Dioxin(-like) exposures are linked to adverse health effects, including cancer. However, metabolic alterations induced by these chemicals remain largely unknown. Beyond known dioxin(-like) compounds, ...we leveraged a chemical-wide approach to assess chlorinated co-exposures and parent compound products termed dioxin(-like)-related compounds among 137 occupational workers. Endogenous metabolites were profiled by untargeted metabolomics, namely, reversed-phase chromatography with negative electrospray ionization (C18-negative) and hydrophilic interaction liquid chromatography with positive electrospray ionization (HILIC-positive). We performed a metabolome-wide association study to select dioxin(-like) associated metabolic features using a 20% false discovery rate threshold. Metabolic features were then characterized by pathway enrichment analyses. There are no significant features associated with polychlorinated dibenzo-
-dioxins (PCDDs), a subgroup of known dioxin(-like) compounds. However, 3,110 C18-negative and 2,894 HILIC-positive features were associated with at least one of the PCDD-related compounds. Abundant metabolic changes were also observed for polychlorinated dibenzofuran-related and polychlorinated biphenyl-related compounds. These metabolic features were primarily enriched in pathways of amino acids, lipid and fatty acids, carbohydrates, cofactors, and nucleotides. Our study highlights the potential of chemical-wide analysis for comprehensive exposure assessment beyond targeted chemicals. Coupled with advanced endogenous metabolomics, this approach allows for an in-depth exploration of metabolic alterations induced by environmental chemicals.
There is growing interest in examining the simultaneous effects of multiple exposures and, more generally, the effects of mixtures of exposures, as part of the exposome concept (being defined as the ...totality of human environmental exposures from conception onwards). Uncovering such combined effects is challenging owing to the large number of exposures, several of them being highly correlated. We performed a simulation study in an exposome context to compare the performance of several statistical methods that have been proposed to detect statistical interactions.
Simulations were based on an exposome including 237 exposures with a realistic correlation structure. We considered several statistical regression-based methods, including two-step Environment-Wide Association Study (EWAS
), the Deletion/Substitution/Addition (DSA) algorithm, the Least Absolute Shrinkage and Selection Operator (LASSO), Group-Lasso INTERaction-NET (GLINTERNET), a three-step method based on regression trees and finally Boosted Regression Trees (BRT). We assessed the performance of each method in terms of model size, predictive ability, sensitivity and false discovery rate.
GLINTERNET and DSA had better overall performance than the other methods, with GLINTERNET having better properties in terms of selecting the true predictors (sensitivity) and of predictive ability, while DSA had a lower number of false positives. In terms of ability to capture interaction terms, GLINTERNET and DSA had again the best performances, with the same trade-off between sensitivity and false discovery proportion. When GLINTERNET and DSA failed to select an exposure truly associated with the outcome, they tended to select a highly correlated one. When interactions were not present in the data, using variable selection methods that allowed for interactions had only slight costs in performance compared to methods that only searched for main effects.
GLINTERNET and DSA provided better performance in detecting two-way interactions, compared to other existing methods.
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.
•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
Background Chloroplatinate salts are well-known respiratory sensitizing agents leading to work-related sensitization and allergies in the work environment. No quantitative exposure-response relation ...has been described for chloroplatinate salts. Objective We sought to evaluate the quantitative exposure-response relation between occupational chloroplatinate exposure and sensitization. Methods A retrospective cohort study was conducted using routinely collected health surveillance data and chloroplatinate exposure data. Workers who newly entered work between January 1, 2000, and December 31, 2010, were included, and the relation between measured chloroplatinate exposure and sensitization (as determined by skin prick test responses) was analyzed in more than 1000 refinery workers from 5 refineries for whom a total of more than 1700 personal exposure measurements were available. Results A clear exposure-response relation was observed, most strongly for more recent platinum salt exposure. Average or cumulative exposure over the follow-up period was less strongly associated with sensitization risk. The exposure-response relation was modified by smoking and atopy. Conclusions Indications exist that recent exposure explains the risk of platinum salt sensitization most strongly. The precision of the estimate of the exposure-response relation derived from this data set appears superior to previous epidemiologic studies conducted on platinum salt sensitization and as a result, might have possible utility for the development of preventive strategies.
We previously showed that exposure to 5-methylchrysene (5MC) and other methylated polycyclic aromatic hydrocarbons (PAHs) best explains lung cancer risks in a case-control study among non-smoking ...women using smoky coal in China. Time-related factors (e.g., age at exposure) and non-linear relations were not explored.
We investigated the relation between coal-derived air pollutants and lung cancer mortality using data from a large retrospective cohort.
Participants were smoky (bituminous) or smokeless (anthracite) coal users from a cohort of 42,420 subjects from four communes in XuanWei. Follow-up was from 1976 to 2011, during which 4,827 deaths from lung-cancer occurred. Exposures were predicted for 43 different pollutants. Exposure clusters were identified using hierarchical clustering. Cox regression was used to estimate exposure–response relations for 5MC, while effect modification by age at exposure was investigated for cluster prototypes. A Bayesian penalized multi-pollutant model was fitted on a nested case-control sample, with more restricted models fitted to investigate non-linear exposure–response relations.
We confirmed the strong exposure–response relation for 5MC (Hazard Ratio 95% Confidence Interval = 2.5 2.4, 2.6 per standard-deviation (SD)). We identified four pollutant clusters, with all but two PAHs in a single cluster. Exposure to PAHs in the large cluster was associated with a higher lung cancer mortality rate (HR 95%CI = 2.4 2.2, 2.6 per SD), while exposure accrued before 18 years of age appeared more important than adulthood exposures. Results from the multi-pollutant model identified anthanthrene (ANT) and benzo(a)chrysene (BaC) as risk factors. 5MC remained strongly associated with lung cancer in models that included ANT and BaC and also benzo(a)pyrene (BaP).
We confirmed the link between PAH exposures and lung cancer in smoky coal users and found exposures before age 18 to be especially important. We found some evidence for the carcinogen 5MC and non-carcinogens ANT and BaC.
There is limited evidence regarding the exposure‐effect relationship between lung‐cancer risk and hexavalent chromium (Cr(VI)) or nickel. We estimated lung‐cancer risks in relation to quantitative ...indices of occupational exposure to Cr(VI) and nickel and their interaction with smoking habits. We pooled 14 case‐control studies from Europe and Canada, including 16 901 lung‐cancer cases and 20 965 control subjects. A measurement‐based job‐exposure‐matrix estimated job‐year‐region specific exposure levels to Cr(VI) and nickel, which were linked to the subjects' occupational histories. Odds ratios (OR) and associated 95% confidence intervals (CI) were calculated by unconditional logistic regression, adjusting for study, age group, smoking habits and exposure to other occupational lung carcinogens. Due to their high correlation, we refrained from mutually adjusting for Cr(VI) and nickel independently. In men, ORs for the highest quartile of cumulative exposure to CR(VI) were 1.32 (95% CI 1.19‐1.47) and 1.29 (95% CI 1.15‐1.45) in relation to nickel. Analogous results among women were: 1.04 (95% CI 0.48‐2.24) and 1.29 (95% CI 0.60‐2.86), respectively. In men, excess lung‐cancer risks due to occupational Cr(VI) and nickel exposure were also observed in each stratum of never, former and current smokers. Joint effects of Cr(VI) and nickel with smoking were in general greater than additive, but not different from multiplicative. In summary, relatively low cumulative levels of occupational exposure to Cr(VI) and nickel were associated with increased ORs for lung cancer, particularly in men. However, we cannot rule out a combined classical measurement and Berkson‐type of error structure, which may cause differential bias of risk estimates.
What's new?
Occupational exposure to hexavalent chromium (Cr(VI)) and nickel is associated with increased lung‐cancer risk. Little is known, however, about quantitative exposure‐effect relationships between lung cancer and Cr(VI) or nickel. Here, quantitative exposure‐effect relationships were investigated using secondary measurement data from different regions and time periods across a wide range of jobs, with adjustment for smoking habits. Lung‐cancer risk was elevated even at low cumulative exposure levels to Cr(VI) or nickel, particularly in men and regardless of smoking habits. The findings warrant ongoing surveillance for carcinogenic risks of occupational metal exposure.
This randomized crossover study investigated the metabolic and mRNA alterations associated with exposure to high and low traffic-related air pollution (TRAP) in 50 participants who were either ...healthy or were diagnosed with chronic pulmonary obstructive disease (COPD) or ischemic heart disease (IHD). For the first time, this study combined transcriptomics and serum metabolomics measured in the same participants over multiple time points (2 h before, and 2 and 24 h after exposure) and over two contrasted exposure regimes to identify potential multiomic modifications linked to TRAP exposure. With a multivariate normal model, we identified 78 metabolic features and 53 mRNA features associated with at least one TRAP exposure. Nitrogen dioxide (NO
) emerged as the dominant pollutant, with 67 unique associated metabolomic features. Pathway analysis and annotation of metabolic features consistently indicated perturbations in the tryptophan metabolism associated with NO
exposure, particularly in the gut-microbiome-associated indole pathway. Conditional multiomics networks revealed complex and intricate mechanisms associated with TRAP exposure, with some effects persisting 24 h after exposure. Our findings indicate that exposure to TRAP can alter important physiological mechanisms even after a short-term exposure of a 2 h walk. We describe for the first time a potential link between NO
exposure and perturbation of the microbiome-related pathways.
This longitudinal study aimed to assess the impact of COVID-19 containment measures on perceived health, health protective behavior and risk perception, and investigate whether chronic disease status ...and urbanicity of the residential area modify these effects. Participants (n = 5420) were followed for up to 14 months (September 2020-October 2021) by monthly questionnaires. Chronic disease status was obtained at baseline. Urbanicity of residential areas was assessed based on postal codes or neighborhoods. Exposure to containment measures was assessed using the Containment and Health Index (CHI). Bayesian multilevel-models were used to assess effect modification of chronic disease status and urbanicity by CHI. CHI was associated with higher odds for worse physical health in people with chronic disease (OR = 1.09, 95% credibility interval (CrI) = 1.01, 1.17), but not in those without (OR = 1.01, Crl = 0.95, 1.06). Similarly, the association of CHI with higher odds for worse mental health in urban dwellers (OR = 1.31, Crl = 1.23, 1.40) was less pronounced in rural residents (OR = 1.20, Crl = 1.13, 1.28). Associations with behavior and risk perception also differed between groups. Our study suggests that individuals with chronic disease and those living in urban areas are differentially affected by government measures put in place to manage the COVID-19 pandemic. This highlights the importance of considering vulnerable subgroups in decision making regarding containment measures.
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