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. Author manuscript; available in PMC: 2021 Jul 1.
Published in final edited form as: Environ Res. 2020 Apr 16;186:109507. doi: 10.1016/j.envres.2020.109507

Urinary levels of environmental phenols and parabens and antioxidant enzyme activity in the blood of women

AZ Pollack 1, SL Mumford 2, JR Krall 1, A Carmichael 1, VC Andriessen 2, K Kannan 3,4, EF Schisterman 2
PMCID: PMC7363544  NIHMSID: NIHMS1586215  PMID: 32325294

Abstract

Background:

The balance between oxidative stress and antioxidant enzymes is one biological mechanism by which environmental and lifestyle exposures affect health outcomes. Yet, no studies have examined the relationship between environmental phenolic compounds and parabens or their mixtures in relation to antioxidant enzyme activity in women of reproductive age.

Methods:

Sixteen environmental phenols and parabens were measured in urine 2–5 times across two months of follow-up in 143 women aged 18–44 years. Four antioxidant enzymes, erythrocyte and plasma glutathione peroxidase (eGPx, pGPx), glutathione reductase (GSHR), superoxide dismutase (SOD) were measured in plasma. Linear mixed models were adjusted for age, body mass index, race, and creatinine and were weighted with inverse probability of exposure weights. Multi-chemical exposures were estimated using hierarchical principal component analysis (PCA).

Results:

In line with our hypothesis that environmental phenols and parabens would be associated with decreased antioxidant enzymes, butyl, benzyl, ethyl, and propyl parabens were associated with lower levels of eGPx. Methyl paraben, 2,4-dichlorophenol and 2,5-dichlorophenol were associated with reduced SOD. 2,4,6-trichlorophenol was associated with increased levels of pGPx and GSHR. Several parabens were associated with modest decreases in eGPx and SOD, biomarkers of antioxidant defense. Increases in pGPx and GSHR were noted in relation to butyl and ethyl parabens. Co-exposures to parabens were associated with decreased eGPx (ß=−1.08, 95% CI: −1.74, −0.43) in principal components mixed models, while co-exposure to benzophenones-3 and −1 were associated with increased eGPx (ß =0.92, 95% CI: 0.20, 1.64).

Conclusion:

These findings indicate that nonpersistent chemicals altered antioxidant enzyme activity. Further human studies are necessary to delineate the relationship between environmental phenol and paraben exposures with erythrocyte and plasma activities of antioxidant enzymes.

Keywords: antioxidant enzyme, benzophenone, glutathione reductase, peroxidase, phenol, paraben, triclosan, superoxide dismutase, women

Introduction

Antioxidant enzyme activity is critical to the maintenance of cellular homeostasis (Valko et al., 2007). The balance between oxidative stress and antioxidant enzyme activity has been linked with cancer, diabetes and pregnancy complications (Al-Gubory et al., 2010; Klaunig et al., 2011; Li et al., 2019; Rajendran et al., 2014). Antioxidant enzyme levels are influenced by environmental pollutants (Iscan et al., 2002; Lushchak, 2011). Further, changes in antioxidant enzyme levels are associated with adverse pregnancy outcomes, underscoring the public health relevance of these biomarkers (Al-Gubory et al., 2010; Gupta et al., 2007; Mistry et al., 2010). Exposure to chemicals found widely in consumer products may play a role in the balance of antioxidant enzymes. Experimental evidence indicates that antioxidant enzyme levels are decreased following exposure to environmental phenolic compounds (Bindhumol et al., 2003; Binelli et al., 2011; Gualtieri et al., 2011; Li et al., 2008; Peng et al., 2013; Rodriguez-Fuentes et al., 2015). Bisphenols, parabens, triclosan and chlorophenols are found in a number of common products, including can linings, mothballs, personal care products such as toothpaste, and moisturizing lotion. Parabens are antimicrobial compounds that are widely used in personal care products. Environmental phenols and parabens include high-volume production chemicals with widespread human exposure (Calafat et al., 2007a, 2007b; Honda et al., 2018; Honda and Kannan, 2018). Further, there is a plausible molecular binding mechanism for this activity (Jayakanthan et al., 2015; Mi et al., 2018).

Epidemiologic evidence linking environmental phenolic compounds to oxidative stress biomarkers is growing (Aung et al., 2019; Ferguson et al., 2016; Huang et al., 2017; Kim and Hong, 2017; Martinez and Kannan, 2018; Wang et al., 2019; Watkins et al., 2015). These studies indicate that environmentally relevant exposures are associated with changes in oxidative stress biomarkers among pregnant women, infants, and elderly adults. The association between phenolic compounds and biomarkers of antioxidant enzyme activity is an emerging area of research. Epidemiologic studies have begun to investigate adipose levels of environmental phenols and parabens in relation to antioxidant enzyme activity (Artacho-Cordón et al., 2019). Data gaps remain, which include epidemiologic studies utilizing urinary biomarkers of exposure to environmental phenols and parabens in relation to antioxidants. Underscoring the importance of these gaps, the balance between oxidative stress and antioxidant enzymes is often regarded as a biological mechanism by which environmental and lifestyle exposures affect health outcomes. Despite this, no studies have examined the relationship between repeated measures of exposure to environmental phenolic compounds and parabens or their mixtures in relation to antioxidant enzyme activity in women of reproductive age.

Therefore, this study sought to examine our hypothesis that environmental phenols and parabens would be associated with reduced antioxidant activity between repeated measures of 16 urinary environmental phenolic compounds separately and in exposure-based mixtures, in relation to repeated measures of four antioxidant enzymes: erythrocyte superoxide dismutase (SOD), glutathione peroxidase (eGPx), and glutathione reductase (GSHR) and plasma glutathione peroxidase (pGPx), in a study of healthy, reproductive-aged women.

Methods

Study participants

The study participants have been described in detail previously (Pollack et al., 2016; Wactawski-Wende et al., 2009). Briefly, this study includes a subset of 143 women from the BioCycle Study (2005–2007), with similar characteristics to the full BioCycle Study cohort (Pollack et al., 2018). Women were followed for up to 16 clinic visits across approximately two months, 93% of participants completed at least 7 visits per month. Participants were healthy regularly menstruating women, aged 18–44, who did not use hormonal birth control, without diagnosed chronic health conditions, not pregnant or breastfeeding in the prior 6 months and did not adhere to a restricted diet. During each clinic visit at the University at Buffalo, urinary and blood biospecimens were collected by trained study staff. Prior to analysis, samples were stored at −80 °C. Polycarbonate-free containers were utilized for urine sample collection, to avoid contamination.

The study was approved by the University at Buffalo Health Sciences Institutional Review Board (IRB), which served as the IRB designated by the National Institutes of Health for the study under a reliance agreement. IRB approval for sample analysis was obtained from the New York State Department of Health. All participants provided written informed consent.

Environmental phenol and paraben measurement

Repeated urine specimens were used to quantify exposure to environmental phenols and parabens as was reported earlier and previously described (Pollack et al., 2016). Benzophenone-1 (BP1), benzophenone-3 (BP3), bisphenol A (BPA), 2,4-dichlorophenol (2,4-DCP), 2,5-dichlorophenol (2,5-DCP), 2,4,5-trichlorophenol (2,4,5-TCP), 2,4,6-trichlorophenol (2,4,6-TCP), triclosan, and six parabens (benzyl (BzP), butyl (BuP), ethyl (EtP), heptyl (HeP), methyl (MeP), propyl (PrP)), and two paraben metabolites (4-hydroxybenzoic acid (4-HB), 3,4-dihydroxybenzoic acid (3,4-DHB)) were measured in spot urine samples. Briefly, samples were analyzed after enzymatic deconjugation, solid phase extraction and high-performance liquid chromatography coupled with API2000 electrospray triple-quadrupole mass spectrometry (Asimakopoulos et al., 2014; Honda and Kannan, 2018; Zhang et al., 2011). Due to biospecimen availability, participants contributed varying numbers of specimens to the exposure assessment. Eleven percent of the participants had two samples, 27% had three, and 56% had four and the remaining 6% had five samples.

Antioxidant enzymes

Four antioxidant enzymes were quantified in plasma: erythrocyte glutathione peroxidase (eGPx), glutathione reductase (GSHR), plasma glutathione peroxidase (pGPx), and superoxide dismutase (SOD). Methods for their measurement have been described previously (Browne et al., 2008). Briefly, assays for kinetic enzymes were adapted to the Cobas Fara II autoanalyzer (Roche Diagnostic Systems, Inc., Basel, Switzerland) (Pippenger et al., 1998). Using OxiTek reagent kits from ZeptoMetrix (Buffalo, NY, USA) eGPx, pGPx, and eGSHR were quantified. Under uniform conditions, SOD activity was determined via the oxidation of cytochrome C by xanthine/xanthine oxidase. One SOD unit of activity was defined as the quantity of enzyme that induced a 50% reaction inhibition. Using purified SOD, calibration curves were generated (percent inhibition vs. SOD activity). Erythrocyte enzyme activities were normalized per gram or milligram of hemoglobin (Hb) (Browne et al., 2007).

Covariable assessment

Using standardized protocols, trained study staff took measurements of weight and height to determine body mass index (BMI) at the enrollment visit (Wactawski-Wende et al., 2009). Race, age, marital status, smoking, reproductive and medical history were ascertained by questionnaire. Less than 5% of participants had incomplete covariate data. Urinary creatinine was measured by a Roche Cobas 6000 chemistry analyzer (Roche Diagnostics Inc., Indianapolis, IN, USA) at the University of Minnesota. Due to low sample volume, specimens were diluted 1:5 and 43 specimens had insufficient volume for measurement of creatinine.

Statistical analysis

The distributions of urinary paraben and environmental phenol concentrations and antioxidant enzyme biomarkers were initially examined along with descriptive statistics of the study population. Natural log-transformed chemical exposures and antioxidant enzymes were utilized in all models to account for right skewed distributions, which were determined by quantile plots. Linear mixed models were utilized to ascertain associations between individual antioxidant biomarkers with each chemical exposure, with random intercepts to account for repeated measures. Continuous, time-varying measures of environmental phenol and paraben levels were included in longitudinal models. Confounding factors were selected based on an a priori approach and models were adjusted for age (continuous), BMI (continuous), race (white/black/other) and urinary creatinine (continuous, natural log-transformed). Inverse probability of exposure weights were used in marginal structural models to address time-dependent confounding from antioxidant enzyme and chemical exposures (Robins et al., 2000). Chemical-specific weights were generated according to menstrual cycle phase (follicular, ovulatory and luteal phases in first cycle; ovulatory phase of second cycle). Machine-read values were used for all biomarker measurements and no imputation was necessary. Due to limited variability, chemicals that measured below the LOD for more than 40% of samples were categorized as less than or greater than LOD in relation to antioxidant biomarkers in linear mixed models.

To estimate associations between multiple chemical exposures above the LOD in at least 40% of samples and biomarkers, a principal component analysis (PCA) approach was applied as in a previous study for these chemicals by this research team (Pollack et al., 2018). Briefly, varimax-rotated principal component (PC) factors were used in a hierarchical approach (Crainiceanu et al., 2011; Krall et al., 2017) to account for temporal variation in estimated PCs. The PCs produced by this approach represent multi-chemical exposures and were subsequently analyzed in single and multiple factor linear mixed models with random intercepts. P-values of less than 0.05 were considered statistically significant. SAS version 9.4 (SAS Corp, Cary, NC, USA) and R version 3.4 (R Core Team, Vienna, Austria) were used for analysis.

Results

Study participants were an average of 27 (standard deviation (SD), 8 years) years of age, with a BMI of 24 (SD, 4 m/kg2) (Table 1). The majority of participants identified as white (63%) and black (20%). Nearly all women were nonsmokers (96%). Among antioxidant enzymes, median levels of SOD were highest, 4546.9 IU/g, followed by PGPx, 776.8 IU/g (Table 2). GSHR levels were lowest, 3.69 IU/g. All antioxidant biomarker values were above the limits of detection (LOD). Median levels of environmental phenols and parabens were highest for 4-hydroxybenzoic acid (398 ng/ml), 3,4-dihydroxybenzoic acid (345 ng/ml), and methyl paraben (59 ng/ml) and were lowest for 2,4,6-TCP and butyl paraben (Supplemental Table 1). Of the 509 samples measured for bisphenol A, 1% of the samples were below the LOD. Greater proportions of 2,4-dichlorophenol (35.4%) and 2,4,5-trichlorophenol (49.1%) were below the LOD. All values of methyl paraben were above the LOD, while 98.8% of heptyl paraben and 74.7% of benzyl paraben were below the LOD.

Table 1.

Participant characteristics by category of paraben factor scores (n=141)

Paraben Factor Scores
Tertile 1 (n=47) Tertile 2 (n=47) Tertile 3 (n=47) Overall (n=141)
Age (years)
 Mean (SD) 27.3 (7.78) 27.0 (8.35) 26.7 (8.64) 27.0 (8.20)
 Median [Min, Max] 24.0 [18.0, 43.0] 23.0 [18.0, 44.0] 23.0 [18.0, 44.0] 24.0 [18.0, 44.0]
Body Mass Index (kg/m2)
 Mean (SD) 24.5 (4.10) 22.8 (3.38) 24.7 (4.18) 24.0 (3.97)
 Median [Min, Max] 23.5 [18.4, 33.8] 22.5 [16.1, 32.0] 23.5 [18.5, 35.0] 23.5 [16.1, 35.0]
Parity
 Parous 10 (21.3) 10 (21.3) 12 (25.5) 32 (22.7)
 Nulliparous 35 (74.5) 36 (76.6) 34 (72.3) 105 (74.5)
 Missing 2 (4.3) 1 (2.1) 1 (2.1) 4 (2.8)
Race
 Non-Hispanic White 31 (66.0) 33 (70.2) 25 (53.2) 89 (63.1)
 Non-Hispanic Black 7 (14.9) 9 (19.1) 13 (27.7) 29 (20.6)
 Other 9 (19.1) 5 (10.6) 9 (19.1) 23 (16.3)
Education
 Post-secondary education 40 (85.1) 43 (91.5) 40 (85.1) 123 (87.2)
 High school graduate 7 (14.9) 4 (8.5) 7 (14.9) 18 (12.8)
Smoking Status
 Nonsmoker 46 (97.9) 44 (93.6) 45 (95.7) 135 (95.7)
 Current smoker 1 (2.1) 3 (6.4) 2 (4.3) 6 (4.3)
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Table 2.

Antioxidant enzyme distribution among 143 healthy reproductive aged women

Percentile
Antioxidants (IU/g) Min 25 50 75 Max
 Erythrocyte glutathione peroxidase 0.0 27.9 34.6 41.9 187.6
 Glutathione reductase 0.0 3.0 3.7 4.5 14.0
 Plasma glutathione peroxidase 333.3 685.7 776.8 896.0 1870.4
 Superoxide dismutase 1066.0 4044.7 4546.9 5221.7 9577.0
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Urinary concentrations of 2,4,6-TCP were associated with higher levels of GSHR (β, 0.03, 95% confidence interval (CI): 0.01, 0.06) pGPx (β, 0.018, 95% CI, 0.005, 0.03), and of eGPx (β, 0.013, 95% CI, −0.012, (Figure 1). Methyl paraben, propyl paraben, 4-HB, and 2,4-DCP, 2,5-DCP, and 2,4,5-TCP were associated with modestly reduced levels of SOD. Several parabens including butyl, benzyl, ethyl, methyl, and propyl paraben were associated with modestly reduced levels of eGPx. Bisphenol A was modestly associated with lower levels of pGPx, GSHR and SOD although these associations were not statistically significant. Other phenols, such as BP1, BP3, and triclosan, were not significantly associated with changes in antioxidant enzymes (Figure 1, Supplemental Table 2).

Figure 1.

Figure 1.

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Repeated measures analysis of plasma and erythrocyte antioxidant enzyme levels in relation to urinary exposure biomarkers of phenols and parabens in reproductive-aged women (n=143).

Abbreviations: BPA, bisphenol A; BP-1, benzophenone-1; BP-3, benzophenone-3; 2,4-DCP, 2,4-dichlorophenol; 2,4-DCP, 2,5-dichlorophenol; 2,4,5-TCP, 2,4,5-trichlorophenol; 2,4,6-TCP, 2,4,6-trichlorophenol; 4-HB, 4-hydroxybenzoic acid; 3,4-DHB, 3,4-dihydroxybenzoic acid; EGPX, erythrocyte glutathione peroxidase; GSHR, glutathione reductase; PGPX, plasma glutathione peroxidase; SOD, superoxide dismutase.

Adjusted for: age (continuous), BMI (continuous), race (white/black/other) and urinary creatinine (continuous, natural log-transformed) and inverse probability of exposure weights.

The hierarchical PCA approach resulted in four factors: 1) a paraben factor, which comprised butyl, ethyl, methyl, and propyl paraben; 2) a phenol factor, which comprised 2,4,6-TCP, 2,4-DCP, 2,5-DCP, and triclosan; 3) a paraben metabolite and BPA factor which comprised 3,4-DHB and 4-HB along with BPA; 4) an ultraviolet (UV) filter factor was composed of BP1 and BP3. Few trends were identified by this approach. In single factor models, parabens were associated with decreased EGPx (β, −1.08, 95% CI: −1.74, −0.43) while the UV filter factor, comprised of benzophenone 1 and 3, was associated with increased EGPx (β, 0.92, 95% CI, 0.20, 1.64) (Table 3).

Table 3.

Linear mixed models of hierarchical principal components and antioxidant biomarkers.

Paraben Factora Phenol Factorb Paraben metabolite & BPA Factorc UV filter Factord
Single-factor model Beta (95% Cl) Multi-factor model Beta (95% Cl) Single-factor model Beta (95% Cl) Multi-factor model Beta (95% Cl) Single-factor model Beta (95% Cl) Multi-factor model Beta (95% Cl) Single-factor model Beta (95% Cl) Multi-factor model Beta (95% Cl)
Antioxidants
 GSHR −0.01 (−0.07, 0.05) 0.001 (−0.08, 0.08) 0.01 (−0.04, 0.07) −0.001 (−0.09, 0.07) −0.01 (−0.06, 0.04) −0.01 (−0.09, 0.06) 0.04 (−0.03, 0.10) 0.038 (−0.05, 0.12)
 SOD −24.55 (−80.79, 31.68) −19.82 (−91.71, 52.07) −11.74 (−62.03, 38.54) −24.76 (−94.64, 45.12) 5.89 (−39.84, 51.62) −7.72 (−72.25, 56.81) 34.20 (−27.25, 95.66) 27.94 (−44.53, 100.41)
 EGPx −1.08 (−1.74, −0.43) −0.84 (−1.70, 0.03) −0.09 (−0.68, 0.50) −0.21 (−1.04, 0.62) 0.40 (−0.14, 0.94) 0.22 (−0.55, 0.98) 0.92 (0.20, 1.64) 0.53 (−0.35, 1.41)
 PGPx 2.49 (−4.48, 9.46) 3.48 (−6.39, 13.34) −4.82 (−11.20, 1.56) −4.63 (−13.66, 4.41) 2.31 (−3.54, 8.15) 0.51 (−7.83, 8.85) −0.51 (−8.22, 7.19) 3.54 (−6.64, 13.72)
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Abbreviations: EGPX, erythrocyte glutathione peroxidase; GSHR, glutathione reductase; PGPX, plasma glutathione peroxidase; SOD, superoxide dismutase

All models adjusted for age, BMI, race, and creatinine

a

Paraben factor: Butyl, ethyl, methyl, and propyl paraben

b

Phenol factor: 2,4,6-TCP, 2,4-DCP, 2,5-DCP, and triclosan

c

Paraben metabolite and BPA factor: 3,4-DHB, 4-HB, and BPA

d

Ultraviolet (UV) filter factor: Benzophenone 1 and 3

Discussion

Several environmental phenols and parabens were associated with diminished levels of antioxidant enzymes, specifically eGPx and SOD. The paraben factor and separately, butyl, benzyl, ethyl, methyl, and propyl parabens were modestly associated with lower eGPx levels and methyl paraben and 2,4-DCP were associated with decreased SOD. In contrast, 2,4,6-TCP was associated with increased levels of pGPx, eGPx, and GSHR, while butyl and ethyl parabens were associated with a small increase in pGPx. Of note, antioxidant enzymes are a critical component within redox pathways, but their deletion can confer benefits in some settings while their overexpression can negatively impact the redox balance (Lei et al., 2016). These results support that environmental phenols and parabens may play a role in antioxidant defenses of reproductive-aged women, which can inform our understanding of the potential pathway from these environmental factors and health outcomes.

Diminished production of enzymatic and non-enzymatic antioxidants contributes to the deleterious impact of free radicals and can contribute to the development of disease (Valko et al., 2007). Antioxidant enzymes are critical in deactivating and eradicating reactive oxygen species. Several studies have identified an association between phenols and parabens with biomarkers of oxidative stress in pregnant women (Aung et al., 2019; Ferguson et al., 2016; Watkins et al., 2015). Oxidative stress during pregnancy may be related to preterm birth (Ferguson et al., 2017, 2015). However, exposures may differ during pregnancy (Woodruff et al., 2011), underscoring the importance of evaluating this relationship in women who are not pregnant. This evidence indicates that phenols and parabens interfere with systemic oxidative stress, but the literature on whether antioxidant levels are influenced is sparse. Importantly, the role of antioxidant enzymes recently was clarified as not being entirely beneficial but rather that they are part of a complex redox balance necessary for homeostasis (Lei et al., 2016).

Limited experimental studies have investigated the effect of environmental phenols and parabens on antioxidant enzymes and non-enzymatic antioxidants. In support of our findings, a mixture of methyl and propyl parabens decreased SOD in tilapia liver, following six days of exposure, but these effects were not seen after twelve days, suggesting a possible reversibility of antioxidant function (Silva et al., 2018). Further supporting our finding that propyl paraben was associated with diminished eGPx and moderately associated with lower levels of SOD and GSHR; propyl paraben dosing led to increased superoxide anion levels in liver cells, indicating reduced function of SOD (Szeląg et al., 2016). In contrast to our results, glutathione peroxidase, SOD, and glutathione reductase were elevated in Nile tilapia gills and liver following exposure to ethyl, propyl, butyl, and benzyl parabens (Silva et al., 2018). SOD is a critically important enzyme in the antioxidant system to protect against reactive oxygen species. Its role is to catalyze the separation of the superoxide anion into the components O2 and H2O2. Notably, mice without SOD activity are resistant to toxicity from acetaminophen (Henderson et al., 2000). Glutathione reductase, glutathione peroxidase, glutathione-S-transferase, and SOD levels were reduced in mouse liver following 30 day dosing of butyl paraben (Shah and Verma, 2011). Our observation of reduced SOD and eGPx levels for several parabens and dichlorophenols could be attributable to protein oxidation.Lipid peroxidation can interact with enzymes by modifying histidine residue and consequently reducing enzyme availability (Kwon et al., 2000).

The association between 2,4,6-TCP, a urinary pesticide metabolite, with increased GSHR and pGPx was contrary to our hypothesis that environmental phenols and parabens would diminish antioxidant activity. Since this pesticide metabolite reflects exposure to legacy pollutants, it may indicate long-term exposure and consequent up-regulation of anti-oxidant defenses. Notably, clams dosed with 2,4,5-TCP had increased glutathione peroxidase levels (Xia et al., 2016), which is in line with our findings of increased levels of glutathione reductase and plasma glutathione peroxidase in relation to 2,4,6-TCP, although we did not observe these associations for 2,4,5-TCP. However, experimental studies show that fish injected directly with 2,4,6-TCP had reduced activity of antioxidant enzymes (Li et al., 2007). Dosing with 2,4,6-TCP induced oxidative stress in mouse embryonic fibroblasts (Zhang et al., 2014). Differences between our findings and experimental studies may be attributable to species differences, different routes of exposure, or the differences in dose. It is also possible that our findings may be due to chance.

Our findings that co-exposure to parabens was associated with reduced eGPx while co-exposure to ultraviolet filters (e.g., benzophenone) were associated with increased eGPx are novel. To our knowledge, no studies have previously evaluated mixtures of environmental phenols and parabens in relation to antioxidant levels in women. However, since real world scenarios entail exposure to numerous chemicals (Woodruff et al., 2011), these approaches are an important first step in attempting to gain a better understanding at the influence of more than one chemical at a time (Carlin et al., 2013). In the present analysis, we utilized repeated measures of environmental phenols and parabens in relation to repeated measures of antioxidant enzymes. This approach is necessary with many nonpersistent chemicals due to their short half-lives (Braun et al., 2011; Mahalingaiah et al., 2007; Meeker et al., 2013). Two types of antioxidant activities were measured in this study, in plasma and in erythrocytes. The activity in these spaces may not be indicative of the entire antioxidant defense due to tissue specific differences (Browne et al., 2008). This study involved many comparisons, and we did not apply a correction due to the exploratory nature of this study. The levels of parabens were lower than those from the National Health and Nutrition Examination Survey (CDC, 2009). Despite the healthy study population, unless we expect that study participants had a different biological relationship between these environmental phenols and parabens with antioxidant enzymes, then these findings generalize to other healthy, reproductive-aged women. Future studies are necessary to confirm associations observed here.

In conclusion, several parabens were associated with modest decreases in eGPx and SOD, biomarkers of antioxidant defense. We found notable increases in antioxidant defense for pGPx and GSHR in relation to 2,4,6-TCP, butyl and ethyl parabens. It is challenging to draw conclusions regarding the changes noted here due to the complex interplay between antioxidants and reactive oxygen species, particularly in light of the lack of corroborating human studies. Further human studies will improve the understanding of the relationship between environmental phenol and paraben exposure with erythrocyte and plasma activities of antioxidant enzymes.

Supplementary Material

1

Highlights.

  • Parabens associated with lower erythrocyte glutathione peroxidase.

  • Methyl paraben, 2,4-DCP and 2,5-DCP associated with lower superoxide dismutase.

  • Paraben co-exposures associated with lower erythrocyte glutathione peroxidase.

  • Environmental phenols, parabens linked with antioxidant enzyme activity in women.

Acknowledgments

Funding: This work was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (Contract Number: HHSN275200403394C HHSN275201100002I, and Task 1 HHSN27500001).

Footnotes

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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