Associations between Exposure to Organochlorine Chemicals and Endometriosis: A Systematic Review of Experimental Studies and Integration of Epidemiological Evidence

Greenspace and human microbiota: A systematic review

BACKGROUND

Potential effect of greenspace exposure on human microbiota have been explored by a number of observational and interventional studies, but the results remained mixed. We comprehensively synthesized these studies by performing a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

METHODS

Comprehensive literature searches in three international databases (PubMed, Embase, and Web of Science) and three Chinese databases (China National Knowledge Infrastructure, Wanfang, and China Biology Medicine disc) were conducted from inception to November 1, 2023. Observational and interventional studies that evaluated associations between greenspace exposure and human microbiota at different anatomical sites were included. Studies were assessed using the National Toxicology Program's office of Health Assessment and Translation risk of bias tool and certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation framework. Two authors independently performed study selection, data extraction, and risk of bias assessment, and evidence grading. Study results were synthesized descriptively.

RESULTS

Twenty studies, including 11 observational studies and 9 interventional studies, were finally included into the systematic review. The microbiota of the included studies was from gut (n = 13), skin (n = 10), oral cavity (n = 5), nasal cavity (n = 5) and eyes (n = 1). The majority of studies reported the associations of greenspace exposure with increased diversity (e.g., richness and Shannon index) and/or altered overall composition of human gut (n = 12) and skin microbiota (n = 8), with increases in the relative abundance of probiotics (e.g., Ruminococcaceae) and decreases in the relative abundance of pathogens (e.g., Streptococcus and Escherichia/Shigella). Due to limited number of studies, evidence concerning greenspace and oral, nasal, and ocular microbiota were still inconclusive.

CONCLUSION

The current evidence suggests that greenspace exposure may diversify gut and skin microbiota and alter their composition to healthier profiles. These findings would be helpful in uncovering the potential mechanisms underlying greenspace and human health and in promoting a healthier profile of human microbiota.

A comprehensive multiplatform metabolomic analysis reveals alterations of 2-hydroxybutyric acid among women with deep endometriosis related to the pesticide trans-nonachlor

BACKGROUND

Exposure to persistent organic pollutants (POPs) has been related to the risk of endometriosis however the mechanisms remain unclear. The objective of the present study was to characterize the metabolic profiles underpinning the associations between POPs and endometriosis risk.

METHODOLOGY

A hospital-based case-control study was conducted in France to recruit women with and without surgically confirmed deep endometriosis. Women's serum was analyzed using gas and liquid chromatography coupled to high-resolution mass spectrometry (HRMS) to measure the levels of polychlorinated biphenyls (PCBs), organochlorinated pesticides (OCPs) and per-/polyfluoroalkyl substances (PFAS). A comprehensive metabolomic profiling was conducted using targeted HRMS and 1H nuclear magnetic resonance (1H NMR) to cover polar and non-polar fractions. A "meet-in-the-middle" statistical framework was applied to identify the metabolites related to endometriosis and POP levels, using multivariate linear and logistic regressions adjusting for confounding variables.

RESULTS

Fourteen PCBs, six OCPs and six PFAS were widely found in almost all serum samples. The pesticide trans-nonachlor was the POP most strongly and positively associated with deep endometriosis risk, with odds ratio (95 % confidence interval) of 2.42 (1.49; 4.12), followed by PCB180 and 167. Women with endometriosis exhibited a distinctive metabolic profile, with elevated serum levels of lactate, ketone bodies and multiple amino acids and lower levels of bile acids, phosphatidylcholines (PCs), cortisol and hippuric acid. The metabolite 2-hydroxybutyrate was simultaneously associated to endometriosis risk and exposure to trans-nonachlor.

CONCLUSIONS

To the best of our knowledge, this is the first comprehensive metabolome-wide association study of endometriosis, integrating ultra-trace profiling of POPs. The results confirmed a metabolic alteration among women with deep endometriosis that could be also associated to the exposure to POPs. Further observational and experimental studies will be required to delineate the causal ordering of those associations and gain insight on the underlying mechanisms.

Proposal for targeted, neo-evolutionary-oriented, secondary prevention of early-onset endometriosis and adenomyosis. Part I: pathogenic aspects

The potential for repeated ovulation and menstruation is thought to have provided a Darwinian advantage during the Palaeolithic. Reproductive conditions remained relatively stable until the pre-industrial era, characterized by late menarche, very young age at first birth, multiple pregnancies, and prolonged periods of lactational amenorrhoea. For hundreds of thousands of years, menstruators experienced few ovulatory cycles, even though they were genetically adapted to ovulate and menstruate every month. In the post-industrial era, the age at menarche gradually declined, the age at first birth progressively increased, and breastfeeding became optional and often of short duration. This created a mismatch between genetic adaptation and socio-environmental evolution, so that what was initially a probable reproductive advantage subsequently contributed to increased susceptibility to diseases associated with lifetime oestrogen exposure, such as ovarian, endometrial and breast cancer and, hypothetically, also those associated with the number of ovulatory menstruations, such as endometriosis and adenomyosis. The incidence of endometriosis shows a steep and progressive increase around the age of 25 years, but given the consistently reported delay in diagnosis, the actual incidence curve should be shifted to the left, supporting the possibility that the disease has its roots in adolescence. This raises the question of whether, from an evolutionary point of view, anovulation and amenorrhoea should not still be considered the physiological state, especially in the postmenarchal period. However, an increase in the frequency of endometriosis in recent decades has not been demonstrated, although this deserves further epidemiological investigation. In addition, as endometriosis occurs in a minority of individuals exposed to retrograde menstruation, other important pathogenic factors should be scrutinised. Research should be resumed to explore in more detail the transtubal reflux of not only blood, but also endometrial cells, and whether they are systematically present in the peritoneal fluid after menstruation. If repetitive ovulatory menstruation during the early reproductive years is shown to increase the risk of endometriosis and adenomyosis development and progression in susceptible individuals, hormonal interventions could be used as secondary prevention in symptomatic adolescents.

A review of statistical strategies to integrate biomarkers of chemical exposure with biomarkers of effect applied in omic-scale environmental epidemiology

Humans are exposed to a growing list of synthetic chemicals, some of them becoming a major public health concern due to their capacity to impact multiple biological endpoints and contribute to a range of chronic diseases. The integration of endogenous (omic) biomarkers of effect in environmental health studies has been growing during the last decade, aiming to gain insight on the potential mechanisms linking the exposures and the clinical conditions. The emergence of high-throughput omic platforms has raised a list of statistical challenges posed by the large dimension and complexity of data generated. Thus, the aim of the present study was to critically review the current state-of-the-science about statistical approaches used to integrate endogenous biomarkers in environmental-health studies linking chemical exposures with health outcomes. The present review specifically focused on internal exposure to environmental chemical pollutants, involving both persistent organic pollutants (POPs), non-persistent pollutants like phthalates or bisphenols, and metals. We identified 42 eligible articles published since 2016, reporting 48 different statistical workflows, mostly focused on POPs and using metabolomic profiling in the intermediate layer. The outcomes were mainly binary and focused on metabolic disorders. A large diversity of statistical strategies were reported to integrate chemical mixtures and endogenous biomarkers to characterize their associations with health conditions. Multivariate regression models were the most predominant statistical method reported in the published workflows, however some studies applied latent based methods or multipollutant models to overcome the specific constraints of omic or exposure of data. A minority of studies used formal mediation analysis to characterize the indirect effects mediated by the endogenous biomarkers. The principles of each specific statistical method and overall workflow set-up are summarized in the light of highlighting their applicability, strengths and weaknesses or interpretability to gain insight into the causal structures underlying the triad: exposure, effect-biomarker and outcome.

Application of AOPs to assist regulatory assessment of chemical risks - Case studies, needs and recommendations

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA.

Development, Validation, and Application of a Human Reproductive Toxicity Prediction Model Based on Adverse Outcome Pathway

A growing number of environmental contaminants have been proved to have reproductive toxicity to males and females. However, the unclear toxicological mechanism of reproductive toxicants limits the development of virtual screening methods. By consolidating androgen (AR)-/estrogen receptors (ERs)-mediated adverse outcome pathways (AOPs) with more than 8000 chemical substances, we uncovered relationships between chemical features, a series of pathway-related effects, and reproductive apical outcomes─changes in sex organ weights. An AOP-based computational model named RepTox was developed and evaluated to predict and characterize chemicals' reproductive toxicity for males and females. Results showed that RepTox has three outstanding advantages. (I) Compared with the traditional models (37 and 81% accuracy, respectively), AOP significantly improved the predictive robustness of RepTox (96.3% accuracy). (II) Compared with the application domain (AD) of models based on small in vivo datasets, AOP expanded the ADs of RepTox by 1.65-fold for male and 3.77-fold for female, respectively. (III) RepTox implied that hydrophobicity, cyclopentanol substructure, and several topological indices (e.g., hydrogen-bond acceptors) were important, unbiased features associated with reproductive toxicants. Finally, RepTox was applied to the inventory of existing chemical substances of China and identified 2100 and 7281 potential toxicants to the male and female reproductive systems, respectively.

Increasing incidence and spatial hotspots of hospitalized endometriosis in France from 2011 to 2017

Endometriosis is a female hormone-dependent disease, possibly related to endocrine disruptor exposure. We aimed to monitor this disease nationwide in France and analyze spatial trends at a fine scale to explore possible environmental contributing risk factors. We conducted a retrospective national descriptive study from 2011 to 2017 in females aged 10 years old and over, using comprehensive hospital discharge data. Cases were identified using ICD-10 N80 codes and were localized at their municipality of residence. We defined incident cases as the first hospital stay of patients, without a stay in at least the previous 5 years. We performed statistical analyses according to age and type of endometriosis, and we modeled the temporal, spatial and spatiotemporal trends. We identified 207,462 incident cases of all-type hospitalized endometriosis (83,112 for non-adenomyosis cases). The crude incidence rate for the study period was 9.85/10,000 person-years (3.95/10,000 for non-adenomyosis cases). From 2011 to 2017, the risk of all-type endometriosis increased by 8.5% (95% CI: 3.9; 13.4) (by 3.6% (95% CI: 0.6; 6.8) for non-adenomyosis cases). The risk was geographically heterogeneous, with 20 high-risk hotspots, showing similar results for non-adenomyosis cases. Shifting practice patterns, improved awareness and healthcare disparities interlinked with environmental risk factors could explain these trends.

Associations between persistent organic pollutants and endometriosis: A multiblock approach integrating metabolic and cytokine profiling

Humans are exposed daily to complex mixtures of chemical pollutants through their environment and diet, some of which have the potential to disrupt the bodies' natural endocrine functions and contribute to reproductive diseases like endometriosis. Increasing epidemiological and experimental evidence supports the association between endometriosis and certain persistent organic pollutants (POPs) like dioxins; however, little is known about the underlying linking mechanisms. The main objective of this study is to proof the methodological applicability and discovery potential of integrating ultra-trace mass spectrometry (MS) profiling of POP biomarkers and endogenous biomarker profiling (MS metabolomics and cytokines) in a case-control study for the etiological research of endometriosis. The approach is applied in a pilot clinical-based study conducted in France where women with and without surgically confirmed endometriosis were recruited. Serum samples were analysed with high-resolution MS for about 30 polychlorinated biphenyls (PCBs), organochlorinated pesticides and perfluoroalkyl substances (PFAS). About 600 serum metabolites and lipids were identified with targeted metabolomics using tandem MS with the Biocrates MxP® Quant 500 Kit. A panel of 4 pro-inflammatory cytokines were analysed using ELISA-based 4-PLEX analyser. Statistical analysis included a battery of variable selection approaches, multivariate logistic regression for single-chemical associations, Bayesian kernel machine regressions (BKMR) to identify mixture effects of POPs and a multiblock approach to identify shared biomarker signatures among high risk clusters. The results showed the positive associations between some POPs and endometriosis risk, including the pesticide trans-nonachlor Odds Ratio (95% Confidence Interval) 3.38 (2.06-5.98), p < 0.0001 and PCB 114 OR (95% CI) 1.83 (1.17-2.93), p = 0.009. The BKMR approach showed a tendency of a positive cumulative effect of the mixture, however trans-nonachlor exhibited significant associations within the mixture and interacted with other PCBs, strengthening the effects at highest concentrations. Finally, the multiblock analysis, relating the various blocks of data, revealed a latent cluster of women with higher risk of endometrioma presenting higher concentrations of trans-nonachlor, PCB 114 and dioxin-like toxic equivalents from PCBs, together with an increased inflammatory profile (i.e. elevated interleukin-8 and monocyte chemoattractant protein-1). It was also highlighted a specific metabolic pattern characterized by dysregulation of bile acid homeostasis and lipase activity. Further research will be required with larger sample size to confirm these findings and gain insight on the underlying mechanisms between POPs and endometriosis.