Environmental Health Perspectives最新文献

Background: Exposure to persistent organic pollutants (POPs) and disruptions in the gastrointestinal microbiota have been positively correlated with a predisposition to factors such as obesity, metabolic syndrome, and type 2 diabetes; however, it is unclear how the microbiome contributes to this relationship.

Objective: This study aimed to explore the association between early life exposure to a potent aryl hydrocarbon receptor (AHR) agonist and persistent disruptions in the microbiota, leading to impaired metabolic homeostasis later in life.

Methods: This study used metagenomics, nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics, and biochemical assays to analyze the gut microbiome composition and function, as well as the physiological and metabolic effects of early life exposure to 2,3,7,8-tetrachlorodibenzofuran (TCDF) in conventional, germ-free (GF), and Ahr-null mice. The impact of TCDF on Akkermansia muciniphila (A. muciniphila) in vitro was assessed using optical density (OD 600), flow cytometry, transcriptomics, and MS-based metabolomics.

Results: TCDF-exposed mice exhibited lower abundances of A. muciniphila, lower levels of cecal short-chain fatty acids (SCFAs) and indole-3-lactic acid (ILA), as well as lower levels of the gut hormones glucagon-like peptide 1 (GLP-1) and peptide YY (PYY), findings suggestive of disruption in the gut microbiome community structure and function. Importantly, microbial and metabolic phenotypes associated with early life POP exposure were transferable to GF recipients in the absence of POP carry-over. In addition, AHR-independent interactions between POPs and the microbiota were observed, and they were significantly associated with growth, physiology, gene expression, and metabolic activity outcomes of A. muciniphila, supporting suppressed activity along the ILA pathway.

Conclusions: These data obtained in a mouse model point to the complex effects of POPs on the host and microbiota, providing strong evidence that early life, short-term, and self-limiting POP exposure can adversely impact the microbiome, with effects persisting into later life with associated health implications. https://doi.org/10.1289/EHP13356.

Background: The field of toxicology has witnessed substantial advancements in recent years, particularly with the adoption of new approach methodologies (NAMs) to understand and predict chemical toxicity. Class-based methods such as clustering and classification are key to NAMs development and application, aiding the understanding of hazard and risk concerns associated with groups of chemicals without additional laboratory work. Advances in computational chemistry, data generation and availability, and machine learning algorithms represent important opportunities for continued improvement of these techniques to optimize their utility for specific regulatory and research purposes. However, due to their intricacy, deep understanding and careful selection are imperative to align the adequate methods with their intended applications.

Objectives: This commentary aims to deepen the understanding of class-based approaches by elucidating the pivotal role of chemical similarity (structural and biological) in clustering and classification approaches (CCAs). It addresses the dichotomy between general end point-agnostic similarity, often entailing unsupervised analysis, and end point-specific similarity necessitating supervised learning. The goal is to highlight the nuances of these approaches, their applications, and common misuses.

Discussion: Understanding similarity is pivotal in toxicological research involving CCAs. The effectiveness of these approaches depends on the right definition and measure of similarity, which varies based on context and objectives of the study. This choice is influenced by how chemical structures are represented and the respective labels indicating biological activity, if applicable. The distinction between unsupervised clustering and supervised classification methods is vital, requiring the use of end point-agnostic vs. end point-specific similarity definition. Separate use or combination of these methods requires careful consideration to prevent bias and ensure relevance for the goal of the study. Unsupervised methods use end point-agnostic similarity measures to uncover general structural patterns and relationships, aiding hypothesis generation and facilitating exploration of datasets without the need for predefined labels or explicit guidance. Conversely, supervised techniques demand end point-specific similarity to group chemicals into predefined classes or to train classification models, allowing accurate predictions for new chemicals. Misuse can arise when unsupervised methods are applied to end point-specific contexts, like analog selection in read-across, leading to erroneous conclusions. This commentary provides insights into the significance of similarity and its role in supervised classification and unsupervised clustering approaches. https://doi.org/10.1289/EHP14001.

Background: Dioxin-like chemicals are a group of ubiquitous environmental toxicants that received intense attention in the last two decades of the 20th century. Through extensive mechanistic research and validation, the global community has agreed upon a regulatory strategy for these chemicals that centers on their common additive activation of a single receptor. Applying these regulations has led to decreased exposure in most populations studied. As dioxin-like chemicals moved out of the limelight, research and media attention has turned to other concerning contaminants, including per- and polyfluoroalkyl substances (PFAS). During the 20th century, PFAS were also being quietly emitted into the environment, but only in the last 20 years have we realized the serious threat they pose to health. There is active debate about how to appropriately classify and regulate the thousands of known PFAS and finding a solution for these "forever chemicals" is of the utmost urgency.

Objectives: Here, we compare important features of dioxin-like chemicals and PFAS, including the history, mechanism of action, and effective upstream regulatory strategies, with the objective of gleaning insight from the past to improve strategies for addressing PFAS.

Discussion: The differences between these two chemical classes means that regulatory strategies for dioxin-like chemicals will not be appropriate for PFAS. PFAS exert toxicity by both receptor-based and nonreceptor-based mechanisms, which complicates mixtures evaluation and stymies efforts to develop inexpensive assays that accurately capture toxicity. Furthermore, dioxin-like chemicals were unwanted byproducts, but PFAS are useful and valuable, which has led to intense resistance against efforts to restrict their production. Nonetheless, useful lessons can be drawn from dioxin-like chemicals and applied to PFAS, including eliminating nonessential production of new PFAS and proactive investment in environmental remediation to address their extraordinarily long environmental persistence. https://doi.org/10.1289/EHP14449.

Background: Phenols and parabens are two classes of high production volume chemicals that are used widely in consumer and personal care products and have been associated with reproductive harm and pregnancy complications, such as preeclampsia and gestational diabetes. However, studies examining their influence on maternal blood pressure and gestational hypertension are limited.

Objectives: We investigated associations between individual phenols, parabens, and their mixture on maternal blood pressure measurements, including systolic and diastolic blood pressure (SBP and DBP) and hypertension during pregnancy (defined as stage 1 or 2 hypertension), among $N=\mathrm{1,433}$ Puerto Rico PROTECT study participants.

Methods: We examined these relationships cross-sectionally at two time points during pregnancy (16-20 and 24-28 wks gestation) and longitudinally using linear mixed models (LMMs). Finally, we used quantile g-computation to examine the mixture effect on continuous (SBP, DBP) and binary (hypertension during pregnancy) blood pressure outcomes.

Results: We observed a trend of higher odds of hypertension during pregnancy with exposure to multiple analytes and the overall mixture [including bisphenol A (BPA), bisphenol S (BPS), triclocarbon (TCC), triclosan (TCS), benzophenone-3 (BP-3), 2,4-dichlorophenol (2,4-DCP), 2,5-dichlorophenol (2,5-DCP), methyl paraben (M-PB), propyl paraben (P-PB), butyl paraben (B-PB), and ethyl paraben (E-PB)], especially at 24-28 wk gestation, with an adjusted mixture $\text{odds\hspace{0.17em}ratio}\left(\text{OR}\right)=1.57$ (95% CI: 1.03, 2.38). Lower SBP and higher DBP were also associated with individual analytes, with results from LMMs most consistent for methyl paraben (M-PB) or propyl paraben (P-PB) and increased DBP across pregnancy [adjusted M-PB $\beta =0.78$ (95% CI: 0.17, 1.38) and adjusted P-PB $\beta =0.85$ (95% CI: 0.19, 1.51)] and for BPA, which was associated with decreased SBP (adjusted $\beta =-0.57$; 95% CI: $-1.09$, $-0.05$). Consistent with other literature, we also found evidence of effect modification by fetal sex, with a strong inverse association observed between the overall exposure mixture and SBP at visit 1 among participants carrying female fetuses only.

Conclusions: Our findings indicate that phenol and paraben exposure may collectively increase the risk of stage 1 or 2 hypertension during pregnancy, which has important implications for fetal and maternal health. https://doi.org/10.1289/EHP14008.