Urinary metals and metal mixtures and oxidative stress biomarkers in an adult population from Spain: The Hortega Study

Domingo‐Relloso, Arce; Grau-Pérez, María; Galán-Chilet, Inmaculada; Garrido-Martinez, Maria J.; Tormos, Carmen; Navas‐Acien, Ana; Gómez‐Ariza, José Luis; Monzó-Beltrán, Lidia; Saez-Tormo, Guillermo; García‐Barrera, Tamara; Laita, Antonio Dueñas; Figuero, L.; Martı́n-Escudero, Juan Carlos; Chaves, Felipe Javier; Redón, Josep; Téllez-Plaza, María

doi:10.1016/j.envint.2018.11.055

Cited by 88 publications

(48 citation statements)

References 74 publications

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“…Variable selection models can also be implemented on binary, categorical, count, and time-to-event data, and can also accommodate clustering in the outcomes, e.g., repeated measures. WQS and BKMR have both been extended to included binary outcomes, with more extensions in progress, such as for survival analyses [27].…”

Section: Discussionmentioning

confidence: 99%

An overview of methods to address distinct research questions on environmental mixtures: an application to persistent organic pollutants and leukocyte telomere length

et al. 2019

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Background Numerous methods exist to analyze complex environmental mixtures in health studies. As an illustration of the different uses of mixture methods, we employed methods geared toward distinct research questions concerning persistent organic chemicals (POPs) as a mixture and leukocyte telomere length (LTL) as an outcome. Methods With information on 18 POPs and LTL among 1,003 U.S. adults (NHANES, 2001–2002), we used unsupervised methods including clustering to identify profiles of similarly exposed participants, and Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) to identify common exposure patterns. We also employed supervised learning techniques, including penalized, weighted quantile sum (WQS), and Bayesian kernel machine (BKMR) regressions, to identify potentially toxic agents, and characterize nonlinear associations, interactions, and the overall mixture effect. Results Clustering separated participants into high, medium, and low POP exposure groups; longer log-LTL was found among those with high exposure. The first PCA component represented overall POP exposure and was positively associated with log-LTL. Two EFA factors, one representing furans and the other PCBs 126 and 118, were positively associated with log-LTL. Penalized regression methods selected three congeners in common (PCB 126, PCB 118, and furan 2,3,4,7,8-pncdf) as potentially toxic agents. WQS found a positive overall effect of the POP mixture and identified six POPs as potentially toxic agents (furans 1,2,3,4,6,7,8-hxcdf, 2,3,4,7,8-pncdf, and 1,2,3,6,7,8-hxcdf, and PCBs 99, 126, 169). BKMR found a positive linear association with furan 2,3,4,7,8-pncdf, suggestive evidence of linear associations with PCBs 126 and 169, and a positive overall effect of the mixture, but no interactions among congeners. Conclusions Using different methods, we identified patterns of POP exposure, potentially toxic agents, the absence of interaction, and estimated the overall mixture effect. These applications and results may serve as a guide for mixture method selection based on specific research questions. Electronic supplementary material The online version of this article (10.1186/s12940-019-0515-1) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

An overview of methods to address distinct research questions on environmental mixtures: an application to persistent organic pollutants and leukocyte telomere length

et al. 2019

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“…Some reports have suggested that TETs activity is influenced by oxidative stress (Delatte et al 2015). Cd has been related to oxidative stress (Chia et al 2011;Domingo-Relloso et al 2019;Lee et al 2009;Moitra et al 2014;Srivastava et al 2014) and could interfere in the DNAm pathways by promoting redox unbalance. We hypothesized that Cd exposure from tobacco could induce changes in genomic DNAm and mediate well-known smokingrelated methylation alterations.…”

Section: Introductionmentioning

confidence: 99%

Cadmium, Smoking, and Human Blood DNA Methylation Profiles in Adults from the Strong Heart Study

Domingo‐Relloso

Riffo‐Campos

Haack

et al. 2020

Environ Health Perspect

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BACKGROUND: The epigenetic effects of individual environmental toxicants in tobacco remain largely unexplored. Cadmium (Cd) has been associated with smoking-related health effects, and its concentration in tobacco smoke is higher in comparison with other metals. OBJECTIVES: We studied the association of Cd and smoking exposures with human blood DNA methylation (DNAm) profiles. We also evaluated the implication of findings to relevant methylation pathways and the potential contribution of Cd exposure from smoking to explain the association between smoking and site-specific DNAm. METHODS: We conducted an epigenome-wide association study of urine Cd and self-reported smoking (current and former vs. never, and cumulative smoking dose) with blood DNAm in 790,026 CpGs (methylation sites) measured with the Illumina Infinium Human MethylationEPIC (Illumina Inc.) platform in 2,325 adults 45-74 years of age who participated in the Strong Heart Study in 1989-1991. In a mediation analysis, we estimated the amount of change in DNAm associated with smoking that can be independently attributed to increases in urine Cd concentrations from smoking. We also conducted enrichment analyses and in silico protein-protein interaction networks to explore the biological relevance of the findings. RESULTS: At a false discovery rate (FDR)-corrected level of 0.05, we found 6 differentially methylated positions (DMPs) for Cd; 288 and 17, respectively, for current and former smoking status; and 77 for cigarette pack-years. Enrichment analyses of these DMPs displayed enrichment of 58 and 6 Gene Ontology and Kyoto Encyclopedia of Genes and Genomes gene sets, respectively, including biological pathways for cancer and cardiovascular disease. In in silico protein-to-protein networks, we observed key proteins in DNAm pathways directly and indirectly connected to Cd-and smoking-DMPs. Among DMPs that were significant for both Cd and current smoking (annotated to PRSS23, AHRR, F2RL3, RARA, and 2q37.1), we found statistically significant contributions of Cd to smoking-related DNAm. CONCLUSIONS: Beyond replicating well-known smoking epigenetic signatures, we found novel DMPs related to smoking. Moreover, increases in smoking-related Cd exposure were associated with differential DNAm. Our integrative analysis supports a biological link for Cd and smoking-associated health effects, including the possibility that Cd is partly responsible for smoking toxicity through epigenetic changes.

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“…There is experimental evidence that oxidative stress can be induced either by redox-cycling metals such as barium or thallium through directly generating free radicals, or indirectly by non-redox cycling metals such as arsenic, lead or mercury [44,45]. A recent study in the general Spanish population has reported an association between elevated oxidative stress and barium [48]. Hanzel et al 2005 reported a link between thallium and oxidative stress through glutathione (GSH) metabolism and peroxide detoxification [46].…”

Section: Discussionmentioning

confidence: 99%

Two-step approach for assessing the health effects of environmental chemical mixtures: application to simulated datasets and real data from the Navajo Birth Cohort Study

et al. 2019

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Background: There is increasing interest in examining the consequences of simultaneous exposures to chemical mixtures. However, a consensus or recommendations on how to appropriately select the statistical approach analyzing the health effects of mixture exposures which best aligns with study goals has not been well established. We recognize the limitations that existing methods have in effectively reducing data dimension and detecting interaction effects when analyzing chemical mixture exposures collected in high dimensional datasets with varying degrees of variable intercorrelations. In this research, we aim to examine the performance of a two-step statistical approach in addressing the analytical challenges of chemical mixture exposures using two simulated data sets, and an existing data set from the Navajo Birth Cohort Study as a representative case study. Methods: We propose to use a two-step approach: a robust variable selection step using the random forest approach followed by adaptive lasso methods that incorporate both dimensionality reduction and quantification of the degree of association between the chemical exposures and the outcome of interest, including interaction terms. We compared the proposed method with other approaches including (1) single step adaptive lasso; and (2) two-step Classification and regression trees (CART) followed by adaptive lasso method. Results: Utilizing simulated data sets and applying the method to a real-life dataset from the Navajo Birth Cohort Study, we have demonstrated good performance of the proposed two-step approach. Results from the simulation datasets indicated the effectiveness of variable dimension reduction and reliable identification of a parsimonious model compared to other methods: single-step adaptive lasso or two-step CART followed by adaptive lasso method. Conclusions: Our proposed two-step approach provides a robust way of analyzing the effects of high-throughput chemical mixture exposures on health outcomes by combining the strengths of variable selection and adaptive shrinkage strategies.

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Urinary metals and metal mixtures and oxidative stress biomarkers in an adult population from Spain: The Hortega Study

Cited by 88 publications

References 74 publications

An overview of methods to address distinct research questions on environmental mixtures: an application to persistent organic pollutants and leukocyte telomere length

An overview of methods to address distinct research questions on environmental mixtures: an application to persistent organic pollutants and leukocyte telomere length

Cadmium, Smoking, and Human Blood DNA Methylation Profiles in Adults from the Strong Heart Study

Two-step approach for assessing the health effects of environmental chemical mixtures: application to simulated datasets and real data from the Navajo Birth Cohort Study

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