The association of total sialic acid and malondialdehyde levels with metabolic and anthropometric variables in obesity FH Yerlikaya1, A Toker1, H Çiçekler2, A Arıbas¸3 1Necmettin
Erbakan University, Meram Faculty of Medicine, Department of Biochemistry, Konya, 2Zonguldak Atatürk State Hospital, Department of Biochemistry, Zonguldak, and 3Necmettin Erbakan University, Meram Faculty of Medicine, Department of Cardiology, Konya, Turkey
Accepted March 29, 2014
Abstract Serum sialic acid levels are abnormally high in pathological states that exhibit tissue destruction, tissue proliferation or inflammation. We measured total serum sialic acid levels in 139 women and 125 men. Subjects were divided into quartiles according to their body mass index (BMI): Q1 (18–24.9 kg/m2), Q2 (25–29.9 kg/m2), Q3 (30–39.9 kg/m2) and Q4 ( 40 kg/m2). The patients in Q1 constituted the control group. Serum sialic acid levels of subjects in Q2, Q3 and Q4 were significantly higher than those in Q1. Higher BMI quartiles also were associated with higher levels of serum glucose, insulin, total cholesterol, LDL-cholesterol, triglycerides, high-sensitivity C-reactive protein, malondialdehyde levels, waist circumference, blood pressure and homeostasis model assessment of insulin resistance in both women and men. Lower BMI quartiles were associated with higher levels of serum HDL-cholesterol levels in both women and men. We found positive associations among serum sialic acid levels, BMI and oxidative stress. Serum sialic acid also is related to some conventional cardiovascular risk factors including elevated lipid profile, increased blood pressure, increased serum glucose and insulin levels, and insulin resistance in obese people. Key words: body mass index, cardiovascular risk, obesity, oxidative stress, sialic acid
Sialic acid is an N-acetylated derivative of neuraminic acid located at the terminal ends of many carbohydrate chains of glycolipids and glycoproteins (Sathiyapriya et al. 2008, Serdar et al. 2007). Sialic acids play a major role in the viscosity of mucous secretions, which act as lubricants and defensive agents in body cavities or on body surfaces. Cell surface sialic acids also may be important for protection against bacterial colonization and subsequent infection of respiratory epithelial cells owing to their ability to alter cellular aggregation
Correspondence: Dr. Fatma Hümeyra Yerlikaya, Necmettin Erbakan Universitesi, Meram Tıp Fakültesi, Biyokimya Anabilim Dalı, Konya, Turkey. Tel: 0 505 / 466 42 31, Fax 0 332 / 236 21 41. E-mail: [email protected] © 2014 The Biological Stain Commission Biotechnic & Histochemistry 2015, 90(1): 31–37.
DOI: 10.3109/10520295.2014.937744
(Abdulazeez et al. 2010). Sialic acid-rich glycoprotein is found mainly in cell membranes and elevated levels may indicate excessive cell membrane damage, especially for cells of vascular tissue. Damage to vascular tissue leads to ischemia which affects primarily the smallest blood vessels, particularly in the retina, kidneys, heart and brain. Serum sialic acid levels also are increased in type 2 diabetes, coronary artery disease, inflammatory disorders, metabolic sydrome, chronic renal disease and alcoholism (Nayak and Roberts 2006, Emre et al. 2011, Pönniö et al. 1999, Zulet et al. 2009). Obesity is a significant health risk that is recognized as a chronic disease with a multifactorial etiology; it is associated with vascular diseases that are often attributed to vascular oxidative stress (Mehmetoğlu et al. 2012). Body mass index (BMI), a measure of obesity, is associated with the risk of 31
developing insulin resistance in both males and females (Chan et al. 1994, Colditz et al. 1990). It has been reported that the risk of developing type 2 diabetes for an obese individual with a BMI of 30 kg/m2 is increased 13 fold for men and 20 fold for women compared to an individual with a BMI of 22 kg/m2. Similarly, individuals with a BMI 29 kg/m2 have three times the risk of cardiovascular disease compared to those with a BMI 21 kg/m2 (Manson et al. 1990). A positive correlation between serum sialic acid levels and BMI has been reported for healthy individuals (Crook et al. 1998). To date, no direct connection between sialic acid levels and obesity have been established. Crook et al. (1998) reported that total serum sialic acid levels may predict cardiovascular disease better in women than in men (Crook et al. 1998). We studied total serum sialic acid levels in men and women. Also, we examined associations of serum malondialdehyde (MDA) levels as biomarker for oxidative stress, and metabolic and anthropometric variables with serum sialic acid levels in men and women.
Material and methods Patients Our study protocol was approved by the Ethics Committee of Meram Medical School, University of Selcuk. We studied 139 women and 125 men; the average age of both groups was 44.21 9.8 years. Subjects were grouped in quartiles (Q) according to their BMI: Q1 (18–24.9 kg/m2), Q2 (25–29.9 kg/m2), Q3 (30–39.9 kg/m2), and Q4 ( 40 kg/m2). The Q2, Q3 and Q4 groups were examined by a cardiologist at the Cardiology Clinics of Meram Medical School, Necmettin Erbakan University. Exclusion criteria for our study included diabetes mellitus, malignant diseases, chronic liver disease, history of cardiovascular disease, infectious disease, pregnancy, alcohol and smoking habits, and taking vitamin, mineral, antioxidant or fish-oil supplements. In addition, fewer than 5% of the participants suffered from hypertension, but none were receiving treatment for this. Blood samples were obtained from the subjects between 8 AM and 9 AM after a 12 h overnight fast. Serum samples were obtained by centrifugation for 10 min at 3000 x g and samples were stored at 80o C until they were analyzed. Anthropometric assessment All anthropometric measurements for each participant, including BMI, were taken with participants 32
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wearing light clothing and no shoes. Waist measurements were taken using a soft tape midway between the lowest rib and the iliac crest. Hip circumference was measured at the widest part of the gluteal region. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured at least twice at 5–10 min intervals by mercury sphygmomanometry in the sitting position after the patients had lain in the supine position for at least 20 min. The means of all measurements were used.
Sialic acid measurements Sialic acid content was measured using Warren’s standard assay (Warren 1959) and by a modified thiobarbituric acid-based method as follows: 200 μl of serum was added to 100 μl of 0.2 N H2SO4, and the samples were incubated for 1 h at 80° C for mild acidic hydrolysis. The tubes then were cooled at 20° C for 20 min and 20 μl of periodate reagent (0.2 M NaIO4 in 9 M H3PO4) was added to the samples. The tubes were vortexed, then incubated for 20 min at 20° C. Then 100 μl of m-arsenite reagent (10% NaAsO2 in 0.1 N H2SO4 with 0.5 M Na2SO4) was added and tubes were vortexed vigorously until the brownish yellow coloration appeared, then disappeared completely. Then 250 μl of thiobarbituric acid reagent (0.6% TBA in 0.5 M Na2SO4) was added, the tubes were vortexed and heated in a boiling water bath for 15 min, then cooled at 20° C. One milliliter of cyclohexanone was added and the tubes were vortexed vigorously twice for 10 sec, then centrifuged for 7 min at 900 x g for phase separation. The optical density of the organic phase was determined at 549 nm in a quartz 0.4 ml cuvette with 1 cm light path against blank samples in a Shimadzu model UV-1601 spectrophotometer.
MDA measurements The concentration of MDA in plasma was determined using the method described by Draper and Hadley (1990) based on TBA reactivity. Briefly, 2.5 ml of 10% trichloracetic acid and 0.5 ml of plasma were added to the tubes and mixed. After incubating for 15 min at 90° C and cooling with cold water, the mixture was centrifuged for 10 min at 900 g. Two milliliters of supernatant were extracted and 1 ml 0.675% TBA was added. The tubes were sealed and incubated at 90° C for 15 min, then cooled to room temperature. The optical density was measured at 532 nm using a Shimadzu UV-1601 spectrophotometer.
Additional analyses Serum total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), glucose and high-sensitivity C-reactive protein (hsCRP) levels were measured using commercially available kits for the Synchron LX System (Beckman Coulter, Fullerton CA). Serum insulin was determined by routine chemiluminesce method using a E170 analyzer (Roche Diagnostics, Basel, Switzerland). Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as insulin (mU/liter) glucose (mU/l)/22.5 (Matthews et al. 1985).
Statistical analysis Statistical analyses were performed using SPSS v. 16.0 (SPSS Inc., Chicago, IL). All data are expressed as means SD. The normality of the variables was evaluated using the one-sample KolmogorovSmirnov test. The normal distribution of variables were examined with one-way ANOVA Tukey test and non-normally distributed variables were examined using the Kruskal-Wallis H test. Oneway ANOVA and Kruskal-Wallis H tests were applied to evaluate the differences between mean serum sialic acid levels and metabolic and anthropometric variables of multiple groups. Pearson’s correlation analysis was performed to identify the
relation between serum sialic acid levels to metabolic and anthropometric variables. Multiple linear regression analyses were performed to analyze the effects of various independent variables on the serum sialic acid levels. Differences were considered significant at p 0.05.
Results Baseline and biochemical characteristics of the patients we studied are given in Tables 1 and 2. Waist circumference, SBP and DBP of subjects in the higher BMI quartiles (groups Q2, Q3, Q4) were significantly greater than those in lowest BMI quartile (group Q1). Higher BMI quartiles also were associated with higher levels of serum glucose, insülin, TC, TG, LDL-C, hsCRP, sialic acid, MDA and HOMA-IR values in both women and men (Tables 1 and 2). To the contrary, the lowest BMI quartile (group Q1) were associated with higher levels of serum HDL-C levels in both women and men (Tables 1 and 2). Simple correlation analyses were performed to investigate the association of serum sialic acid levels with anthropometric variables and biochemical parameters. There were positive correlations between serum sialic acid levels and BMI (r 0.672, p 0.001) in all groups (Fig. 1). There were positive correlations between serum sialic acid levels and the values of BMI, waist circumference, SBP, DBP,
Table 1. Baseline characteristics and biochemical parameters of women according to BMI quartiles
Age (years) BMI (kg/m2) Waist circumference (cm) SBP (mm Hg) DBP (mm Hg) Glucose (mg /dl) Insulin (μU/ml) HOMA-IR Total cholesterol (mg/dl) Triglycerides (mg/dl) HDL-C (mg/dl) LDL-C (mg/dl) hsCRP (mg/l) MDA (μmol/l) Sialic acid (mmol/ml)
Q1 (n ⴝ 35)
Q2 (n ⴝ 30)
Q3 (n ⴝ 31)
Q4 (n ⴝ 43)
p
44.13 13,4 22.8 2.4 75.14 5.9 12.05 0.7 7.68 0.8 83.49 5.4 5.16 2.2 1.06 0.4 166.60 20.8 57.11 23.9 51.43 15.0 106.22 17.1 3.52 1.8 12.56 1.0 0.20 0.03
45.17 7.4 27.64 1.3a 84.64 5.4a 13.07 1.2b 8.17 1.0 88.64 7.6 5.71 2.4 1.16 0.5 189.21 20.4b 84.03 16.3c 48.36 11.9 111.08 13.9 4.57 4.7 13.02 1.3 0.23 0.04
46.64 9.9 37.61 1.8ad 109.42 8.5ad 13.83 1.1af 8.77 0.7af 97.83 8.7af 18.52 8.7ad 4.41 2.0ad 203.39 25.6a 146.52 30.2ad 40.50 10.6af 126.17 31.6c 11.55 6.8ad 15.93 2.4ad 0.27 0.09
43.02 10.1 46.86 5.4adg 122.58 9.7adg 14.16 1.1ad 8.81 0.8af 108.65 17.1adm 20.21 8.3ad 5.35 2.5ad 215.79 33.6ad 172.26 51.8adn 42.95 10.4a 136.06 33.6ae 16.78 6.7adg 18.99 3.7adg 0.42 0.2adg
0.383 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.001, bp 0.01, cp 0.05 compared to Q1; dp 0.001, ep 0.01, fp 0.05 compared to Q2; gp 0.001, mp 0.01, np 0.05, compared to Q3.
Sialic acid and obesity 33
Table 2. Baseline characteristics and biochemical parameters of men according to BMI quartiles
Age (years) BMI (kg/m2) Waist circumference (cm) SBP (mm Hg) DBP (mm Hg) Glucose (mg/dl) Insulin (μU/ml) HOMA-IR Total cholesterol (mg/dl) Triglycerides (mg/dl) HDL-C (mg/dl) LDL-C (mg/dl) hsCRP (mg/l) MDA (μmol/l) Sialic acid (mmol/ml)
Q1 (n ⴝ 31)
Q2 (n ⴝ 28)
Q3 (n ⴝ 32)
Q4 (n ⴝ 34)
p
43.61 9.8 24.10 1.2 85.64 4.1 12.29 0.7 8.06 0.6 82.29 10.6 5.84 3.9 1.20 0.8 178.32 17.6 95.12 26.6 46.49 6.1 108.19 8.8 5.48 3.8 12.63 1.6 0.19 0.04
44.79 8.6 27.75 1.3b 96.16 6.5a 13.25 0.9b 8.66 0.7 87.37 5.4 6.61 3.5 1.39 0.8 191.12 14.6 104.46 26.0 44.79 5.9 114.88 16.6 6.85 1.9 14.32 2.1 0.21 0.05
46.18 13.6 36.44 2.5ad 119.19 7.2ad 13.81 1.2a 8.93 0.7a 104.19 13.1ad 19.01 8.9ad 4.92 2.1ad 208.56 31.1a 179.94 63.5ad 40.00 9.7c 132.47 25.2c 9.50 3.9c 18.70 4.2ad 0.33 0.1ad
41.11 9.6 47.29 5.7adg 131.29 11.1adg 14.55 1.3adn 8.85 0.9a 106.12 19.0ad 21.89 15.2ad 5.73 5.1ad 222.29 34.5ad 193.53 53.8ad 36.35 11.0ae 141.15 24.1ad 17.21 9.1adg 20.3 5.8ad 0.37 0.1ad
0.273 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.001, bp 0.01, cp 0.05 compared to Q1; dp 0.001, ep 0.01 compared to Q2; gp 0.001, np 0.05, compared to Q3.
HOMA-IR and the levels of serum glucose, insulin, TC, TG, LDL-C, hsCRP and MDA in group Q4 in both women (p 0.05 for DBP, TC, LDL-C and p 0.01 for the other parameters) and men (p 0.05 for waist circumference, DBP, glucose, insulin, LDL-C, hsCRP and p 0.01 for the other parameters) (Tables 3 and 4). Also, there were positive correlations between serum sialic acid levels and BMI, waist circumference, SBP, DBP, hsCRP, TC, glucose and MDA in group Q3 women (p 0.01 for SBP, hsCRP and p 0.05 for the other parameters). There were positive correlations between serum
sialic acid levels and BMI, waist circumference, SBP, DBP, hsCRP, TG, insulin, HOMA-IR, LDL-C and MDA in group Q3 women (p 0.01 for TG, hsCRP and p 0.05 for the other parameters). On the other hand, there were positive correlations between serum sialic acid levels and SBP (p 0.05), Table 3. Pearson correlation coefficients (r) for total serum sialic acid with other variables in women Q1 Q2 Q3 Q4 (n ⴝ 35) (n ⴝ 30) (n ⴝ 31) (n ⴝ 43) Age 0.235 0.349 0.178 0.091 BMI 0.289 0.123 0.434a 0.609b Waist circumference 0.194 0.244 0.436a 0.449b SBP 0.105 0.414a 0.528b 0.421b DBP 0.262 0.461a 0.392a 0.320a Glucose 0.069 0.172 0.398a 0.566b Insulin 0.051 0.264 0.040 0.573b HOMA-IR 0.023 0.176 0.070 0.669b Total cholesterol 0.201 0.151 0.439a 0.358a Triglycerides 0.031 0.240 0.204 0.488b HDL-C 0.038 0.079 0.263 0.232 LDL-C 0.073 0.120 0.240 0.305a hsCRP 0.40a 0.421a 0.542b 0.506b MDA 0.300 0.297 0.411a 0.608b
Fig. 1. Scatter plot showing relation between serum sialic acid levels (mmol/ml)) and BMI for all groups.
34
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BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.05; bp 0.01.
Table 4. Pearson correlation coefficients (r) for total serum sialic acid with other variables in men
Table 5. Pearson correlation coefficients (r) for total serum sialic acid with other variables in the mixed groups
Q1 Q2 Q3 Q4 (n ⴝ 31) (n ⴝ 28) (n ⴝ 32) (n ⴝ 34)
Q1 Q2 Q3 Q4 (n ⴝ 66) (n ⴝ 58) (n ⴝ 63) (n ⴝ 77)
0.260 0.101 0.200 0.458a 0.439a 0.487b 0.487a 0.459a 0.349a 0.365 0.362a 0.526b 0.383 0.380* 0.427a 0.145 0.279 0.388a 0.196 0.365a 0.403a 0.214 0.389a 0.484b 0.321 0.297 0.563b 0.048 0.536b 0.461b 0.105 0.356 0.190 0.338 0.389a 0.351a 0.555b 0.587b 0.434a 0.387 0.407a 0.681b
Age 0.033 0.247 0.207 0.184 BMI 0.220 0.262 0.310a 0.524b Waist circumference 0.027 0.102 0.522b 0.299b SBP 0.139 0.262b 0.398b 0.378b DBP 0.232 0.339a 0.428b 0.307b Glucose 0.112 0.175 0.387b 0.478b Insulin 0.022 0.182 0.207 0.391b b HOMA-IR 0.147 0.233 0.442 0.001 Total cholesterol 0.079 0.196 0.370b 0.365b Triglycerides 0.006 0.014 0.472b 0.408b HDL-C 0.051 0.038 0.290a 0.154 LDL-C 0.059 0.197 0.331b 0.293b a hsCRP 0.233 0.328 0.473b 0.414b MDA 0.117 0.234 0.460b 0.502b
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.05; bp 0.01.
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.05; bp 0.01.
DBP (p 0.05) and hsCRP (p 0.05) in group Q2I women, while there were positive correlations between serum sialic acid levels and BMI (p 0.05), waist circumference (p 0.05) and hsCRP (p 0.01) in group Q2 men (Tables 3 and 4). There was a positive correlation between serum sialic acid levels and hsCRP (p 0.05) in group Q1 women, while there was no correlation in group Q1 men (Tables 3 and 4). Simple correlation analyses were performed to investigate the association of serum sialic acid levels with anthropometric variables and biochemical parameters in the mixed group. As shown in Table 5, there were positive correlations between serum sialic acid levels and the values of BMI, waist circumference, SBP, DBP, HOMA-IR and the levels of serum glucose, insulin, TC, TG, LDL-C, hsCRP and MDA in the mixed group Q4 (p 0.01). There were positive correlations between serum sialic acid levels and BMI, waist circumference, SBP, DBP, glucose, insulin, TC, TG, LDL-C, hsCRP and MDA in the mixed group Q3 (p 0.05 for BMI and p 0.01 for the other parameters). There were negative correlations, however, between serum sialic acid levels and HDL-C in the mixed group Q3 (p 0.05). There were positive correlations between serum sialic acid levels and SBP, DBP, hsCRP in the mixed group Q2 (p 0.01 for SBP and p 0.05 for the other parameters).
Multiple linear regression analysis revealed that there was a positive correlation between the dependent variable, sialic acid, and BMI in the mixed group Q4 (β 0.260, p 0.018). Also, there was a positive correlation between the dependent variable, sialic acid, and glucose (β 0.220, p 0.045) in the mixed group Q4.
Age BMI Waist circumference SBP DBP Glucose Insulin HOMA-IR Total cholesterol Triglycerides HDL-C LDL-C hsCRP MDA
0.080 0.354 0.177 0.210 0.309 0.119 0.030 0.008 0.062 0.158 0.054 0.085 0.266 0.035
Discussion Obesity frequently causes significant impairment of health (Mehmetoğlu et al. 2012). BMI is the most widely used measure of body size and it frequently is used to estimate the prevalence of obesity within a population (Dalton et al. 2003). Patients with a high BMI may present with disease symptoms and acute decompensation earlier than patients with a low BMI (Horwich et al. 2001, Curtis et al. 2005). We found that the serum sialic acid levels of patients with high BMI were significantly higher than those with low BMI. Also, there were positive correlations between serum sialic acid levels and BMI and waist circumference in both obese women and men. It has been reported that BMI and sialic acid are related, because as BMI increases, the volume of body fluids increases, and therefore sialic acid increases (Abdulazeez et al. 2010). Englyst et al. (2006) reported that the percentage of body fat is an indepentent predictor of fasting serum sialic
Sialic acid and obesity 35
acid. These investigators suggested also that sialic acid concentration may reflect metabolic status and BMI. High C-reactive protein levels in obese subjects is evidence that obesity may be considered a low-grade inflammatory state (Wellen and Hotamisligil 2005, Hotamisligil 2006). The inflamation is caused by macrophage secretion of proinflammatory cytokines (Weisberg et al. 2003). Macrophages are an important source of proinflammatory factors including tumor necrosis factor (TNF)-α, interleukin (IL)-1 and IL-6 (Antuna-Puente et al. 2008, Hauner 2005). Serum sialic acid is a marker of acute-phase response (Crook et al. 2001) in which glycoproteins with sialic acid attached to the oligosaccharide side chains are produced by the liver in response to proinflammatory cytokines (Crook et al. 2001). We found a significant increase in serum hsCRP levels in groups Q3 and Q4 compared to group Q1 in both women and men. We also found that there were positive correlations between serum sialic acid levels and serum hsCRP levels in both obese women and men (groups Q2, Q3 and Q4). MDA is a naturally occurring product of lipid oxidation after exposure to reactive oxygen species (ROS) and free radicals; it can be used to evaluate oxidative damage by measuring serum TBARS levels (Yilmaz et al. 2007). We observed a significant increase in the serum MDA levels in groups Q3 and Q4 compared to group Q1 ( p 0.001). Also, there were positive correlations between serum sialic acid levels and serum MDA levels in both obese women and men (p 0.05 for group Q3 and p 0.01 for group Q4). We concluded that serum sialic acid levels of obese people increased with increasing oxidative stress. Earlier studies have shown that sialic acid may be a part of the defense against increased oxidative stress by acting as a H2O2 scavenger (Mohan and Priyav 2010, Iijima 2004), which may explain the correlation between sialic acid and MDA. On the other hand, it has been reported that nonreducing terminal sialic acid residues as well as proteins, lipids and DNA may be targets for ROS (Eguchi 2005). The release of sialic acid from the terminal residues of glycolipids of cell membranes could result from the breakdown of cell membranes and/or lipid oxidation; the released sialic acid would enter the serum to elevate plasma levels. Elevation of sialic acid levels has been considered a reflection of altered structural integrity of glycolipids in cell membranes (Yapar et al. 2007). Some earlier studies have suggested that serum sialic acid is a predictor of cardiovascular events (Gopaul and Crook 2006, Knuiman et al. 2004). We 36
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found a correlation between serum sialic acid and TC, TG and LDL-C levels in both obese women and men in group Q4. How sialic acid can predict cardiovascular events is not known, but the mechanism may be, in part, sialylation of lipoproteins (Crook et al. 1998). We also found correlations between serum sialic acid and SBP and DBP in both obese women and men. A possible explanation of these correlations is that sialic acid levels were elevated because of increased atherosclerosis (Pönniö et al. 1999). We demonstrated also correlations between serum sialic acid and glucose, and between insulin levels and resistance as assessed by the HOMA-IR values in both obese women and men. Fasting serum glucose and insulin levels may be associated with insulin resistance, which are associated with increased cardiovascular disease. On the other hand, we found no significant differences between serum sialic acid and age in either women or men. Earlier studies showed that there were no correlations between serum sialic acid levels and age for either sex (Crook et al. 1994, 1998). Our finding that there was no sex difference in serum sialic acid levels in obese people is consistent with the findings of other investigators (Hangloo et al. 1990). We found a correlation between serum sialic acid levels, BMI and oxidative stress. Also, serum sialic acid is associated with some conventional cardiovascular risk factors including lipid profile, blood pressure, fasting serum glucose and insulin levels, and insulin resistance in obese people. Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this paper.
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Sialic acid and obesity 37
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Erbakan University, Meram Faculty of Medicine, Department of Biochemistry, Konya, 2Zonguldak Atatürk State Hospital, Department of Biochemistry, Zonguldak, and 3Necmettin Erbakan University, Meram Faculty of Medicine, Department of Cardiology, Konya, Turkey
Accepted March 29, 2014
Abstract Serum sialic acid levels are abnormally high in pathological states that exhibit tissue destruction, tissue proliferation or inflammation. We measured total serum sialic acid levels in 139 women and 125 men. Subjects were divided into quartiles according to their body mass index (BMI): Q1 (18–24.9 kg/m2), Q2 (25–29.9 kg/m2), Q3 (30–39.9 kg/m2) and Q4 ( 40 kg/m2). The patients in Q1 constituted the control group. Serum sialic acid levels of subjects in Q2, Q3 and Q4 were significantly higher than those in Q1. Higher BMI quartiles also were associated with higher levels of serum glucose, insulin, total cholesterol, LDL-cholesterol, triglycerides, high-sensitivity C-reactive protein, malondialdehyde levels, waist circumference, blood pressure and homeostasis model assessment of insulin resistance in both women and men. Lower BMI quartiles were associated with higher levels of serum HDL-cholesterol levels in both women and men. We found positive associations among serum sialic acid levels, BMI and oxidative stress. Serum sialic acid also is related to some conventional cardiovascular risk factors including elevated lipid profile, increased blood pressure, increased serum glucose and insulin levels, and insulin resistance in obese people. Key words: body mass index, cardiovascular risk, obesity, oxidative stress, sialic acid
Sialic acid is an N-acetylated derivative of neuraminic acid located at the terminal ends of many carbohydrate chains of glycolipids and glycoproteins (Sathiyapriya et al. 2008, Serdar et al. 2007). Sialic acids play a major role in the viscosity of mucous secretions, which act as lubricants and defensive agents in body cavities or on body surfaces. Cell surface sialic acids also may be important for protection against bacterial colonization and subsequent infection of respiratory epithelial cells owing to their ability to alter cellular aggregation
Correspondence: Dr. Fatma Hümeyra Yerlikaya, Necmettin Erbakan Universitesi, Meram Tıp Fakültesi, Biyokimya Anabilim Dalı, Konya, Turkey. Tel: 0 505 / 466 42 31, Fax 0 332 / 236 21 41. E-mail: [email protected] © 2014 The Biological Stain Commission Biotechnic & Histochemistry 2015, 90(1): 31–37.
DOI: 10.3109/10520295.2014.937744
(Abdulazeez et al. 2010). Sialic acid-rich glycoprotein is found mainly in cell membranes and elevated levels may indicate excessive cell membrane damage, especially for cells of vascular tissue. Damage to vascular tissue leads to ischemia which affects primarily the smallest blood vessels, particularly in the retina, kidneys, heart and brain. Serum sialic acid levels also are increased in type 2 diabetes, coronary artery disease, inflammatory disorders, metabolic sydrome, chronic renal disease and alcoholism (Nayak and Roberts 2006, Emre et al. 2011, Pönniö et al. 1999, Zulet et al. 2009). Obesity is a significant health risk that is recognized as a chronic disease with a multifactorial etiology; it is associated with vascular diseases that are often attributed to vascular oxidative stress (Mehmetoğlu et al. 2012). Body mass index (BMI), a measure of obesity, is associated with the risk of 31
developing insulin resistance in both males and females (Chan et al. 1994, Colditz et al. 1990). It has been reported that the risk of developing type 2 diabetes for an obese individual with a BMI of 30 kg/m2 is increased 13 fold for men and 20 fold for women compared to an individual with a BMI of 22 kg/m2. Similarly, individuals with a BMI 29 kg/m2 have three times the risk of cardiovascular disease compared to those with a BMI 21 kg/m2 (Manson et al. 1990). A positive correlation between serum sialic acid levels and BMI has been reported for healthy individuals (Crook et al. 1998). To date, no direct connection between sialic acid levels and obesity have been established. Crook et al. (1998) reported that total serum sialic acid levels may predict cardiovascular disease better in women than in men (Crook et al. 1998). We studied total serum sialic acid levels in men and women. Also, we examined associations of serum malondialdehyde (MDA) levels as biomarker for oxidative stress, and metabolic and anthropometric variables with serum sialic acid levels in men and women.
Material and methods Patients Our study protocol was approved by the Ethics Committee of Meram Medical School, University of Selcuk. We studied 139 women and 125 men; the average age of both groups was 44.21 9.8 years. Subjects were grouped in quartiles (Q) according to their BMI: Q1 (18–24.9 kg/m2), Q2 (25–29.9 kg/m2), Q3 (30–39.9 kg/m2), and Q4 ( 40 kg/m2). The Q2, Q3 and Q4 groups were examined by a cardiologist at the Cardiology Clinics of Meram Medical School, Necmettin Erbakan University. Exclusion criteria for our study included diabetes mellitus, malignant diseases, chronic liver disease, history of cardiovascular disease, infectious disease, pregnancy, alcohol and smoking habits, and taking vitamin, mineral, antioxidant or fish-oil supplements. In addition, fewer than 5% of the participants suffered from hypertension, but none were receiving treatment for this. Blood samples were obtained from the subjects between 8 AM and 9 AM after a 12 h overnight fast. Serum samples were obtained by centrifugation for 10 min at 3000 x g and samples were stored at 80o C until they were analyzed. Anthropometric assessment All anthropometric measurements for each participant, including BMI, were taken with participants 32
Biotechnic & Histochemistry 2015, 90(1): 31–37
wearing light clothing and no shoes. Waist measurements were taken using a soft tape midway between the lowest rib and the iliac crest. Hip circumference was measured at the widest part of the gluteal region. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured at least twice at 5–10 min intervals by mercury sphygmomanometry in the sitting position after the patients had lain in the supine position for at least 20 min. The means of all measurements were used.
Sialic acid measurements Sialic acid content was measured using Warren’s standard assay (Warren 1959) and by a modified thiobarbituric acid-based method as follows: 200 μl of serum was added to 100 μl of 0.2 N H2SO4, and the samples were incubated for 1 h at 80° C for mild acidic hydrolysis. The tubes then were cooled at 20° C for 20 min and 20 μl of periodate reagent (0.2 M NaIO4 in 9 M H3PO4) was added to the samples. The tubes were vortexed, then incubated for 20 min at 20° C. Then 100 μl of m-arsenite reagent (10% NaAsO2 in 0.1 N H2SO4 with 0.5 M Na2SO4) was added and tubes were vortexed vigorously until the brownish yellow coloration appeared, then disappeared completely. Then 250 μl of thiobarbituric acid reagent (0.6% TBA in 0.5 M Na2SO4) was added, the tubes were vortexed and heated in a boiling water bath for 15 min, then cooled at 20° C. One milliliter of cyclohexanone was added and the tubes were vortexed vigorously twice for 10 sec, then centrifuged for 7 min at 900 x g for phase separation. The optical density of the organic phase was determined at 549 nm in a quartz 0.4 ml cuvette with 1 cm light path against blank samples in a Shimadzu model UV-1601 spectrophotometer.
MDA measurements The concentration of MDA in plasma was determined using the method described by Draper and Hadley (1990) based on TBA reactivity. Briefly, 2.5 ml of 10% trichloracetic acid and 0.5 ml of plasma were added to the tubes and mixed. After incubating for 15 min at 90° C and cooling with cold water, the mixture was centrifuged for 10 min at 900 g. Two milliliters of supernatant were extracted and 1 ml 0.675% TBA was added. The tubes were sealed and incubated at 90° C for 15 min, then cooled to room temperature. The optical density was measured at 532 nm using a Shimadzu UV-1601 spectrophotometer.
Additional analyses Serum total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), glucose and high-sensitivity C-reactive protein (hsCRP) levels were measured using commercially available kits for the Synchron LX System (Beckman Coulter, Fullerton CA). Serum insulin was determined by routine chemiluminesce method using a E170 analyzer (Roche Diagnostics, Basel, Switzerland). Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as insulin (mU/liter) glucose (mU/l)/22.5 (Matthews et al. 1985).
Statistical analysis Statistical analyses were performed using SPSS v. 16.0 (SPSS Inc., Chicago, IL). All data are expressed as means SD. The normality of the variables was evaluated using the one-sample KolmogorovSmirnov test. The normal distribution of variables were examined with one-way ANOVA Tukey test and non-normally distributed variables were examined using the Kruskal-Wallis H test. Oneway ANOVA and Kruskal-Wallis H tests were applied to evaluate the differences between mean serum sialic acid levels and metabolic and anthropometric variables of multiple groups. Pearson’s correlation analysis was performed to identify the
relation between serum sialic acid levels to metabolic and anthropometric variables. Multiple linear regression analyses were performed to analyze the effects of various independent variables on the serum sialic acid levels. Differences were considered significant at p 0.05.
Results Baseline and biochemical characteristics of the patients we studied are given in Tables 1 and 2. Waist circumference, SBP and DBP of subjects in the higher BMI quartiles (groups Q2, Q3, Q4) were significantly greater than those in lowest BMI quartile (group Q1). Higher BMI quartiles also were associated with higher levels of serum glucose, insülin, TC, TG, LDL-C, hsCRP, sialic acid, MDA and HOMA-IR values in both women and men (Tables 1 and 2). To the contrary, the lowest BMI quartile (group Q1) were associated with higher levels of serum HDL-C levels in both women and men (Tables 1 and 2). Simple correlation analyses were performed to investigate the association of serum sialic acid levels with anthropometric variables and biochemical parameters. There were positive correlations between serum sialic acid levels and BMI (r 0.672, p 0.001) in all groups (Fig. 1). There were positive correlations between serum sialic acid levels and the values of BMI, waist circumference, SBP, DBP,
Table 1. Baseline characteristics and biochemical parameters of women according to BMI quartiles
Age (years) BMI (kg/m2) Waist circumference (cm) SBP (mm Hg) DBP (mm Hg) Glucose (mg /dl) Insulin (μU/ml) HOMA-IR Total cholesterol (mg/dl) Triglycerides (mg/dl) HDL-C (mg/dl) LDL-C (mg/dl) hsCRP (mg/l) MDA (μmol/l) Sialic acid (mmol/ml)
Q1 (n ⴝ 35)
Q2 (n ⴝ 30)
Q3 (n ⴝ 31)
Q4 (n ⴝ 43)
p
44.13 13,4 22.8 2.4 75.14 5.9 12.05 0.7 7.68 0.8 83.49 5.4 5.16 2.2 1.06 0.4 166.60 20.8 57.11 23.9 51.43 15.0 106.22 17.1 3.52 1.8 12.56 1.0 0.20 0.03
45.17 7.4 27.64 1.3a 84.64 5.4a 13.07 1.2b 8.17 1.0 88.64 7.6 5.71 2.4 1.16 0.5 189.21 20.4b 84.03 16.3c 48.36 11.9 111.08 13.9 4.57 4.7 13.02 1.3 0.23 0.04
46.64 9.9 37.61 1.8ad 109.42 8.5ad 13.83 1.1af 8.77 0.7af 97.83 8.7af 18.52 8.7ad 4.41 2.0ad 203.39 25.6a 146.52 30.2ad 40.50 10.6af 126.17 31.6c 11.55 6.8ad 15.93 2.4ad 0.27 0.09
43.02 10.1 46.86 5.4adg 122.58 9.7adg 14.16 1.1ad 8.81 0.8af 108.65 17.1adm 20.21 8.3ad 5.35 2.5ad 215.79 33.6ad 172.26 51.8adn 42.95 10.4a 136.06 33.6ae 16.78 6.7adg 18.99 3.7adg 0.42 0.2adg
0.383 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.001, bp 0.01, cp 0.05 compared to Q1; dp 0.001, ep 0.01, fp 0.05 compared to Q2; gp 0.001, mp 0.01, np 0.05, compared to Q3.
Sialic acid and obesity 33
Table 2. Baseline characteristics and biochemical parameters of men according to BMI quartiles
Age (years) BMI (kg/m2) Waist circumference (cm) SBP (mm Hg) DBP (mm Hg) Glucose (mg/dl) Insulin (μU/ml) HOMA-IR Total cholesterol (mg/dl) Triglycerides (mg/dl) HDL-C (mg/dl) LDL-C (mg/dl) hsCRP (mg/l) MDA (μmol/l) Sialic acid (mmol/ml)
Q1 (n ⴝ 31)
Q2 (n ⴝ 28)
Q3 (n ⴝ 32)
Q4 (n ⴝ 34)
p
43.61 9.8 24.10 1.2 85.64 4.1 12.29 0.7 8.06 0.6 82.29 10.6 5.84 3.9 1.20 0.8 178.32 17.6 95.12 26.6 46.49 6.1 108.19 8.8 5.48 3.8 12.63 1.6 0.19 0.04
44.79 8.6 27.75 1.3b 96.16 6.5a 13.25 0.9b 8.66 0.7 87.37 5.4 6.61 3.5 1.39 0.8 191.12 14.6 104.46 26.0 44.79 5.9 114.88 16.6 6.85 1.9 14.32 2.1 0.21 0.05
46.18 13.6 36.44 2.5ad 119.19 7.2ad 13.81 1.2a 8.93 0.7a 104.19 13.1ad 19.01 8.9ad 4.92 2.1ad 208.56 31.1a 179.94 63.5ad 40.00 9.7c 132.47 25.2c 9.50 3.9c 18.70 4.2ad 0.33 0.1ad
41.11 9.6 47.29 5.7adg 131.29 11.1adg 14.55 1.3adn 8.85 0.9a 106.12 19.0ad 21.89 15.2ad 5.73 5.1ad 222.29 34.5ad 193.53 53.8ad 36.35 11.0ae 141.15 24.1ad 17.21 9.1adg 20.3 5.8ad 0.37 0.1ad
0.273 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.001, bp 0.01, cp 0.05 compared to Q1; dp 0.001, ep 0.01 compared to Q2; gp 0.001, np 0.05, compared to Q3.
HOMA-IR and the levels of serum glucose, insulin, TC, TG, LDL-C, hsCRP and MDA in group Q4 in both women (p 0.05 for DBP, TC, LDL-C and p 0.01 for the other parameters) and men (p 0.05 for waist circumference, DBP, glucose, insulin, LDL-C, hsCRP and p 0.01 for the other parameters) (Tables 3 and 4). Also, there were positive correlations between serum sialic acid levels and BMI, waist circumference, SBP, DBP, hsCRP, TC, glucose and MDA in group Q3 women (p 0.01 for SBP, hsCRP and p 0.05 for the other parameters). There were positive correlations between serum
sialic acid levels and BMI, waist circumference, SBP, DBP, hsCRP, TG, insulin, HOMA-IR, LDL-C and MDA in group Q3 women (p 0.01 for TG, hsCRP and p 0.05 for the other parameters). On the other hand, there were positive correlations between serum sialic acid levels and SBP (p 0.05), Table 3. Pearson correlation coefficients (r) for total serum sialic acid with other variables in women Q1 Q2 Q3 Q4 (n ⴝ 35) (n ⴝ 30) (n ⴝ 31) (n ⴝ 43) Age 0.235 0.349 0.178 0.091 BMI 0.289 0.123 0.434a 0.609b Waist circumference 0.194 0.244 0.436a 0.449b SBP 0.105 0.414a 0.528b 0.421b DBP 0.262 0.461a 0.392a 0.320a Glucose 0.069 0.172 0.398a 0.566b Insulin 0.051 0.264 0.040 0.573b HOMA-IR 0.023 0.176 0.070 0.669b Total cholesterol 0.201 0.151 0.439a 0.358a Triglycerides 0.031 0.240 0.204 0.488b HDL-C 0.038 0.079 0.263 0.232 LDL-C 0.073 0.120 0.240 0.305a hsCRP 0.40a 0.421a 0.542b 0.506b MDA 0.300 0.297 0.411a 0.608b
Fig. 1. Scatter plot showing relation between serum sialic acid levels (mmol/ml)) and BMI for all groups.
34
Biotechnic & Histochemistry 2015, 90(1): 31–37
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.05; bp 0.01.
Table 4. Pearson correlation coefficients (r) for total serum sialic acid with other variables in men
Table 5. Pearson correlation coefficients (r) for total serum sialic acid with other variables in the mixed groups
Q1 Q2 Q3 Q4 (n ⴝ 31) (n ⴝ 28) (n ⴝ 32) (n ⴝ 34)
Q1 Q2 Q3 Q4 (n ⴝ 66) (n ⴝ 58) (n ⴝ 63) (n ⴝ 77)
0.260 0.101 0.200 0.458a 0.439a 0.487b 0.487a 0.459a 0.349a 0.365 0.362a 0.526b 0.383 0.380* 0.427a 0.145 0.279 0.388a 0.196 0.365a 0.403a 0.214 0.389a 0.484b 0.321 0.297 0.563b 0.048 0.536b 0.461b 0.105 0.356 0.190 0.338 0.389a 0.351a 0.555b 0.587b 0.434a 0.387 0.407a 0.681b
Age 0.033 0.247 0.207 0.184 BMI 0.220 0.262 0.310a 0.524b Waist circumference 0.027 0.102 0.522b 0.299b SBP 0.139 0.262b 0.398b 0.378b DBP 0.232 0.339a 0.428b 0.307b Glucose 0.112 0.175 0.387b 0.478b Insulin 0.022 0.182 0.207 0.391b b HOMA-IR 0.147 0.233 0.442 0.001 Total cholesterol 0.079 0.196 0.370b 0.365b Triglycerides 0.006 0.014 0.472b 0.408b HDL-C 0.051 0.038 0.290a 0.154 LDL-C 0.059 0.197 0.331b 0.293b a hsCRP 0.233 0.328 0.473b 0.414b MDA 0.117 0.234 0.460b 0.502b
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.05; bp 0.01.
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HOMA-IR, homeostasis model assesment; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; hsCRP, high-sensitivity C-reactive protein; MDA, malondialdehyde. ap 0.05; bp 0.01.
DBP (p 0.05) and hsCRP (p 0.05) in group Q2I women, while there were positive correlations between serum sialic acid levels and BMI (p 0.05), waist circumference (p 0.05) and hsCRP (p 0.01) in group Q2 men (Tables 3 and 4). There was a positive correlation between serum sialic acid levels and hsCRP (p 0.05) in group Q1 women, while there was no correlation in group Q1 men (Tables 3 and 4). Simple correlation analyses were performed to investigate the association of serum sialic acid levels with anthropometric variables and biochemical parameters in the mixed group. As shown in Table 5, there were positive correlations between serum sialic acid levels and the values of BMI, waist circumference, SBP, DBP, HOMA-IR and the levels of serum glucose, insulin, TC, TG, LDL-C, hsCRP and MDA in the mixed group Q4 (p 0.01). There were positive correlations between serum sialic acid levels and BMI, waist circumference, SBP, DBP, glucose, insulin, TC, TG, LDL-C, hsCRP and MDA in the mixed group Q3 (p 0.05 for BMI and p 0.01 for the other parameters). There were negative correlations, however, between serum sialic acid levels and HDL-C in the mixed group Q3 (p 0.05). There were positive correlations between serum sialic acid levels and SBP, DBP, hsCRP in the mixed group Q2 (p 0.01 for SBP and p 0.05 for the other parameters).
Multiple linear regression analysis revealed that there was a positive correlation between the dependent variable, sialic acid, and BMI in the mixed group Q4 (β 0.260, p 0.018). Also, there was a positive correlation between the dependent variable, sialic acid, and glucose (β 0.220, p 0.045) in the mixed group Q4.
Age BMI Waist circumference SBP DBP Glucose Insulin HOMA-IR Total cholesterol Triglycerides HDL-C LDL-C hsCRP MDA
0.080 0.354 0.177 0.210 0.309 0.119 0.030 0.008 0.062 0.158 0.054 0.085 0.266 0.035
Discussion Obesity frequently causes significant impairment of health (Mehmetoğlu et al. 2012). BMI is the most widely used measure of body size and it frequently is used to estimate the prevalence of obesity within a population (Dalton et al. 2003). Patients with a high BMI may present with disease symptoms and acute decompensation earlier than patients with a low BMI (Horwich et al. 2001, Curtis et al. 2005). We found that the serum sialic acid levels of patients with high BMI were significantly higher than those with low BMI. Also, there were positive correlations between serum sialic acid levels and BMI and waist circumference in both obese women and men. It has been reported that BMI and sialic acid are related, because as BMI increases, the volume of body fluids increases, and therefore sialic acid increases (Abdulazeez et al. 2010). Englyst et al. (2006) reported that the percentage of body fat is an indepentent predictor of fasting serum sialic
Sialic acid and obesity 35
acid. These investigators suggested also that sialic acid concentration may reflect metabolic status and BMI. High C-reactive protein levels in obese subjects is evidence that obesity may be considered a low-grade inflammatory state (Wellen and Hotamisligil 2005, Hotamisligil 2006). The inflamation is caused by macrophage secretion of proinflammatory cytokines (Weisberg et al. 2003). Macrophages are an important source of proinflammatory factors including tumor necrosis factor (TNF)-α, interleukin (IL)-1 and IL-6 (Antuna-Puente et al. 2008, Hauner 2005). Serum sialic acid is a marker of acute-phase response (Crook et al. 2001) in which glycoproteins with sialic acid attached to the oligosaccharide side chains are produced by the liver in response to proinflammatory cytokines (Crook et al. 2001). We found a significant increase in serum hsCRP levels in groups Q3 and Q4 compared to group Q1 in both women and men. We also found that there were positive correlations between serum sialic acid levels and serum hsCRP levels in both obese women and men (groups Q2, Q3 and Q4). MDA is a naturally occurring product of lipid oxidation after exposure to reactive oxygen species (ROS) and free radicals; it can be used to evaluate oxidative damage by measuring serum TBARS levels (Yilmaz et al. 2007). We observed a significant increase in the serum MDA levels in groups Q3 and Q4 compared to group Q1 ( p 0.001). Also, there were positive correlations between serum sialic acid levels and serum MDA levels in both obese women and men (p 0.05 for group Q3 and p 0.01 for group Q4). We concluded that serum sialic acid levels of obese people increased with increasing oxidative stress. Earlier studies have shown that sialic acid may be a part of the defense against increased oxidative stress by acting as a H2O2 scavenger (Mohan and Priyav 2010, Iijima 2004), which may explain the correlation between sialic acid and MDA. On the other hand, it has been reported that nonreducing terminal sialic acid residues as well as proteins, lipids and DNA may be targets for ROS (Eguchi 2005). The release of sialic acid from the terminal residues of glycolipids of cell membranes could result from the breakdown of cell membranes and/or lipid oxidation; the released sialic acid would enter the serum to elevate plasma levels. Elevation of sialic acid levels has been considered a reflection of altered structural integrity of glycolipids in cell membranes (Yapar et al. 2007). Some earlier studies have suggested that serum sialic acid is a predictor of cardiovascular events (Gopaul and Crook 2006, Knuiman et al. 2004). We 36
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found a correlation between serum sialic acid and TC, TG and LDL-C levels in both obese women and men in group Q4. How sialic acid can predict cardiovascular events is not known, but the mechanism may be, in part, sialylation of lipoproteins (Crook et al. 1998). We also found correlations between serum sialic acid and SBP and DBP in both obese women and men. A possible explanation of these correlations is that sialic acid levels were elevated because of increased atherosclerosis (Pönniö et al. 1999). We demonstrated also correlations between serum sialic acid and glucose, and between insulin levels and resistance as assessed by the HOMA-IR values in both obese women and men. Fasting serum glucose and insulin levels may be associated with insulin resistance, which are associated with increased cardiovascular disease. On the other hand, we found no significant differences between serum sialic acid and age in either women or men. Earlier studies showed that there were no correlations between serum sialic acid levels and age for either sex (Crook et al. 1994, 1998). Our finding that there was no sex difference in serum sialic acid levels in obese people is consistent with the findings of other investigators (Hangloo et al. 1990). We found a correlation between serum sialic acid levels, BMI and oxidative stress. Also, serum sialic acid is associated with some conventional cardiovascular risk factors including lipid profile, blood pressure, fasting serum glucose and insulin levels, and insulin resistance in obese people. Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this paper.
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