Antioxidants and Oxidative Stress in Children: Influence of Puberty and Metabolically Unhealthy Status

antioxidants Article Antioxidants and Oxidative Stress in Children: Influence of Puberty and Metabolically Unhealthy Status Azahara I. Rupérez 1,†, María D. Mesa 2,3,†, Augusto Anguita-Ruiz 2,3,4 , Esther M. González-Gil 1,2,4 , Rocío Vázquez-Cobela 4,5, Luis A. Moreno 1,4 ,Ángel Gil 2,3,4 , Mercedes Gil-Campos 4,6 , Rosaura Leis 4,5,7 , Gloria Bueno 1,4,8,* and Concepción M. Aguilera 2,3,4 1GENUD Research Group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria (IIS) Aragón, University of Zaragoza, 50013 Zaragoza, Spain; [email protected] (A.I.R.); [email protected] (E.M.G.-G.); [email protected] (L.A.M.) 2Department of Biochemistry and Molecular Biology II, Institute of Nutrition and Food Technology “JoséMataix”, Center of Biomedical Research, University of Granada, Armilla, 18016 Granada, Spain; [email protected] (M.D.M.); [email protected] (A.A.-R.); [email protected] (Á.G.); [email protected] (C.M.A.) 3Instituto de Investigación Biosanitaria ibs, 18014 Granada, Spain 4CIBEROBN, (Physiopathology of Obesity and Nutrition Network) Institute of Health Carlos III (ISCIII), 28029 Madrid, Spain; [email protected] (R.V.-C.); [email protected] (M.G.-C.); [email protected] (R.L.) 5Pediatric Gastroenterology, Hepatology and Nutrition Unit. Pediatric Department, Clinic University Hospital of Santiago, Instituto de Investigación Sanitaria de Santiago (IDIS), 15706 Santiago de Compostela, Spain 6Metabolism and Investigation Unit, Reina Sofia University Hospital, Maimónides Institute of Biomedicine Research of Córdoba (IMIBIC), University of Córdoba, 14004 Córdoba, Spain 7Unit of Investigation in Nutrition, Growth and Human Development of Galicia, Pediatric Department, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain 8Pediatric Endocrinology Unit, Clinic University Hospital Lozano Blesa, Facultad de Medicina, Universidad de Zaragoza, 50009 Zaragoza, Spain *Correspondence: [email protected]; Tel.: +34-619-223-420 †These authors contributed equally to this work. Received: 4 June 2020; Accepted: 13 July 2020; Published: 15 July 2020   Abstract: Oxidative stress could help explain the relationship between childhood obesity and a metabolically unhealthy (MU) status. Moreover, puberty could also influence this relationship, since it entails physiological cardiometabolic changes. We aimed to evaluate plasma antioxidants and oxidative stress biomarkers in MU and metabolically healthy (MH) prepubertal and pubertal children and their associations with pro-inflammatory and endothelial damage biomarkers, taking puberty into account. A total of 1444 Spanish children aged 3–17 years (48.9% males, 66% prepubertal, 47.1% with obesity) were recruited. Blood pressure, anthropometric and biochemical parameters were measured, and children were categorized as having a MU or MH status according to risk factors. Retinol, carotenes, tocopherols, total antioxidant capacity (TAC), oxidized low-density lipoprotein and selected pro-inflammatory and endothelial damage biomarkers were analyzed. General linear models adjusted for age, sex, recruitment center and body mass index, partial correlations and stepwise linear regressions were performed. Lower carotenes and tocopherols levels were found in MU than in MH children. Plasma TAC was lower in prepubertal and higher in pubertal children with obesity compared to normal-weight children. Antioxidants and oxidative stress biomarkers showed novel associations with several pro-inflammatory and endothelial damage biomarkers, with pubertal differences, supporting the importance of considering both the antioxidant and oxidative stress status and puberty in the prevention of metabolic diseases in childhood. Antioxidants 2020,9, 618; doi:10.3390/antiox9070618 www.mdpi.com/journal/antioxidants Antioxidants 2020,9, 618 2 of 19 Keywords: carotenoids; tocopherols; oxidized low-density lipoprotein; inflammatory biomarkers; childhood obesity; metabolically healthy; metabolic syndrome 1. Introduction Overweight and obesity are increasing worldwide, having become important health issues in childhood [ 1 ]. Sedentariness, low physical activity, and unhealthy diets are the greatest contributors to this epidemic [ 2 ]. Obesity is frequently associated with the presence of hypertension, dyslipidemia, and insulin resistance, which have been clustered under the term of metabolically unhealthy (MU) status. However, there are also individuals with obesity who do not present any of these cardiometabolic derangements, known as metabolically healthy (MH) [ 3 ]. Although there are several available definitions of MU status, there is evidence that both childhood obesity and MU status increase cardiovascular disease risk in adulthood [ 4 , 5 ]. Moreover, systemic inflammation and endothelial damage have also been described in children with obesity [ 6 , 7 ], as well as increased oxidative stress [ 8 , 9 ]. The relationship between oxidative stress, obesity, and cardiometabolic disease seems to be a consequence of low-grade inflammation [ 10 ]. In addition, in the presence of excess weight, a decreased antioxidant defense could further contribute to a higher cardiometabolic risk [ 11 ]. However, these changes are often complex to detect, due to the homeostatic responses of the organism, as well as to changes associated with childhood development, such as the onset of puberty [ 12 ]. Indeed, puberty entails a physiological insulin resistance that influences oxidative stress and inflammation [ 13 , 14 ]. Furthermore, it could accelerate cardiometabolic alterations, since it has been observed that puberty worsens endothelial dysfunction in young patients with type 1 diabetes [ 15 ]. Also, puberty reduces insulin sensitivity and triggers hyperinsulinemia, both having a reciprocal relationship with endothelial dysfunction [ 16 ]. Taken together, these findings show that puberty influences insulin resistance and oxidative stress, known to contribute to the development and progression of cardiometabolic risk and, particularly, endothelial damage [12]. Children and adolescents with obesity often follow inadequate diets, characterized by a low intake of fruits and vegetables and high intake of sugars and fats, associated with a negative antioxidant status [ 17 – 19 ]. Dietary vitamins such as carotenoids and tocopherols are of great interest as bioactive compounds with antioxidant properties and potential positive effects on adipogenesis, lipid, and glucose metabolisms [ 20 , 21 ], since they are involved in lipid metabolism and adipocyte differentiation [ 22 ]. Serum circulating concentrations of carotenes have been negatively associated with obesity [ 23 ] and metabolic syndrome in children [ 11 ], and in adults and adolescents [ 24 ]. As for tocopherols, their levels are lower in children with obesity, hypertension [ 25 ], and metabolic syndrome [ 11 ], and negatively associated with body mass index (BMI), waist circumference (WC) [ 26 ], and C reactive protein (CRP) plasma/serum levels [ 27 ]. Lower serum or plasma total antioxidant capacity (TAC) has also been associated with metabolic syndrome in children, adolescents and adults [ 11 , 28 ]. In addition, increased circulating oxidized low-density lipoproteins (ox-LDL) plasma levels have already been observed in children with obesity [ 29 ]. However, most available studies to date have investigated individual cardiometabolic alterations, type 1 diabetes, or obesity, without considering important aspects such as puberty or studying its influence on their findings. In fact, pubertal children have shown higher plasma levels of lipoperoxidation products than prepubertal children [ 14 ]. In addition, puberty has been shown to influence endothelial function and blood antioxidant enzymes in patients with type 1 diabetes [ 15 ]. However, broader studies are required to investigate the close relationship between puberty and antioxidant and oxidative stress biomarkers in terms of their impact on MU status risk, understood as the presence of one or more cardiometabolic alterations (hypertension, hyperglycemia, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C) or insulin resistance; as well as its association with inflammation and endothelial damage biomarkers. Antioxidants 2020,9, 618 3 of 19 The aims of the present study were: (1) To analyze and compare circulating plasma concentrations of retinol, carotenes, tocopherols, TAC, and ox-LDL in prepubertal and pubertal children, (2) to study the association between a MH or MU status and circulating plasma concentrations of the mentioned antioxidants and oxidative stress biomarkers, and (3) to analyze their potential associations with biomarkers of inflammation and endothelial damage, in a group of Spanish children aged 3 to 17 years. 2. Materials and Methods 2.1. Population A total of 1444 children (706 males and 738 females), aged 3 to 17 years, were recruited at three Spanish Hospitals (Hospital Universitario Reina Sof í a in C ó rdoba, Hospital Cl í nico Universitario in Santiago de Compostela, and Hospital Cl í nico Universitario Lozano Blesa in Zaragoza) in the GENOBOX case-control study [ 30 ]. Inclusion criteria were: Caucasian ethnicity, children and adolescents aged 3 to 17 and having normal-weight (controls) or overweight or obesity. Exclusion criteria were: Presence of diabetes mellitus, presence of congenital, chronic, or inflammatory disease, psychomotor disability, use of hormonal medication or other that modifies blood pressure, glucose or lipid metabolism, having performed intense exercise in the 24 h previous to the examination, and/or having participated in a research study in the previous three months. Written informed consent was obtained from parents or caregivers, and children gave their assent, after fully explaining the study protocol. The study protocol was approved by the local Ethics Committees of each participating hospital (Code IDs: C ó rdoba 01/2017, Santiago 1011/198, Zaragoza 10/2010). The study was performed according to the ethical guidelines of the Edinburgh revision of Declaration of Helsinki (2000). 2.2. Clinical and Anthropometric Examination Clinical features and Tanner stage according to puberty developmental signs were evaluated by clinicians. From the studied population, 953 children were prepubertal (Tanner stage I) and 491 were at higher pubertal stages (Tanner stages II–V) [31]. Weight and height were measured according to standard international procedures with the children barefooted and in their underwear. BMI was calculated as height (m)/weight (kg) 2 . Children where then categorized according to their BMI status as having normal-weight (406 children: 28.1%, of which 53.7% were males), overweight (358 children: 24.8%, of which 41.6% were males) and obesity (680 children: 47.1%, of which 49.9% were males) (Table S1), using the International Obesity Task Force definition [32]. Blood pressure (BP) was measured from the non-dominant upper arm by a trained staffmember in a quiet, temperature-controlled room, using an automatic device (Omron M4-I Intellisense, Omron Corporation, Osaka, Japan) after a 20-min rest. Three values were taken at 2-min intervals and the average of the two closest measures was used for further analyses. 2.3. Blood Sampling Blood samples were taken in a fasting state between 8:00 and 11:00 am and were centrifuged immediately. Serum glucose, triacylglycerols (TAG), HDL-C and LDL cholesterol (LDL-C) concentrations were measured in fresh samples using the clinical analysis system Roche Hitachi Modular DPP (Roche, Basel, Switzerland). Fasting serum insulin was determined in fresh samples using an Elecsys Modular E-170 (Roche, Basel, Switzerland). The Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was calculated based on the published equation: HOMA-IR = fasting glucose (mmol) × fasting insulin ( µ U/mL)/22.5 [ 33 ]. After centrifugation, plasma aliquots and blood erythrocytes were separated and frozen at −80 ◦C until further analyses. Antioxidants 2020,9, 618 4 of 19 2.4. Plasma Antioxidants and Ox-LDL Analysis Measurement of plasma concentrations of retinol, carotenes and tocopherols were determined after extraction with 1-propanol by ultra-high-pressure liquid chromatography coupled to mass spectrometry (UHPLC-MS), using methanol 0.1% and isocratic formic as solvent, with a flow of 0.5 mL/min in a ACQUITY UPLCr BEH C18 50 mm column (internal diameter 2.1 mm and particle size 1.7 µ m) [ 34 ]. Concentrations were expressed in µ g/dL for retinol and total carotenes, and in mg/dL for total tocopherols. In addition, plasma carotenes and tocopherols ratio to TAG were also calculated. Plasma TAC was determined using a commercial antioxidant assay kit (Cat no. 709001, Cayman Chemical, Ann Arbor, MI, USA). Plasma ox-LDL (coefficient of variation [CV]: 7.8%) was determined with an enzymatic immunoassay (Cat no. BI-20042, Biomedica Medizinprodukte GmbH & Co KG, Vienna, Austria). 2.5. Plasma Pro-Inflammatory and Endothelial Damage Biomarkers Analysis Plasma pro-inflammatory and endothelial damage biomarkers were measured using commercial LINCOplex TM kits of human monoclonal antibodies (Linco Research, St. Charles, MO, USA) on a Luminex ® 200TM System (Luminex Corporation, Austin, TX, USA). Plasma active plasminogen activator inhibitor-1 (aPAI-1) was measured with the HADK1-61K-A kit (CV: 6.6%). Interleukin (IL)-6 (CV: 7.8%), IL-8 (CV: 7.9%), monocyte chemoattractant protein 1 (MCP-1) (CV: 6%), hepatocyte growth factor (HGF) (CV: 3%) and tumor necrosis factor alpha (TNF α ) (CV: 7.8%) were measured using the HADK2-61K-B kit. Myeloperoxidase (MPO) (CV: 12.3%), matrix metalloproteinase 9 (MMP-9) (CV: 6.8%) and total PAI-1 (tPAI-1) (CV: 11.8%) were measured with the HCVD1-67 AK kit. High sensitivity CRP (hsCRP) (CV: 4%) was determined by particle-enhanced turbidimetric immunoassay (Dade Behring Inc., Deerfield, IL, USA). 2.6. Metabolic Health Definition Children were classified in relation to the presence of a MU status according to the five published criteria [ 7 , 35 ]: Systolic or diastolic BP ≥ 90th percentile for age, sex and height; glucose ≥ 100 mg/dL; TAG >90th percentile for age, sex and race; HDL-C serum concentration <10th percentile for age and sex; and elevated HOMA-IR, as described previously [ 7 ]. HOMA-IR cutoffs were ≥ 2.5 for prepubertal children and ≥ 3.38 or ≥ 3.905 for pubertal males or females, respectively, these cutoffs were previously obtained from the present population as described in [ 36 ] due to the absence of reference values [ 37 ]. A total of 767 children (47.5% males) fulfilled one or more criteria and were thus considered to have a MU status (Tables S1 and S2). 2.7. Dietary Assessment Food frequency consumption was evaluated with a qualitative food frequency questionnaire that included common foods consumed in Spain. The children and their caregivers were interviewed, and consumption frequency of each food item was recorded as never or hardly ever; once, 2–3, 4–6, or >6 times per day; once, 2–4 or 5–6 times per week; and 1–3 times per month. Coded answers were then converted into times per week and standardized Z-scores were obtained to use in further analyses. Groups of individual foods high in carotenes (cooked and raw vegetables, fruit with and without sugar and fruit juices) or tocopherols (nuts, seeds, vegetable oils and mayonnaise) were created by summing their standardized values into new variables, according to the Spanish Food Composition Database [38]. 2.8. Statistical Analysis Descriptive statistics, included evaluation of the distribution of continuous variables, were evaluated using the Kolmogorov–Smirnov test and through visualization of histogram plots. Non-normally distributed variables (aPAI-1, carotenes, carotenes/TAG, HGF, hsCRP, IL-6, IL-8, MCP-1, Antioxidants 2020,9, 618 5 of 19 MMP-9, TNF α , and tocopherols/TAG, tPAI-1, ox-LDL) were ln-transformed for statistical analyses. Student’s t-test was applied to evaluate differences in the descriptive characteristics of the participants. General linear regression models adjusted by sex, age, recruitment center and BMI were used to compare concentrations of antioxidant biomarkers, ox-LDL and standardized consumption frequency of carotene and tocopherol-rich foods between the study groups (male vs. female, prepubertal vs. pubertal, MH vs. MU, etc.). Partial correlations adjusted by age, sex, and BMI were used to analyze the relationship between antioxidant biomarkers and ox-LDL among themselves and the rest of studied biomarkers (cardiometabolic variables and biomarkers of inflammation and endothelial damage). Finally, forward stepwise multiple regression analysis (including age, sex, recruitment center, and BMI as confounders) were carried out to evaluate what antioxidant and oxidative stress biomarkers (independent variables) could be considered as predictors of inflammatory risk and endothelial damage (dependent variables). 3. Results 3.1. Antioxidant and Oxidative Stress Biomarkers in Prepubertal and Pubertal Children According to Metabolic Health and Obesity A description of the participants can be found in Appendix Aand Supplementary Table S1. Our analyses showed significantly higher TAC in pubertal compared to prepubertal children independently of BMI (Table 1). Due to these observed differences between prepubertal and pubertal children, as well as to the different cutoffs of the applied criteria to classify the children as MH or MU, all subsequent analyses were stratified by pubertal status. Table 1also shows the results of the BMI-adjusted general linear models run to study the association between the different antioxidant and oxidative stress biomarkers with MU status. We found significantly lower plasma tocopherols/TAG and carotenes/TAG levels and higher ox-LDL concentrations in prepubertal MU compared with MH children. Pubertal children with a MU status also showed lower concentrations of retinol, tocopherols/TAG and carotenes/TAG concentrations than MH participants. Table 1. Plasma antioxidant and oxidative stress biomarkers according to metabolic health and pubertal status. All MH MU p nMean SD nMean SD nMean SD Prepubertal Retinol (µg/dL) 705 26.2 7.0 319 25.7 6.6 342 26.6 7.5 0.456 Carotene/TAG 104705 20.31 19.77 319 25.97 21.94 342 14.07 12.61 0.000 Tocopherols/TAG 103706 14.3 6.4 320 16.5 6.4 342 12.0 5.6 0.000 TAC (mM eq. Trolox) 781 1.95 ** 0.82 359 2.06 0.80 375 1.86 ** 0.81 0.336 Ox-LDL (mg/L) 579 1.95 1.88 288 1.86 1.90 259 2.01 1.81 0.002 Pubertal Retinol (µg/dL) 279 30.9 8.6 102 31.6 8.6 168 30.3 8.6 0.048 Carotene/TAG 104272 14.49 13.03 102 19.03 14.58 163 10.90 8.54 0.000 Tocopherols/TAG 103277 12.9 6.1 102 15.4 6.6 168 11.1 5.1 0.000 TAC (mM eq. Trolox) 391 2.16 ** 0.90 169 2.07 0.80 209 2.25 ** 0.97 0.430 Ox-LDL (mg/L) 189 1.51 1.62 80 1.37 1.53 104 1.60 1.71 0.414 Mean and standard deviation (SD) of the studied biomarkers for children with MH or MU status, stratified by pubertal status. p: Statistical significance of the general linear model (adjusted for sex, age, recruitment center and BMI) for MU status (independent variable) and individual biomarkers (dependent variables). ** Statistical significance (p<0.01) of the general linear model (adjusted for sex, age, recruitment center, and BMI) between prepubertal and pubertal children within each category (columns). Carotene/TAG, Tocopherols/TAG and ox-LDL were ln-transformed for statistical analyses. BMI: body mass index; MH: metabolically healthy; MU: metabolically unhealthy; ox-LDL: oxidized low-density lipoprotein; TAC: total antioxidant capacity; TAG: triacylglycerols. We also evaluated the association between the assessed vitamins and oxidative stress markers with obesity in order to corroborate previous findings. Differences in plasma biomarker concentrations between children with normal-weight or overweight/obesity are shown in Table S3. We observed Antioxidants 2020,9, 618 6 of 19 higher plasma retinol concentrations in prepubertal children with overweight/obesity compared to normal-weight children, while plasma carotenes/TAG and tocopherols/TAG were significantly lower in both prepubertal and pubertal children with overweight/obesity compared to normal-weight children. TAC showed an opposite behavior in prepubertal and pubertal children, being significantly lower in prepubertal and higher in pubertal overweight/obese children compared with their normal-weight counterparts. No significant differences were observed for ox-LDL between children with normal-weight or overweight/obesity. Next, Figure 1shows the plasma antioxidant vitamins and ox-LDL stratified according to MH/MU status, weight categories (normal-weight, overweight, and obesity), and pubertal status. Plasma retinol values (Figure 1a) vary within a narrow range and show significant differences between prepubertal children with MH normal-weight compared to children with MU obesity. Regarding carotenes/TAG (Figure 1b) and tocopherols/TAG (Figure 1c) ratios, the figure illustrates how obesity and MU status display a cumulative effect in these antioxidant markers, which are at significantly lower values in children with overweight or obesity and a MU status, both in prepubertal and pubertal children. In addition, it can be observed how TAC (Figure 1d) behaves in an opposite manner in prepubertal vs. pubertal children, which depends on weight rather than MU status. Finally, ox-LDL does not show statistically significant differences among the compared groups (Figure 1e). Antioxidants 2020, 9, x FOR PEER REVIEW Figure 1. Mean values of plasma retinol (a), carotenes/TAG (b), tocopherols/TAG (c), TAC (d), and ox-LDL (e) of prepubertal and pubertal children, according to their weight categories (normal-weight, overweight, and obesity) and metabolic health (healthy or unhealthy) status. Within each pubertal category, different letters indicate significant differences at p < 0.05 in pairwise comparisons of the general linear model adjusted for sex, age and recruitment center, (sharing the same letters indicates no significant differences between groups, absence of letters indicates no significant differences between any of the groups). MH: metabolically healthy; MU: metabolically unhealthy; ox-LDL: oxidized low-density lipoprotein; TAC: total antioxidant capacity; TAG: triacylglycerols. 3.2. Evaluation of the Dietary Sources of Carotenes and Tocopherols and Their Influence on Carotene/TAG and Tocopherol/TAG Levels Next, we compared the standardized consumption frequency of carotene- and tocopherol-rich foods between children with or without excess weight and MU status (Table 2). We observed a significantly lower consumption frequency of tocopherol-rich foods in MU compared with MH prepubertal children, independently of BMI and no differences in the consumption frequency of carotene-rich foods. The partial correlation analysis (adjusted by age, sex and BMI) between the consumption frequency of carotene or tocopherol-rich foods and plasma carotene/TAG and tocopherols/TAG concentrations, respectively, stratified by the children’s weight status (normal-weight, overweight, obesity) showed a positive association between the standardized consumption frequency of carotene-rich foods and plasma carotene/TAG concentrations (R = 0.367, p = 0.009) exclusively in normal-weight children, which was only confirmed in the pubertal group (R = 0.727, p = 0.005) in the puberty-stratified analysis (data not shown). Figure 1. Mean values of plasma retinol ( a ), carotenes/TAG ( b ), tocopherols/TAG ( c ), TAC ( d ), and ox-LDL ( e ) of prepubertal and pubertal children, according to their weight categories (normal-weight, overweight, and obesity) and metabolic health (healthy or unhealthy) status. Within each pubertal category, different letters indicate significant differences at p<0.05 in pairwise comparisons of the general linear model adjusted for sex, age and recruitment center, (sharing the same letters indicates no significant differences between groups, absence of letters indicates no significant differences between any of the groups). MH: metabolically healthy; MU: metabolically unhealthy; ox-LDL: oxidized low-density lipoprotein; TAC: total antioxidant capacity; TAG: triacylglycerols. Antioxidants 2020,9, 618 7 of 19 3.2. Evaluation of the Dietary Sources of Carotenes and Tocopherols and Their Influence on Carotene/TAG and Tocopherol/TAG Levels Next, we compared the standardized consumption frequency of carotene- and tocopherol-rich foods between children with or without excess weight and MU status (Table 2). We observed a significantly lower consumption frequency of tocopherol-rich foods in MU compared with MH prepubertal children, independently of BMI and no differences in the consumption frequency of carotene-rich foods. The partial correlation analysis (adjusted by age, sex and BMI) between the consumption frequency of carotene or tocopherol-rich foods and plasma carotene/TAG and tocopherols/TAG concentrations, respectively, stratified by the children’s weight status (normal-weight, overweight, obesity) showed a positive association between the standardized consumption frequency of carotene-rich foods and plasma carotene/TAG concentrations (R =0.367, p=0.009) exclusively in normal-weight children, which was only confirmed in the pubertal group (R =0.727, p=0.005) in the puberty-stratified analysis (data not shown). Table 2. Standardized consumption frequency of carotene-rich and tocopherol-rich foods in metabolically unhealthy and healthy children, by pubertal status. Prepubertal Pubertal MH MU MH MU nMean SD nMean SD p n Mean SD nMean SD p Carotene-rich foods Z-score 122 − 0.02 2.79 184 − 0.16 2.47 0.738 122 − 0.51 2.08 162 0.11 2.25 0.152 Cooked vegetables Z-score 122 0.08 1.10 184 − 0.14 0.92 0.238 122 − 0.17 0.74 162 0.15 1.06 0.024 Raw vegetables Z-score 122 − 0.17 1.07 184 − 0.11 0.91 0.968 122 − 0.15 0.93 162 0.11 0.93 0.412 Fruit (no sugar) Z-score 122 − 0.06 1.02 184 0.02 0.97 0.785 122 − 0.14 0.93 162 0.10 1.09 0.220 Fruit (sugar) Z-score 122 0.01 0.93 184 0.06 1.10 0.811 122 − 0.16 0.66 162 − 0.07 0.83 0.464 Juices Z-score 122 0.11 1.02 184 0.02 1.00 0.790 122 0.12 1.08 162 − 0.18 0.91 0.115 Tocopherol-rich foods Z-score 122 0.34 2.11 184 − 0.18 1.91 0.018 122 0.04 1.84 162 0.14 1.77 0.354 Nuts +Seeds Z-score 122 0.14 1.06 184 − 0.18 0.88 0.029 122 − 0.05 1.00 162 0.13 1.04 0.120 Vegetable oils Z-score 122 0.10 1.00 184 − 0.03 0.98 0.374 122 0.11 1.03 162 0.07 0.93 0.946 Mayonnaise Z-score 122 0.10 1.11 184 0.04 1.09 0.144 122 − 0.03 0.89 162 − 0.05 0.91 0.898 Mean and standard deviation (SD) of the standardized Z-score of the consumption frequency of foods rich in carotenes and tocopherols for children with MH or MU status, stratified by pubertal status. pvalue indicates statistical significance of the general linear model adjusted by sex, age, recruitment center and BMI. MH: metabolically healthy; MU: metabolically unhealthy. 3.3. Exploring the Relationship between Antioxidants and Oxidative Stress Biomarkers and Cardiometabolic, Pro-inflammatory and Endothelial Damage Markers A partial correlation analysis was conducted to evaluate the relationship between antioxidant and oxidative stress biomarkers among themselves (Table 3). As could be expected, carotenes/TAG and tocopherols/TAG were strongly and positively correlated with each other (R >0.500, p<0.001) in the total and puberty stratified analyses. Less strong correlations were observed between retinol and tocopherols/TAG (R >0.200, p<0.001). Retinol and tocopherols/TAG were also negatively correlated with ox-LDL when analyzing the total sample (p<0.001). Antioxidants 2020,9, 618 8 of 19 Table 3. Partial correlation analyses between analyzed plasma antioxidants and ox-LDL. Retinol (µg/dL) Carotenes/TAG Tocopherols/TAG TAC (mM eq.Trolox) nCorr. nCorr. nCorr. nCorr. Prepubertal children Retinol (µg/dL) Carotenes/TAG 700 0.063 Tocopherols/TAG 700 0.200 *** 700 0.532 *** TAC (mM eq.Trolox) 574 −0.006 574 −0.011 574 0.010 ox-LDL (mg/L) 572 −0.141 *** 572 −0.041 572 −0.130 ** 575 −0.003 Pubertal children Retinol (µg/dL) Carotenes/TAG 266 0.120 Tocopherols/TAG 272 0.316 *** 266 0.598 *** TAC (mM eq.Trolox) 182 −0.011 181 −0.011 182 −0.026 ox-LDL (mg/L) 181 −0.140 180 −0.261 *** 181 −0.187 * 184 −0.132 Total sample Retinol (µg/dL) Carotenes/TAG 971 0.075 * Tocopherols/TAG 977 0.242 *** 971 0.548 *** TAC (mM eq.Trolox) 761 −0.026 760 0.028 761 0.022 ox-LDL (mg/L) 758 −0.125 *** 757 −0.085 * 758 −0.131 *** 764 −0.012 Partial correlation adjusted for sex, age and body mass index in the total samples and separately by pubertal stage, superscript letters indicate statistical significance (* p<0.05, ** p<0.01 y *** p<0.001). All variables were logarithmically transformed for analyses except retinol and TAC. ox-LDL: oxidized low-density lipoprotein; TAC: total antioxidant capacity; TAG: triacylglycerols. When studying the correlation between the analyzed antioxidants and oxidative stress biomarkers and cardiometabolic variables (Table 4), we found a negative correlation between carotenes/TAG and tocopherols/TAG and insulin and HOMA-IR (all R = − 0.170, p<0.01) in the total sample and puberty-stratified analyses. Retinol was positively correlated with cholesterol and TAG in all analyses (R >0.140, p<0.001). TAC was negatively correlated with SBP in the total sample (R = − 0.087, p<0.01 ) and prepubertal children (R = − 0.103, p<0.01), negatively correlated with HDL-C in the total sample (R = − 0.86, p<0.01) and pubertal children (R = − 0.118, p<0.05), and positively correlated with TAG in the total sample (R =0.087, p<0.01) and pubertal children (R =0.162, p<0.01). (Table 4). Finally, we examined the association between the analyzed antioxidants and oxidative stress biomarkers and pro-inflammatory and endothelial damage biomarkers, in the total sample and stratifying by pubertal stage. We first performed a partial correlation analysis to identify potential associations between the studied biomarkers (Table S4). In view of the multiple observed associations, we conducted a forward stepwise multiple regression analysis which results are shown in Table 5. We found a strong positive association between ox-LDL and tPAI-1 in both the total and puberty stratified analyses. Retinol was positively associated with MCP-1, TNF α , aPAI-1, and tPAI-1, and negatively associated with hsCRP and MPO in prepubertal children, and in the total sample (with slightly less significant associations). Similarly, carotenes/TAG values were negatively associated with aPAI-1 and tPAI-1. Plasma tocopherols/TAG were positively associated with TNF α and plasma TAC was negatively associated with MPO in prepubertal children and in the total sample. Concerning significant associations in pubertal children, a strong positive association was found between TAC and MCP-1 and TNF α , paralleled by a less significant positive association between ox-LDL and MCP-1. Also, negative associations were observed between plasma tocopherols/TAG and IL-8 concentrations, and between TAC and tPAI-1 in both pubertal children and the total sample. Antioxidants 2020,9, 618 9 of 19 Table 4. Partial correlation analyses between plasma antioxidants and ox-LDL and metabolically unhealthy status components. SBP (mm Hg) DBP (mm Hg) Glucose (mg/dL) Insulin (mU/L) HOMA-IR Chol (mg/dL) TAG (mg/dL) HDL-C (mg/dL) nCorr. nCorr. nCorr. nCorr. nCorr. nCorr. nCorr. nCorr. Prepubertal children Retinol (µg/dL) 665 0.014 665 −0.051 700 0.063 673 0.075 673 0.071 700 0.206 *** 700 0.154 *** 690 −0.038 Carotenes/TAG * 665 −0.004 665 −0.021 700 −0.046 673 −0.223 *** 673 −0.210 *** 700 0.050 700 NA 690 0.288 *** Tocopherols/TAG * 665 −0.052 665 −0.062 700 −0.095 * 673 −0.223 *** 673 −0.213 *** 700 0.030 700 NA 690 0.367 *** TAC (mM eq.Trolox) 735 −0.103 ** 735 −0.031 775 0.046 740 −0.003 739 0.006 776 0.038 776 0.055 774 −0.057 ox-LDL (mg/L) * 544 0.056 544 0.074 577 0.051 555 −0.014 555 −0.013 577 0.022 577 0.062 575 −0.110 ** Pubertal children Retinol (µg/dL) 266 0.023 266 0.099 273 0.022 270 0.050 270 0.045 272 0.231 *** 272 0.142 * 267 0.167 ** Carotenes/TAG * 259 −0.146 259 −0.050 266 −0.085 263 −0.170 ** 263 −0.171 ** 266 0.006 266 NA 261 0.285 *** Tocopherols/TAG * 265 0.015 265 0.014 272 −0.094 269 −0.237 *** 269 −0.239 *** 272 0.039 272 NA 267 0.389 *** TAC (mM eq.Trolox) 376 −0.063 376 −0.061 385 −0.023 377 0.009 376 0.002 386 0.026 386 0.162 ** 382 −0.118 * ox-LDL (mg/L) * 179 0.009 179 −0.042 184 0.187 * 182 0.094 182 0.118 184 −0.068 184 0.065 183 −0.038 Total sample Retinol (µg/dL) 936 0.036 936 0.012 978 0.071 * 948 0.057 948 0.055 977 0.217 *** 977 0.142 *** 962 −0.006 Carotenes/TAG * 929 −0.059 929 −0.050 971 −0.075 * 941 −0.189 *** 941 −0.185 *** 971 0.031 971 NA 956 0.285 *** Tocopherols/TAG * 935 −0.041 935 −0.053 977 −0.113 *** 947 −0.236 *** 947 −0.233 *** 977 0.026 977 NA 962 0.357 *** TAC (mM eq.Trolox) 1116 −0.087 ** 1116 −0.052 1165 0.014 1122 0.019 1120 0.020 1167 0.025 1167 0.087 ** 1161 −0.086 ** ox-LDL (mg/L) * 728 0.043 728 0.040 766 0.073 * 742 0.018 742 0.025 766 −0.002 766 0.059 763 −0.104 ** Partial correlation adjusted for sex, age and body mass index in the total samples and separately by pubertal stage, asterisks indicate statistical significance (* p<0.05, ** p<0.01, *** p<0.001 ). * Ln-transformed variable used for analyses. 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