Evaluation of vascular and kidney injury biomarkers in Mexican children exposed to inorganic fluoride

Author’s Accepted Manuscript Evaluation of vascular and kidney injury biomarkers in Mexican children exposed to inorganic fluoride Mónica I. Jiménez-Córdova, Carmen GonzálezHorta, Julio C. Ayllón-Vergara, Laura ArreolaMendoza, Guadalupe Aguilar-Madrid, Efraín E. Villareal-Vega, Ángel Barrera-Hernández, Olivier C. Barbier, Luz M. Del Razo

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S0013-9351(18)30388-8 https://doi.org/10.1016/j.envres.2018.10.028 YENRS8123

To appear in: Environmental Research Received date: 8 July 2018 Revised date: 12 October 2018 Accepted date: 25 October 2018 Cite this article as: Mónica I. Jiménez-Córdova, Carmen González-Horta, Julio C. Ayllón-Vergara, Laura Arreola-Mendoza, Guadalupe Aguilar-Madrid, Efraín E. Villareal-Vega, Ángel Barrera-Hernández, Olivier C. Barbier and Luz M. Del Razo, Evaluation of vascular and kidney injury biomarkers in Mexican children exposed to inorganic fluoride, Environmental Research, https://doi.org/10.1016/j.envres.2018.10.028 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Evaluation of vascular and kidney injury biomarkers in Mexican children exposed to inorganic fluoride Mónica I. Jiménez-Córdova1, M..Carmen González-Horta2, Julio C. Ayllón-Vergara3, Laura Arreola-Mendoza4, Guadalupe Aguilar-Madrid5, Efraín E. Villareal-Vega2, Ángel BarreraHernández1, Olivier C. Barbier1, Luz M. Del Razo1* 1

Departamento de Toxicología, Centro de Investigación y de Estudios Avanzados del Instituto

Politécnico Nacional, Mexico City, Mexico. 2

Facultad de Ciencias Químicas, Universidad Autónoma de Chihuahua, Chihuahua, Mexico.

3

Hospital Español, Mexico City, Mexico.

4

Departamento de Biociencias e Ingeniería, Centro Interdisciplinario de Investigaciones y Estudios

sobre Medio Ambiente y Desarrollo del Instituto Politécnico Nacional, Mexico City, Mexico. 5

Unidad de Investigación y Salud en el Trabajo, Instituto Mexicano del Seguro Social, Mexico City,

Mexico. *Corresponding author: Departamento de Toxicología del Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV-IPN), Avenida Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Ciudad de México, Mexico, 07360, Phone: +(55)57473306. [email protected]

Abstract Exposure to inorganic fluoride (F) has been implicated in cardiovascular and kidney dysfunction mainly in adult populations. However, limited epidemiological information from susceptible populations, such as children, is available. In this study we evaluated the relationship of F exposure with some vascular and kidney injury biomarkers in children. A cross-sectional study was conducted in 374 Mexican schoolchildren. Dental fluorosis and F concentrations in the water and urine were evaluated. The glomerular filtration rate (eGFR) and the urinary concentrations of kidney injury molecule 1 (KIM-1) and cystatin-C (uCys-C) were examined to assess kidney injury. 1

The carotid intima media thickness (cIMT) and serum concentrations of vascular adhesion molecule 1 (VCAM-1), intracellular adhesion molecule 1 (ICAM-1), endothelin 1(ET-1) and cystatin-C (sCys-C) were measured to assess vascular alterations. High proportions of children exposed to F were observed (79.7% above 1.2 ppm F in urine) even in the low water F exposure regions, which suggested additional sources of F exposure. In robust multiple linear regression models, urinary F was positively associated with eGFR (β=1.3, p =0.015), uCys-C (β=-8.5, p=0.043), VCAM-1 (β=111.1, p=0.019), ICAM-1 (β=57, p=0.032) and cIMT (β=0.01, p=0.032). An inverse association was observed with uCys-C (β=-8.5, p=0.043) and sCys-C (β =-9.6, p=0.021), and no significant associations with ET-1 (β=0.069, p=0.074) and KIM-1 (β=29.1, p=0.212) were found. Our findings revealed inconclusive results regarding F exposure and kidney injury. However, these results suggest that F exposure is related to early vascular alterations, which may increase the susceptibility of cardiovascular diseases in adult life.

Keywords: fluoride, children, kidney injury, atherosclerosis, biomarkers

1. Introduction

Cardiovascular disease (CVD) is the most common cause of death worldwide and is commonly associated with kidney dysfunction; additionally, its comorbidity has been increasingly recognized (Gansevoort et al., 2013). In addition to the well-known risk factors (e.g., genetic, lifestyle, obesity, diabetes and dyslipidaemia), environmental exposure to toxicants during early life stages and childhood has been implicated in cardiovascular and kidney dysfunction (Weidemann et al., 2016). Children are especially vulnerable to environmental toxicants due to their unique rapid development, physiological characteristics and behaviour patterns. However, information about cardiovascular and kidney toxicity in children for most environmental toxicants remains limited.

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Since the middle of 20th century inorganic fluoride (F), that is an element widely distributed in nature, has been recognized to prevent tooth decay and its consumption in low levels can limit the disability-adjusted life years (DALYs) due to dental caries (Abtahi et al., 2018). However, its most cariostatic effect is topical, and it has been proposed that its systemic ingestion is not required (Hellwig and Lennon, 2004). F is an element that is found most frequently in groundwater, which is the main source of F exposure. Nevertheless, other sources such as fluorinated toothpastes, foods, beverages and fluorinated salt consumption can importantly contribute to the total daily F exposure, especially in children, who are exposed to higher doses of F compared than adults under the same F exposure conditions (NRC, 2006). High levels of F ingestion is an environmental risk in many worldwide regions. In Mexico, there is an extensive area of endemic fluorosis mainly located in the central and northern region. It has been estimated that approximately 18% (6 millions) of Mexican children between 0-14 years are exposed to high F levels through drinking water in the country (Limón-Pacheco et al., 2018). In Chihuahua, a state located in the north of Mexico, the groundwater is the main source of water supply for many communities located in arid and semiarid regions. Previous studies conducted in the area revealed that F levels in drinking water are ranged from 0.05 to 11.8 mg/L (González-Horta et al., 2015; Ruiz-Payan et al., 2005), increasing the risk of adverse health effects such as dental and skeletal fluorosis, thyroid dysfunction and neurodevelopmental alterations in the population (Bashash et al., 2016; Mohammadi et al., 2017; Singh et al., 2014). Experimental studies have demonstrated that high F exposure induces oxidative stress, inflammation, expression of cellular adhesion molecules, apoptosis and tubular dysfunction, which are recognized mechanisms associated with cardiovascular and kidney toxicity (Cárdenas-González et al., 2013; Ma et al., 2017; Quadri et al., 2018a). In chronic F exposure, epidemiological studies have also report atherosclerosis (Liu et al., 2014), hypertension (Amini et al., 2011; Sun et al., 2013), cardiovascular dysfunction (Karademir et al., 2011; Varol et al., 2010a) and early kidney injury (Jiménez-Córdova et al., 2018; Xiong et al., 2007; Quadri et al., 2018b) in an independent

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manner. However, most of these studies have been conducted in adult populations and have ignored the potential cardiovascular-kidney toxicity of the environmental F exposure in children. The long latency period and the lack of sensitive biomarkers to the early sub-clinical detection of cardiovascular and kidney diseases increases the difficulty of providing epidemiological information about early cardio-renal toxicity of environmental toxicants. Biological molecules such as endothelial adhesion molecules, inflammatory markers, and serum lipids and the intima media thickness have been useful biomarkers for the appraisal of early stages of atherosclerosis (Poredoš and Kaja Ježovnik, 2015). Similarly, early kidney injury biomarkers, such as kidney injury biomarker 1 (KIM-1) and Cystatin-C (Cys-C) have demonstrated high sensitivity for the detection of kidney damage (Vaidya et al., 2008). All these biomarkers can be helpful for the early detection of vascular and kidney alterations in children who are exposed to environmental toxicants. Therefore, the aim of this study was to evaluate the relationship between F exposure and some vascular and kidney injury biomarkers to assess the potential cardiovascular and kidney toxicity of F exposure in Mexican children.

2. Material and methods 2.1. Study participants From October to November 2015, a cross-sectional study was performed with 417 schoolchildren (5-12 years old) who attended one of two selected schools from the municipalities of Hidalgo del Parral and Aldama in Chihuahua, Mexico (Fig. 1). Hidalgo del Parral is a city located in the south of the state at an altitude of 1718 m and Aldama is a city located in the central region at an altitude of 1270 m. The schools were selected based on the following: i) previous data of differential F exposure in drinking water [0.18 mg/L in Hidalgo del Parral and 2 mg/L in Aldama]; ii) no concurrent exposure to arsenic as reported in this region (González-Horta et al., 2015); the arsenic levels in the water were 10 µg/L in Hidalgo del Parral and 9.7 µg/L in Aldama; and iii) a minimum of 400 registered students. The children were invited to participate through school 4

meetings with the parents that were performed with school authorities. The parents of the participating children signed a written informed consent document, and the children signed a written informed assent document. The children who commonly drink tap water with a minimum of 2 years of residence in the city were included in the study. Children with a previous diagnosis of chronic disease were excluded. From 417 children who participated, 374 had complete information, and all samples available. This study was approved by the Institutional Bioethics Committee for Research in Humans (COBISH-CINVESTAV-025/2015].

2.2. Interview A structured questionnaire was applied via parent/caregiver interview and included questions to obtain selected general characteristic information, socioeconomical status (SES), potential sources of F exposure, secondhand smoke (SHS) exposure, actual health condition, medication, antecedents of chronic diseases, physical activity and dietary information. The SES was defined according to the classification developed by the Mexican Association of Marketing and Public Opinion Agencies (AMAI) (López-Romo, 2011). Physical activity was assessed with a section of the Physical Activity Questionnaire for Children (PAQ-C) (Kowalski et al., 2004), and the dietary information was assessed by a 24-hr dietary recall, the nutrition content of the food was obtained by the Mexican Equivalent Food System (Pérez Lizaur et al., 2014).

2.3. Paediatric examination Height was measured with a measuring tape (Seca 206, seca, Hamburg, Germany) using standard protocols, and weight and body fat percentage were measured with a body composition analyser (BC-601F, Tanita Corporation®, Tokyo, Japan). Standard deviation scores (Z-scores) and WHO growth standards were used to determine the growth and malnutrition statuses (de Onis and Blössner, 2003). Blood pressure (BP) measurements were conducted according to the Mexican Official Standards (SSA, 2009), and the children were classified according to hypertension 5

definitions based on the normative distributions of BP in healthy children (NHBPEPWG, 2004). Additionally, carotid intima media thickness (cIMT) measurements were performed by an expert cardiologist who was blinded to the F exposure and was not involved in the statistical analysis of the study using a standard B-Mode ultrasound device (Vivid i®, General Electric, Milwaukee WI, USA) with a high frequency (14-MHz) linear transducer. Multiple measurements of cIMT were performed, following a standardized protocol with the child in the supine position, and the results are reported as average cIMTs. Dental fluorosis was evaluated by an expert odontologist using the classification systems of Dean´s Index (Dean, 1942).

2.4. Blood sample collection and serum biochemical analysis Blood samples were collected in vacuum serum separator tubes and centrifuged 1500 rpm for 15 min to obtain serum samples. One serum aliquot was transported and stored at 4ºC until biochemical analysis and another was stored at -80°C until vascular biomarker quantification. Biochemical analysis (glucose, lipid profile, uric acid and creatine) was performed by an automatic analyser (Prestige 24i, Tokyo Boeki Medical System Ltd., Tokyo, Japan). The atherogenic index of the serum (AI) was calculated as the log (triglycerides/high density lipoproteins) in molar concentrations (Dobiášová and Frohlich, 2001), and eGFR was determined by the CreatinineCystatin C-Based CKiD Equation (Schwartz et al., 2012).

2.5. Urine sample collection and urinalysis A first morning void urine was provided. After receiving the urine sample, specific gravity was measured immediately using a refractometer (PAL-10S, ATAGO®, Tokyo, Japan), and urinalysis was performed with a urine analyser (U-66, Mindray Co., Shenzhen, China). A 2X protease inhibitor solution (Sigma FASTTM, Sigma-Aldrich, USA) was mixed with an aliquot of the urine sample (1:3000), that was centrifuged at 3000 rpm for 10 min. The urine supernatant was aliquoted into polypropylene tubes and transported and stored at -80ºC until analysis. 6

2.6. Water and urine F quantification A water sample was provided into polypropylene recipients by each participant. The concentrations of F in the water and urine samples were assessed by a potentiometric method using an ion selective electrode (Orion 9609BNWP, Thermo Fisher Scientific Inc., USA), as previously described (Del Razo et al., 1993). The analysis of urine fluoride reference material (U-F-0907 and U-F1510), Quebec Centre of Toxicologie) and controls were used for quality control. The accuracy obtained ranged from 94 to 107%, and the coefficients of variation for duplicate samples were lower than 5%. The urine dilution-adjustment by specific gravity was used as previous described (Levine and Fahy, 1946).

2.7. Urine and serum biomarkers measurement Before the analysis, the urine and serum samples were thawed, but only the urine samples were centrifuged at 3000 rpm for 10 min at 4ºC and the supernatant was used for analysis. The serum concentration of vascular adhesion molecule 1 (VCAM-1), intracellular adhesion molecule 1 (ICAM-1), endothelin 1 (ET-1) and Cystatin C (sCys-C), and urinary levels of KIM-1 and Cys-C (uCys-C) were measured using a custom human Magnetic Luminex Screening Assay (R&D Systems, Inc., Minneapolis MN, USA) that was read on a Luminex xMAP® Instrument (MAGPIX®, Luminex Corp., Austin TX, USA). This assay provides a quantitative measure of the analytes. The measures were performed out following the manufacturer’s instructions. Long periods of storage or multiple (>2) freeze/thaw cycles of urine and serum samples were avoided.

2.8. Statistical Analysis All analyses were performed with the STATA statistical package version 15.0 (Stata Corp, College Station, TX, USA). Continues variables are expressed as the mean ± the standard deviation or geometric mean (GM) with interquartile range (IQR). Categorical variables are expressed as 7

proportions or percentages. To evaluate potential differences between communities of residence, Mann-Whitney tests, t-tests and chi squared tests were used where appropriate. Spearman´s correlations for the water and urinary F concentrations were performed among communities. Additionally, robust multiple linear regression models for the urinary F for each community were performed. To analyse the association between the kidney and cardiovascular biomarkers (eGFR, KIM-1, uCys-C, VCAM-1, ICAM-1, ET-1, cIMT and sCys-C), robust multiple linear regression models were performed and included covariates chosen on based on biological plausibility and improved model fit (contribution to R2-adjusted value or 10% change in β coefficient). The results are expressed as the regression coefficient (β) and p-value for each explanatory variable. Multiple imputation of 39% of samples that were below the limit of detection (LOD) for KIM-1 was tested using an interval regression imputation method with 32 imputations including the model and auxiliary variables (BMI, age and sex).

3. Results 3.1. General characteristics The sociodemographic, anthropometric, biochemical and nutrition characteristics of the participants are presented in Table 1. The characteristics are described as the total participants and according to child’s residence community. The mean total children’s age was 9 years old and ranged from 5 to 12 years; nearly of 47% were boys, and 53% were girls. Most of the children came from a low SES, and a statistically significant higher proportion of them were observed in Hidalgo del Parral. For all children, a prevalence of 2.1% of low weight for age and nearly of 25% of overweight-obesity were found. No statistically significant differences between communities were found in relation to biochemical parameters, anthropometric values or most of the blood pressure values, except systolic blood pressure (SBP), physical activity and daily lipid intake.

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3.2. F exposure assessment Water and urine F concentrations and dental fluorosis are presented in Table 1. The median of F in the water was approximately 10 times higher in Aldama, in which approximately 37% of the samples had F concentrations above the maximum permissible limit (1.5 mg/L). The geometric mean of the F concentration the in children’s urine were 1.7 µg/mL and 2.7 µg/mL in Hidalgo del Parral and Aldama, respectively. Significant differences in the water and urine F concentration between the communities were found. However, in both, high proportions of children presented with urinary F levels above biomonitoring equivalent (BE) value [1.2 µg/mL], which is an estimate of the urinary F concentration that is consistent with an exposure guidance value (reference dose (RfD), 0.08 mg/kg/day) for children (Aylward et al., 2015), which was used as a reference value. Additionally, a high prevalence of dental fluorosis was found in Aldama according to the Dean index. To assess the relationship between the F concentration in the water and urine for each community a scatterplot is presented in Fig. 2. Although positive Spearman’s correlation coefficients were observed for both communities, only for that of Aldama was statistically significant. Additionally, to investigate the relationship of urinary F with other variables, robust multiple linear regression models by community are shown (Table 2). In Hidalgo del Parral, the urinary F was not associated with water F concentration but was marginally high in those whose brush their teeth twice or more per day and was significantly high in boys compared with girls. While in Aldama, urinary F was associated with F concentration in the water, and eGFR and was marginally high in children with low SES. The models were adjusted by urinary specific gravity.

3.3. Kidney and cardiovascular biomarkers The geometric means and IQRs of the traditional kidney biomarkers [eGFR, serum creatinine and blood urea nitrogen (BUN)], the early kidney injury biomarkers (uCys-C and KIM-1) and the cardiovascular biomarkers (cIMT, VCAM-1, ICAM-1, ET-1 and sCys-C) for all and each 9

community are presented in Table 3. Although a 23% of serum samples were above the serum creatinine reference values (>0.7 mg/dL) and 1% above the BUN reference values (>20 mg/dL), no child with reduced eGFR (<60 mL/min/1.73 m2) was found. The GM of uCys-C for all the children was 43.3 ng/mL. Nearly 39% of the samples from both communities were under LOD for KIM-1 (17.3 pg/mL). Regarding vascular biomarkers, only a proportion of 9% (n=29) of serum samples were below the LOD for ET-1, which were replaced by LOD/√2. For all children, the GM for cIMT was 0.43 mm, 1.07 µg/mL to VCAM-1, 0.25 µg/mL to ICAM-1, 4.4 pg/mL for ET-1 and 674 ng/mL for sCys-C. No statistically significant differences between communities for any kidney or cardiovascular biomarker were observed.

3.4. Multiple regression models to kidney biomarkers Robust multiple linear regression models of eGFR, uCys-C and KIM-1 for all children population are presented in Table 4. To ensure the F exposure gradient, it was decided to include all children, regardless of their community of residence, in the multiple regression models. The eGFR was positively and significantly associated with urinary F, physical activity, age, and very high body fat, and negatively associated with total cholesterol. While the uCysC was negatively and statistically significant associated with urinary F. The KIM-1 was not significantly associated with urinary F or other variables in database, however, the familiar history or chronic kidney disease and the total daily energy intake contributed to the model. In addition, due to 39% of samples were below LOD, a multiple imputation was performed as previous described in methods. However, the regression coefficients showed same direction and meaning, and no substantial changes were observed in the model with the imputed values (data not shown). Therefore, the model without imputed values was showed for KIM-1. The eGFR, KIM-1 and uCys-C models included specific gravity as covariates to adjust urine dilution. The multiple regression analysis was performed also using urinary creatinine to adjust urine dilution (Supplementary Material, Table S1) and regression coefficients in same direction and meaning were observed. 10

3.5. Multiple regression models of cardiovascular biomarkers Multiple linear regression models of cardiovascular biomarkers are presented in Table 5. The serum VCAM-1 concentrations were positively and significantly associated with urinary F levels ≥ BE, with height and SHS exposure and, was negatively significant associated with eGFR. While serum ICAM-1 levels were positive and significant associated with urinary F levels ≥ BE, serum uric acid and age, and was higher in boys compared with girls. To ET-1 only a statistically marginal positive association were found with urinary F levels ≥ BE. Additionally, the cIMT was positively and significantly associated with urinary F concentration with an average increase of 0.01 mm per unit increase of urinary F and was marginally associated with daily lipid intake and SBP percentile. Moreover, the sCys-C concentrations were negatively and significantly associated with urinary F, eGFR and daily lipid intake, and positive and significant associated with AI and serum VCAM-1. To cIMT and sCys-C models urinary F was adjusted by specific gravity.

3.6. Sensitivity analysis The inclusion of variables such as BMI, LDL cholesterol, triglycerides and HDL cholesterol did not show changes in models. Outliers were identify based on graphical visualization. Based on Cook´s distance, the data did not show influential points. The regression coefficients exhibited the same direction and meaning when outliers where excluded and when robust analysis was used; for that reason, the outliers were maintained and robust regression analysis was used to show the results (data not shown). The models did not shown evidence of co-linearity (VIF values ranged from 1.00 to 1.43). Moreover, the inclusion of biomarkers and the F concentration adjusted by specific gravity or the inclusion of specific gravity as a co-variate in the models for urinary F, eGFR, uCysC and KIM-1 showed regression coefficients in same direction and meaning (data not shown).

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4.

Discussion The association of F exposure with kidney and cardiovascular toxicity has been reported mainly

in adults, but little is known about its potential toxic effect in susceptible populations such as children. To our knowledge this is the first study to examine the co-evaluation of kidney and vascular biomarkers in children exposed to F. The main findings of this study were the positive associations of urinary F with eGFR and some vascular biomarkers (cIMT, VCAM-1 and ICAM-1), and their negative association with uCys-C and sCys-C levels. Fluoride exposure is mainly by water intake. It is estimated that about 6 million of Mexican children are exposed to high F levels by drinking water (Limón-Pacheco et al., 2018). Our results revealed a relationship of F in drinking water with F exposure biomarkers such as urine F concentration and dental fluorosis in children from Aldama, which suggests that drinking water is the main possible source of F exposure in this community. However, in Hidalgo del Parral, this relationship was not found. Low F concentrations in water were observed but an unexpectedly high proportion of children (65.1%) with urinary F levels ≥ BE and 33.1% with dental fluorosis was observed. Consistent with this, studies conducted in other Mexican regions have reported an increased prevalence of dental fluorosis, a chronic biomarker of F exposure, in schoolchildren exposed to optimal and sub-optimal water F concentrations, indicating the contribution of other potential sources to chronic F exposure (García-Pérez et al., 2013; Perez-Perez et al., 2014). In addition to water, a relationship of toothpaste use with urine F concentration was identified, which suggests that toothpaste is an alternative source of F exposure. However, other sources such as soft drinks, juices, soil ingestion, teas infusions, foods and fluorinated salt consumption are not discarded (Jiménez-Farfán et al., 2011; Sariñana-Ruiz et al., 2017). The high dental fluorosis prevalence observed in Mexico, even in those areas where drinking water contain low F levels (Aguilar-Díaz et al., 2017) indicate a serious problem in chronic exposure to F since childhood. Therefore, we regard that a reevaluation of the “optimal” water F levels based on studies of risk assessment, in which all sources of F exposure are considered, as well as, surveillance and 12

biomonitoring programmes are required in our country to avoid adverse health effects by high F exposure. Previous studies conducted in the study area have been reported dental fluorosis in children and adolescents, and kidney damage in adults exposed to F (Jiménez-Córdova et al., 2018; Rodríguez-Dozal et al., 2005), but in other Mexican populations have also observed neurodevelopmental, immunological and reproductive alterations (Bashash et al., 2016; Ortiz-Pérez et al., 2003), which could be potential toxic effects present in the study population. Several studies provide evidence that F exposure induces kidney injury, especially in the proximal tubule, generating changes such as cytoplasmatic vacuolization, nuclear condensation and apoptosis of tubular cells (Cárdenas-González et al., 2013; Quadri et al., 2018b). KIM-1 is a type 1 transmembrane protein that is up-regulated in the injured proximal tubule epithelial cells in ischaemic and toxic injury (Bonventre, 2014). Whereas Cys-C is a 13-kDa cysteine protease inhibitor that is produced by all nucleated cells that is filtered by the glomerulus and catabolized by proximal tubule cells (Filler et al., 2005). Generally, the urinary Cys-C and KIM-1 concentrations are low in healthy subjects. High concentrations have been considered good biomarkers of kidney injury by toxic environmental exposure (Cárdenas-González et al., 2016; Prozialeck et al., 2016). In the present study, the F exposure was not significantly associated with KIM-1, and an inverse association with uCys-C was found. Our findings differ from those observed in a previous study that was conducted in an adult population in which increased urinary excretions of albumin, Cys-C, osteopontin and KIM-1 associated with F exposure were found (Jiménez-Córdova et al., 2018). A possible explanation of this differences is that children had lower urine levels of F and lower exposure times than adults. The negative association of uCys-C with F exposure may be partially explained by the low sCys-C levels found in the exposed children, which is discussed later. Furthermore, our results revealed increased eGFR associated with F exposure. Lead and cadmium exposure have also been positively associated with eGFR (Buser et al., 2016). However, it remains controversial whether this increase is due to an hyperfiltration stage or a reverse causality effect. In a study by Xiong (2007), F concentrations in drinking water above 2 mg/L were related to kidney 13

damage in healthy children. Likewise, schoolchildren with a mean urinary concentration of 3 µg/mL have exhibited a decreased eGFR (Khandare et al., 2017). Our results do not confirm these findings. Nevertheless, we cannot discard the potential nephrotoxic effect of F in higher exposure scenarios and in susceptible populations such as those with a pre-existing renal impairment, since it has been reported an increased kidney injury in those populations (Quadri et al., 2018b). Therefore, further studies that include other kidney injury biomarkers measurement are required to assess the potential nephrotoxic effect of F exposure in children and susceptible populations. Because drinking water was not the unique source of F exposure, the urine F concentration was more reliable to assess F exposure. Additionally, urine samples were used to quantify the kidney injury biomarkers, due to its stability and non-invasiveness characteristics. However, one of the mayor concern when urine samples are used is the dilution adjustment (Weaver et al., 2016). In our study, the urinary specific gravity and creatinine concentration were used to adjust urine dilution. Traditionally, urinary creatinine is used to urine dilution adjustment. Nonetheless, it concentration is influenced by several factors, which can lead in biased results (Pearson et al., 2009). Therefore, urinary specific gravity adjustment could be more appropriate to urine dilution adjustment in child populations. Moreover, because F exposure and the kidney biomarkers were quantified in the same urine sample, as proposed by Barr (2005) (Barr et al., 2005) specific gravity was included as a covariate to assess the individual contribution of each variable and avoid a biased association of F exposure and kidney biomarkers. Atherosclerosis, the leading cause of cardiovascular damage, has its origins in childhood. It is a systemic inflammatory disease characterized by the accumulation of lipids and fibrous elements within arterial walls (Libby et al., 2011). There is evidence that endothelial dysfunction and inflammatory processes are involved in the early-life atherosclerosis development; for that reason, we focused in some biomarkers associated with that early atherosclerosis event. ET-1, a 21-amino acid peptide mainly produced by endothelial cells, is a potent vasoconstrictor that counteracts the nitric oxide (NO) relaxation effect, of which the increased plasma levels have been associated with 14

hypertension and atherosclerosis (Novo et al., 2014; Xu et al., 2017). There is evidence that excessive F exposure, increase ET-1 levels by oxidative stress generation (Sun et al., 2016) and high plasma levels of ET-1 have been reported in subjects that living in endemic fluorosis areas (Sun et al., 2013), which suggests an association between F exposure and endothelial cell dysfunction. Our results do not confirm those findings. However, a marginal increase of ET-1 in children exposed to high F levels was observed. In contrast, the adhesion molecules VCAM-1 and ICAM-1 are transmembrane glycoproteins, members of the immunoglobulin family, which mediates the firm adhesion of endothelium with circulating leucocytes, which facilitates its subsequent migration into the arterial wall (Schmidt et al., 2016). It has been reported a correlation between the circulating soluble forms of ICAM-1 and VCAM-1 with inflammatory diseases such as atherosclerosis in children (Fotis et al., 2012). In this study, associations of high F exposure with increased VCAM-1 and ICAM-1 levels were observed. Our findings partially agree with those of Liu (2014) who reported significantly high levels of ICAM-1 but not VCAM-1 in adult subjects exposed to F by drinking water. Similarly, previous experimental studies have reported increased expression of one or both adhesion molecules in cells and animals exposed to high F, which suggests an induction of an inflammatory response by that exposure to F (Ma et al., 2017, 2012; Szczepański et al., 2012). Regarding Cys-C, it is potent cysteine protease inhibitor produced by all nucleated cells as previously aforementioned. It has been commonly employed to appraise kidney function; however, it has been recently used as biomarker in CVD. The pathogenesis of atherosclerosis involves the participation of cysteine proteases (cathepsins S, K, B, H, L) and their inhibitor Cys-C to remodelling the extracellular matrix in the arterial walls (Yetkin and Waltenberger, 2009). Generally, high levels of sCys-C are linked to cardiovascular risk; however, it remains controversial, and low sCys-C levels have also been reported in patients with abdominal aortic aneurisms and have been associated with the severity and extent of atherosclerosis burden (Salgado et al., 2013). Our results revealed a reduction of sCys-C with F exposure. Similarly, de Burbure 15

(2006) (de Burbure et al., 2006) reported a decrease of sCys-C levels in children exposed to lead; but the authors attribute this reduction to a possible hyperfiltration stage. In our study, this inverse association was observed after eGFR adjustment. The reduction of sCys-C levels may be explained by it the consumption process against the proteolytic activity increases the atherosclerosis process, and, inflammatory stimulus, oxidative stress, thyroid dysfunction and polymorphisms (van der Laan et al., 2016; Xu et al., 2015); some of these are also associated with F exposure (Jothiramajayam et al., 2014; Ma et al., 2012; Singh et al., 2014). However, the exact mechanism behind the reduction of sCys-C and its association with F exposure, as well as its relationship with physiopathological conditions are not completely understood, and further studies are needed. Functional and morphological changes, such as the thickening of the arterial walls and elastic properties alterations, have been observed in early stages of atherosclerosis since childhood (Hong, 2010) and in adults exposed to F (Varol et al., 2010b). In cIMT, an ultrasound-based measurement of the intima-media space of carotid artery wall is a valuable tool to assess preclinical atherosclerosis due to its simple, reproducible and non-invasive characteristics (Nezu et al., 2016). Increased cIMT has been associated with cardiovascular risk factors, such as metabolic syndrome, obesity, diabetes mellitus and dyslipidaemia in children (Kusters et al., 2014; Rostampour et al., 2017; Rumińska et al., 2017). In the present study, a significant association was observed between F exposure and cIMT. Our results agree with those observed in adult subjects who live in an endemic fluorosis area (Liu et al., 2014), which suggests that F exposures could be related to atherosclerosis. In our study we observed an increased F toxicity in male child, this difference can be partially explained by the conjunction of socio-cultural practices related to gender and observed in this study population such as higher physical activity that may increase the consumption of water and F exposure, as well as high daily energy consumption and higher obesity indicators that may increase susceptibility to cardiovascular injury. However, further studies are necessary to establish the risk of F toxicity related to gender disparities.

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We recognize our study is subject to some limitations, that should be mentioned. Because a cross-sectional study design was performed, no causation could be established. Selection bias could also have occurred due to the non-random selection of participants. We selected the communities based on F and arsenic concentrations in water. However, the F exposure via other sources than drinking water was not under control in the study and there was no information available to identify all the sources of F exposure and estimate its contribution. Therefore, we cannot exclude the possibility of exposure to other environmental toxicants that can interfere in the observed results. Additionally, no historical concentrations of F exposure were available, and the genetic characteristics were not included in the study.

5. Conclusions In summary, our results suggest the presence of other sources of F exposure in addition to drinking water in the study population that may increase the risk of adverse health effects. Likewise, our findings showed inconclusive results (increased eGFR, decreased uCys-C and nonrelationship with F exposure) of the relationship of F exposure in children with kidney injury. However, significant relationships between F exposure and the vascular biomarkers VCAM-1, ICAM-1, sCys-C and cIMT were found. These results suggest that early F exposure may favor the atherosclerotic process and support the growing evidence that F exposure can induce alterations since childhood contributing to the development of cardiovascular diseases. Nevertheless, further longitudinal studies are necessary to establish the risk of atherosclerosis and kidney disease due to F exposure and, to explore its associated mechanisms.

Acknowledgments: This research was supported by grant #239689 and Children´s Environmental Health Network grant #293450 from National Council of Science and Technology (CONACyT-Mexico). M.I.J.C. was a

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recipient of a CONACyT fellowship. The authors are indebted to Anahi Perez-Galicia and Luz C. Sánchez Peña for their technical assistance. The authors gratefully to staff of Faculty of Odontology, University of Chihuahua for dental evaluation. The authors thank all children and their parents who voluntary participate in this study. Conflict of interest The authors declare that there is no conflict of interest

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Fig. 1. Geographic localization of the two communities included in the study Fig. 2. Scatterplot and correlations between water and urine fluoride concentration values by community. Spearman correlation coefficients were showed to Hidalgo del Parral (n=151) and Aldama (n=219)

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Table 1. General characteristics of the study population (n=374) Characteristic Age (years) [mean ± SD (min-max)] Boys (%) Low SES (%) Biochemical analysis [GM (IQR)] Glycaemia (mg/dL) TCol (mg/dL) c-LDL (mg/dL) c-HDL (mg/dL) Triglycerides (mg/dL) AI [mean ± SD (min-max)] Anthropometry Low weight for age (%) Weight for Height z-score [mean ± SD (min-max)] <-2 SD thinness (%) >1 SD overweight (%) >2 SD obese (%) High BF (%) Very high BF (%) Blood pressure SBP (Percentile) [GM (IQR)] DBP (Percentile) [GM (IQR)] Normal (%) Pre-Hypertension (%) Hypertension Grade 1(%) Hypertension Grade 2(%) Physical activity [GM (IQR)] Daily energy intake Total (Kcal) [GM (IQR)] Lipids (Kcal) [GM (IQR)] Fluoride Water (mg/mL) [GM (IQR)] > MPL (1.5) (%) Urinea (µg/mL) [GM (IQR)] > BE (1.2 µg/mL) (%) Dental Fluorosis Very Mild-Severe (%)

9 ± 2 (5-12) 46.8 55.2

Hidalgo del Parral (n=219) 9 ± 2 (6-12) 43.9 68.8

78 (73-83) 158 (142-175) 85 (74-100) 54 (47-63) 66 (46-97) -0.63 ± 0.63 (-2.83-1.12)

79 (73-84) 158 (143-172) 84 (73-96) 55 (49-64) 67 (44-97) -0.68 ± 0.63 (-2.1-1.11)

77 (72-82) 158 (142-179) 88 (75-102) 54 (46-62) 64 (48-97) -0.60 ± 0.63 (-2.1-1.11)

2.1 0.30 ± 1.05 (-3.49-2.98) 1.6 20.3 5.1 28.1 22.2

1.3 0.24 ± 1.0 (-2.09-2.61) 1.3 17.4 3.9 24.5 23.9

2.7 0.34 ± 1.1 (-3.49-2.98) 1.8 22.4 5.9 30.6 21.0

43 (24-73) 74 (58-86) 79.2 9.6 7.2 4.0 1.5 (1.25-1.75)

53 (30-75) 77 (60-90) 74.9 11.6 10.3 3.2 1.17 (1.33-1.58)

38 (22-66)* 73 (58-84) 82.2 8.2 5.0 4.6 1.58 (1.33-1.92)**

1758 (1440-2226) 685 (544-890)

1853 (1518-2310) 702 (555-903)

1715 (1402-2159)* 668 (532-883)

0.3 (0.01-1.9) 37 2.2 (1.6-3.2) 79.7

0.18 (0.2-0.3) 4 1.7 (1.4-2.2) 65.1

1.93 (0.3-2.1)** 60** 2.7 (2.0-3.6)** 89.9**

38.2

33.1

41.7

All (n=374)

Aldama (n=178) 8.5 ± 2 (5-12)* 48.9 45.7**

Abbreviations: SD, standard deviation; GM, geometric mean; IQR, interquartile range, TCol total cholesterol; c-LDL, low density lipoprotein cholesterol; c-HDL, high density lipoprotein cholesterol; AI, atherogenic index; BMI, body mass index; BF, body fat; SBP, systolic blood pressure; DBP, diastolic blood pressure; MPL, maximum permissible limit; BE, biomonitoring equivalent. *p<0.05, **p<0.001 vs Hidalgo del Parral a Adjusted by specific gravity

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Table 2. Robust multiple linear regression model to urinary fluoride concentration

Predictive variables

Hidalgo del Parral

Aldama

(n=135, R2-adjusted=0.406)

(n=209, R2-adjusted= 0.446)

F in drinking water (mg/L) Urine SG Tooth brushing >2 per day > ½ toothbrush of toothpaste eGFR (mL/min/1.73 m2) Low socioeconomic level Boys

βa

p-value

βa

p-value

0.25 0.06b 0.35 0.14 --0.33

0.131 <0.001 0.056 0.233 --0.009

0.39 0.11b --0.02 0.22 --

<0.001 <0.001 --0.004 0.093 --

Abbreviatures: F, fluoride; SG, specific gravity; eGFR, estimated glomerular filtration rate. a

Average difference of urinary F per unit variation of the independent variable Average change per 0.010 SG increase

b

Table 3. Kidney and cardiovascular kidney biomarkers Total

Hidalgo del Parral

Aldama

Characteristic n

MG (IQR)

n

MG (IQR)

n

MG (IQR)

Kidney biomarkers sCreatinine (mg/dL) BUN (mg/dL) eGFRa (mL/min/1.73 m2) uCys-C (ng/mL) KIM-1 (pg/mL)

374 372 324 366 227

0.7 (0.6-0.7) 10 (8-12) 90 (85-98) 43.3 (24.2-81.1) 179 (75-359

155 153 114 147 93

0.7 (0.6-0.8) 9 (8-11) 90 (85-96) 45.9 (15.8-97.4) 170 (77-352)

219 219 210 219 134

0.7 (0.6-0.7) 10 (9-12) 92 (85-99) 42.2 (27.0-73.1) 182 (67-357)

Cardiovascular biomarkers cIMT (mm) VCAM-1 (µg/mL) ICAM-1 (µg/mL) ET-1 (pg/mL) sCys-C (ng/mL)

371 357 357 307 326

0.43 (0.4-0.48) 1.07 (0.91-1.28) 0.25 (0.19-0.32) 4.4 (1.6-5.1) 676 (618-730)

155 141 141 118 116

0.43 (0.39-0.48) 1.07 (0.89-1.29) 0.25 (0.18-0.31) 2.6 (1.6-5.1) 688 (609-761)

216 216 216 189 210

0.43 (0.4-0.48) 1.07 (0.91-1.27) 0.25 (0.20-0.32) 4.4 (1.6-5.1) 668 (620-720)

Abbreviations: GM, geometric mean; IQR, interquartile range, eGFR, estimated glomerular filtration rate; BUN, blood urea nitrogen; KIM-1, kidney injury molecule 1; uCys-C, urinary cystatin-C; cIMT, carotid intima media thickness; VCAM-1, vascular adhesion molecule 1; ICAM-1, intracellular adhesion molecule 1; ET-1, endothelin 1; sCys-C, serum cystatin-C. a

Creatinine-cystatin C-based CKiD equation (2012)

Table 4. Robust multiple linear regression model to eGFR, uCys-C and urinary KIM-1. Biomarkers

Predictive Variables 2

eGFR (mL/min/1.73 m ) (n=322, R2= 0.235)

F in urine (µg/mL) Urinary SG Tot-Chol (mg/dL) Physical activity

βa

p-Value

1.3 -0.17b -0.07 2.9

0.015 0.064 <0.001 0.023 26

uCys-C (ng/mL) (n=365, R2= 0.096)

KIM-1 (pg/mL) (n=215, R2= 0.053)

Age (years) High BF Very high BF

2.3 2.0 3.0

<0.001 0.099 0.031

F in urine (µg/mL) Urinary SG SBPp

-8.5 4.8b 0.18

0.043 <0.001 0.178

F in urine (µg/mL) Urinary SG Familiar history CKD Daily energy intake (Kcal)

29.1 2.3b 170.2 0.12

0.212 0.541 0.265 0.065

Abbreviatures: F, fluoride; eGFR, estimated glomerular filtration rate; TChol, total serum cholesterol; BF, body fat; SG, specific gravity; SBPp, systolic blood pressure percentile; uCys-C, Cystatin C in urine; KIM-1, Kidney Injury Molecule 1; CKD, chronic kidney disease. a

Average change per unit variation of the independent variable Average change per 0.010 SG increase

b

Table 5. Robust multiple linear regression model to VCAM-1, ICAM-1, ET-1, cIMT and sCys-C. Biomarker (Dependent variable) VCAM-1 (µg/mL) (n=322, R2=0.074)

ICAM-1 (ng/mL) (n=357, R2 =0.058)

ET-1 (pg/mL) (n=276, R2=0.024)

cIMT (mm) 2

(n=369, R =0.051)

sCys-C (ng/mL) 2

(n=324, R =0.127)

βa

p-Value

F in urine ≥ BE Height z-score Exposure SHS eGFR (mL/min/1.73 m2) Age (years)

111.1 66.6 57.3 -6.9 20.2

0.019 <0.001 0.011 <0.001 0.088

F in urine ≥ BE Uric acid (mg/dL) Age (years) Boys

57.0 32.7 -18.2 56.6

0.032 0.035 0.016 0.024

F in urine ≥ BE eGFR (mL/min/1.73 m2)

0.69 -0.04

0.074 0.068

F in urinec (µg/mL) Daily lipid intake (Kcal) SBPp

0.01 0.04 b 0.0003

0.032 0.076 0.066

F in urinec (µg/mL) AI [log(TG/HDL-c)] eGFRd (mL/min/1.73 m2) VCAM-1 (µg/mL) Daily lipid intake (Kcal) Boys

-9.6 27.7 -2.4 45.0 -0.04 21.8

0.021 0.001 <0.001 0.001 0.021 0.052

Predictive variables

Abbreviatures: F, fluoride; VCAM-1, vascular adhesion molecule 1; ICAM-1, intracellular adhesion molecule 1; cIMT, carotid intima media thickness; sCys-C, serum Cystatin-C; BE, biomonitoring equivalent; SHS, second hand smoke; eGFR, estimated glomerular filtration rate; SBPp, systolic blood pressure percentile; AI, atherogenic index.

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a

Average difference of biomarker change per unit variation of the independent variable

b

Average change per 1000 Kcal increase

c

Adjusted by specific gravity d Estimated with Bedside-Schwartz equation

Highlights 

The relationship of child F exposure with vascular and kidney injury was assessed



The F exposure in children was partially explained by water F levels



Overall, the results were unable to elucidate kidney damage by F exposure



Childhood F exposure was associated with atherosclerotic biomarkers



Decreased serum and urine Cystatin-C levels were related with F exposure

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