.

Early-life exposure to natural and synthetic chemicals can impact acute and chronic health conditions. Here, a suspect screening workflow anchored on high-resolution mass spectrometry was applied to elucidate xenobiotics in breast milk and matching stool samples collected from Nigerian mother-infant pairs (n = 11) at three time points. Potential correlations between xenobiotic exposure and the developing gut microbiome, as determined by 16S rRNA gene amplicon sequencing, were subsequently explored. Overall, 12,192 and 16,461 features were acquired in the breast milk and stool samples, respectively. Following quality control and suspect screening, 562 and 864 features remained, respectively, with 149 of these features present in both matrices. Taking advantage of 242 authentic reference standards measured for confirmatory purposes of food bio-actives and toxicants, 34 features in breast milk and 68 features in stool were identified and semi-quantified. Moreover, 51 and 78 features were annotated with spectral library matching, as well as 416 and 652 by in silico fragmentation tools in breast milk and stool, respectively. The analytical workflow proved its versatility to simultaneously determine a diverse panel of chemical classes including mycotoxins, endocrine-disrupting chemicals (EDCs), antibiotics, plasticizers, perfluorinated alkylated substances (PFAS), and pesticides, although it was originally optimized for polyphenols. Spearman rank correlation of the identified features revealed significant correlations between chemicals of the same classification such as polyphenols. One-way ANOVA and differential abundance analysis of the data obtained from stool samples revealed that molecules of plant-based origin elevated as complementary foods were introduced to the infants' diets. Annotated compounds in the stool, such as tricetin, positively correlated with the genus Blautia. Moreover, vulgaxanthin negatively correlated with Escherichia-Shigella. Despite the limited sample size, this exploratory study provides high-quality exposure data of matched biospecimens obtained from mother-infant pairs in sub-Saharan Africa and shows potential correlations between the chemical exposome and the gut microbiome.

Tailored Mass Spectral Data Exploration Using the SpecXplore Interactive Dashboard.

Untargeted metabolomics promises comprehensive characterization of small molecules in biological samples. However, the field is hampered by low annotation rates and abstract spectral data. Despite recent advances in computational metabolomics, manual annotations and manual confirmation of in-silico annotations remain important in the field. Here, exploratory data analysis methods for mass spectral data provide overviews, prioritization, and structural hypothesis starting points to researchers facing large quantities of spectral data. In this research, we propose a fluid means of dealing with mass spectral data using specXplore, an interactive Python dashboard providing interactive and complementary visualizations facilitating mass spectral similarity matrix exploration. Specifically, specXplore provides a two-dimensional t-distributed stochastic neighbor embedding embedding as a jumping board for local connectivity exploration using complementary interactive visualizations in the form of partial network drawings, similarity heatmaps, and fragmentation overview maps. SpecXplore makes use of state-of-the-art ms2deepscore pairwise spectral similarities as a quantitative backbone while allowing fast changes of threshold and connectivity limitation settings, providing flexibility in adjusting settings to suit the localized node environment being explored. We believe that specXplore can become an integral part of mass spectral data exploration efforts and assist users in the generation of structural hypotheses for compounds of interest.

Adopting Mechanistic Molecular Biology Approaches in Exposome Research for Causal Understanding.

Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.

Neuroactive metabolites and bile acids are altered in extremely premature infants with brain injury.

The gut microbiome is associated with pathological neurophysiological evolvement in extremely premature infants suffering from brain injury. The exact underlying mechanism and its associated metabolic signatures in infants are not fully understood. To decipher metabolite profiles linked to neonatal brain injury, we investigate the fecal and plasma metabolome of samples obtained from a cohort of 51 extremely premature infants at several time points, using liquid chromatography (LC)-high-resolution mass spectrometry (MS)-based untargeted metabolomics and LC-MS/MS-based targeted analysis for investigating bile acids and amidated bile acid conjugates. The data are integrated with 16S rRNA gene amplicon gut microbiome profiles as well as patient cytokine, growth factor, and T cell profiles. We find an early onset of differentiation in neuroactive metabolites between infants with and without brain injury. We detect several bacterially derived bile acid amino acid conjugates in plasma and feces. These results provide insights into the early-life metabolome of extremely premature infants.

Polyphenol exposure of mothers and infants assessed by LC-MS/MS based biomonitoring in breast milk.

Exposure to polyphenols is relevant throughout critical windows of infant development, including the breastfeeding phase. However, the quantitative assessment of polyphenols in human breast milk has received limited attention so far, though polyphenols may positively influence infant health. Therefore, a targeted LC-MS/MS assay was developed to investigate 86 analytes representing different polyphenol classes in human breast milk. The sample preparation consisted of liquid extraction, salting out, freeze-out, and a dilution step. Overall, nearly 70% of the chemically diverse polyphenols fulfilled all strict validation criteria for full quantitative assessment. The remaining analytes did not fulfill all criteria at every concentration level, but can still provide useful semi-quantitative insights into nutritional and biomedical research questions. The limits of detection for all analyzed polyphenols were in the range of 0.0041-87 ng*mL-1, with a median of 0.17 ng*mL-1. Moreover, the mean recovery was determined to be 82% and the mean signal suppression and enhancement effect was 117%. The developed assay was applied in a proof-of-principle study to investigate polyphenols in breast milk samples provided by twelve Nigerian mothers at three distinct time points post-delivery. In total, 50 polyphenol analytes were detected with almost half being phenolic acids. Phase II metabolites, including genistein-7-ß-D-glucuronide, genistein-7-sulfate, and daidzein-7-ß-D-glucuronide, were also detected in several samples. In conclusion, the developed method was demonstrated to be fit-for-purpose to simultaneously (semi-) quantify a wide variety of polyphenols in breast milk. It also demonstrated that various polyphenols including their biotransformation products were present in breast milk and therefore likely transferred to infants where they might impact microbiome development and infant health.

Enhancing microbiome research in sub-Saharan Africa.

While there are lighthouse examples of microbiome research in sub-Saharan Africa (SSA), a significant proportion of local researchers face several challenges. Here, we highlight prevailing issues limiting microbiome research in SSA and suggest potential technological, societal, and research-based solutions. We emphasize the need for considerable investment in infrastructures, training, and appropriate funding to democratize modern technologies with a view to providing useful data to improve human health.

Biomonitoring of Dietary Mycotoxin Exposure and Associated Impact on the Gut Microbiome in Nigerian Infants.

Mycotoxins are toxic chemicals that adversely affect human health. Here, we assessed the influence of mycotoxin exposure on the longitudinal development of early life intestinal microbiota of Nigerian neonates and infants (NIs). Human biomonitoring assays based on liquid chromatography tandem mass spectrometry were applied to quantify mycotoxins in breast milk (n = 68) consumed by the NIs, their stool (n = 82), and urine samples (n = 15), which were collected longitudinally from month 1-18 postdelivery. Microbial community composition was characterized by 16S rRNA gene amplicon sequencing of stool samples and was correlated to mycotoxin exposure patterns. Fumonisin B1 (FB1), FB2, and alternariol monomethyl ether (AME) were frequently quantified in stool samples between months 6 and 18. Aflatoxin M1 (AFM1), AME, and citrinin were quantified in breast milk samples at low concentrations. AFM1, FB1, and ochratoxin A were quantified in urine samples at relatively high concentrations. Klebsiella and Escherichia/Shigella were dominant in very early life stool samples (month 1), whereas Bifidobacterium was dominant between months 3 and 6. The total mycotoxin levels in stool were significantly associated with NIs' gut microbiome composition (PERMANOVA, p < 0.05). However, no significant correlation was observed between specific microbiota and the detection of certain mycotoxins. Albeit a small cohort, this study demonstrates that mycotoxins may influence early life gut microbiome composition.

The Austrian children's biomonitoring survey 2020 Part B: Mycotoxins, phytotoxins, phytoestrogens and food processing contaminants.

This study assessed the levels of environment and food-related exposures in urine of Austrian school children aged six to ten (n = 85) focusing on mycotoxins, phytoestrogens, and food processing by-products using two multi-analyte LC-MS/MS methods. Out of the 55 biomarkers of exposure reported in this study, 22 were quantified in the first void urine samples. Mycotoxins frequently quantified included zearalenone (detection rate 100%; median 0.11 ng/mL), deoxynivalenol (99%; 15 ng/mL), alternariol monomethyl ether (75%; 0.04 ng/mL), and ochratoxin A (19%; 0.03 ng/mL). Several phytoestrogens, including genistein, daidzein, and its metabolite equol, were detected in all samples at median concentrations of 22 ng/mL, 43 ng/mL, and 14 ng/mL, respectively. The food processing by-product 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), was detected in 4% of the samples (median 0.016 ng/mL). None of the investigated samples contained the tested phytotoxins that were rarely considered for human biomonitoring previously (pyrrolizidine alkaloids, tropane alkaloids, aristolochic acids). When relating estimated exposure to current health-based guidance values, 22% of the children exceeded the tolerable daily intake for deoxynivalenol, and the estimated MOE for OTA indicates possible health risks for some children. The results clearly demonstrate frequent low-level (co-)exposure and warrant further exposome-scale exposure assessments, especially in susceptible sub-populations and longitudinal settings.

Comparing the sensitivity of a low- and a high-resolution mass spectrometry approach for xenobiotic trace analysis: An exposome-type case study.

The chemical exposome consists of environmental exposures experienced throughout a lifetime but to date analytical approaches to investigate the plethora of low-abundance chemicals remain very limited. Liquid chromatography high-resolution mass spectrometry (HRMS) is commonly applied in untargeted exposome-wide analyses of xenobiotics in biological samples; however, human biomonitoring approaches usually utilize targeted low-resolution triple quadrupole (QQQ) mass spectrometry tailored to a small number of chemicals. HRMS can cover a broader chemical space but the detection of molecules from low-level exposure amidst a background of highly-abundant endogenous molecules has proven to be difficult. In this study, a triple quadrupole (QQQ) and a high-resolution mass spectrometer (HRMS) with identical chromatography were utilized to determine the limits of quantitation (LOQ) of >100 xenobiotics and estrogenic hormones in pure solvent and human urine. Both instrumental platforms are currently applied in exposure assessment studies and were operated in their most frequently used acquisition mode (full scan for HRMS and multiple reaction monitoring for QQQ) to mimic typical applications. For HRMS analyses, the median LOQ was 0.9 and 1.2 ng/mL in solvent and urine, respectively, while for low-resolution QQQ measurements, the median LOQ was 0.1 and 0.2 ng/mL in solvent and urine, respectively. To evaluate the calculated LOQs in complex biological samples, spot urine samples from 24 Nigerian female volunteers were investigated. The higher LOQ values for HRMS resulted in less quantified low-abundance analytes and decreased the number of compounds detected below the LOQ. Even at chronic low-dose exposure, such compounds might be relevant for human health because of high individual toxicity or potential mixture effects. Nevertheless, HRMS enabled the additional screening for exposure to unexpected/unknown analytes, including emerging compounds and biotransformation products. Therefore, a synergy between high- and low-resolution mass spectrometry may currently be the best option to elucidate and quantify xenobiotics in comprehensive exposome-wide association studies (ExWAS).

Ecophysiology and interactions of a taurine-respiring bacterium in the mouse gut.

Taurine-respiring gut bacteria produce H2S with ambivalent impact on host health. We report the isolation and ecophysiological characterization of a taurine-respiring mouse gut bacterium. Taurinivorans muris strain LT0009 represents a new widespread species that differs from the human gut sulfidogen Bilophila wadsworthia in its sulfur metabolism pathways and host distribution. T. muris specializes in taurine respiration in vivo, seemingly unaffected by mouse diet and genotype, but is dependent on other bacteria for release of taurine from bile acids. Colonization of T. muris in gnotobiotic mice increased deconjugation of taurine-conjugated bile acids and transcriptional activity of a sulfur metabolism gene-encoding prophage in other commensals, and slightly decreased the abundance of Salmonella enterica, which showed reduced expression of galactonate catabolism genes. Re-analysis of metagenome data from a previous study further suggested that T. muris can contribute to protection against pathogens by the commensal mouse gut microbiota. Together, we show the realized physiological niche of a key murine gut sulfidogen and its interactions with selected gut microbiota members.

Exposomic Biomonitoring of Polyphenols by Non-Targeted Analysis and Suspect Screening.

Polyphenols, prevalent in plants and fungi, are investigated intensively in nutritional and clinical settings because of their beneficial bioactive properties. Due to their complexity, analysis with untargeted approaches is favorable, which typically use high-resolution mass spectrometry (HRMS) rather than low-resolution mass spectrometry (LRMS). Here, the advantages of HRMS were evaluated by thoroughly testing untargeted techniques and available online resources. By applying data-dependent acquisition on real-life urine samples, 27 features were annotated with spectral libraries, 88 with in silico fragmentation, and 113 by MS1 matching with PhytoHub, an online database containing >2000 polyphenols. Moreover, other exogenous and endogenous molecules were screened to measure chemical exposure and potential metabolic effects using the Exposome-Explorer database, further annotating 144 features. Additional polyphenol-related features were explored using various non-targeted analysis techniques including MassQL for glucuronide and sulfate neutral losses, and MetaboAnalyst for statistical analysis. As HRMS typically suffers a sensitivity loss compared to state-of-the-art LRMS used in targeted workflows, the gap between the two instrumental approaches was quantified in three spiked human matrices (urine, serum, plasma) as well as real-life urine samples. Both instruments showed feasible sensitivity, with median limits of detection in the spiked samples being 10-18 ng/mL for HRMS and 4.8-5.8 ng/mL for LRMS. The results demonstrate that, despite its intrinsic limitations, HRMS can readily be used for comprehensively investigating human polyphenol exposure. In the future, this work is expected to allow for linking human health effects with exposure patterns and toxicological mixture effects with other xenobiotics.

Metabolomics as an emerging approach for deciphering the biological impact and toxicity of food contaminants: the case of mycotoxins.

Exposure to mycotoxins through the dietary route occurs on a daily basis while their deleterious effects are exhibited in the form of ailments, such as inflammation, cancer, and hormonal imbalance. The negative impact of mycotoxins can be attributed to their interaction with various biomolecules and their interference in metabolic pathways. The activity of biomolecules, such as enzymes/receptors, which engage the intricate mechanism of endogenous metabolism, is more susceptible to disruption by metabolites of high toxicity, which gives rise to adverse health effects. Metabolomics is a useful analytical approach that can assist in unraveling such information. It can simultaneously and comprehensively analyze a large number of endogenous and exogenous molecules present in biofluids and can, thus, reveal biologically relevant perturbations following mycotoxin exposure. Information provided by genome, transcriptome and proteome analyses, which have been utilized for the elucidation of biological mechanisms so far, are further complemented by the addition of metabolomics in the available bioanalytics toolbox. Metabolomics can offer insight into complex biological processes and their respective response to several (co-)exposures. This review focuses on the most extensively studied mycotoxins reported in literature and their respective impact on the metabolome upon exposure.

Results of the Austrian Children's Biomonitoring Survey 2020 part A: Per- and polyfluorinated alkylated substances, bisphenols, parabens and other xenobiotics.

In 85 Austrian school children aged 6-10 years, two multi-analyte LC-MS/MS methods were used to study the concentrations of 33 chemical substances in urine, including per- and polyfluorinated alkylated substances (PFAS), bisphenols, parabens, benzophenones, triclosan, polycyclic aromatic hydrocarbon metabolites, and cotinine. Each of the children was exposed to 14-21 substances simultaneously. Correlations were found between compounds of the same and of divergent substance groups supporting the strong need to consider multiple exposures and mixture effects. Eight compounds, including perfluorohexanoic acid (PFHxA), perfluorononanoic acid (PFOA), methyl paraben (n-MeP), ethyl paraben (n-EtP), propyl paraben (n-PrP), benzophenone-1 (BP-1), 2-naphthol, and 3-hydroxyphenanthrene were detected in all urine samples. In the PFAS group the medians of detectable substances ranged between <0.0005 µg/l for perfluorononanoic acid (PFNA) and 0.004 µg/l for PFHxA. For other environmental contaminants investigated, a maximum urinary level of 893 µg/l was identified for n-MeP. The highest median value was 2.5 µg/l for 2-naphthol. Daily intakes were calculated for bisphenol A (BPA), triclosan (TCS), and four parabens. These values did not exceed the tolerable or acceptable daily intakes currently in force. Based on a recently proposed TDI for BPA, daily intakes of all children exceeded this value. A cumulative risk assessment was conducted for four parabens not showing exceedances of acceptable exposures. The results demonstrate simultaneous exposure to several different chemicals, with the majority showing impact on the endocrine system being of particular concern with respect to mixture effects. Further assessments with a stronger focus on mixtures are warranted. The results also highlight the need of policy actions as foreseen in the EU Chemicals Strategy for Sustainability.

Understanding the Chemical Exposome During Fetal Development and Early Childhood: A Review.

Early human life is considered a critical window of susceptibility to external exposures. Infants are exposed to a multitude of environmental factors, collectively referred to as the exposome. The chemical exposome can be summarized as the sum of all xenobiotics that humans are exposed to throughout a lifetime. We review different exposure classes and routes that impact fetal and infant metabolism and the potential toxicological role of mixture effects. We also discuss the progress in human biomonitoring and present possiblemodels for studying maternal-fetal transfer. Data gaps on prenatal and infant exposure to xenobiotic mixtures are identified and include natural biotoxins, in addition to commonly reported synthetic toxicants, to obtain a more holistic assessment of the chemical exposome. We highlight the lack of large-scale studies covering a broad range of xenobiotics. Several recommendations to advance our understanding of the early-life chemical exposome and the subsequent impact on health outcomes are proposed.