Telomere length in children environmentally exposed to low-to-moderate levels of lead

YTAAP-13375; No of Pages 8 Toxicology and Applied Pharmacology xxx (2015) xxx–xxx

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Telomere length in children environmentally exposed to low-to-moderate levels of lead Natalia Pawlas a,⁎, Anna Płachetka b, Agnieszka Kozłowska a, Karin Broberg c, Sławomir Kasperczyk d a

Institute of Occupational Medicine and Environmental Health, PL 41-200 Sosnowiec, Poland Department of Animal Physiology and Ecotoxicology, University of Silesia, Bankowa str. 9, 40-007 Katowice, Poland Institute of Environmental Medicine, Unit of Metals & Health, Box 210, SE-171 77 Stockholm, Sweden d Department of Biochemistry, Medical University of Silesia, Katowice, SMDZ in Zabrze, 41-808 Zabrze, Poland b c

a r t i c l e

i n f o

Article history: Received 4 January 2015 Revised 4 May 2015 Accepted 6 May 2015 Available online xxxx Keywords: Cadmium Selenium Smoking Environment Oxidative stress Prenatal exposure

a b s t r a c t Shorter relative telomere length in peripheral blood is a risk marker for some types of cancers and cardiovascular diseases. Several environmental hazards appear to shorten telomeres, and this shortening may predispose individuals to disease. The aim of the present cross-sectional study was to assess the effect of environmental exposure to lead on relative telomere length (rTL) in children. A cohort of 99 8-year-old children was enrolled from 2007–2010. Blood lead concentrations (B-Pb) were measured by graphite furnace atomic absorption spectrometry, and blood rTL was measured by quantitative PCR. The geometric mean of B-Pb was 3.28 μg/dl (range: 0.90–14.2), and the geometric mean of rTL was 1.08 (range: 0.49–2.09). B-Pb was significantly inversely associated with rTL in the children (rS = −0.25, p = 0.013; in further analyses both log-transformed-univariate regression analysis β = − 0.13, p = 0.026, and R2adj 4%; and β = − 0.12, p = 0.056 when adjusting for mothers' smoking during pregnancy, Apgar score, mother's and father's ages at delivery, sex and mother's education, R2adj 12%, p = 0.011). The effect of lead remained significant in children without prenatal tobacco exposure (N = 87, rS = − 0.24, p = 0.024; in further analyses, β = −0.13, p = 0.029, and R2adj 4%). rTL was not affected by sex, the concentrations of other elements in the blood (i.e., cadmium and selenium concentrations), or oxidative injury parameters (total antioxidant status, 8hydroxydeoxyguanosine and thiobarbituric acid-reactive substances). Lead exposure in childhood appears to be associated with shorter telomeres, which might contribute to diseases, such as cardiovascular disease. The inverse association between blood lead level and the telomeres in children emphasizes the importance of further reducing lead levels in the environment. © 2015 Elsevier Inc. All rights reserved.

Introduction Telomeres are repeated oligomer sequences (TTAGGG)n that are at the ends of chromosomes. Together with the associated telomere proteins, which form the shelterin complex they form a type of a cap that prevents chromosome damage. The telomeres are shortened during each DNA replication cycle, and telomere shortening may be a marker of biological aging (for review: Stewart et al., 2012; Lu et al., 2013). Short telomere length in leukocytes in retrospective case control studies appeared to be a risk marker for cardiovascular diseases, such as arterial

Abbreviations: B-Pb, blood lead concentration; B-Cd, blood cadmium concentration; BSe, blood selenium concentration; GM, geometric mean; HBG, hemoglobin β chain; NTC, no template control; rTL, relative telomere length. ⁎ Corresponding author at: Institute of Occupational Medicine and Environmental Health, 13, Kościelna Str., 41-200 Sosnowiec, Poland. Fax: +48 32 2661124. E-mail address: [email protected] (N. Pawlas).

hypertension, arteriosclerosis, ischemic coronary disease and acute coronary syndromes (Fyhrquist et al., 2013; Willeit et al., 2010a), and for diabetes mellitus type 2 (Willeit et al., 2014), as well as susceptibility marker to cancer incidence and cancer mortality (Ma et al., 2011; Willeit et al., 2010b; McGrath et al., 2007). However, the opposite associations were observed in some cancers (Seow et al., 2014). Environmental and occupational exposures appear to modify telomere length. Most studies have shown shorter telomeres in subjects that had been exposed to polycyclic aromatic hydrocarbons (Pavanello et al., 2010), N-nitrosamines (Li et al., 2011), pesticides (2,4-D, diazinon and aldrin; Andreotti et al., 2014), cadmium (Zota et al., 2015) and paints (for review: Zhang et al., 2013). Some toxic agents, such as arsenic (Li et al., 2012), benzene (Bassig et al., 2014), pesticides (alachlor; Andreotti et al., 2014) or persistent organic pollutants (Shin et al., 2010), have been associated with longer telomeres. In contrast, the data regarding particulate matter are contradictory and depend on whether the exposure is long- or short-term (Dioni et al., 2011; Wong

http://dx.doi.org/10.1016/j.taap.2015.05.005 0041-008X/© 2015 Elsevier Inc. All rights reserved.

Please cite this article as: Pawlas, N., et al., Telomere length in children environmentally exposed to low-to-moderate levels of lead, Toxicol. Appl. Pharmacol. (2015), http://dx.doi.org/10.1016/j.taap.2015.05.005

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N. Pawlas et al. / Toxicology and Applied Pharmacology xxx (2015) xxx–xxx

et al., 2014a; Zhang et al., 2013). In addition, both prenatal exposure and later exposure to tobacco smoke were associated with shorter telomere length (Theall et al., 2013; Babizhayev and Yegorov, 2011; Valdes et al., 2005; Salihu et al., 2014). Therefore, telomere length is a promising biomarker of exposure and of susceptibility to disease (Silins and Hogberg, 2011). Heavy metals, including lead, may interfere with nucleic acid physiology via either oxidative stress (Fenton-type reaction) (Fowler et al., 2011) or DNA changes at the epigenetic level (Broberg et al., 2014; Fragou et al., 2011; Kippler et al., 2013). Heavy metals have also been shown to affect the organization of chromatin and to lead to impairments in the nuclear membrane (Banfalvi et al., 2012), which is essential for telomere stability (Crabbe et al., 2012; Schober et al., 2009). Environmental exposure to lead has decreased in recent decades in Europe (Strömberg et al., 2008; Hruba et al., 2012; Pawlas et al., 2013); however, adverse health effects, particularly neurotoxic effects, on developing children may still exist (Pawlas et al., 2012). Wu et al. (2012) showed that occupational exposure to high lead levels was associated with telomere length shortening in workers. However, less is known regarding the effects of environmental exposure to lead. One recent study did not observe any effects of lead exposure on leukocyte telomere length in an adult population with low blood lead levels (Zota et al., 2015). In the other there was no association between placental lead concentration and placental telomere length (Lin et al., 2013). Lead exposure during childhood may affect not only the health status during childhood but also the functioning and disease susceptibility of adults (Mazumdar et al., 2011; Theall et al., 2013) possibly through effects on telomere length. The effects of accelerated telomere shortening during childhood on adult health are not fully understood; however, in the literature, short telomeres in blood are clearly associated with adult disease in retrospective case–control studies. The older mothers whose telomeres were shorter at delivery of their child appeared to have more frequently children with Down Syndrome (Ghosh et al., 2010). In case–control studies shorter telomeres were observed in children with autism (Li et al, 2014), as well as in those who experienced family violence (Drury et al, 2014), childhood trauma and developed posttraumatic stress disorder (O'Donovan et al, 2011). The literature is sparse and there is a need for follow-up to confirm the relationship between telomere length at childhood and diseases at adult age. There are few prospective studies in adults regarding the follow-up of participants with estimated telomere length at the baseline. Shorter baseline telomere length was associated with a higher risk of metabolic syndrome development in 2 and 6 years of follow-up in participants aged 18–65 (Revesz et al., 2014). Bakaysa et al. (2007) demonstrated in within pair analyses of 350 participants (175 pairs of twins) with a mean age of 78.8 that telomere length was a predictor of survival. Risk of death during the follow-up (mean 6.9 years) in twins with shorter telomeres was three times higher than in their co-twins with longer telomeres (Bakaysa et al., 2007). Shorter telomeres at baseline were associated with worse survival in idiopathic pulmonary fibrosis assessed as transplant-free survival time (Stuart et al., 2014), in patients with bladder cancer followed for up to 18 years (Russo et al., 2014) and in patients with colorectal cancer (Chen et al., 2014). Telomere length most likely affects DNA methylation levels and gene expression in health and diseases (Buxton et al., 2014). Shorter telomeres and altered DNA methylation were shown in patients with Alzheimer's disease (Guan et al., 2013) and in patients with mild cognitive impairments (Moverare-Skrtic et al., 2012). Shorter telomere length has been used as a predictor of dementia and morbidity (Honig et al., 2012), diabetes type 2 (Zhao et al., 2013), cancer (Ma et al., 2011) and cardiovascular diseases (Muller and Rabelink, 2014). Therefore, nutritional, life-style or therapeutic intervention to slow telomere shortening would be promising for risk-associated populations.

In the present study, we examined telomere length in children with environmental exposure to lead near industrial emitters. Materials and methods Participants and study design. From 2007–2010, 365 children from southern Poland who were living near industrial lead emitters were randomly invited to participate in the cross-sectional PHIME study (PHIME, Public health impact of long-term, low-level mixed element exposure in susceptible population strata). The participation rate was 82%, and 300 children aged 6–10 participated as described previously (Pawlas et al., 2012). In case of siblings, only one randomly selected child from each family was included. Out of the 300 children, 99 8year-old children were selected for this cross-sectional study to limit the potential influence of age on telomeres. There were no differences between the whole cohort of 300 children and those selected for this study with regard to area of living, socioeconomic status (including parents' education), blood lead level, health outcomes, or prenatal and environmental exposures to tobacco smoke. Questionnaire data regarding the child's sex, weight, and height; the parents' age, education and habits; and the child's medical history, habits and development were obtained. This study was approved by the Bioethics Committee at the Institute of Occupational Medicine and Environmental Health, Sosnowiec, Poland. Written informed consent was obtained from one parent, and oral consent was obtained from the child. Blood sampling. Two blood samples were obtained from the cubital vein of each child and collected into vacuum tubes (Vacuette®; Greiner-Bio, Frickenhausen, Germany) containing either lithium heparin for lead determination or K3EDTA for genetic analyses. The blood samples were frozen within 1 h after sampling and stored at −20 °C until use. Telomere length determination. DNA was extracted from peripheral whole blood using a GeneJET Whole Blood Genomic DNA Purification Mini kit (Thermo Scientific) according to the manufacturer's instructions, diluted with sterile nuclease-free water (Qiagen) to 20 ng/μl and stored at −20 °C. Relative telomere length (rTL) assessment was performed in whole blood as described by Cawthon (2002) with minor modifications (Gil and Coetzer, 2004). The telomere length (TL) was determined relative to a single copy gene (hemoglobin beta chain, HBG) by quantitative real-time PCR. Reference DNA samples to produce a standard curve (pooled from eight randomly selected DNA samples, 1.19–38 ng of template) as well as blanks (NTCs: no template controls) were included in each run to ensure quality control. Each sample and the standard curve were run in triplicate. The primer sequences were obtained from Cawthon's manuscript (2002) (written 5′ → 3′) as follows: telomere forward, GGTTTTTGAGGGTGAGGGTGAGGGTGAGGGTGAGGGT; telomere reverse, TCCCGACTATCCCTATCCCTATCCCTATCCCTATCCCTA; HBG forward, GCTTCTGACACAACTGTGTTCACTAGC; and HBG reverse, CACCAA CTTCATCCACGTTCACC. The reactions were run separately on a LightCycler 480 II (Roche) for telomeres and HBG in 96-well white plates (Roche). Each reaction (10 μl) contained the following components: 20 ng of template DNA (1 μl), 5 μl of LightCycler 480 SYBR Green I Master (2 × conc., containing FastStart Taq DNA polymerase, reaction buffer, dNTP mix, SYBR Green I dye and MgCl2), forward and reverse primers (0.25 μM each for telomeres and HBG) and PCR-grade water. The temperature profile for telomere amplification was as follows: 95 °C for 5 min, followed by 45 cycles of 95 °C for 20 s, 58 °C for 1 min, and 72 °C for 30 s, with a final melting step. The temperature profile for HBG amplification was as follows: 95 °C for 5 min, followed by 45 cycles of 95 °C for 15 s, 62 °C for 30 s, and 72 °C for 30 s, with a final melting step. The specificity of the HBG product and the smear of telomeres and NTCs were examined by agarose gel electrophoresis. The Ct was obtained using the absolute quantification 2nd derivative formula. The R2 for the

Please cite this article as: Pawlas, N., et al., Telomere length in children environmentally exposed to low-to-moderate levels of lead, Toxicol. Appl. Pharmacol. (2015), http://dx.doi.org/10.1016/j.taap.2015.05.005

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standard curve was N 0.99, and the efficiency ranged from 1.94–1.99 (the slope showed coefficients of −3.485 and −3.32 for telomeres and HBG, respectively). The accepted standard deviations for the Ct values in triplicates were b0.2. A mix of reference DNA was included in each run, and the CV values (inter-assay coefficient of variation, which was calculated as C = [standard deviation / mean] ∗ 100%) for different runs were 1% based on 4 runs for telomeres and 1% based on 4 runs for HBG. The ratio of the telomere product to the HBG product (a single copy gene) (T/S of one sample relative to the T/S of another sample) was calculated using the following formula: 2−(ΔCt1 − ΔCt2) = 2−ΔΔCt. This study was conducted in blinded fashion, i.e., the scientist who performed the rTL analyses did not know the B-Pb concentrations and had not accessed the questionnaire data. Determination of elements in blood. Whole B-Pb assessment was performed by graphite furnace atomic absorption spectrometry (Stoeppler et al., 1978) using a Perkin-Elmer 4100ZL instrument (Bodenseewerk Perkin-Elmer, Ueberlingen, Germany). The detection limit was 0.3 μg/dl. The laboratory in which the present study was performed meets the requirements of two proficiency tests for blood lead analysis (the Lead and Multielement Proficiency of CDC in Atlanta, and the METOS Program of Instituto Superiore di Sanita in Rome). We also included two other elements in this analysis, i.e., cadmium (B-Cd) and selenium (B-Se) in blood, which could potentially interfere with the rTL. B-Cd and B-Se were assessed by graphite furnace atomic absorption spectrometry as described previously (Gać et al., 2014). The detection limits for B-Cd and B-Se were 0.1 μg/l and 10 μg/l, respectively. Measurement of oxidative stress in urine. The detection of DNA damage products (8-OHdG) in urine was performed using a commercially available ELISA-based assay (Cat. RSCN213100R, BioVendor) according to the manufacturer's instructions. Urinary concentrations of thiobarbituric acid-reactive substances (TBARS), which are composed of lipid peroxides, primarily malonyldialdehyde, were determined using a Caymans TBARS Assay Kit (Cat. 10009055, Cayman Chemical, USA). Total antioxidant status (TAS) was measured in urine using an antioxidant assay kit (Cat. 709001, Cayman Chemical) according to the manufacturer's instructions. Spectrophotometric readings were obtained using a BioTek PowerWave XS microplate reader (BioTek Instruments) and expressed as grams of creatinine in urine. Statistical analyses. Correlations between B-Pb and rTL and potential confounders were initially assessed by Spearman's rank coefficients (rS). The cohort was divided into two groups using the median values of B-Pb b 3.2 μg/dl and B-Pb ≥ 3.2 μg/dl. The non-parametric Mann– Whitney U test was used to compare two groups, and the Kruskal–Wallis test was used to compare more than two groups. The variable rTL was naturally log-transformed to approximate a normally distributed outcome. Additionally, the variable B-Pb was naturally log-transformed to obtain the linear dose–response relation with rTL. The potential confounders that were considered in multivariable stepwise regression model were as follows: the child's sex (nominal variable with “boys” as the reference), height, weight, and body mass index (BMI); the mother's age at delivery; the father's age at delivery; the mother's education; the father's education; (both dichotomized into “lower and secondary” and “secondary and higher” and classified as nominal variable with “secondary and higher” as the reference) and the child's prenatal smoking exposure (nominal variable — “children without prenatal smoking exposure” were taken as the reference), Apgar score, child's exposure to environmental tobacco smoke (nominal variable — “children without environmental tobacco exposure” were taken as the reference), birth weight, white blood cell count and blood lead, cadmium and selenium levels. The model showed that prenatal smoking exposure, Apgar scale and blood lead level (model p-value = 0.0055) are potentially influential and they were adjusted for in a partially adjusted model. We further made a fully adjusted model taking other potentially influential variables

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into account (mother's education, mother's and father's ages at delivery and sex). We used a general linear model that considered covariates to evaluate the relation between lead and rTL further. The analysis of residual distribution enabled us to use the general linear model. To further explore the effect of lead and to remove the effect of prenatal smoking we performed the analyses in children without prenatal smoking exposure. Statistical analyses were performed using STATISTICA 10 PL software (StatSoft, Inc.). Statistical significance was considered at p b 0.05.

Results The general characteristics of the cohort (divided into two groups by the median values of B-Pb b 3.2 μg/dl and B-Pb ≥ 3.2 μg/dl) are shown in Table 1. The geometric mean values of B-Pb and rTL were 3.28 μg/dl and 1.08 relative units, respectively. Significant differences in rTL and mother's education were found with increasing B-Pb, namely, the rTL gradually shortened, and mothers were less educated. Overall, a significant difference in rTL was observed in children with higher B-Pb (median split B-Pb ≥ 3.2 μg/dl) and lower (B-Pb b 3.2 μg/dl) (two tailed p value = 0.008), and a significant negative correlation between rTL and B-Pb was found (Table 2, Fig. 1). No differences in B-Pb or rTL were found between boys and girls (Mann–Whitney U test, p = 0.11 and p = 0.86, respectively). Children's rTL was significantly associated with the mothers' education (rS = 0.205; p = 0.041) but not with the fathers' education. When we compared rTL in children using Kruskal– Wallis ANOVA there was no difference between groups categorized by mother's education (p = 0.19) and when we dichotomized mother's education as the criterion, there was no difference (Mann–Whitney U test p = 0.27). Positive associations with rTL were observed with the mothers' and fathers' ages at delivery (rS = 0.23 and p = 0.019; rS = 0.21 and p = 0.043, respectively). Children of those mothers who smoked during pregnancy had shorter rTL at the age of 8 (Mann–Whitney U test; p = 0.00072), and no effect of exposure to environmental tobacco smoke was found for non-smoking women. No correlations were found between rTL and other studied parameters, including whole blood cadmium and selenium concentrations and oxidative stress parameters, including urinary 8-hydroxydeoxyguanosine and urinary TBARS concentrations (primarily malonyldialdehyde). Univariate analysis indicated that B-Pb was associated with shorter rTL (β = −0.13; p = 0.026; R2adj 4%) (Table 3) and that the association between B-Pb and rTL remained borderline significant (p = 0.056), even when adjusting for maternal smoking at pregnancy, mother's and father's ages at delivery, mother's education, sex and for the Apgar scale or when analyzing children (n = 87) who were not prenatally exposed to mother's smoking (rS = −0.24; p = 0.024; β = −0.13, p = 0.029; Table 3). In the multiplicative model children with B-Pb levels that were 3.2 μg/dl or more had 13% shorter telomeres than those children with B-Pb levels that were lower than 3.2 μg/dl, and prenatal tobacco exposure led to a 13% decrease in the multivariable-adjusted model (p = 0.0083). Smoking during pregnancy alone appeared to explain 12% of the entire rTL variance. Children of mothers who smoked during pregnancy seem to have 18% shorter telomeres compared with children of non-smoking mothers (p = 0.0003). In the multivariable-adjusted analyses, mothers' smoking during pregnancy remained the strongest factor that influenced the rTL; however, the effect of B-Pb was also significant (Table 3).

Discussion This study shows that increasing B-Pb is associated with shorter telomere length in 8-year-old children with low-to-moderate lead exposure levels.

Please cite this article as: Pawlas, N., et al., Telomere length in children environmentally exposed to low-to-moderate levels of lead, Toxicol. Appl. Pharmacol. (2015), http://dx.doi.org/10.1016/j.taap.2015.05.005

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N. Pawlas et al. / Toxicology and Applied Pharmacology xxx (2015) xxx–xxx

Table 1 Characteristics of the cohort. Variablea

All (total N = 99)

B-Pb b 3.2 μg/dl (N = 49)

B-Pb ≥ 3.2 μg/dl (N = 50)

p value

Boys (%)/girls Age Weight [kg] (GM, range) Height [m] (GM, range) BMI [kg/m2] (GM, range) B-Pb [μg/dl] (GM, range) B-Cd [μg/l] (GM, range) B-Se [μg/l] (GM, range) Telomere length [relative units] (GM, range) Mother's education (%) Primary Apprenticeship Secondary Bachelor's degree Master's degree Father's education (%) Primary Apprenticeship Secondary Bachelor's degree Master's degree Mothers' smoking during pregnancy Yes (%) Environmental tobacco smoke exposure at home Yes (%) Apgar score at birth (GM, range) Birth weight [g] (GM, range) TBARS [μmol/g creatinine] (GM. range) TAS [mmol/g creatinine] (GM, range) 8-OHdG [ng/g creatinine] (GM. range)

55 (55.6)/44 (44.4) 8 29.7 (19.5–54) 1.32 (1.18–1.46) 17.0 (12.4–25.2) 3.28 (0.9–14.2) 0.18 (0.030–0.68) 76.87 (54.0–130.0) 1.08 (0.49–2.09)

26 (53)/23 (47) 8 30.6 (19.5–46.4) 1.33 (1.20–1.45) 17.5 (12.4–25.1) 2.04 (0.9–3.10) 0.15 (0.03–0.64) 79.1 (56.0–130.0) 1.18 (0.49–2.06)

29 (58)/21 (42) 8 28.7 (20.0–54.0) 1.31 (1.18–1.46) 16.5 (12.8–25.2) 5.23 (3.20–14.2) 0.21 (0.07–0.68) 74.7 (54.0–95.0) 0.99 (0.63–2.09)

0.62b – 0.18c 0.21c 0.12c b0.0001c 0.019c 0.10c 0.008c b0.05b

7 (7) 24 (24) 46 (46) 5 (5) 17 (17)

2 (4) 7 (14) 23 (46) 3 (6) 14 (28)

5 (10) 17 (34) 23 (46) 2 (4) 3 (6)

6 (6) 38 (38) 35 (35) 5 (5) 9 (9) 10 (10)

4 (8) 17 (35) 17 (35) 4 (8) 6 (13) 3 (6)

2 (4) 21 (42) 18 (36) 1 (2) 3 (6) 7 (14)

0.19b

25 (25)

10 (20)

15 (30)

0.39b

9.3 (3–10) 3238 (1500–4450) 5.33 (0.23–41.9) 3.14 (0.46–70.7) 4.31 (1.04–9.97)

9.4 (3–10) 3220 (2100–3850) 5.17 (0.23–41.9) 3.38 (0.46–70.7) 4.56 (1.20–9.89)

9.2 (5–10) 3255 (1500–4450) 5.49 (0.81–18.1) 2.92 (0.86–17.8) 4.08 (1.04–9.97)

0.49c 0.22c 0.95c 0.25c 0.31c

b0.05b

GM: geometric mean; TBARS: thiobarbituric acid reactive substances; TAS: total antioxidant status; 8-OHdG: 8-hydroxydeoxyguanosine. a Missing data: Weight, 23 individuals (23.2%); height, 26 individuals (26.2%); BMI, 26 individuals (26.2%); father's education, 6 individuals (6.1%); mothers' smoking during pregnancy, 2 individuals (2%); environmental tobacco smoke exposure at home, 1 individual (1%); Apgar score, 4 individuals (4%); birth weight, 3 individuals (3%); and cadmium, 1 individual (1%). b Chi2 test p value. c Mann–Whitney U test p value.

Few studies regarding the association between lead and telomere length have been conducted. Telomere length shortening was observed in in vitro studies of hepatocytes (Liu et al., 2004). Wu et al. showed that occupational exposure to high lead levels in adult workers resulted in shorter telomeres (Wu et al., 2012). They showed inverse correlation between telomere length and both blood and urinary lead levels, however, but not with age. In the multivariable model, there was a negative association between telomere length and body lead burden and exposure duration (work years) and a weak positive association with blood lead level only in the very high exposed group (blood lead level higher than 40 μg/dl or urinary lead level higher than 7 μg/dl) (Wu et al., 2012). Our study shows that much lower environmental exposure to lead than in occupational settings results in shorter telomeres in children, while we did not observe any effects of cadmium or selenium exposure on telomere length. Zota et al. (2015) showed that environmental exposure to cadmium in the NHANES cohort (NHANES, National Health and Nutrition Examination Survey) was associated with shorter telomeres, while an effect of lead was not observed. However, higher mean B-Cd (GM B-Cd = 0.44 μg/l) and lower B-Pb (GM B-Pb = 1.67 μg/dl) were observed in their adult population compared to our juvenile population (Zota et al., 2015). Also environmental exposure to cadmium, but not to lead (measured in the placental tissue), was associated with shorter telomere length in pregnant women living in the vicinity of electronic waste recycling site (Lin et al., 2013). Because guanosine-rich telomeres form G-quadruplexes (Lu et al., 2013), one possible explanation for the observed shortening is the displacement of physiological ions by lead ions, which leads to more compacted G-quadruplex formation and in turn results in telomere instability and telomere maintenance impairment during replication (Pottier et al., 2013). In in vitro studies, Pottier et al. showed that Pb exposure leads to telomere instability and telomere loss due to the

induction of γH2Ax foci, which are biomarkers of DNA double-strand breaks, at the end of chromosomes, near telomeres (Pottier et al., 2013). Such DNA breaks were previously reported in lead-exposed humans using the comet assay (Olewińska et al., 2010) or the micronuclei formation cytokinesis-block test (Kapka et al., 2007). Pb exposure also leads to an inflammatory response (Liu et al., 2012); systemic inflammation was associated with decreased telomere length in peripheral leukocytes (Wong et al., 2014b). The molecular mechanism of lead-induced telomere shortening remains unknown. Telomere length may also be a biomarker of chronic oxidative stress (Houben et al., 2008), and oxidative stress is thought to be induced by metal ions (Fowler et al., 2011). However, we did not see any associations between oxidative stress measurements and either B-Pb or rTL in our study of children with chronic low to moderate environmental exposure most likely due to adaptation to moderate and long-term lead exposure. The other possible explanation is that urine may not be the best material for assessing the intracellular oxidative stress. We decided to limit our analysis to children aged 8 years to exclude different ages, which is the important confounding factor in telomere length biology. The assessment of rTL and B-Pb were performed under strict quality control and followed MIQE guidelines (Bustin et al., 2009) and an inter-laboratory proficiency test, respectively. Additionally, the sampling and handling of blood were strictly controlled because blood proceeding appears to have a significant effect on telomere length (Zanet et al., 2013). However, although the mean European B-Pb in urban children is lower than the level of concern, which was established at 50 μg/l (CDC, 2012; Hruba et al., 2012), areas where this level doubles still exist (Hruba, unpublished) primarily near industrial emitters (lead smelters). An association between prenatal exposure to tobacco smoke and shorter telomeres at the age of 8 was also found. Children of mothers

Please cite this article as: Pawlas, N., et al., Telomere length in children environmentally exposed to low-to-moderate levels of lead, Toxicol. Appl. Pharmacol. (2015), http://dx.doi.org/10.1016/j.taap.2015.05.005

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0.055 0.072 0.040 −0.024 – 0.229⁎ 0.122 −0.084 0.095 0.055 0.062 0.055

– 0.023 0.156 0.072 −0.028 0.072

−0.013 0.158 0.167 0.122 0.152 0.091 − 0.578⁎⁎⁎

– 0.502⁎⁎⁎ −0.350⁎⁎ −0.197 0.167 0.236 0.129 0.306⁎⁎ −0.060 −0.016 0.018

– −0.239⁎ −0.104 0.122 0.169 0.056 0.052 −0.188 −0.094 0.056

0.152 −0.117 −0.038 −0.197 0.071 0.00099 −0.059

−0.056 −0.168 −0.197 −0.104 0.733⁎⁎⁎ – 0.091 0.0063 −0.030 −0.043 0.207⁎ 0.027 0.064 −0.149 −0.288⁎ −0.350⁎⁎ −0.239⁎ – 0.733⁎⁎⁎

0.074 0.062 0.114 −0.0048 −0.077 0.002 0.079 0.022 −0.034 0.167 0.114 0.154 −0.132 −0.117 0.095 −0.082 −0.124 −0.102

0.161 −0.191 −0.175 −0.196 −0.127 −0.160 −0.397⁎⁎⁎

B-Pb: blood lead concentration; B-Cd: blood cadmium concentration; B-Se: blood selenium concentration; TBARS: thiobarbituric acid reactive substances; TAS: total antioxidant status; 8-OHdG: 8-hydroxydeoxyguanosine. a Boys = 1, girls = 0. b Primary = 1, Apprenticeship = 2, Secondary = 3, Bachelor's degree = 4, Master's degree = 5. ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

−0.102 −0.103 0.154 0.002 −0.139 −0.00074 0.018 0.056 −0.059 0.064 0.055 0.072 −0.010 −0.0015 0.122 0.097 – −0.124 0.054 0.114 −0.077 −0.073 −0.114 −0.016 −0.094 0.00099 0.027 0.062 −0.028 −0.144 −0.072 0.229⁎ – 0.097 −0.082 −0.058 0.167 −0.0048 0.037 −0.141 −0.060 −0.188 0.071 0.207⁎

0.095 0.075 −0.034 0.114 0.150 0.166 0.306⁎⁎ 0.052 −0.197 −0.043 0.095 0.156 0.150 – −0.024 −0.072 −0.0015 −0.117 −0.125 0.022 0.062 −0.032 0.091 0.129 0.056 −0.038 −0.030 −0.084 0.023 – 0.150 0.040 −0.144 −0.010 −0.132 −0.146 0.079 0.074 0.051 0.216 0.236 0.169 −0.117 0.0063 0.578⁎⁎⁎ −0.160 −0.098 0.055 0.206⁎

0.190 − −0.137 −0.090 0.081 0.0049 −0.070 0.064 −0.047 −0.098 −0.153 −0.146 −0.125 0.075 −0.058 0.054 −0.103 – 0.190 −0.164 −0.250⁎

B-Pb B-Cd B-Se rTL Sexa Weight Height BMI Mother's age at delivery Father's age at delivery Mother's educationb Father's educationb Apgar score Birth weight TBARS TAS 8-OHdG

−0.164 −0.137 – 0.100 0.049 0.131 0.120 0.109 −0.0045 0.055 0.238⁎

−0.250⁎ −0.090 0.100 – −0.018 −0.032 0.108 −0.052 0.235⁎ 0.206⁎ 0.205⁎

0.161 0.081 0.049 −0.018 – 0.149 0.167 0.066 −0.149 −0.056 −0.013 0.051 −0.032 0.150 0.037 −0.073 −0.139

−0.191 0.0049 0.131 −0.032 0.149 – 0.771⁎⁎⁎ 0.925⁎⁎⁎ −0.288⁎ −0.168 0.158 0.216 0.091 0.166 −0.141 −0.114 −0.00074

−0.175 −0.070 0.120 0.108 0.167 0.771⁎⁎⁎

−0.196 0.064 0.109 −0.052 0.066 0.925⁎⁎⁎ 0.502⁎⁎⁎

−0.127 −0.047 −0.0045 0.235⁎

−0.397⁎⁎⁎ −0.153 0.238⁎ 0.205⁎

Apgar score Sexa rTL B-Se B-Cd B-Pb Variables

Table 2 Associations (rS) between B-Pb and rTL of the child and potential confounders.

Weight

Height

BMI

Mother's age at delivery

Father's age at delivery

Mother's educationb

Father's educationb

Birth weight

TBARS

TAS

8-OHdG

N. Pawlas et al. / Toxicology and Applied Pharmacology xxx (2015) xxx–xxx

Fig. 1. Association between B-Pb (log transformed) and rTL (log transformed) in 8-yearold children.

who smoked during pregnancy had significantly shorter telomeres (0.82) compared to references who did not smoke, and prenatal exposure explained a substantial amount of variability (12%). However, because our cohort included few children with prenatal tobacco exposure, these results should be interpreted cautiously. Similar results for prenatal smoke exposure were observed by Theall et al. (2013) and by Salihu et al. (2014). The problem of tobacco-induced telomere loss, most likely due to reactive oxygen species generation, was observed in adults as well (Valdes et al., 2005). Studies regarding the prevention of decreased telomere length in smokers by either pharmacological or nutritional intervention have been conducted (Babizhayev and Yegorov, 2011). We included only those women who declared that they had not smoked in analyses of children without prenatal smoking exposure; therefore, we excluded both children with smoking mothers and missing data from that cohort. In our cohort, 10% of all women smoked during pregnancy, and up to 16% of the women in the quartile with the highest B-Pb smoked during pregnancy. However, other reports regarding Polish populations (Polańska et al., 2014) showed that 16% of pregnant women (in 2007–2011) could be considered smokers based upon the cotinine levels in their saliva. Therefore, in our case, the number of women who smoked during pregnancy might be underestimated, which may be a limitation of the present study. We also observed positive correlations between parents' ages at delivery, mother's education and rTL. A recent report showed that parents are generally older at delivery than they were two decades ago (Mathews and Hamilton, 2014; http://www.pewsocialtrends.org/files/ 2010/10/754-new-demography-of-motherhood.pdf), and that the parents' education level is increasing. Better educated parents should most likely provide a better home environment, better nutrition and psychosocial factors than poorly educated parents. Our results support another study that found a positive association between social environment and telomere length (Mitchell et al., 2014). In addition, psychosocial factors might affect telomere length (Shalev et al., 2013; Starkweather et al., 2014). Childhood stress (analyzed as socioeconomic adversities) led to shortened telomere length in adults (Kananen et al., 2010). Starkweather et al. (2014) reviewed several studies regarding telomere length and found that both chronic stress and acute stress appeared to lead to telomere shortening. The negative association between the number of perinatal complications (including Apgar score) and telomere length at the age 38 was observed (Shalev et al., 2014). We are aware that this is a pilot study with a modest sample size and further studies are needed to confirm those associations. Also the design of the study — cross-sectional study — limits the information to single

Please cite this article as: Pawlas, N., et al., Telomere length in children environmentally exposed to low-to-moderate levels of lead, Toxicol. Appl. Pharmacol. (2015), http://dx.doi.org/10.1016/j.taap.2015.05.005

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N. Pawlas et al. / Toxicology and Applied Pharmacology xxx (2015) xxx–xxx

Table 3 Univariate and multivariable-adjusted analyses of the effects of B-Pb (Log B-Pb) on rTL in children with environmental lead exposure. Variable

Beta [U per μg/dl] (PE; CI)

Univariate analysis a Intercept Log B-Pb

0.52 (0.12; 0.92) −0.13 (−0.23; −0.016)

Multivariable-adjusted analysis b Intercept Log B-Pb Mother's educationc Prenatal smoking exposured Sexe Mother's age at delivery Father's age at delivery Apgar score

0.13 (−0.98; 0.72) −0.12 (−0.24; 0.0030) 0.0051 (−0.072; 0.082) −0.14 (−0.26; −0.029) −0.014 (−0.080; 0.052) 0.012 (−0.0095; 0.035) −0.0026 (−0.023; 0.017) 0.026 (−0.026; 0.078)

p value 0.026 0.010 0.026 0.011 0.76 0.056 0.89 0.015 0.68 0.26 0.80 0.32

R2adj 4%

12%

Beta: regression coefficient; PE: point estimate; CI: 95% confidence interval. a Model used: Log rTL = Intercept + β1 (Log B-Pb). b Model used: Log rTL = Intercept + β1 (Log B-Pb) + β2 (mother's education) + β3 (mothers' smoking during pregnancy) + β4 (sex) + β5 (Apgar score) + β6 (mother's age at delivery) + β7 (father's age at delivery). c Secondary and higher mother's education was taken as a reference (vs lower education). d No prenatal smoking exposure was taken as the reference. e Boys were taken as a reference.

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Please cite this article as: Pawlas, N., et al., Telomere length in children environmentally exposed to low-to-moderate levels of lead, Toxicol. Appl. Pharmacol. (2015), http://dx.doi.org/10.1016/j.taap.2015.05.005

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Please cite this article as: Pawlas, N., et al., Telomere length in children environmentally exposed to low-to-moderate levels of lead, Toxicol. Appl. Pharmacol. (2015), http://dx.doi.org/10.1016/j.taap.2015.05.005