Urinary phthalate metabolites in relation to biomarkers of inflammation and oxidative stress: NHANES 1999-2006

Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA.
Environmental Research (Impact Factor: 4.37). 02/2011; 111(5):718-26. DOI: 10.1016/j.envres.2011.02.002
Source: PubMed


Phthalate esters are a class of compounds utilized extensively in widely-distributed consumer goods, and have been associated with various adverse health outcomes in previous epidemiologic research. Some of these health outcomes may be the result of phthalate-induced increases in oxidative stress or inflammation, which have been demonstrated in animal studies. The aim of this study was to explore the relationship between urinary phthalate metabolite concentrations and serum markers of inflammation and oxidative stress (C-reactive protein (CRP) and gamma glutamyltransferase (GGT), respectively). Subjects were participants in the National Health and Nutrition Examination Survey (NHANES) between the years 1999 and 2006. In multivariable linear regression models, we observed significant positive associations between CRP and mono-benzyl phthalate (MBzP) and mono-isobutyl phthalate (MiBP). There were CRP elevations of 6.0% (95% confidence interval (CI) 1.7-10.8%) and 8.3% (95% CI 2.9-14.0%) in relation to interquartile range (IQR) increases in urinary MBzP and MiBP, respectively. GGT was positively associated with mono(2-ethylhexyl) phthalate (MEHP) and an MEHP% variable calculated from the proportion of MEHP in comparison to other di(2-ethylhexyl) phthalate (DEHP) metabolites. IQR increases in MEHP and MEHP% were associated with 2.5% (95% CI 0.2-4.8%) and 3.7% (95% CI 1.7-5.7%) increases in GGT, respectively. CRP and GGT were also inversely related to several phthalate metabolites, primarily oxidized metabolites. In conclusion, several phthalate monoester metabolites that are detected in a high proportion of urine samples from the US general population are associated with increased serum markers of inflammation and oxidative stress. On the other hand, several oxidized phthalate metabolites were inversely associated with these markers. These relationships deserve further exploration in both experimental and observational studies.

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Available from: Rita Loch-Caruso, Dec 12, 2013
    • "Several authors have reported a relationship between phthalates and oxidative stress demonstrating increasing generation of reactive oxygen species (ROS) (Seo et al., 2004;Tetz et al., 2013). Others have associated the presence of several phthalate monoester metabolites detected in urine, with increased serum markers of inflammation and oxidative stress (Hauser et al., 2007;Ferguson et al., 2011). With this study, we aimed to investigate the mechanism underlying the possible adjuvant effect of DBP. "
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    ABSTRACT: Recent studies suggest that phthalates may have a role in the development of allergic diseases, probably due to an adjuvant effect. The present study aimed to investigate the possible adjuvant effect of dibutyl phthalate (DBP) in two in vitro models of contact-allergen induced cell activation, namely the NCTC 2544 IL-18 assay and the THP-1 activation assay. Results show no adjuvant effect in the human keratinocyte cell line NCTC 2544, indicated by lack of increase in interleukin 18 (IL-18) production after exposure to p-phenylediamine (PPD) in association with DBP. On the contrary, increased upregulation of CD86 and interleukin 8 (IL-8) production were observed in THP-1 cells exposed to combinations of citral (Cit) or imidazolidinyl urea (IMZ) with DBP, indicative of an adjuvant effect. Additionally, higher production of reactive oxygen species (ROS) in THP-1 cells treated with DBP associated to Cit supports that oxidative stress could be part of the molecular mechanism of the observed adjuvant effect. In conclusion, we demonstrate that DBP presents in vitro an adjuvant effect for immune stimulation in dendritic cells but not in keratinocytes. Future studies are necessary to elucidate the precise mechanism underlying the adjuvant effect of DBP in vitro and in vivo.
    No preview · Article · Aug 2015 · Toxicology in Vitro
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    • "MEHP is the active monoester metabolite of DEHP in vivo and discharged in the urine [5]. It has been reported that in the NHANES cohort between 1999 and 2006, MEHP was found in their urine samples in about 80% participants [6], which indicated that the human DEHP exposure was universal. "
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    ABSTRACT: Mono-(2-ethylhexyl) phthalate (MEHP), the active metabolite of di-(2-ethylhexyl) phthalate (DEHP), is a widespread environmental contaminant and has been proved to have potential adverse effects on the reproductive system, carcinogenicity, liver, kidney and developmental toxicities. However, the effect of MEHP on vascular system remains unclear. The main purpose of this study was to evaluate the cytotoxic effects of MEHP on human umbilical endothelial cells (HUVEC) and its possible molecular mechanism. HUVEC cells were treated with MEHP (0, 6.25, 12.5, 25,50 and 100 µM), and the cellular apoptosis and mitochondrial membrane potential as well as intracellular reactive oxygen species were determined. In present study, MEHP induced a dose-dependent cell injury in HUVEC cell via an apoptosis pathway as characterized by increased percentage of sub-G1, activation of caspase-3, -8and -9, and increased ratio of Bax/bcl-2 mRNA and protein expression as well as cytochrome C releasing. In addition, there was obvious oxidative stress, represented by decreased glutathione level, increased malondialdehyde level and superoxide dismutase activity. N-Acetylcysteine, as an antioxidant that is a direct reactive oxygen species scavenger, could effectively block MEHP-induced reactive oxygen species generation, mitochondrial membrane potential loss and cell apoptosis. These data indicated that MEHP induced apoptosis in HUVEC cells through a reactive oxygen species-mediated mitochondria-dependent pathway.
    Full-text · Article · May 2014 · PLoS ONE
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    • "NHANES is an ongoing cross-sectional study designed to measure subject exposure to various environmental chemicals, dietary intake patterns, and various health outcomes [69]. Our previous studies indicated several associations between urinary phthalate metabolites and serum markers of oxidative stress in a large human population [70,71]. As a follow-up, this analysis examines the same association when phthalate exposure occurs in conjunction with exposure to other environmental contaminants that may also be capable of causing an oxidative stress response. "
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    ABSTRACT: As public awareness of consequences of environmental exposures has grown, estimating the adverse health effects due to simultaneous exposure to multiple pollutants is an important topic to explore. The challenges of evaluating the health impacts of environmental factors in a multipollutant model include, but are not limited to: identification of the most critical components of the pollutant mixture, examination of potential interaction effects, and attribution of health effects to individual pollutants in the presence of multicollinearity. In this paper, we reviewed five methods available in the statistical literature that are potentially helpful for constructing multipollutant models. We conducted a simulation study and presented two data examples to assess the performance of these methods on feature selection, effect estimation and interaction identification using both cross-sectional and time-series designs. We also proposed and evaluated a two-step strategy employing an initial screening by a tree-based method followed by further dimension reduction/variable selection by the aforementioned five approaches at the second step. Among the five methods, least absolute shrinkage and selection operator regression performs well in general for identifying important exposures, but will yield biased estimates and slightly larger model dimension given many correlated candidate exposures and modest sample size. Bayesian model averaging, and supervised principal component analysis are also useful in variable selection when there is a moderately strong exposure-response association. Substantial improvements on reducing model dimension and identifying important variables have been observed for all the five statistical methods using the two-step modeling strategy when the number of candidate variables is large. There is no uniform dominance of one method across all simulation scenarios and all criteria. The performances differ according to the nature of the response variable, the sample size, the number of pollutants involved, and the strength of exposure-response association/interaction. However, the two-step modeling strategy proposed here is potentially applicable under a multipollutant framework with many covariates by taking advantage of both the screening feature of an initial tree-based method and dimension reduction/variable selection property of the subsequent method. The choice of the method should also depend on the goal of the study: risk prediction, effect estimation or screening for important predictors and their interactions.
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