Search

BACKGROUND: Understanding the mechanistic basis of air pollution toxicity is dependent on accurately characterizing both exposure and biological responses. Untargeted metabolomics, an analysis of small-molecule metabolic phenotypes, may offer improved estimation of exposures and corresponding health responses to complex environmental mixtures such as air pollution. The field remains nascent, however, with questions concerning the coherence and generalizability of findings across studies, study designs and analytical platforms. OBJECTIVES: We aimed to review the state of air pollution research from studies using untargeted high-resolution metabolomics (HRM), highlight the areas of concordance and dissimilarity in methodological approaches and reported findings, and discuss a path forward for future use of this analytical platform in air pollution research. METHODS: We conducted a state-of-the-science review to a) summarize recent research of air pollution studies using untargeted metabolomics and b) identify gaps in the peer-reviewed literature and opportunities for addressing these gaps in future designs. We screened articles published within Pubmed and Web of Science between 1 January 2005 and 31 March 2022. Two reviewers independently screened 2,065 abstracts, with discrepancies resolved by a third reviewer. RESULTS: We identified 47 articles that applied untargeted metabolomics on serum, plasma, whole blood, urine, saliva, or other biospecimens to investigate the impact of air pollution exposures on the human metabolome. Eight hundred sixteen unique features confirmed with level-1 or-2 evidence were reported to be associated with at least one or more air pollutants. Hypoxanthine, histidine, serine, aspartate, and glutamate were among the 35 metabolites consistently exhibiting associations with multiple air pollutants in at least 5 independent studies. Oxidative stress and inflammation-related pathways—including glycerophospholipid metabolism, pyrimidine metabolism, methionine and cysteine metabolism, tyrosine metabolism, and tryptophan metabolism—were the most commonly perturbed pathways reported in >70% of studies. More than 80% of the reported features were not chemically annotated, limiting the interpretability and generalizability of the findings. CONCLUSIONS: Numerous investigations have demonstrated the feasibility of using untargeted metabolomics as a platform linking exposure to internal dose and biological response. Our review of the 47 existing untargeted HRM–air pollution studies points to an underlying coherence and consistency across a range of sample analytical quantitation methods, extraction algorithms, and statistical modeling approaches. Future directions should focus on validation of these findings via hypothesis-driven protocols and technical advances in metabolic annotation and quantification. https://doi.org/10.1289/EHP11851.

Current-use pesticide (CUP) exposure occurs mainly through diet and environmental application in both agricultural and urban settings. While pesticide exposure has been associated with many adverse health outcomes, the intermediary molecular mechanisms are still not completely elucidated. Among others, their roles in epigenetics (DNA methylation) and DNA damage due to oxidative stress are presumed. Scientific evidence on urinary biomarkers of such body response in general population is limited, especially in children. A total of 440 urine samples (n = 110 parent-child pairs) were collected during the winter and summer seasons in order to describe levels of overall DNA methylation (5-mC, 5-mdC, 5-hmdC, 7-mG, 3-mA) and oxidative stress (8-OHdG) biomarkers and investigate their possible associations with metabolites of pyrethroids (3-PBA, t/c-DCCA), chlorpyrifos (TCPY), and tebuconazole (TEB-OH). Linear mixed-effects models accounting for intraindividual and intrahousehold correlations were utilized. We applied false discovery rate procedure to account for multiplicity and adjusted for potential confounding variables. Higher urinary levels of most biological response biomarkers were measured in winter samples. In adjusted repeated measures models, interquartile range (IQR) increases in pyrethroid metabolites were associated with higher oxidative stress. t/c-DCCA and TCPY were associated with higher urinary levels of cytosine methylation biomarkers (5-mC and/or 5-mdC). The most robust association was observed for tebuconazole metabolite with 3-mA (-15.1% change per IQR increase, 95% CI = -23.6, -5.69) suggesting a role of this pesticide in reduced demethylation processes through possible DNA glycosylase inhibition. Our results indicate an urgent need to extend the range of analyzed environmental chemicals such as azole pesticides (e.g. prothioconazole) in human biomonitoring studies. This is the first study to report urinary DNA methylation biomarkers in children and associations between CUP metabolites and a comprehensive set of biomarkers including methylated and oxidized DNA alterations. Observed associations warrant further large-scale research of these biomarkers and environmental pollutants including CUPs.

Background: Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure–response curve (ERC) modeling when data across the exposure range are sparse. Methods: We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and nonhuman studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, 10 human biomarker studies, and four experimental animal studies. Results: A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range [ Conclusions: Integrating the available epidemiologic, biomarker, and animal data resulted in more precise risk estimates for benzene exposure and AML, although the large between-study heterogeneity hampers interpretation of these results. The harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation. Impact: By describing a framework for data integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach. See related commentary by Keil, p. 695

BACKGROUND: Per- and polyfluoroalkyl substances (PFASs) are emerging environmental contaminants with multiple hazardous properties including immunomodulation potency. Human exposure to PFASs has been associated with various immune-mediated diseases and outcomes. This study aimed to investigate the association between PFAS exposure and immune-mediated diseases such as allergies, eczemas, and autoimmune diseases in a population of adults in the Czech Republic. METHODS: This study included 309 adults from the Central European Longitudinal Study of Parents and Children: Young Adults (CELSPAC: YA). 12 PFASs were measured in participants' serum by HPLC-MS/MS, 3 PFASs were removed from the subsequent analyses due to low detection frequency. The associations of 9 PFASs with 9 immune-mediated diseases were assessed by logistic regression. Furthermore, Bayesian kernel machine regression (BKMR) was used to estimate the effect of the PFAS mixture on immune-mediated diseases. All analyses were adjusted for sex, age, BMI, smoking, education, and family history of immune-mediated diseases. In cases of a statistically significant interaction of PFASs and sex, stratified analyses were performed for men and women. RESULTS: Perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) were negatively associated with both atopic eczema (OR per IQR increase 0.58 (95% CI 0.37-0.90) for PFOA and 0.56 (0.32-0.95) for PFOS) and contact dermatitis (0.37 (0.16-0.85) for PFOA and 0.33 (0.11-0.94) for PFOS). Perfluoroundecanoate (PFUnDA) was negatively associated with pollen, dust, and mite allergy (0.62 (0.43-0.89)). BKMR modelling showed a negative tendency in the overall effect of PFAS mixture on immune-health outcomes. Based on the stratified analysis, sex was suggested to be an effect modifier in the association of PFOS and atopic eczema. CONCLUSION: Our results contribute to the body of literature that observes the immunosuppressive effect of PFAS exposure during eczemas and allergies, both for PFASs individually and as a mixture.

Human biomonitoring has become a pivotal tool for supporting chemicals’ policies. It provides information on real-life human exposures and is increasingly used to prioritize chemicals of health concern and to evaluate the success of chemical policies. Europe has launched the ambitious REACH program in 2007 to improve the protection of human health and the environment. In October 2020 the EU commission published its new chemicals strategy for sustainability towards a toxic-free environment. The European Parliament called upon the commission to collect human biomonitoring data to support chemical’s risk assessment and risk management. This manuscript describes the organization of the first HBM4EU-aligned studies that obtain comparable human biomonitoring (HBM) data of European citizens to monitor their internal exposure to environmental chemicals. The HBM4EU-aligned studies build on existing HBM capacity in Europe by aligning national or regional HBM studies. The HBM4EU-aligned studies focus on three age groups: children, teenagers, and adults. The participants are recruited between 2014 and 2021 in 11 to 12 primary sampling units that are geographically distributed across Europe. Urine samples are collected in all age groups, and blood samples are collected in children and teenagers. Auxiliary information on sociodemographics, lifestyle, health status, environment, and diet is collected using questionnaires. In total, biological samples from 3137 children aged 6–12 years are collected for the analysis of biomarkers for phthalates, HEXAMOLL® DINCH, and flame retardants. Samples from 2950 teenagers aged 12–18 years are collected for the analysis of biomarkers for phthalates, Hexamoll® DINCH, and per and polyfluoroalkyl substances (PFASs), and samples from 3522 adults aged 20–39 years are collected for the analysis of cadmium, bisphenols, and metabolites of polyaromatic hydrocarbons (PAHs). The children’s group consists of 50.4% boys and 49.5% girls, of which 44.1% live in cities, 29.0% live in towns/suburbs, and 26.8% live in rural areas. The teenagers’ group includes 50.6% girls and 49.4% boys, with 37.7% of residents in cities, 31.2% in towns/suburbs, and 30.2% in rural areas. The adult group consists of 52.6% women and 47.4% men, 71.9% live in cities, 14.2% in towns/suburbs, and only 13.4% live in rural areas. The study population approaches the characteristics of the general European population based on age-matched EUROSTAT EU-28, 2017 data; however, individuals who obtained no to lower educational level (ISCED 0–2) are under represented. The data on internal human exposure to priority chemicals from this unique cohort will provide a baseline for Europe’s strategy towards a non-toxic environment and challenges and recommendations to improve the sampling frame for future EU-wide HBM surveys are discussed. The HBM4EU initiative is co-financed under Horizon 2020 (grant agreement No 733032). Additional financial support for the conduct of the studies is provided by each participating country. More information on co-funding of the individual studies is provided in Supplementary Materials, Table S14. info:eu-repo/semantics/publishedVersion

Background: Few studies have modeled smoking histories by combining smoking intensity and duration to show what profile of smoking behavior is associated with highest risk of bladder cancer. This study aims to provide insight into the association between smoking exposure history and bladder cancer risk by modeling both smoking intensity and duration in a pooled analysis.Methods: We used data from 15 case-control studies included in the bladder cancer epidemiology and nutritional determinants study, including a total of 6,874 cases and 17,727 controls. To jointly interpret the effects of intensity and duration of smoking, we modeled excess odds ratios per pack-year by intensity continuously to estimate the risk difference between smokers with long duration/low intensity and short duration/high intensity.Results: The pattern observed from the pooled excess odds ratios model indicated that for a fixed number of pack-years, smoking for a longer duration at lower intensity was more deleterious for bladder cancer risk than smoking more cigarettes/day for a shorter duration. We observed similar patterns within individual study samples.Conclusions: This pooled analysis shows that long duration/low intensity smoking is associated with a greater increase in bladder cancer risk than short duration/high intensity smoking within equal pack-year categories, thus confirming studies in other smoking-related cancers and demonstrating that reducing exposure history to a single metric such as pack-years was too restrictive.

Type 2 diabetes is one of the major chronic diseases accounting for a substantial proportion of disease burden in Western countries. The majority of the burden of type 2 diabetes is attributed to environmental risks and modifiable risk factors such as lifestyle. The environment we live in, and changes to it, can thus contribute substantially to the prevention of type 2 diabetes at a population level. The 'exposome' represents the (measurable) totality of environmental, i.e. nongenetic, drivers of health and disease. The external exposome comprises aspects of the built environment, the social environment, the physico-chemical environment and the lifestyle/food environment. The internal exposome comprises measurements at the epigenetic, transcript, proteome, microbiome or metabolome level to study either the exposures directly, the imprints these exposures leave in the biological system, the potential of the body to combat environmental insults and/or the biology itself. In this review, we describe the evidence for environmental risk factors of type 2 diabetes, focusing on both the general external exposome and imprints of this on the internal exposome. Studies provided established associations of air pollution, residential noise and area-level socioeconomic deprivation with an increased risk of type 2 diabetes, while neighbourhood walkability and green space are consistently associated with a reduced risk of type 2 diabetes. There is little or inconsistent evidence on the contribution of the food environment, other aspects of the social environment and outdoor temperature. These environmental factors are thought to affect type 2 diabetes risk mainly through mechanisms incorporating lifestyle factors such as physical activity or diet, the microbiome, inflammation or chronic stress. To further assess causality of these associations, future studies should focus on investigating the longitudinal effects of our environment (and changes to it) in relation to type 2 diabetes risk and whether these associations are explained by these proposed mechanisms.

International audience; Suspect and non-targeted screening approaches are a matter of increasing interest notably with regard to the Exposome contextual framework, but their application to human samples still remains limited at this date. The aim of the present study was to develop a non-targeted workflow from sample preparation to data processing and method assessment to characterise the human internal chemical exposure at early life stage. The method was focused on human milk to investigate mother and newborn exposure to known organic contaminants and to extend the characterisation to unknown compounds. We specifically focused on halogenated biomarkers of exposure due to persistence and potential toxicological impact reasons. The newly developed approach was based on a simple and fast sample preparation followed by a comprehensive analysis by both liquid and gas phase chromatography coupled to high resolution mass spectrometry. Critical steps of the non-targeted workflow as the method assessment have been addressed with a reference mix of 30 chlorinated and brominated contaminants encompassing various substances groups and a statistical approach. Data processing until the identification of biomarkers of exposure was possible with homemade bioinformatics tools. On the other hand, the method was validated by the identification of historical chemicals as hexachlorobenzene and p,p’-DDE and emerging chemical as 4-hydroxychlorothalonil. This approach opens the door to further extensions and consolidations to offer new capabilities for exposomics and environmental health research.

Supplemental Digital Content is available in the text., By 2030, more than 80% of Europe’s population will live in an urban environment. The urban exposome, consisting of factors such as where we live and work, where and what we eat, our social network, and what chemical and physical hazards we are exposed to, provides important targets to improve population health. The EXPANSE (EXposome Powered tools for healthy living in urbAN SEttings) project will study the impact of the urban exposome on the major contributors to Europe’s burden of disease: Cardio-Metabolic and Pulmonary Disease. EXPANSE will address one of the most pertinent questions for urban planners, policy makers, and European citizens: “How to maximize one’s health in a modern urban environment?” EXPANSE will take the next step in exposome research by (1) bringing together exposome and health data of more than 55 million adult Europeans and OMICS information for more than 2 million Europeans; (2) perform personalized exposome assessment for 5,000 individuals in five urban regions; (3) applying ultra-high-resolution mass-spectrometry to screen for chemicals in 10,000 blood samples; (4) evaluating the evolution of the exposome and health through the life course; and (5) evaluating the impact of changes in the urban exposome on the burden of cardiometabolic and pulmonary disease. EXPANSE will translate its insights and innovations into research and dissemination tools that will be openly accessible via the EXPANSE toolbox. By applying innovative ethics-by-design throughout the project, the social and ethical acceptability of these tools will be safeguarded. EXPANSE is part of the European Human Exposome Network.

Large-scale suspect and non-targeted screening approaches based on high-resolution mass spectrometry (HRMS) are today available for chemical profiling and holistic characterisation of biological samples. These advanced techniques allow the simultaneous detection of a large number of chemical features, including markers of human chemical exposure. Such markers are of interest for biomonitoring, environmental health studies and support to risk assessment. Furthermore, these screening approaches have the promising capability to detect chemicals of emerging concern (CECs), document the extent of human chemical exposure, generate new research hypotheses and provide early warning support to policy. Whilst of growing importance in the environment and food safety areas, respectively, CECs remain poorly addressed in the field of human biomonitoring. This shortfall is due to several scientific and methodological reasons, including a global lack of harmonisation. In this context, the main aim of this paper is to present an overview of the basic principles, promises and challenges of suspect and non-targeted screening approaches applied to human samples as this specific field introduce major specificities compared to other fields. Focused on liquid chromatography coupled to HRMS-based data acquisition methods, this overview addresses all steps of these new analytical workflows. Beyond this general picture, the main activities carried out on this topic within the particular framework of the European Human Biomonitoring initiative (project HBM4EU, 2017-2021) are described, with an emphasis on harmonisation measures.

ObjectivesAccumulated evidence implies that night shift work may trigger liver dysfunction. Non-alcoholic fatty liver (NAFL) is suggested to be a necessary mediator in this process. This study aimed to examine the relationship between night shift work and elevated level of alanine transaminase (e-ALT) of workers and investigate the potential mediation effect of NAFL.MethodsThis study included all male workers from the baseline survey of a cohort of night shift workers. Information on demographics, lifestyle and lifetime working schedule was collected by face-to-face interview. Liver sonography was used to identify NAFL cases. Serum ALT level was detected by an automatic biochemical analyser. e-ALT was defined as ALT >40 U/L. Logistic regression models were used to evaluate ORs, and mediation analysis was employed to examine the mediation effect.ResultsAmong 4740 male workers, 39.5% were night shift workers. Night shift workers had an increased risk of e-ALT (OR, 1.19, 95% CI 1.00 to 1.42). With the increase in night shift years, the OR of e-ALT increased from 1.03 (95% CI 0.77 to 1.36) to 1.60 (95% CI 1.08 to 2.39) among workers without NAFL. A similar trend was not found among workers with NAFL. In addition, no significant mediation effect of NAFL in the association between night shift work and e-ALT was found.ConclusionsNight shift work is positively associated with abnormal liver function, in particular among workers without NAFL. Shift work involving circadian disruption is likely to exert a direct effect on liver dysfunction rather than rely on the mediation effect of NAFL.

Background: One of the potential mechanisms linking air pollution to health effects is through changes in DNA-methylation, which so far has mainly been analyzed globally or at candidate sites. Objective: We investigated the association of personal and ambient air pollution exposure measures with genome-wide DNA-methylation changes. Methods: We collected repeated 24-hour personal and ambient exposure measurements of particulate matter (PM2.5), PM2.5 absorbance, and ultrafine particles (UFP) and peripheral blood samples from a panel of 157 healthy non-smoking adults living in four European countries. We applied univariate mixed-effects models to investigate the association between air pollution and genome-wide DNA-methylation perturbations at single CpG (cytosine-guanine dinucleotide) sites and in Differentially Methylated Regions (DMRs). Subsequently, we explored the association of air pollution-induced methylation alterations with gene expression and serum immune marker levels measured in the same subjects. Results: Personal exposure to PM2.5 was associated with methylation changes at 13 CpG sites and 69 DMRs. Two of the 13 identified CpG sites (mapped to genes KNDC1 and FAM50B) were located within these DMRs. In addition, 42 DMRs were associated with personal PM2.5 absorbance exposure, 16 DMRs with personal exposure to UFP, 4 DMRs with ambient exposure to PM2.5, 16 DMRs with ambient PM2.5 absorbance exposure, and 15 DMRs with ambient UFP exposure. Correlation between methylation levels at identified CpG sites and gene expression and immune markers was generally moderate. Conclusion: This study provides evidence for an association between 24-hour exposure to air pollution and DNA-methylation at single sites and regional clusters of CpGs. Analysis of differentially methylated regions provides a promising avenue to further explore the subtle impact of environmental exposures on DNA-methylation. Keywords: DNA-methylation, Air pollution, Fine particles, Ultrafine particles, Immune markers

Air pollution is associated with a broad range of adverse health effects, including mortality and morbidity due to cardio- and cerebrovascular diseases (CCVD), but the molecular mechanisms involved are not entirely understood. This study aims to investigate the involvement of oxidative stress and inflammation in the causal chain, and to identify intermediate biomarkers that are associated retrospectively with the exposure and prospectively with the disease. We designed a case-control study on CCVD nested in a cohort of 18,982 individuals from the EPIC-Italy study. We measured air pollution, inflammatory biomarkers, and whole-genome DNA methylation in blood collected up to 17 years before the diagnosis. The study sample includes all the incident CCVD cases among former- and never-smokers, with available stored blood sample, that arose in the cohort during the follow-up. We identified enrichment of altered DNA methylation in "ROS/Glutathione/Cytotoxic granules" and "Cytokine signaling" pathways related genes, associated with both air pollution (multiple comparisons adjusted p for enrichment ranging from 0.01 to 0.03 depending on pollutant) and with CCVD risk (P = 0.04 and P = 0.03, respectively). Also, Interleukin-17 was associated with higher exposure to NO; 2; (P = 0.0004), NO; x; (P = 0.0005), and CCVD risk (OR = 1.79; CI 1.04-3.11; P = 0.04 comparing extreme tertiles). Our findings indicate that chronic exposure to air pollution can lead to oxidative stress, which in turn activates a cascade of inflammatory responses mainly involving the "Cytokine signaling" pathway, leading to increased risk of CCVD. Inflammatory proteins and DNA methylation alterations can be detected several years before CCVD diagnosis in blood samples, being promising preclinical biomarkers. Environ. Mol. Mutagen. 59:234-246, 2018. © 2017 Wiley Periodicals, Inc.

SummaryAims This systematic review and meta-analysis evaluated the associations between shift work patterns and risks of specific types of obesity. Methods PubMed was searched until March 2017 for observational studies that examined the relationships between shift work patterns and obesity. Odds ratio for obesity was extracted using a fixed-effects or random-effects model. Subgroup meta-analyses were carried out for study design, specific obesity types and characteristics of shift work pattern. Results A total of 28 studies were included in this meta-analysis. The overall odds ratio of night shift work was 1.23 (95% confidence interval = 1.17–1.29) for risk of obesity/overweight. Cross-sectional studies showed a higher risk of 1.26 than those with the cohort design (risk ratio = 1.10). Shift workers had a higher frequency of developing abdominal obesity (odds ratio = 1.35) than other obesity types. Permanent night workers demonstrated a 29% higher risk than rotating shift workers (odds ratio 1.43 vs. 1.14). Conclusion This meta-analysis confirmed the risks of night shift work for the development of overweight and obesity with a potential gradient association suggested, especially for abdominal obesity. Modification of working schedules is recommended, particularly for prolonged permanent night work. More accurate and detailed measurements on shift work patterns should be conducted in future research.

Exposure information is a critical element in various regulatory and non-regulatory frameworks in Europe and elsewhere. Exposure science supports to ensure safe environments, reduce human health risks, and foster a sustainable future. However, increasing diversity in regulations and the lack of a professional identity as exposure scientists currently hamper developing the field and uptake into European policy. In response, we discuss trends, and identify three key needs for advancing and harmonizing exposure science and its application in Europe. We provide overarching building blocks and define six long-term activities to address the identified key needs, and to iteratively improve guidelines, tools, data, and education. More specifically, we propose creating European networks to maximize synergies with adjacent fields and identify funding opportunities, building common exposure assessment approaches across regulations, providing tiered education and training programmes, developing an aligned and integrated exposure assessment framework, offering best practices guidance, and launching an exposure information exchange platform. Dedicated working groups will further specify these activities in a consistent action plan. Together, these elements form the foundation for establishing goals and an action roadmap for successfully developing and implementing a European Exposure Science Strategy 2020 2030, which is aligned with advances in science and technology. We thank Claudia Cascio and Amelie Crépet for input to the initial manuscript. Open access was kindly provided by the German Federal Institute for Occupational Safety and Health (BAuA). peer-reviewed

Exposure to traffic-related air pollution (TRAP) has been associated with adverse health outcomes but underlying biological mechanisms remain poorly understood. Two randomized crossover trials were used here, the Oxford Street II (London) and the TAPAS II (Barcelona) studies, where volunteers were allocated to high or low air pollution exposures. The two locations represent different exposure scenarios, with Oxford Street characterized by diesel vehicles and Barcelona by normal mixed urban traffic. Levels of five and four pollutants were measured, respectively, using personal exposure monitoring devices. Serum samples were used for metabolomic profiling. The association between TRAP and levels of each metabolic feature was assessed. All pollutant levels were significantly higher at the high pollution sites. 29 and 77 metabolic features were associated with at least one pollutant in the Oxford Street II and TAPAS II studies, respectively, which related to 17 and 30 metabolic compounds. Little overlap was observed across pollutants for metabolic features, suggesting that different pollutants may affect levels of different metabolic features. After observing the annotated compounds, the main pathway suggested in Oxford Street II in association with NO2 was the acyl-carnitine pathway, previously found to be associated with cardio-respiratory disease. No overlap was found between the metabolic features identified in the two studies., Highlights • Two randomized crossover trials were used to assess the relationship between TRAP and metabolic features with MS-based metabolomics (MWAS) • The locations represent different exposure scenarios, with London characterized by diesel vehicles and Barcelona by normal mixed urban traffic • Levels of 17 and 30 metabolic compounds associated with different air pollutants in the studies, with little overlap in features across pollutants • No overlap found between metabolomic features identified in the two studies, possibly due to different levels of single pollutants • The acyl-carnitine pathway, involved in cardio-respiratory disease, was suggested as a potential pathway in association with NO2 in one study