Evaluation of Oxidative Stress in Overweight Subjects With or Without Metabolic Syndrome

Authors


(dcianame@yahoo.com.br)

Abstract

Although oxidative stress is considered the underlying mechanism by which dysfunctional metabolism occurs in obese subjects, there are few studies on oxidative stress in overweight subjects. The objective of this study was to verify the influence of metabolic syndrome (MetS) on oxidative stress and antioxidant defense in overweight subjects. There were 123 subjects (50 in the control group and 73 in the overweight group) chosen to participate in this cross-sectional study. The control group included 50 healthy individuals with a BMI between 20 and 24.9 kg/m2 and without MetS. The overweight group included 73 subjects with a BMI between 25 and 29.9 kg/m2. Overweight subjects were divided into two groups: with MetS (29 subjects) and without MetS (44 subjects). Control group and overweight group subjects without MetS showed no differences in oxidative stress parameters and total antioxidant capacity (TRAP). Overweight subjects with MetS had higher hydroperoxide concentrations measured by chemiluminescence compared to the control group (P < 0.05), higher hydroperoxide and hydrogen peroxide concentrations determined by ferrous oxidation-xylenol orange assay compared to overweight subjects without MetS (P < 0.001), and higher advanced oxidation protein product (AOPP) concentrations (P < 0.001) compared to the other groups. AOPP was directly correlated with uric acid concentrations. Overweight subjects with MetS had lower TRAP concentrations compared to the control group (P < 0.001). In conclusion, this study showed that overweight subjects with MetS, in contrast to overweight subjects without MetS, have a redox imbalance characterized by increased plasma oxidation and reduced antioxidant capacity.

Introduction

Metabolic syndrome (MetS) consists of pathological conditions including insulin resistance, arterial hypertension, obesity, and dyslipidemia, which accelerate atherosclerosis and increase cardiovascular disease risk (1,2). Existing evidence suggests that the incidence of MetS is rising in developed countries and in developing countries such as Brazil (3).

The harmful effects of free radicals, mainly reactive oxygen species (ROS) and/or reactive nitrogen species, have been implicated in the physiopathology of obesity, hypertension, endothelial dysfunction, and MetS (4,5,6), suggesting that oxidative stress may be the underlying mechanism of dysfunctional metabolism in obese subjects (7,8).

Although several studies have been performed to verify the role of oxidative stress in obese subjects with MetS (9,10), few studies have reported its role in overweight subjects (11). Furthermore, the measurement of total antioxidant capacity (TRAP) in conditions associated with hyperuricemia, as in subjects with MetS, may be inaccurate because uric acid concentration is responsible for 60% of total plasma antioxidant capacity. Some reports have verified an unexpected increase in TRAP in MetS subjects (10,12). Thus, a correction of TRAP based on uric acid concentration is needed. We are not aware of any other studies that have reported the influence of MetS on oxidative stress and TRAP in overweight subjects.

Therefore, the aim of this study was to verify the influence of MetS on lipid and protein oxidation and on antioxidant defenses in overweight subjects.

Methods and Procedures

Subjects

There were 123 subjects (50 control subjects and 73 overweight subjects) selected to participate in this cross-sectional study from Internal Medicine ambulatory subjects and healthy workers of the University Hospital of Londrina, Londrina, Brazil. Control and overweight subjects were paired by sex, age, ethnicity, and smoking status; the control group included 50 healthy individuals with a BMI between 20 and 25 kg/m2 and without MetS. The overweight group consisted of 73 subjects with a BMI between 25 and 30 kg/m2. Overweight subjects were divided into two groups: those with MetS (29 subjects) and those without MetS (44 subjects). Information on lifestyle factors and medical history was obtained through clinical evaluation. MetS was defined using the Adult Treatment Panel III criteria (13). A diagnosis of MetS was arrived at for subjects with at least three of the following five characteristics: (i) abdominal obesity: waist circumference ≥102 cm in men and ≥88 cm in women; (ii) hypertriglyceridemia: triglycerides ≥150 mg/dl; (iii) low levels of high-density lipoprotein (HDL) cholesterol: HDL ≤40 mg/dl in men and ≤50 mg/dl in women; (iv) high-blood pressure: blood pressure ≥130/85 mm Hg; and (v) high-fasting glucose: glucose ≥100 mg/dl. None of the subjects presented with thyroid, renal, hepatic, gastrointestinal, or oncological disease, and none of the subjects had clinically evident infections had not had hormone replacement therapy or taken medications to treat hyperglycemia, medications known to affect lipoprotein metabolism, uric acid metabolism, or inflammatory markers, for at least 4 weeks prior to the study. All individuals gave written informed consent, and the study protocol was fully approved by the ethics committee of the University of Londrina (Londrina, Brazil)

Anthropometric and blood pressure measurements

Height and weight were measured in the morning with subjects wearing light clothing, but no shoes. After 5 min of rest in a sitting position, each subject had his/her blood pressure measured on the left arm. We considered the current use of antihypertensive medication as an indication of high-blood pressure. BMI was calculated as weight (kg) divided by height (m) squared. Waist circumference was measured with a soft tape midway between the lowest rib and the iliac crest while subjects were standing.

Biochemical and inflammatory biomarkers measurements

After fasting for 12 h, blood was obtained from the subjects to measure glucose, total cholesterol, HDL-cholesterol, low-density lipoprotein cholesterol, triacylglycerol, and uric acid, all of which were evaluated using a biochemical auto-analyzer (Dimension Dade AR Dade Behring, Deerfield, IL) and Dade Behring kits. Plasma insulin levels were determined by chemiluminescence microparticle imunno assay (CMIA, ARCHITECT; Abbott Laboratory, Abbot Park, IL). All blood samples were centrifuged at 3,000 r.p.m. for 15 min, and plasma or serum aliquots were stored at −70 °C until assayed. Serum C-reactive protein was measured using a high-sensitivity nephelometric assay (Behring Nephelometer II; Dade Behring, Marburg, Germany). Interassay and intra-assay coefficient variation for all assays were <10% as determined using human serum.

The homeostasis model assessment of insulin resistance (HOMAIR) was used as a surrogate measure of insulin sensitivity (14). HOMAIR = fasting insulin (U/ml) × fasting glucose (mmol/l)/22.5.

Oxidative stress measurements

The measurements for evaluating oxidative stress and TRAP were performed using EDTA as an anticoagulant and antioxidant. All samples were centrifuged at 3,000 r.p.m. for 15 min, and plasma aliquots were stored at −70 °C until assayed.

Analysis of tert-butyl-hydroperoxide-initiated chemiluminescence (CL-LOOH)

CL-LOOH in plasma was evaluated as described previously by Flecha et al. (15). CL-LOOH is considered to be much more sensitive and specific than the TBARS measurement (16), the usual method to determine lipid oxidation. For CL measurement, reaction mixtures were aliquoted into 20 ml scintillation vials (low-potassium glass). Reaction mixtures included 250 µl of plasma, 30 mmol/l KH2PO4/K2HPO4 buffer (pH 7.4), 120 mmol/l KCl, and 3 mmol/l LOOH in a final volume of 2 ml. CL-LOOH was measured in a Beckman LS 6,000 liquid scintillation counter set to the out-of-coincidence mode with a response of 300–620 nm. The vials were kept in the dark until the assay, which was conducted in a dark room at 30 °C. The results are expressed in counts per minute.

Ferrous oxidation-xylenol orange assay (FOX)

Lipid hydroperoxide and hydrogen peroxide (H2O2) concentrations were determined by FOX assay (17), and the results are expressed in mmol/l.

Determination of AOPP

Advanced oxidation protein products (AOPP) was determined in the plasma using the semiautomated method described by Witko-Sarsat et al. (18). AOPP concentrations were expressed as micromoles per liter (µmol/l) of chloramine-T equivalents.

Total radical-trapping antioxidant parameter (TRAP)

TRAP was determined by the method described by Reppeto et al. (19). This method detects hydrosoluble and/or liposoluble plasma antioxidants by measuring the chemiluminescence inhibition time induced by 2,2-azobis (2-amidinopropane). The system was calibrated with the vitamin E analog Trolox, and the TRAP values were expressed in µmol/l of Trolox. TRAP concentrations were expressed relative to uric acid values.

Statistical analysis

Data are expressed as medians (minimum-maximum). Sex, ethnicity, and smoking were evaluated by the χ2-test. As the data obtained in the laboratory analyses did not have a Gaussian distribution, comparisons between groups were performed using the nonparametric Kruskal—Wallis test with the post-hoc Dunn test. The results were considered significant when P < 0.05. A statistical analysis program Graph Pad Prism version 3.0 was used for evaluations.

Results

There were no differences between groups with respect to age, gender, ethnicity, and smoking status (Table 1). The parameters related to body composition (BMI and waist circumference), and systolic and diastolic blood pressure showed no statistically significant differences when overweight subjects with MetS were compared to overweight subjects without MetS. However, both groups were significantly different from the control group (Table 1).

Table 1.  Clinical and laboratory characteristics of control subjects (C) and overweight subjects without (O) or with metabolic syndrome (OMS)
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Regarding the biochemical and inflammatory parameters evaluated, there were no significant differences between overweight subjects without MetS and the control group. However, relative to control subjects and overweight subjects without MetS, overweight subjects with MetS had higher blood glucose (P < 0.05), insulin (P < 0.001), and HOMAIR (P < 0.001). Overweight subjects with MetS had higher total cholesterol values (P < 0.01) than overweight subjects without MetS. However, no differences were observed in low-density lipoprotein cholesterol values between the three groups (Table 1).

Regarding oxidative stress, there were no differences in the parameters evaluated between control subjects and overweight subjects (Table 2). Overweight subjects with MetS had higher hydroperoxide concentrations measured by CL compared to control subjects (P < 0.05), but there was no difference compared to overweight subjects without MetS. However, overweight subjects with MetS presented higher hydroperoxide and hydrogen peroxide concentrations determined by FOX compared to overweight subjects without MetS (P < 0.001). Overweight subjects with MetS also showed higher protein oxidation (AOPP) concentrations (P < 0.001) compared to the other groups. There was a trend (P < 0.09) towards TRAP differences between overweight subjects with and without MetS (Table 2). There was a direct correlation between TRAP and uric acid concentrations in overweight subjects (Figure 1). However, when TRAP concentration was corrected according to uric acid values, overweight subjects with MetS showed significant differences (P < 0.001) compared to control subjects (Figure 2). Uric acid values were also positively correlated to AOPP concentrations (Figure 3).

Table 2.  Oxidative stress evaluation in control subjects (C) and overweight subjects without (O) or with metabolic syndrome (OMS)
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Figure 1.

Spearman's correlation between total radical-trapping antioxidant parameter (TRAP) and uric acid concentrations in overweight subjects (O + OMS) (r = 0.34, P = 0.018). O, overweight subjects without metabolic syndrome; OMS, overweight subjects with metabolic syndrome.

Figure 2.

Total radical-trapping antioxidant capacity (TRAP)/uric acid ratio in control (C) and overweight subjects without (O) or with metabolic syndrome (OMS). *C vs. OMS (P < 0.001).

Figure 3.

Spearman's correlation between advanced oxidation protein products (AOPP) and uric acid concentrations in overweight subjects (O + OMS) (r = 0.57, P < 0.001). O, overweight subjects without metabolic syndrome; OMS, overweight subjects with metabolic syndrome.

Discussion

The present study showed that oxidative stress is increased and antioxidant defense is decreased in overweight subjects with Mets. However, overweight subjects without MetS were similar to normal weight controls. In the present study, we evaluated oxidative stress with different and reliable methods. The group of subjects with MetS had increases in lipidic oxidative stress as measured by CL and FOX. These methodologies assess earlier phases of lipoperoxidation by measuring hydroperoxide concentrations. Although both FOX and CL-LOOH evaluate hydroperoxide production, the former is a colorimetric method, whereas the latter is based on chemiluminescence analysis. This may explain the different results obtained in these oxidative stress measurements when overweight subjects with MetS were compared with overweight subjects without MetS and control subjects. Furthermore, CL is considered much more sensitive and specific than TBARS (12,16), which is more frequently used to determine oxidative stress and measures malondialdehyde, the final product of lipid peroxidation.

There were no significant differences in the parameters evaluated between overweight subjects without MetS and control subjects, except for systolic and diastolic pressure, which were increased in overweight subjects without MetS. Overweight is highly associated with arterial hypertension, independent of MetS. It was found that a BMI of 25 kg/m2 or greater accounted for ∼34% and 62% of the incidence of hypertension in men and in women, respectively (20).

Some studies have shown the importance of oxidative stress in the physiopathology of obesity, diabetes, and MetS (9,21), but there are few studies on oxidative stress in overweight subjects. Piwowar et al. (22) found a significant direct correlation between AOPP and BMI in diabetic subjects with a BMI higher than 30 kg/m2, but not in overweight diabetic subjects. Skalicky et al. (10) found that in obese subjects, oxidative stress seemed to be increased by a combination of risk factors associated with MetS rather than by obesity itself, while Krzystek-Korpacka et al. (11) found these same results in overweight and obese adolescents. Fujita et al. (23) demonstrated that oxidative stress values increased with the number of components of MetS. In the present study, overweight alone did not provoke changes in oxidative stress biomarkers. However, when overweight was associated with MetS, there were higher concentrations of both lipid and protein oxidation. Taken together, these data suggest that although weight gain or visceral fat may contribute to increases in oxidative stress, the presence of MetS is required to for reactive oxygen and nitrogen species to be increased in overweight subjects. The present study is in line with a recent study (24) showing that an increased production of ROS and an impaired antioxidant glutathione system were associated with cardiometabolic abnormalities in obese but otherwise healthy postmenopausal women. Our data are also consistent with the finding s of previous studies showing that hypertriacylglycerolemia, hyperglycemia, hypertension, and lower HDL-cholesterol values are important factors in increasing oxidative stress (23,25,26). MetS subjects may have a redox imbalance characterized by increased plasma oxidation and reduced antioxidant capacity, which may contribute to increased pathophysiology. Hypertriacylglycerolemia, hyperglycemia, and hypertension lead to an increased production of superoxide anion (O2) via the nicotinamide adenosine diphosphate oxidase pathway (10). This anion reacts rapidly with NO to form peroxynitrite (ONOO), thus inactivating NO and leading to endothelial dysfunction, one of the mechanisms responsible for hypertension in these subjects (27). Antioxidant activity in HDL-cholesterol, a mechanism mediating cardioprotective effects, is impaired in MetS subjects (25).

Several reports have suggested that oxidative stress triggers components of MetS through the development of insulin resistance (5,28). Increased ROS promotes free fatty acid liberation, increases deregulation of adipocytokines in adipose tissue, and decreases glucose uptake in the liver and skeletal muscle (6). In addition, hydrogen peroxide impairs insulin signaling and inhibits glucose transport, two cardinal features of insulin resistance (21). Other evidence supporting the idea that oxidative stress is the pathogenic mechanism underlying insulin resistance include findings showing that medications used in the treatment of cardiovascular diseases, such as statins, angiotensin-converting enzyme inhibitors, angiotensin-receptor antagonists, calcium-channel blockers, and the β-blocker carvedilol, have strong intracellular antioxidant capacities but no effect on glycemia. Therefore, it has been hypothesized that the many beneficial effects of these medications that are not fully accounted for by hypotensive or lipid-lowering effects could be explained by those properties (7,28).

Some studies have shown a positive association between increases in serum uric acid concentrations and cardiac event risk in the general population (29,30), as well as its direct association with MetS (31). Uric acid synthesis leads to ROS production and can hence contribute to increased ROS in obesity and MetS (12). Our data showed a significant increase in uric acid concentrations in overweight subjects with MetS and a direct correlation between uric acid and AOPP, reinforcing the role of uric acid in the physiopathology of oxidative stress, especially in subjects with MetS. Uric acid is involved in cardiovascular disease risk and is also responsible for ∼60% of plasma TRAP (12); therefore, TRAP status may be overestimated in subjects with hyperuricemia.

Some studies have found decreases in individual antioxidants, such as carotenoids, vitamin C, and vitamin E (22,31), as well as TRAP (22) in MetS subjects. However, Skalicky et al. (10) found an increase in TRAP concentrations in obese subjects with MetS compared with obese subjects without MetS. Similarly, in the present study there was an increase in both uric acid and TRAP concentrations in overweight subjects with MetS when compared to the other groups. The increase in TRAP concentrations was likely due to the significant increase in acid uric values in these subjects, as mentioned above. These data are in agreement with a previous study that reported a direct correlation between TRAP and uric acid concentrations (12). When the TRAP values of each patient were normalized to uric acid values, it was found that there was a decrease in TRAP concentrations in overweight subjects with MetS due to changes in other low-weight antioxidant molecules in plasma.

MetS subjects display chronic low-grade systemic inflammation related to central obesity (32), however, insulin resistance may also have a role (33). Our data seem to confirm the importance of insulin resistance in the inflammatory process. Only overweight subjects with MetS, and therefore, with insulin resistance, had higher C-reactive protein levels compared to control subjects. The inflammatory process appears to be responsible for oxidative stress generation and may induce gene expression related to proinflammatory cytokines (33).

In conclusion, this study demonstrated that overweight subjects with MetS, in contrast with overweight subjects without MetS, have a redox imbalance, characterized by increased plasma oxidation and reduced antioxidant capacity. As cross-sectional design does not allow for inference causality, it remains to be determined if oxidative stress is a cause or a consequence of MetS.

ACKNOWLEDGMENTS

This study was financially supported by Research Funds of University of Londrina (FAEPE).

DISCLOSURE

The authors declared no conflict of interest.

See the online ICMJE Conflict of Interest Forms for this article.

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