Positive associations of serum perfluoroalkyl substances with uric acid and hyperuricemia in children from Taiwan

Environmental Pollution 212 (2016) 1e6

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Positive associations of serum perfluoroalkyl substances with uric acid and hyperuricemia in children from Taiwan* Xiao-Di Qin a, Zhengmin Qian b, Michael G. Vaughn c, Jin Huang c, Patrick Ward b, Xiao-Wen Zeng a, Yang Zhou a, Yu Zhu a, Ping Yuan a, Meng Li a, Zhipeng Bai d, Gunther Paul e, Yuan-Tao Hao f, Wen Chen a, Pau-Chung Chen g, h, Guang-Hui Dong a, *, Yungling Leo Lee h, i, ** a

Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yatsen University, Guangzhou 510080, China b Department of Epidemiology, College for Public Health and Social Justice, Saint Louis University, Saint Louis 63104, USA c School of Social Work, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO 63104, USA d State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China e Faculty of Health, School of Public Health and Social Work, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia f Department of Epidemiology and Biostatistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China g Institute of Occupational Medicine and Industrial Hygiene and Department of Public Health, National Taiwan University College of Public Health, Taipei, Taiwan, ROC h Department of Environmental and Occupational Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan, ROC i Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100, Taiwan, ROC

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 January 2016 Received in revised form 24 February 2016 Accepted 24 February 2016 Available online xxx

To investigate the risk of hyperuricemia in relation to Perfluoroalkyl substances (PFASs) in children from Taiwan, 225 Taiwanese children aged 12e15 years were recruited from 2009 to 2010. Linear and logistic regression models were employed to examine the influence of PFASs on serum uric acid levels. Findings revealed that eight of ten PFASs analyses were detected in >94% of the participants' serum samples. Multivariate linear regression models revealed that perfluorooctanic acid (PFOA) was positively associated with serum uric acid levels (b ¼ 0.1463, p < 0.05). Of all the PFASs analyses, only PFOA showed a significant effect on elevated levels of hyperuricemia (aOR ¼ 2.16, 95%CI: 1.29e3.61). When stratified by gender, the association between serum PFOA and uric acid levels was only evident among boys (aOR ¼ 2.76, 95%CI: 1.37e5.56). In conclusion, PFOA was found to be associated with elevated serum levels of uric acid in Taiwanese children, especially boys. Further research is needed to elucidate these links. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Perfluoroalkyl substances Uric acid Hyperuricemia Children

1. Introduction Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are a diverse class of chemicals that possess unique properties such as extremely high thermal and chemical stability and are widely used

in various manufacturing and industrial processes, such as firefighting foams, paints, semiconductors, photographic films, and pesticide formulations (Rahman et al., 2014). Because of their chemical stability and widespread use, a growing number of studies have found that PFASs are ubiquitous and persistent in both

Abbreviations: PFASs, polyfluoroalkyl substances; PFBS, perfluorobutane sulfonate; PFHxS, perfluorohexane sulfonate; PFOS, perfluorooctane sulfonate; PFHxA, perfluorohexane acid; PFHpA, perfluoroheptanoic acid; PFNA, perfluorononanoic acid; PFOA, perfluorooctanic acid; PFDA, perfluorodecanoic acid; PFDoA, perfluorododecanoic acid; PFTA, perfluorotetradecanoic acid; GBCA, Genetic and Biomarkers study for Childhood Asthma; IQR, interquartile range; ORs, odds ratio; 95%CI, 95% confidence intervals. * This paper has been recommended for acceptance by Eddy Y. Zeng. * Corresponding author. Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou 510080, PR China. ** Corresponding author. Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, No.17 Xuzhou Road, Taipei 100, Taiwan, ROC. E-mail addresses: [email protected], [email protected] (G.-H. Dong), [email protected] (Y.L. Lee). http://dx.doi.org/10.1016/j.envpol.2016.02.050 0269-7491/© 2016 Elsevier Ltd. All rights reserved.

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biotic samples and the abiotic environment worldwide, for example, lakes (Cao et al., 2015), sea sediments (Zhu et al., 2014) and even in the world's southernmost marine mammal, the Weddell seal (Routti et al., 2015). In addition, human exposure to PFASs is well demonstrated, as these compounds have been found in blood samples from both children and adults (Fromme et al., 2007; Schecter et al., 2012; Zhou et al., 2014). In recent years, semiconductor, electrochemical, and optoelectronic industries have quickly grown in northern Taiwanese cities. This has resulted in high levels of PFOS and PFOA contamination in several river systems in Taiwan (PFOS up to 5440 ng/L; PFOA up to 310 ng/L) (Chimeddulam and Wu, 2013). As such, this situation may pose a potential health risk to children living near these rivers. Some recent studies have already found adverse associations for PFASs on children (Frisbee et al., 2010; Vuong et al., 2016; Wang et al., 2015). For example, Frisbee et al. (2010) found a significant positive association between PFOA and PFOS exposure and dyslipidemia in children. Wang et al. (2015) reported that prenatal PFASs concentrations were inversely associated with children's intelligence quotient (IQ); also, another recent study from the United States found that PFASs exposure may be associated with executive function deficits in school-age children (Vuong et al., 2016). One adverse health outcome of PFASs that has recently attracted attention is serum uric acid. Uric acid, which has both oxidant and antioxidant properties, is the final metabolic product of purine metabolism in humans (So and Thorens, 2010). Elevated serum uric acid levels and hyperuricemia have been documented to be an independent precursor of kidney disease, including chronic kidney disease (Johnson et al., 2013; Miyaoka et al., 2014; Prasad and Qing, 2015). In addition, it is also associated with cardiovascular disease and hypertension in both children and adults (Feig et al., 2008; Heinig and Johnson, 2006; Mellen et al., 2006). Because of these considerations, it may be critically important to identify novel risk factors. Some of these novel risk factors could include environmental factors like PFASs that may be associated with elevated serum uric acid levels in children. Studies sampled from adult populations demonstrating high PFASs levels have revealed a positive relationship between exposure to this class of chemicals and elevated serum uric acid levels. Two of these studies was comprised of occupational cohorts of workers from PFASs -handling chemical plants (Costa et al., 2009; Sakr et al., 2007), while another was derived from a communitybased study of citizens residing near the Ohio River valley that was heavily exposed to PFOA in drinking water from a nearby chemical plant (Steenland et al., 2010). Recently, two other studies that analyzed data from the National Health and Nutrition Examination Survey (Gleason et al., 2015; Shankar et al., 2011) also found evidence of a link between PFASs and uric acid. However, it should be mentioned that Lin et al. (2013) did not find an association between PFOS and serum uric acid. To the best of our knowledge, there has only been one study that has focused on examining associations between serum concentrations of PFASs and serum uric acid levels in children, which studied participants from the NHANES (Geiger et al., 2013). The objective of this study is to build on previous work among adults and assess the link between serum levels of PFASs and uric acid by using data from a well-executed community-based biomarker study of 225 healthy children (12e15 years of age) in Taiwan (Tsai et al., 2010). 2. Material and methods 2.1. Study participants Study participants consisted of the entire control sample of the

Genetics and Biomarkers study for Childhood Asthma (GBCA) in Taiwan. This sample was composed of a total of 225 healthy children (the response rate was 72% among those contacted by phone) selected from seven public schools in the Taipei area from 2009 to 2010 (Bao et al., 2014). The sample consisted of 102 boys and 124 girls who ranged in age from 12 to 15 years. A survey was used to acquire information regarding demographic variables and environmental exposures. The questionnaires were responded to by parents or guardians of participants. All children and their parents provided written informed consent. The study protocol was approved by the Institutional Review Board of the Institutional Review Board (National Taiwan University Hospital Research Ethics Committee). 2.2. Serum uric acid determination The primary outcome of interest for this study was serum uric acid levels. Serum was divided from red blood cells, transported in tubes, and chilled prior to being shipped to an analytical laboratory. We measured uric acid in serum via the enzymatic uricase method (Geiger et al., 2013). Uricase oxidizes uric acid to allantoin and hydrogen peroxide. When in the presence of peroxidase, 3, 5Dichloro-2-hydroxybenzene sulfonate coupled with 4aminoantipyrine and hydrogen peroxide forms a compound that can be measured at 520 nm by its color (Geiger et al., 2013). The intensity of color is proportional to the uric acid concentration. 2.3. Serum PFASs measurement Serum PFASs measurement has been described in recent publications (Zeng et al., 2015). Details regarding the analytical procedures capable of measuring ten PFASs analyses, consisting of perfluorobutane sulfonate (PFBS), perflurohexane sulfonate (PFHxS), PFOS, perfluorohexane acid (PFHxA), perfluoroheptanoic acid (PFHpA), perfluorononanoic acid (PFNA), PFOA, perfluorodecanoic acid (PFDA), perfluorododecanoic acid (PFDoA), and perfluorotetradecanoic acid (PFTA) in serum samples has been previously published (Bao et al., 2011). 2.4. Statistical analysis Statistical analyses were performed using SPSS 18.0 J software (SPSS Inc. Chicago, IL, USA). Data were tested for normality (ShapiroeWilks W test) and homogeneity (Bartlett's test for unequal variances) and all PFAS levels were natural log transformed to correct skewed distributions. Continuous variables with normality and homogeneity were given as the mean ± SD, otherwise, as median [Quartile 1(Q1)-Quartile 3(Q3)]. We performed linear regression analyses with uric acid as the outcome variable. Uric acid was treated as a continuous variable in a separate linear regression model with each single PFASs exposure variable. Except for the coefficients of total population, we analyzed the coefficients stratified by gender. Covariates including age, gender, body mass index (BMI), regular exercise (yes/no, defined as yes if the participant has exercised at least 1 h per day in the past year excluding physical education in the school, and no if vice versa), parental education (less than high school, more than high school), and environmental tobacco smoke exposure (ETS, the information was collected from the current and past household smoking status of each participant's adult household members and regular household visitors) were chosen by a priori whether their established relation to uric acid (independent of whether they are associated with PFASs), and all covariates were statistically significant predictors of uric acid, in the predicted direction. In addition to linear regression, a logistic regression model was

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used to calculate the odds ratios and 95% confidence intervals for the association between each quartile of PFASs exposure levels with a “high” level of uric acid (defined as6 mg/dL), with quartile 1 used as the referent category. We also calculated the odds ratios and 95% confidence intervals for boys and girls. Multiple general linear models were used to estimate associations with uric acid levels in PFASs quartiles, with the lowest PFOA quartile as a reference group and adjusted for identified covariates. We modeled an ordinal variable assigned to the median value for each corresponding quartile to estimate p-values for any detected trends. A p-value of <0.05 was considered statistically significant. 3. Results Detailed information about the study sample is shown in Table 1 (n ¼ 225). The mean age was 13.6 years (±0.7), and participation was similar across both genders. The frequency of detection of PFBS, PFHxS, PFOS, PFOA, PFNA, and PFDA were more than 96%, but the other three compounds PFHxA, PFHpA, and PFTA were lower than 20%. As a result, they are not considered in the following discussion. Serum PFOS level was significantly higher than the other PFASs, with medians of 28.8 ng/ml in boys and medians of 29.9 ng/ml in girls, respectively (Table 1). Consistent with established definitions identified in prior research, high uric acid levels in children were defined as serum levels 6 mg/dL (Asayama et al., 2003; Ford et al., 2007). The proportion of high levels in boys was significantly higher than in girls (20.6% versus 9.8%, p ¼ 0.022). Table 2 presents the association between serum uric acid measure (mg/dL) and ln-PFASs (mg/L). We observed a significant association between PFOA and uric acid (b ¼ 0.1463, p ¼ 0.032). When the results were stratified by gender, however, a stronger association was found for boys between PFOA and uric acid (b ¼ 0.2359, p ¼ 0.011), while there was no significant association for girls (b ¼ 0.0142, p ¼ 0.8917). When the lowest PFAS quartile was used as a reference group, serum uric acid levels appeared to be related to the serum levels of PFOA in boys, but not in girls (Fig. 1). Boys in the

Table 1 Characteristics of Taiwanese school children in the study population. Characteristic

Total (n ¼ 225)

Boys (n ¼ 102)

Girls (n ¼ 123)

Age(years) Height(cm) Weight(kg) BMI(kg/m2) Regular exercisea No Yes Parental educationa
13.6 ± 0.7 159.8 ± 7.0 52.5 ± 13.2 20.4 ± 4.1

13.6 ± 0.7 163.1 ± 7.2 55.9 ± 15.4 20.8 ± 4.7

13.6 ± 0.8 157.1 ± 5.5 49.6 ± 10.3 20.0 ± 3.6

53(23.6) 172(76.4)

17(16.7) 85(83.3)

36(29.3) 87(70.7)

86(38.2) 139(61.8)

42(41.2) 60(58.8)

44(35.8) 79(64.2)

93(41.3) 132(58.7) 28.9(14.1e43.0) 0.5(0.4e1.3) 0.5(0.4e0.5) 0.9(0.8e1.2) 2.7(0.8e6.0) 0.2(0.1e0.3) 1.3(0.6e2.8) 0.8(0.6e1.1) 5.0(0.3e23.3) 4.9 ± 0.9 192(85.3) 33(14.7)

42(41.2) 60(58.8) 29.9(13.0e43.8) 0.5(0.4e1.4) 0.5(0.4e0.5) 0.9(0.8e1.1) 2.4(0.7e5.9) 0.2(0.1e0.3) 1.4(0.7e2.6) 0.8(0.6e1.0) 6.0(0.6e25.9) 5.1 ± 0.9 81(79.4) 21(20.6)

51(41.5) 72(58.5) 28.8(14.8e42.6) 0.5(0.4e1.2) 0.5(0.4e0.5) 1.0(0.8e1.2) 3.1(0.9e6.2) 0.2(0.1e0.3) 1.2(0.5e3.0) 0.9(0.6e1.1) 4.5(0.3e18.4) 4.7 ± 0.8 111(90.2) 12(9.8)

Values are mean ± SD (median). a Values are presented as number (%). b Values are presented as median (Q1 ~ Q3).

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highest PFOA quartile had mean uric acid levels of 5.65 mg/dL (95% CI: 5.33e5.96), compared with 4.85 mg/dL (95% CI: 4.53e5.17) in the lowest quartile (P for trend ¼ 0.033). Girls in the highest PFOA quartile had mean uric acid levels of 4.73 mg/dL (95% CI: 4.41e5.06), compared with 4.64 mg/dL (95% CI: 4.43e4.94) in the lowest quartile (P for trend ¼ 0.756). Table 3 displays the association between increasing serum levels of PFASs and the presence of hyperuricemia by using a logistic regression model, and includes both an unadjusted and adjusted model. Of all the PFASs, only PFOA showed a strong effect on hyperuricemia in both models (aOR ¼ 2.16, 95%CI: 1.29e3.61). When data was stratified by gender, the effect of PFASs was only found in boys. For example, in the unadjusted model, PFOA (OR ¼ 2.23, 95% CI: 1.35e3.69), and PFHxS (OR ¼ 1.65, 95%CI: 1.10e2.69) all showed a positive association with hyperuricemia in boys. After covariate adjustment, however, only PFOA (aOR ¼ 2.76, 95%CI: 1.37e5.56) remained significant. There was no significant association found among girls. 4. Discussion In the present investigation, we found a positive association between serum levels of PFASs and uric acid, with the relationship exhibiting a stronger effect among boys. Findings suggest that PFASs might be an important factor for the elevation of serum uric acid. In addition to PFOA, some other PFASs such as PFHxS was also associated with serum uric acid levels in our study, and these associations were more apparent among boys. Several relevant epidemiological studies have already examined the impact of PFASs exposure on serum uric acid levels in adults (Kataria et al., 2015; Shankar et al., 2011; Steenland et al., 2010). Steenland et al. (2010) conducted a cross-sectional study of PFOA and PFOS and uric acid among 54,951 adult community residents  20 years of age in Ohio and West Virginia of the United States, and found that an increase of 0.2e0.3 mg/dL uric acid was associated with an increase from the lowest to highest decile of either PFOA or PFOS. Hyperuricemia risk increased modestly with increasing PFOA; the odds ratios by quintile of PFOA were 1.00, 1.33 (95% CI, 1.24e1.43), 1.35 (95% CI, 1.26e1.45), 1.47 (95% CI, 1.37e1.58), and 1.47 (95% CI, 1.37e1.58; test for trend, p < 0.0001). Results from the National Health and Nutritional Examination Surveys of the US showed an increase of 0.12e0.56 mg/dL uric acid was associated with an increase from the lowest to highest decile of either PFOA or PFOS in 3883 US adults with mean age of 46.4 years old (SD ¼ 0.5 years). Recently, another survey was conducted in US populations aged 12e19 years and also reported that highest PFOA and PFOS quartiles were also associated with 0.21 mg/dL (95% CI: 0.056 to 0.37) and 0.19 mg/dL (95% CI: 0.032 to 0.34) increases in uric acid, respectively (Kataria et al., 2015). Compared to other studies that have reported the association between PFASs and uric acid, the serum PFOS concentration was higher, but the PFOA and PFHxS level was lower. Consistent with most studies we have found that the effects of PFOS on uric acid was weaker than PFOA, and this may indicate that PFOA is a more important predictor of PFASs. Gleason et al. (2015) determined that PFOA and uric acid have a strong linear relationship (p < 0.001). In the same study, an increasing measure of effect as quartiles of PFOA increase [(Q2: OR ¼ 1.46, 95% CI 1.16e1.85), (Q3: OR ¼ 1.74, 95% CI 1.35e2.25), and (Q4: OR ¼ 1.88, 95% CI 1.37e2.58)], along with a statistically significant trend (p < 0.001) was also found. Though the participants in their study were 12 years of age or older, they did not examine the effect of PFASs on children separately from other age groups. To the best of our knowledge, there is only one study reporting the effects of PFASs on elevated uric acid levels in children. Geiger et al. (2013) found that, after controlling for potential confounders, serum

0.0105 0.0142 0.1387 0.1830 0.0305 0.1182 0.0938 0.1865 0.0098 0.01357 0.0204 0.1478 0.1267 0.0376 0.0436 0.0795 0.1859 0.0025 Coefficient (b) represents the mean change in serum uric acid levels for each 1 ln-(ug/L) increase in PFASs concentration. a Models are adjusted for age, gender, BMI, parental education level, exercise, EST exposure, and serum creatinine. b Models are adjusted for age, BMI, parental education level, exercise, EST exposure, and serum creatinine. c p value <0.05.

PFOS PFOA PFBS PFDA PFDOA PFHxA PFHxS PFNA PFTA

0.0315 (0.0475e0.1104) 0.1454 (0.0339e0.2569) 0.0064 (0.2205e0.2333) 0.0624 (0.1317e0.2564) 0.0199 (0.0906e0.0508) 0.0732 (0.0723e0.2187) 0.1492c (0.0332e0.2652) 0.1004 (0.3868e0.1860) 0.0021 (0.0497e0.0540)

0.0497 (0.0295e0.1289) 0.1463c (0.0126e0.2801) 0.0045 (0.2191e0.2280) 0.0834 (0.1127e0.2796) 0.0255 (0.0986e0.0475) 0.0107 (0.1367e0.1581) 0.1372c (0.0152e0.2593) 0.0691 (0.3893e0.2510) 0.0086 (0.0594e0.0422)

0.0771 (0.0206e0.1748) 0.2581 (0.1056e0.4107) 0.1704 (0.1718e0.5126) 0.0389 (0.2448e0.3227) 0.0080 (0.1020e0.1179) 0.2076c (0.0008e0.4143) 0.2100c (0.0442e0.3957) 0.1071 (0.3617e0.5759) 0.0087 (0.0878e0.0705)

0.0525 (0.0442e0.1491) 0.2359c (0.0560e0.4157) 0.1687 (0.1684e0.5058) 0.0539 (0.2345e0.3423) 0.0043 (0.1170e0.1084) 0.1606 (0.0636e0.3849) 0.1651 (0.0352e0.3653) 0.1019 (0.4538e0.6577) 0.0146 (0.0923e0.0630)

(0.1457e0.1186) (0.1332e0.1740) (0.4369e0.1412) (0.1298e0.3832) (0.1261e0.0508) (0.2384e0.1512) (0.0684e0.2274) (0.5315e0.1598) (0.0687e0.0637)

Adjustedb (95% CI) Unadjusted (95% CI) Adjustedb (95% CI) Boys, coefficient

Unadjusted (95% CI) Adjusteda (95% CI) Unadjusted (95% CI)

Total population, coefficient PFASs

Table 2 The association between serum uric acid measure (mg/dL) and ln-PFASs (mg/L) levels by using multivariate linear regression analysis.

(0.1436e0.1646) (0.1919e0.2203) (0.4404e0.1631) (0.0943e0.4602) (0.1280e0.0669) (0.3156e0.0792) (0.0610e0.2485) (0.5766e0.2035) (0.0586e0.0781)

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Girls, coefficient

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levels of PFOA and PFOS were positively associated with hyperuricemia among 1919 children aged between 12 and 18 years. Participants in quartile 4 had multivariable-adjusted odds ratios for hyperuricemia of 1.62 (95% CI: 1.10e2.37) for PFOA and 1.65 (95% CI: 1.10e2.49) for PFOS when compared to participants in quartile 1. While we did not find a relationship between PFOS and uric acid, the differing age range of participants in these two studies may be the reason for the different findings in this study and Geiger et al. (2013). The underlying mechanism that links PFASs and uric acid is unresolved. Purines are finally metabolized as a 2,6,8-three oxygen purine (known as uric acid) in the liver, and uric acid is then dissolved in the blood and passed through the kidneys into the urine where it is eliminated. If there is an increase in the production of uric acid or if the kidneys do not eliminate enough uric acid from the body, it can build up in the blood (Hediger et al., 2005). Despite the fact that the biological mechanism underlying the effects of PFASs on serum uric acid is unclear, research has demonstrated that PFOA exposure could be associated with oxidative stress in the liver (Huang et al., 2013; Yao and Zhong, 2005). In turn, it is possible that oxidative stress may be associated with elevated uric acid levels (Nieto et al., 2000; Patterson et al., 2003). Another putative mechanism is that PFASs and uric acid may be indirectly associated. Organic anion transporters 1 and 3 (OAT 1and 3) are involved in uric acid excretion in the kidneys (Emami Riedmaier et al., 2012), and studies have found that OAT1 and OAT3 have a high affinity for PFOA (Nakagawa et al., 2008). Thus, it is possible that with an increase in serum PFOA level, PFOA and uric acid might competitively bind OAT1 and 3, resulting in a decrease in excretion of uric acid. This may finally result in an indirect increase in serum uric acid levels (Steenland et al., 2010). Moreover, Watkins et al. (2013) found a positive association between PFOA and reduced kidney function (indicated by GFR), meaning PFOA may influence the uric acid level by reducing kidney function. Increased investigational attention into these mechanisms appears warranted in order to clarify the biological mechanisms underlying our observations. With respect to our findings on gender, Steenland et al. (2010) reported that the linear exposure-response relationship was more consistent for females rather than for males. Shankar et al. (2011) also observed similar results. Our study has also revealed that the association between PFASs and serum uric acid levels appears to differ between boys and girls, as the relationship between PFASs exposure and serum uric acid levels was evident only for boys, and the differing findings between our study and theirs may be due to the different study populations. Evidence has shown that the association of race with environmental risk factors is different, even with regards to exposure to the same environmental pollutant (Stevenson et al., 2007). For example, Aminov et al. (2014) assessed the racial differences in effects of exposure to persistent organic pollutants (35 polychlorinated biphenyl congers and nine organochlorine pesticides) on lipid levels in Caucasian and African American residents of Anniston, and found that the associations between total pesticides and serum lipids were much stronger in African Americans compared to Caucasians. The mechanisms underlying the gender difference in PFASs exposure is unclear. Some potential explanations have been proposed. One possibility may be related to sex steroids (including androgens such as testosterone, estrogens, and progestins), as multiple studies have reported that sex steroids seem to differentially affect the expression of OAT1 and OAT3 mRNA (Sabolic et al., 2007). Breljak et al. (2013) provided evidence that the expression of renal OAT3 and OAT1 mRNA are sex-dependent in C57Bl/6 mice, and OAT3 mRNA is female dominant due to androgen inhibition while OAT1 mRNA is male dominant due to androgen stimulation. Buist and Klaassen (2004), however, identified species differences in OATs and pointed out

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Fig. 1. Differences in serum uric acid levels, with increasing quartile of PFOA exposure in boys and girls. Multiple general linear model analysis was performed to estimate the association with uric acid levels in PFOA quartiles, with the lowest PFAS quartile used as a reference group. The data are expressed as estimated mean and 95% CI adjusted for age, BMI, parental education level, exercise and EST exposure, p-values for trend are presented.

Table 3 OR and 95% CI of Serum PFASs Levels and High Uric Acid Level (6 mg/dL). PFASs

PFOS PFOA PFBS PFDA PFDOA PFHxA PFHxS PFNA PFTA

Total

Boys

Girls

Unadjusted-OR (95%CI)

Adjusted-ORa (95%CI)

Unadjusted-OR (95%CI)

Adjusted-ORb (95%CI)

Unadjusted-OR (95%CI)

Adjusted-ORb (95%CI)

1.31 (0.94e1.83) 1.74c (1.21e2.50) 1.24 (0.88e1.72) 1.07 (0.77e1.49) 0.96 (0.69e1.34) 1.21 (0.87e1.69) 1.39 (0.99e1.95) 1.14 (0.82e1.59) 1.05 (0.75e1.45)

1.35 (0.95e1.93) 2.16c (1.29e3.61) 1.23 (0.86e1.75) 1.26 (0.82e1.92) 0.93 (0.65e1.34) 1.08 (0.77e1.61) 1.39 (0.93e2.07) 1.28 (0.83e1.96) 0.97 (0.69e1.36)

1.35 (0.88e2.07) 2.23c (1.35e3.69) 1.47 (0.92e2.40) 1.05 (0.68e1.63) 1.06 (0.69e1.62) 1.61c (1.04e2.51) 1.65c (1.01e2.69) 1.22 (0.78e1.92) 1.06 (0.70e1.61)

1.40 (0.88e2.21) 2.76c (1.37e5.56) 1.53 (0.92e2.54) 0.97 (0.55e1.71) 0.99 (0.63e1.58) 1.63 (0.98e2.72) 1.49 (0.84e2.64) 1.18 (0.67e2.08) 1.02 (0.67e1.58)

1.26 1.19 1.01 1.23 0.88 0.77 1.12 1.11 0.93

1.51 1.64 0.99 1.83 0.93 0.65 1.28 1.39 0.93

(0.72e2.18) (0.68e2.07) (0.61e1.67) (0.72e2.10) (0.52e1.50) (0.44e1.35) (0.67e1.87) (0.66e1.86) (0.54e1.62)

(0.79e2.89) (0.69e3.85) (0.58e1.73) (0.90e3.71) (0.48e1.79) (0.34e1.23) (0.70e2.32) (0.68e2.87) (0.55e1.90)

OR were scaled with increasing quartiles (Q1, Q2, Q3, and Q4) of each PFASs. a Models are adjusted for age, gender, BMI, parental education level, exercise, EST exposure, and serum creatinine. b Models are adjusted for age, BMI, parental education level, exercise, EST exposure, and serum creatinine. c p value <0.05.

that these differences may have important implications in interpreting data regarding pharmacokinetics and toxicity of organic anions. Recently, studies conducted on isolated rat Leydig cells showed that PFOA had the potential to decrease testosterone levels in vitro (Zhao et al., 2010). This suggests that it is possible that PFOA alters endocrine function, disturbs the expression of OATs mRNA, and finally interferes with serum uric acid levels. In addition, Wei et al. (2008) found that the comparison of the male and female hepatic protein profiles in rare minnow (gobiocypris rarus) indicated marked gender differences in response to PFOA. Since the liver is an important organ for uric acid metabolism, gender differences in liver toxicity induced by PFOA might be another mechanism to explain the different serum uric acid levels between boys and girls in the present study. The strengths of our study include its population-based nature, availability of detailed data on confounders and standardized, high quality data collection. Several limitations in this study should be considered. First, findings cannot establish a causal relationship between PFASs and serum uric acid levels because of the nature of the cross-sectional study design. Second, other uncontrolled confounding, like dietary sources, especially the sea foods which may influence both PFAS exposure and the uric acid concentrations, can also lead to an underestimation of the true association between PFASs and serum uric acid levels. Finally, only 12 girls were defined with high serum uric acid levels, so this may undermine our ability

to examine the associations between PFASs and high serum uric acid in girls. We observed that PFOA was associated with elevated serum levels of uric acid in Taiwanese children, especially boys in this study. While these findings need to be confirmed using other better-designed studies, such as cohort studies, they may provide useful information for regulatory agencies for their mission of protecting local populations from adverse health effects of exposure to important pollution sources. Reducing or minimizing potential exposure to PFASs may be an essential step for the children, considering PFASs are ubiquitous and persistent in both biotic samples and the abiotic environment and the potential serious adverse health effects of the exposure.

5. Conclusion In summary, PFASs were positively associated with serum uric acid levels in boys. Our results contribute to the nascent research literature by suggesting that PFASs are related to serum uric acid levels in children.

Disclosure The authors report no conflicts of interest to declare.

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