Associations between circulating levels of bisphenol A and phthalate metabolites and coronary risk in the elderly

Associations between circulating levels of bisphenol A and phthalate metabolites and coronary risk in the elderly

Ecotoxicology and Environmental Safety 80 (2012) 179–183 Contents lists available at SciVerse ScienceDirect Ecotoxicology and Environmental Safety j...

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Ecotoxicology and Environmental Safety 80 (2012) 179–183

Contents lists available at SciVerse ScienceDirect

Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv

Associations between circulating levels of bisphenol A and phthalate metabolites and coronary risk in the elderly Lena Olse´n a, Lars Lind b, P. Monica Lind a,n a b

Department of Medical Sciences, Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden Department of Medical Sciences, Acute and Internal Medicine, Uppsala University, Uppsala, Sweden

a r t i c l e i n f o

abstract

Article history: Received 5 November 2011 Received in revised form 21 February 2012 Accepted 23 February 2012 Available online 14 March 2012

Studies have pointed out associations between various chemicals with estrogenic activity and cardiovascular disease. Being ubiquitous, the plastic additive substances bisphenol A (BPA), and phthalates have been detected in almost all types of analyzed human samples. The aim of this study was to investigate whether circulating levels of BPA and/or four selected phthalate metabolites are associated to coronary risk in an elderly population. In the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study, coronary risk was assessed by the Framingham Risk Score (FRS) together with circulating serum levels of BPA and the four phthalate metabolites monoisobutyl phthalate (MiBP), monomethyl phthalate (MMP), monoethyl phthalate (MEP), mono-(2-ethylhexyl) phthalate (MEHP) in 1016 subjects aged 70 years. BPA, MEHP, and MMP were associated to LDLcholesterol and MEHP to HDL-cholesterol, MEP to diastolic blood pressure and MiBP to fasting glucose when the compounds were investigated one by one. After Bonferronni correction, only the relations for MMP to LDL-cholesterol (p o 0.0001), MEP to diastolic blood pressure (p o0.0002), and MiBP to fasting glucose (p o 0.0001) remained significant. MMP was associated to the FRS (p ¼0.02), but after Bonferronni correction, this association was not significant. In conclusion, associations were found between MMP and LDL-cholesterol, MEP and diastolic blood pressure, and MiBP and fasting glucose. We did not observe any strong associations between BPA nor any of the four phthalate metabolites and Framingham Risk Score in this elderly population. & 2012 Elsevier Inc. All rights reserved.

Keywords: Serum levels Bisphenol A (BPA) Phthalate metabolites Elderly Coronary risk

1. Introduction Bisphenol A (BPA) and phthalates are high volume chemicals that have been used as components in plastics for a long period of time. BPA is mainly used for making polycarbonate plastic but is also widely used in the production of other plastics, in epoxy resins lining food and beverage containers, and in cash receipts. Phthalates are derivatives of phthalic acid used primarily as plasticizers to make plastic products more flexible. Consumer products containing plastics include food packaging materials,

Abbreviations: BMI, body mass index; BPA, bisphenol A; CV, cardiovascular; CHD, coronary heart disease; DBP, dibutyl phthalate; DEHP, diethylhexyl phthalate; DiBP, diisobutyl phthalate; EDC, endocrine disrupting compounds; LOD, limit of detection; MECPP, mono(2-ethyl-5-carboxypentyl) phthalate; MEHHP, mono(2ethyl-5-hydroxyhexyl) phthalate; MEOHP, mono(2-ethyl-5-oxohexyl) phthalate; MEHP, mono-(2-ethylhexyl) phthalate; MEP, monoethyl phthalate; MiBP, monoisobutyl phthalate; MMP, monomethyl phthalate; NHANES, National Health and Nutrition Examination Survey; PPAR, peroxisome proliferator activated receptor; PIVUS, Prospective Investigation of the Vasculature in Uppsala Seniors n Corresponding author. Fax: þ46 18519978. E-mail addresses: [email protected] (L. Olse´n), [email protected] (L. Lind), [email protected] (P.M. Lind). 0147-6513/$ - see front matter & 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.ecoenv.2012.02.023

children’s toys, and water pipes but phthalates are also used in medical devices such as bags for blood and in personal care products such as cosmetics. Both BPA and phthalates can migrate out of the plastic product and into the environment (Halden, 2010; Heudorf et al., 2007; Koch and Calafat, 2009; Schettler, 2006; Schug et al., 2011). Ingested BPA is mainly conjugated with glucuronic acid which is eliminated in the urine. A fraction of the absorbed BPA may also be distributed to body storage sites followed by a slow, low-level release of BPA into the bloodstream (Fernandez et al., 2007). Metabolism and elimination of phthalates is more complex. The phthalates are metabolized to the corresponding monoester metabolites, which are eliminated in the urine as glucuronide conjugates or are further metabolized (Frederiksen et al., 2007; Wittassek and Angerer, 2008). BPA and phthalates act as endocrine-disrupting compounds (EDCs), i.e., compounds capable of causing dysfunction in hormonally regulated body systems. The main action attributed to BPA is estrogen-like activity, while the phthalates function mainly as anti-androgens (Talsness et al., 2009; Wolstenholme et al., 2010; vom Saal et al., 2007). Most plastic products release chemicals having estrogenic activity (Schug et al., 2011). These

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chemicals are widespread in all kinds of different environments all over the world and have been detected in human urine, milk, saliva, serum, plasma, ovarian follicular fluid, and amniotic fluid. For reading more about exposure, toxicology, and metabolism of BPA and phthalates, see e.g., the following articles (Heudorf et al., 2007; Olsen et al., 2012; Wittassek and Angerer, 2008). Elevated circulating levels of environmental contaminants and pollutants have been found to be associated with prevalent coronary heart disease (CHD), a number of cardiovascular (CV) risk factors such as hypertension, obesity, and diabetes, and metabolic syndrome (Dirinck et al., 2010; Kreiss et al., 1981; Sergeev and Carpenter, 2010; Uemura et al., 2009). Urinary levels of BPA were also recently found to be associated with CHD in the NHANES sample (Lang et al., 2008; Melzer et al., 2010). There are also a recent study suggesting that exposure to BPA and phthalates, measured in serum, is associated with atherosclerosis (Lind and Lind, 2011). The Framingham Risk Score (FRS) is the most commonly used scoring system aiming at predicting the risk of cardiovascular disease in an individual within a certain time period in research and clinical practice. FRS is a scoring system that uses age, gender, smoking history, blood pressure, HDL-cholesterol, LDL-cholesterol, and blood glucose levels to estimate coronary event risk over the course of ten years among individuals without previously diagnosed CHD (Wilson et al., 1998). The aim of this cross-sectional study was to investigate whether there is a relationship between circulating levels of BPA and/or four common phthalate metabolites and FRS and/or for the CV risk factors included in the score. For these aims, we used the population-based Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study (Lind et al., 2005) in which we have data on CV risk factors and circulating levels of BPA and four different phthalate metabolites in over 1000 subjects (Olsen et al., 2012). 2. Material and methods 2.1. Subjects All subjects eligible to the study were living in the community of Uppsala, Sweden and were 70 years old. The subjects were randomly chosen from the register of community residents. A total of 1,016 subjects participated, giving a participation rate of 50.1 percent. The study was approved by the Ethics Committee of the University of Uppsala. 2.2. Basic Investigation All subjects were investigated in the morning after an overnight fast. No medication or smoking was allowed after midnight. An arterial cannula was inserted in the brachial artery for blood sampling. The participants were asked to answer a questionnaire about their medical history, smoking habits, and regular medication. Blood pressure was measured by a calibrated mercury sphygmomanometer in the non-cannulated arm to the nearest mmHg after at least 30 min of rest, whereupon the average of three recordings was used. Lipid variables and fasting blood glucose were measured by standard laboratory techniques (Carlsson et al., 2010). From these data, the FRS was calculated (Wilson et al., 1998). Basic characteristics are given in Table 1. Approximately 10 percent of the cohort reported a history of coronary heart disease, 4 percent reported stroke and 9 percent diabetes mellitus. Almost half the cohort reported any CV medication (45 percent), with antihypertensive medication being the most prevalent (32 percent). Fifteen percent reported use of statins, while insulin and oral antiglycemic drugs were reported in 2 and 6 percent, respectively (Lind et al., 2005). 2.3. Chemical analyses Human serum were analyzed for the levels of Bisphenol A (BPA) and ten phthalate metabolites at ALS Environmental Canada, Serum samples (0,5 ml) was analyzed for levels of BPA and ten phthalate metabolites using isotope liquid

Table 1 Baseline characteristics in the investigated sample. Values are given in means and (standard deviation, SD). n

1016

Females (percent) Height (cm) Weight (kg) Waist circumference (cm) BMI (kg/m2) Waist/hip ratio SBP (mmHg) DBP (mmHg) Serum cholesterol (mmol/L) LDL-cholesterol (mmol/L) HDL-cholesterol (mmol/L) Serum triglycerides (mmol/L) Fasting blood glucose (mmol/L) Antihypertensive treatment (percent) Statin use (percent) Current smoking (percent)

50.2 169 (9.1) 77 (14) 91 (12) 27.0 (4.3) 0.90 (0.075) 150 (23) 79 (10) 5.4 (1.0) 3.3 (0.88) 1.5 (0.42) 1.3 (0.60) 5.3 (1.6) 31.5 14.7 11

chromatograph/tandem mass spectrometer (API4000LC-MS/MS), following the general procedures presented by the Centers for Disease Control and Prevention as previously described more in detail (Olsen et al., 2012). Briefly quality control of the analysis was maintained by analyzing a method blank (calf serum) and two spiked calf serum samples (20 ng/mL, all analytes) along with every17 samples. The detection limits (LOD), was 0.2 ng/mL. Four out of the ten phthalate metabolites, namely mono-(2-ethylhexyl) phthalate (MEHP); mono-ethyl phthalate (MEP); mono-isobutyl phthalate (MiBP); and mono-methyl phthalate (MMP), were detectable in all, but 5–12 subjects (at least 96 percent of subjects). The fact that some subjects showed undetectable levels rules out a general contamination of these compounds. Only the four metabolites with detectable levels were used in the statistical analysis. For the rest of the metabolites, 31–100 percent of the observations were below the detection limit.

2.4. Statistics Since all compounds were skewed, the variables were log-transformed to achieve normal distributions. Relationships between BPA and phthalate metabolites and continuous risk factors were evaluated by linear multiple regression models. Gender, BMI, serum cholesterol and triglycerides, hypertension, smoking and diabetes mellitus were used as confounders in the analysis, except for the confounding variable being analyzed as the outcome it the respective regression model. Thus, if fasting glucose was the dependent variable, all confounding variables except diabetes were included in the model, etc.. Interactions between the BPA and phthalate metabolites and gender regarding risk factors were evaluated by introducing an interaction term (BPA and phthalate metabolites x gender) in the models. Logistic regression was used when the effects of smoking on levels of BPA and phthalate metabolites were evaluated, adjusting for confounders as described above. The independency of the compounds in their relation to the Framingham Risk Score was evaluated by adding all of the BPA and phthalate metabolites as independent variables together with gender in a multiple linear regression model. Finally, to check for possible non-linear relationships, multivariable fractional polynomial models were used that evaluate whether the powers of -2, -1, 0.5, 2 or 3 fit the regression model better than the linear term (power 1) for each variable in the model. The statistical program package STATA 11 (College Station, TX, USA) was used.

3. Results Mean values or proportions of the established risk factors are shown in Table 1. 3.1. BPA and phthalate metabolites and CV risk factors Of the investigated compounds, BPA, MEHP, and MMP were associated to LDL-cholesterol; for HDL-cholesterol, only BPA and MEHP were associated (p o0.05, Table 2). There were also associations for MEP to blood pressure, for MiBP vs fasting glucose, and for MMP vs BMI and smoking when the compounds were investigated one by one (Table 2). After Bonferroni

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Table 2 Relationships between circulating levels of BPA and the detected phthalate metabolites MEHP, MEP, MIBP, and MMP in serum and the different cardiovascular risk factors included in the Framingham Risk Score. For each metal and risk factor, the regression coefficient, (95 percent Confidence Interval, CI) and [p-value] are presented except for smoking, where the Odds Ratio (95 percent CI) and [p-value] are presented. Gender, BMI, serum cholesterol and triglycerides, hypertension, smoking and diabetes mellitus were used as confounders in the analysis, except for the confounding variable being analyzed as the outcome it the respective regression model. Thus, if fasting glucose was the dependent variable, all confounding variables except diabetes were included in the model, etc. BPA

MEHP

MEP

MiBP

MMP

LDL-cholesterol

0.074 (0.02;0.13) [0.02]

 0.052 (  0.09;  0.01) [0.008]

0.062 (  0.01;0.14) [0.11]

0.044 ( 0.01;0.09) [0.07]

0.098 (0.05;0.14) [0.0001]

HDL-cholesterol

0.030 (0.01;0.06) [0.02]

 0.014 (  0.03;0.01) [0.10]

 0.007 (  0.03;0.04) [0.68]

0.017 ( 0.01;0.04) [0.11]

0.023 (  0.01;0.04) [0.03]

Triglycerides

 0.005 ( 0.03;0.02) [0.71]

 0.003 (  0.02;0.02) [0.77]

 0.002 (  0.03;0.04) [0.90]

 0.009 ( 0.03;0.01) [0.45]

 0.006 (  0.03;0.02) [0.638]

BMI

0.085 ( 0.19;0.36) [0.54]

0.001 (  0.18;0.18) [0.98]

0.197 (  0.17;0.56) [0.29]

0.094 ( 0.13;0.32) [0.41]

0.246 (0.02;0.47) [0.03]

SBP

 0.70 ( 2.17;0.77) [0.35]

0.25 (  0.74;1.24) [0.62]

 2.35 (  4.31; 0.40) [0.02]

 0.05 ( 1.28;1.18) [0.93]

 0.30 (  1.51;0.92) [0.63]

DBP

 0.09

0.09

 1.79

0.35

0.16

( 0.75;0.57) [0.79]

(  0.36;0.53) [0.71]

(  2.56;  0.82) [0.002]

( 0.20;0.90) [0.21]

(  0.39;0.70) [0.57]

Glucose

0.005 ( 0.01;0.01) [0.50]

0.001 (  0.01;0.01) [0.97]

0.007 (  0.01;0.03) [0.44]

0.024 (0.01;0.04) [0.0001]

0.01 (  0.01;0.02) [0.09]

Smoking

0.96 (0.78;1.20) [0.75]

0.92 (0.79;1.07) [0.28]

0.84 (0.62;1.13) [0.25]

1.03 (0.87;1.23) [0.70]

1.22 (1.01;1.46) [0.03]

MEHP¼mono-2-ethylhexyl phthalate; MEP ¼mono-ethyl phthalate; MiBP¼ mono-isobutyl phthalate; MMP¼ mono-methyl phthalate.

Table 3 Relationships between the Framingham Risk Score and circulating levels of BPA and the detected phthalate metabolites MEHP, MEP, MiBP, and MMP in serum. In the regression model, the compounds were related one by one to the Framingham Risk Score, adjusting for gender.

BPA MEHP MEP MIBP MMP

Separate analysis for each compound Regression coefficient (95 percent CI)

p-value

0.07 ( 0.15–0.29)  0.06 ( 0.20–0.09) 0.02 ( 0.27–0.32) 0.13( 0.05–0.31) 0.21 (0.03–0.38)

0.52 0.45 0.87 0.17 0.02

MEHP¼ mono-2-ethylhexyl phthalate; MEP¼mono-ethyl phthalate; MiBP¼monoisobutyl phthalate; MMP¼ mono-methyl phthalate.

correction, the critical p-value is o0.0012, which only gives significance to the relations for MMP to LDL-cholesterol. MEP was associated to DBP and MiBP to fasting glucose. For the analyses of BPA vs. triglycerides, MiBP vs. HDLcholesterol, and MEHP vs. smoking, significant gender interactions were found but when genders were analyzed separately, no significant relations (p o0.001) were found.

3.2. BPA and phthalate metabolites and the Framingham risk score Of the investigated compounds, only MMP was associated to the Framingham score (Table 3) but applying a strict Bonferroni correction results in a critical p-value of 0.01, then this relation is not significant.

No apparent significant nonlinear relationships were disclosed by applying multiple fractional polynomial regression analysis.

4. Discussion Although no strong relationships were seen between BPA or phthalates and coronary risk, assessed by the FRS, three of the phthalate metabolites were associated with coronary risk factors. 4.1. BPA and phthalate metabolites and lipids BPA, MEHP, and MMP were associated to LDL-cholesterol and MEHP to HDL-cholesterol, but when applying Bonferroni correction, only the association between MMP and LDL-cholesterol remained significance. In a study of concentrations of multiple phthalate metabolites in milk and fluids (serum, saliva, and urine) of 33 lactating North Carolina women, the urinary phthalate metabolites MEHP, mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) showed significant positive correlations with serum triglycerides. Eight of the 33 women had serum triglyceride levels defined as high for healthy adults (Hines et al., 2009). We did not however found any association between the investigated compounds and serum triglyceride levels in this elderly cohort. The disposition and protein-binding of the phthalate metabolites is complex. MEHP is bound principally to non-lipoprotein constituents in the serum, and this binding distribution is unaffected by lipid concentration, while its di-ester equivalent, diethylhexyl phthalate (DEHP), was shown to be proportionally

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dependent of the lipid concentration of the serum. As the cholesterol and triglyceride concentrations increase, the percentage of DEHP bound to VLDL, IDL, and LDL increased (Griffiths et al., 1988). 4.2. BPA and phthalate metabolites and glucose In a report from the NHANES population (Lang et al., 2008), urinary BPA levels were related to prevalent diabetes. Furthermore, urinary concentrations of phthalate metabolites have been positively correlated with obesity and insulin resistance in humans in data analyses from NHANES (Hatch et al., 2008; Stahlhut et al., 2007). Hatch et al. noted however that the observed associations among 60–80-year-olds differed from the other age groups. In the elderly in general, BMI and waist circumference declined with increasing levels of phthalate metabolites. It is possible that a physiological change in older people is related to both weight loss and altered phthalate metabolism. Fasting serum glucose levels increased with higher concentrations of urinary and/or serum phthalate metabolites (MECPP, MEHP, MEHHP, MEOHP) also in lactating women (Hines et al., 2009). However, in the present study, it was only MiBP that was associated with fasting glucose levels. Phthalates are known to affect PPARs (Bility et al., 2004; Hurst and Waxman, 2003; Lampen et al., 2003; Maloney and Waxman, 1999)., and since PPAR gamma agonists are known to improve glucose control, this is a likely mechanism whereby phthalates are linked to fasting glucose levels. 4.3. BPA and phthalate metabolites and smoking

Stahlhut et al., 2007) could be demonstrated in prospective studies in a uniform manner, the future use of these compounds is questionable. 4.6. Limitations of the study The present sample is limited to Caucasians aged 70. So, caution should be made in drawing conclusions about other ethnic and age groups. Furthermore, the present study had a moderate participation rate, although an analysis of non-participants showed the present sample to be fairly representative of the total population regarding most cardiovascular disorders and drug intake.

5. Conclusion Associations were found between MMP and LDL-cholesterol, MEP and diastolic blood pressure, and MiBP and fasting glucose, although we did not observe any strong associations between BPA or any of the four phthalate metabolites and coronary risk in this elderly population.

Conflict of interest statement None of the authors of this paper has a financial or personal relationship with other people or organizations that could inappropriately influence or bias the content of the paper.

In a study of 425 men, current smokers had higher median concentrations of MEP but lower concentrations of MEHHP and MEOHP compared with never smokers (Frederiksen et al., 2007). No differences were seen regarding MEP and MEHP, which were also investigated in that study. This result is in line with the results in the present study, where a significant gender interaction was found for MEHP vs. smoking, but when men and women were analyzed separately, no significant relations were found.

Acknowledgments

4.4. BPA and phthalate metabolites and heart disease

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Although we could not show any clear associations between FRS and BPA or the four phthalate metabolites, there are studies suggesting a relation to various heart conditions. An epidemiological study of NHANES data, for instance, showed that urinary BPA concentrations were associated with a history of CV disease (Lang et al., 2008). In the present study, MEP was inversely associated to DBP, and it is known that a low pulse pressure (determined by the difference between SBP and DBP) in the elderly could be hazardous if DBP decreases. MMP was associated with FRS if not applying a strict Bonferroni correction. Our research group recently found that MMP was associated to atherosclerotic plaques independently of CV risk factors (Lind and Lind, 2011). The phthalates and BPA were also related to the echogenicity of the plaques, suggesting that these compounds could play a role in atherosclerosis development. 4.5. Clinical implications BPA and phthalates are high volume chemicals and as could be seen in the present sample (Olsen), detectable levels are found in almost all subjects. This, given that effects on important CV risk factors and overt CV disease, as found in cross-sectional studies like the present study and in others (Hatch et al., 2008; Lang et al., 2008;

The work was supported by funds from the Swedish Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) and the Swedish Research Council (VR). References

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