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Lack of association of serum resistin levels with metabolic syndrome criteria in obese female patients
Clinical Biochemistry 44 (2011) 1280–1283
Contents lists available at SciVerse ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Lack of association of serum resistin levels with metabolic syndrome criteria in obese female patients D.A. de Luis ⁎, M. Gonzalez Sagrado, R. Conde, R. Aller, O. Izaola, D. Primo Institute of Endocrinology and Nutrition, Medicine School and Unit of Investigation, Hospital Rio Hortega, University of Valladolid, Valladolid Spain
a r t i c l e
i n f o
Article history: Received 21 July 2011 Received in revised form 31 August 2011 Accepted 4 September 2011 Available online 16 September 2011 Keywords: Females Metabolic syndrome Obesity Resistin
a b s t r a c t Background: As unclear data of resistin relation with metabolic syndrome has been published, we decide to investigate the association between metabolic syndrome and resistin levels in female obese subjects. Subjects: A sample of 551 female obese subjects was analyzed. A complete nutritional and biochemical evaluation was performed. Results: Levels of C reactive protein, weight, fat mass and waist circumference were higher in patients in the highest tertile group of resistin than the lowest and middle tertiles of resistin. In the multivariate analysis with metabolic syndrome presence/absence-, only fat mass remained as an independent predictor in the model. Resistin concentration increases 0.020 ng/ml (CI95%:0.006–0.038) for each kg of fat mass in female obese subjects. Conclusion: Only fat mass was associated in an independent way. Serum resistin was not associated with the accumulation of MetS factors or the diagnosis of MetS in obese female subjects. © 2011 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction Obesity and insulin resistance are associated with inflammatory markers and adipocytokines [1]. Metabolic syndrome (MetS) is a cluster of abnormalities including central obesity, glucose intolerance or diabetes, hypertension (HT) and dyslipidaemia [high triglycerides (TG) and/or low HDL], which increases the risk of cardio-vascular disease (CVD) [2]. As underlying insulin resistance could be fundamental for this syndrome, MetS factors could be correlated with serum resistin. Resistin has been shown to be inversely correlated with HDL cholesterol in healthy subjects [3] and subjects with mild diabetes, impaired glucose tolerance or normal glucose tolerance with family history of diabetes mellitus type 2 [4]. Resistin is associated with C-reactive protein in an independent way in naïve diabetic patients [5]. In contrast, it has been reported that resistin is not correlated with the number of MetS criteria or any of the individual factors in no diabetic subjects [6]. The adipose tissue is an active secretor organ of adipocytokines, sending out and responding to signals that modulate appetite, insulin sensitivity, energy expenditure, inflammation and immunity [7]. These molecules have been shown to be involved in the pathogenesis of the metabolic syndrome and one of these molecules is the abovementioned resistin. Resistin was identified as a gene whose expression is induced by adipocyte differentiation and inhibited by peroxisome
⁎ Corresponding author at: Institute of Endocrinology and Nutrition, Medicine Schooll, Valladolid University, C/Los perales 16, Simancas 47130, Valladolid, Spain. E-mail address: [email protected] (D.A. de Luis).
proliferators activated receptor ligands in 3T3-L1 cells [8]. In mice, resistin is secreted from adipocytes, and its serum levels are increased in obesity. The over-expression of the resistin gene in the liver increases insulin resistance, whereas its disruption reduces blood glucose [9]. Therefore, high serum resistin levels cause insulin resistance in rodents. In humans, data on the role of this adipocytokine in insulin sensitivity and obesity are controversial. Serum resistin levels are associated with obesity, visceral fat [10] and type 2 diabetes [11], while other groups failed to observe such correlations [12]. Also a sex interaction has been described in serum resistin levels [13]. Considering these previous unclear data, we decide to investigate the association between metabolic syndrome and resistin levels in female obese subjects. Subjects and methods Subjects A sample of 551 female obese subjects (body mass index N30 kg/m 2) was analyzed in a cross-sectional survey. This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving patients were approved by the HURH ethics committee. Written informed consent was obtained from all patients and signed. These patients were recruited in a Nutrition Clinic Unit and signed an informed consent. Exclusion criteria included history of cardiovascular disease or stroke during the previous 36 months, malignant tumor or major surgery during the previous 6 months as well as the use of glucocorticoids, antineoplastic agents, and drinking and/or smoking habit.
0009-9120/$ – see front matter © 2011 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.clinbiochem.2011.09.002
D.A. de Luis et al. / Clinical Biochemistry 44 (2011) 1280–1283
Protocol Weight, blood pressure, fasting glucose, insulin, total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides blood and resistin levels were measured at basal time. To estimate the prevalence of Metabolic Syndrome, the definitions of the ATPIII was considered [14]. The cutoff points for the criteria used are 3 or more of the following; central obesity (waist circumference N 88 cm in women and N102 cm in men), hypertriglyceridemia (triglycerides N150 mg/dL or specific treatment), hypertension (systolic blood pressureN 130 mm Hg or diastolic blood pressure N85 mm Hg or specific treatment) or fasting plasma glucoseN 110 mg/dL or drug treatment for elevated blood glucose. Biochemical assays CRP was measured by immunoturbimetry (Roche Diagnostics GmbH, Mannheim, Germany), analytical sensivity 0.5 mg/dL. Resistin was measured by ELISA (Biovendor Laboratory, Inc., Brno, Czech Republic) with a sensitivity of 0.2 ng/ml with a normal range of 4– 12 ng/ml. Serum total cholesterol and triglyceride concentrations were determined by enzymatic colorimetric assay (Technicon Instruments, Ltd., New York, N.Y., USA), while HDL cholesterol was determined enzymatically in the supernatant after precipitation of other lipoproteins with dextran sulfate–magnesium. LDL cholesterol was calculated using Friedewald formula. Plasma glucose levels were determined by using an automated glucose oxidase method (Glucose analyser 2, Beckman Instruments, Fullerton, California). Insulin was measured by enzymatic colorimetric (Insulin, WAKO Pure-Chemical Industries, Osaka, Japan) and the homeostasis model assessment for insulin resistance (HOMA-IR) was calculated using these values [15]. Anthropometric measurements Waist (narrowest diameter between xiphoid process and iliac crest) and hip (widest diameter over greater trochanters) circumferences to derive waist-to hip ratio (WHR) were measured, too. Body weight was measured to an accuracy of 0.1 kg and body mass index computed as body weight/(height 2). Tetrapolar body electrical bio impedance was used to determine body composition [16] (EFG, Akern, Italy) and applied to the skin using adhesive electrodes placed on right-side limbs. Resistance and reactance were used to calculate total body water, fat and fat-free mass. Blood pressure was measured twice after a 10 minute rest with a random zero mercury sphygmomanometer, and averaged. Dietary intake and habits Patients received prospective serial assessment of nutritional intake with 3 days written food records. All enrolled subjects received instruction to record their daily dietary intake for 3 days including a weekend day. Handling of the dietary data was by means of a personal computer equipped with personal software, incorporating use of food scales and models to enhance portion size accuracy. Records were analyzed with a computer-based data evaluation system. National composition food tables were used as reference [17]. Statistical analysis Sample size was calculated to detect differences over 45% of prevalence of metabolic syndrome with 90% power and 5% significance. The distribution of variables was analyzed with Kolmogorov–Smirnov test. Quantitative variables with normal distribution were analyzed with a two-tailed Student's-t test. Patients were divided by tertiles of resistin in 3 groups and ANOVA test was used where indicated. Non-parametric variables were analyzed with the Mann–Whitney U
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test. Pearson test was used to analyze correlation. Qualitative variables were analyzed with the chi-square test, with Yates correction as necessary, and Fisher's test. A multiple regression analysis was performed involving significant factors from ANOVA and simple regression analysis. A p-value under 0.05 was considered statistically significant. Results 551 patients gave informed consent and were enrolled in the study. The mean age was 56.9 ± 11.6 years. Baseline biochemical and anthropometrical characteristics of female obese subjects were presented in Table 1. Anthropometric measurements showed an average waist circumference (109.7±10.1 cm), waist-to hip ratio (0.90±0.06), BMI (36.6± 6.7) and average weight (92.8±17.7 kg). Serial assessment of nutritional intake with 3 days written food records showed a caloric intake of 1815 ± 340 kcal/day, a carbohydrate intake of 188.2±50.3 g/day, a fat intake of 80.4±30.6 g/day and a protein intake of 84.2±21.5 g/day. Tetrapolar body electrical bio impedance showed the next data; fat free mass (44.6±8.1 kg) and fat mass (45.5±12.3 kg). Patients were divided into three groups by tertiles of resistin value, group I (patients with values, below of 3.2 ng/ml), group II (patients with values, from 3.2 ng/ml till 4.7 ng/ml) and group 3 (patients with the high values, above of 4.7 ng/ml). A total of 255 females had metabolic syndrome (46.3%). Table 2 shows percentages of metabolic syndrome among groups of resistin tertiles. No statistical differences were detected. Table 3 shows the statistical differences among these 3 groups of resistin tertiles in epidemiological and biochemical parameters. Levels of C reactive protein, weight, fat mass and waist circumference were higher in patients in the highest tertile group of resistin than the lowest and middle tertiles of resistin. Table 4 shows dietary intake of three groups (tertiles of resistin). No statistical differences were observed. Table 5 shows levels of resistin according to number of determinant of the metabolic syndrome. The increase in the number of these determinants was not related with resistin levels. Correlation analysis showed a significant correlation among serum resistin levels and the independent variables; weight (r = 0.21; p b 0.05), BMI (r = 0.16; p b 0.05), waist circumference (r = 0.23; p b 0.05), fat mass (r = 0.17; p b 0.05) and C reactive protein (r = 0.24; p b 0.05) (Table 6).
Table 1 Anthropometric and biochemical variables, metabolic syndrome vs no metabolic syndrome in female obese subjects. Parameters
Metabolic syndrome (n = 450)
No metabolic syndrome (n = 101)
BMI Weight (kg) Fat mass (kg) WC (cm) Waist to hip ratio Systolic BP (mm Hg) Diastolic BP (mm Hg) Glucose (mg/dL) Total ch. (mg/dL) LDL-ch. (mg/dL) HDL-ch. (mg/dL) TG (mg/dL) Insulin (mUI/L) HOMA-IR CRP (mg/dL)
37.8 ± 6.7 93.6 ± 17.6 47.5 ± 14.3 112.4 ± 14.5 0.92 ± 0.07 137.3 ± 15.8 86.6 ± 9.5 110.1 ± 26.4 209.6 ± 37.5 128.4 ± 36.2 56.8 ± 15.8 132.6 ± 59.7 16.1 ± 9.3 4.38 ± 2.8 6.29 ± 8.1
35.3 ± 5.7⁎ 90.3 ± 15.6⁎ 41.3 ± 12.2⁎ 105.6 ± 12.9⁎ 0.88 ± 0.07⁎ 121.9 ± 13.3⁎ 78.3 ± 9.4⁎ 91.2 ± 11.2⁎ 196.4 ± 40.5⁎ 118.7 ± 39.5⁎ 56.5 ± 22.6 96.4 ± 40.4⁎ 12.8 ± 6.6⁎ 2.79 ± 1.5⁎ 5.54 ± 8.8
BMI: body mas index. Ch: Cholesterol. TG: Triglycerides. HOMA-IR: Homeostasis model assessment. WC: Waist circumference. ⁎ p b 0.05, between groups.
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D.A. de Luis et al. / Clinical Biochemistry 44 (2011) 1280–1283
Table 2 Percentage of metabolic syndrome in tertiles of resistin in female obese subjects.
Table 4 Dietary intake in tertiles of resistin in female obese subjects.
Tertiles
1 (b3.2 ng/ml)
2 (3.2–4,7 ng/ml)
3 (N4.7 ng/ml)
Tertiles
1 (b3.2 ng/ml)
2 (3.2–4.7 ng/ml)
3 (N4.7 ng/ml)
Metabolic syndrome (%) No metabolic syndrome (%)
52.2% 47.8%
44.8% 55.2%
52.4% 47.6%
Energy (kcal/day) CH (g/day) Fat (g/day) Protein (g/day) Exercise (h/week) Dietary fiber
1855 ± 654 189.3 ± 80.4 81.9 ± 34.3 90.8 ± 26.8 2.0 ± 3.5 15.8 ± 7.1
1888 ± 644 199.9 ± 77.5 86.8 ± 39.1 88.3 ± 21.3 1.5 ± 2.6 15.5 ± 6.7
1932 ± 689 186.5 ± 80.1 88.7 ± 39.5 92.5 ± 30.3 1.7 ± 2.8 14.1 ± 6.2
In the multivariate analysis with metabolic syndrome presence/ absence-, diabetes mellitus presence/absence, age- and weightadjusted basal resistin concentration as a dependent variable, only fat mass remained as an independent predictor in the model (F = 5.5; p b 0.05), with a direct correlation. Resistin concentration increases 0.020 ng/ml (CI95%: 0.006–0.038) for each kg of fat mass in female obese subjects (Table 6). Discussion Our findings showed that serum resistin was correlated with weight, fat mass, waist circumference and C reactive protein in female obese subjects. However in the multivariate analysis, only fat mass remained associated. Serum resistin was not associated with the presence of metabolic syndrome or the accumulation of MetS factors in female obese patients. We have shown that serum resistin was correlated in female obese subjects with weight, wais circumference, and especially with fat mass in the multivariate model, although body mass index itself was not correlated with serum resistin. Actually, the relation between serum resistin and weight has been controversial [18–20]. As the main source of serum resistin in humans is thought to be macrophages [21,22], adiposity itself may not be simply correlated with serum resistin. It has been reported that macrophages infiltrate into adipose tissues in obesity, and secrete cytokines, which induce systemic insulin resistance [23]. The secretion of resistin from these infiltrating macrophages. In our study, serum resistin was positively associated with C reactive protein (CRP). Serum resistin has been reported to be positively associated with CRP [24,25]. In vitro, resistin increases intracellular adhesion molecule-1(ICAM-1) gene expression in vascular endothelial cells, vascular cell adhesion molecule-1 (VCAM-1) and promotes endothelial cell activation by increasing endothelin-1 (ET-1) release [26]. Cell-culture experiments on isolated monocytes demonstrated
Table 3 Anthropometric and biochemical variables in tertiles of resistin in female obese subjects. Tertiles
1 (b 3.2 ng/ml)
2 (3.2–4.7 ng/ml)
3 (N4.7 ng/ml)
BMI Weight (kg) Fat mass (kg) Waist circumference Waist to hip ratio Systolic BP (mm Hg) Diastolic BP (mm Hg) Glucose (mg/dL) Total ch. (mg/dL) LDL-ch. (mg/dL) HDL-ch. (mg/dL) TG (mg/dL) Insulin (mUI/L) HOMA-IR CRP (mg/dL)
35.9 ± 5.9 90.4 ± 16.3 41.9 ± 12.1 108.1 ± 11.4 0.90 ± 0.08 139.5 ± 17.7 85.1 ± 7.9 101.1 ± 17.1 208.2 ± 44.4 124.9 ± 42.7 57.7 ± 14.1 111.7 ± 56.7 13.8 ± 8.4 3.54 ± 2.5 5.30 ± 5.6
36.0 ± 5.7 92.6 ± 16.3+ 43.9 ± 13.3+ 110.5 ± 14+ 0.90 ± 0.07 138.4 ± 21.2 83.8 ± 14.2 101.6 ± 20.9 209.3 ± 43.6 134.7 ± 42.3 55.7 ± 11.1 112.8 ± 59.3 13.7 ± 6.8 3.50 ± 2.1 7.71 ± 8.2+
36.9 ± 8.1* 95.2 ± 19.9* 46.9 ± 12.9* 111.9 ± 13* 0.89 ± 0.1 135.6 ± 19.7 80.1 ± 10.2 96.8 ± 16.6 201.8 ± 37.8 125.6 ± 36.2 56.5 ± 27.2 116.8 ± 51.1 14.4 ± 8.6 3.55 ± 2.4 7.34 ± 7.1*
MS: metabolic syndrome. BMI: body mas index. Ch: Cholesterol. HOMA-IR: Homeostasis model assessment. TG: Triglycerides . WC: Waist circumference. Statistical differences (pb 0.05) between second and first tertile (+). Statistical differences (pb 0.05) between third and first tertile (⁎).
CH: Carbohydrate. No statistical differences.
that resistin regulates proinflammatory cytokine secretion through the nuclear factor-kappa Beta pathway [27], a master controller of the proinflammatory process. However, the relation of resistin and CRP disappeared in multivariate analysis, and this could demonstrate an indirect relation of both molecules with total fat mass of the body and the presence of macrophages in this tissue of female obese subjects. Our findings show that serum resistin was not correlated with cholesterol and triglyceride levels in female obese subjects. In other studies, it has been demonstrated that resistin is associated with low HDL in healthy and T2DM (diabetes mellitus type 2) subjects [28,2]. Mice, of which resistin is over-expressed in the liver by adenovirus, have the characteristics of MetS such as increased insulin resistance, low serum HDL and high triglyceride [29]. Insulin is known to up-regulate lipoprotein lipase, a critical factor for the production of HDL, and the lipolysis of triglyceride, and this relation could be the explanation of this association. Other authors [30] have reported that blood pressure was positively correlated with circulating resistin, which did not remain significant when adjusted by age, gender and BMI in the general population. However, in our female obese subjects, this association has not been reported. Our data did not show an association between resistin and metabolic syndrome. Other authors [30] have shown that serum resistin was positively correlated with the accumulation of MetS factors in patients with diabetes mellitus type 2. Menzaghi et al. also reported that significant genetic correlations were observed between resistin and weight, waist circumference, insulin resistance (HOMA-IR), and the MetS score by analyzing nondiabetic subjects and their adult family members [31]. In contrast, it has been reported that plasma resistin was not correlated with the number of MetS criteria or any of the individual factors in no diabetic subjects [6]. These differences with metabolic syndrome association, lipid or blood pressure levels, could be explained by the studied subjects (diabetic or non diabetic patients), sex distribution, different average of BMI, the sample numbers, type of design (cross-sectional vs. cohort) and potential effect of drugs used by subjects could not be excluded. Prospective studies are required to address this critical question. In summary, serum resistin was correlated with CRP, weight, fat mass and waist circumference. However, only fat mass was associated, in an independent way. Serum resistin was not associated with the accumulation of MetS factors or the diagnosis of MetS in obese female subjects.
Table 5 Levels of resistin according to number of determinant of the metabolic syndrome in female obese subjects. Number of determinant
(RESISTIN levels ng/ml)
0 (n = 101) 1 (n = 93) 2 (n = 102) 3 and 4 (n = 255)
4.51 ± 2.4 (ng/ml) 4.08 ± 2.1 (ng/ml) 4.52 ± 1.3 (ng/ml) 4.41 ± 2.39 (ng/ml)
D.A. de Luis et al. / Clinical Biochemistry 44 (2011) 1280–1283 Table 6 Correlation analysis and multivariate analysis results in female obese subjects. Parameter
(r value with RESISTIN ng/ml)
Weight BMI Waist circumference Fat mass C reactive protein Multivariate analysis Fat mass
(r = 0.21;p b 0.05) (r = 0.16;p b 0.05) (r = 0.23;p b 0.05) (r = 0.17;p b 0.05) (r = 0.24;p b 0.05) Beta coefficient and CI 95% 0.020 ng/ml (0.006–0.038)
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[15] Mathews DR, Hosker JP, Rudenski AS, Naylor BA. Treacher Df. Homesotasis model assessment: insulin resistance and beta cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–4. [16] Lukaski H, Johson PE. Assessment of fat-free mass using bioelectrical impedance measurements of the human body. Am J Clin Nutr Apr 1985;41(4):810–7. [17] Mataix J, Mañas M. Tablas de composición de alimentos españoles. Ed: University of Granada, 2003. [18] Azuma K, Katsukawa F, Oguchi S, Murata M, Yamazaki H, Shimada A, et al. Correlation between serum resistin level and adiposity in obese individuals. Obes Res 2003;11:997–1001. [19] McTernan PG, Fisher FM, Valsamakis G, Chetty R, Harte A, McTernan CL, et al. Resistin and type 2 diabetes: regulation of resistin expression by insulin and rosiglitazone and the effects of recombinant resistin on lipid and glucose metabolism in human differentiated adipocytes. J Clin Endocrinol Metab 2003;88: 6098–106. [20] Youn B-S, Yu K-Y, Park HJ, Lee NS, Min SS, Youn MY, et al. Plasma resistin concentrations measured by enzyme-linked immunosorbent assay using a newly developed monoclonal antibody are elevated in individuals with type 2 diabetes mellitus. J Clin Endocrinol Metab 2004;89:150–6. [21] Osawa H, Onuma H, Ochi M, Murakami A, Yamauchi J, Takasuka T, et al. Resistin SNP-420 determines its monocyte mRNA and serum levels inducing type 2 diabetes. Biochem Biophys Res Commun 2005;335:596–602. [22] Savage DB, Sewter CP, Klenk ES, Segal DG, Vidal-Puig A, Considine RV, et al. Resistin/ Fizz3 expression in relation to obesity and peroxisome proliferator-activated receptor-γ action in humans. Diabetes 2001;50:2199–202. [23] Xu H, Barnes GT, Yang Q, Tan G, Yang D, Chou CJ, et al. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J Clin Invest 2003;112:1821–30. [24] Shetty GK, Economides PA, Horton ES, Mantzoros CS, Veves A. Circulating adiponectin and resistin levels in relation to metabolic factors, inflammatory markers, and vascular reactivity in diabetic patients and subjects at risk for diabetes. Diabetes Care 2004;27:2450–7. [25] Fujinami A, Obayashi H, Ohta K, Ichimura T, Nishimura M, Matsui H, et al. Enzymelinked immunosorbent assay for circulating human resistin: resistin concentrations in normal subjects and patients with type 2 diabetes. Clin Chim Acta 2004;339: 57–63. [26] Kawanami D, Maemura K, Takeda N, Harada T, Nojiri T, Imai Y, et al. Direct reciprocal effects of resistin and adiponectin on vascular endothelial cells: a new insight into adipocytokine–endothelial cell interactions. Biochem Biophys Res Commun 2004;314:415–9. [27] Bokarewa M, Nagaev I, Dahlberg L, Smith U, Tarkowski A. Resistin, an adipokine with potent proinflammatory properties. J Immunol 2005;174:5789–95. [28] Chen CC, Li TC, Li CI, Liu CS, Wang HJ, Lin CC. Serum resistin level among healthy subjects: relationship to anthropometric and metabolic parameters. Metabolism 2005;54:471–5. [29] Sato N, Kobayashi K, Inoguchi T, Sonoda N, Imamura M, Sekiguchi N, et al. Adenovirusmediated high expression of resistin causes dyslipidemia in mice. Endocrinology 2005;146:273–9. [30] Osawa H, Ochi M, Tabara Y, Kat K, Yamauchi J, Takata Y, et al. Serum resistin is positively correlated with the acumulation of metabolic síndrome factors in type 2 diabetes. Clin Endocrinol 2008;69:74–80. [31] Menzaghi C, Coco A, Salvemini L, Thompson R, De Cosmo S, Doria A, et al. Heritability of serum resistin and its genetic correlation with insulin resistancerelated features in nondiabetic Caucasians. J Clin Endocrinol Metab 2006;91: 2792–5.
Contents lists available at SciVerse ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Lack of association of serum resistin levels with metabolic syndrome criteria in obese female patients D.A. de Luis ⁎, M. Gonzalez Sagrado, R. Conde, R. Aller, O. Izaola, D. Primo Institute of Endocrinology and Nutrition, Medicine School and Unit of Investigation, Hospital Rio Hortega, University of Valladolid, Valladolid Spain
a r t i c l e
i n f o
Article history: Received 21 July 2011 Received in revised form 31 August 2011 Accepted 4 September 2011 Available online 16 September 2011 Keywords: Females Metabolic syndrome Obesity Resistin
a b s t r a c t Background: As unclear data of resistin relation with metabolic syndrome has been published, we decide to investigate the association between metabolic syndrome and resistin levels in female obese subjects. Subjects: A sample of 551 female obese subjects was analyzed. A complete nutritional and biochemical evaluation was performed. Results: Levels of C reactive protein, weight, fat mass and waist circumference were higher in patients in the highest tertile group of resistin than the lowest and middle tertiles of resistin. In the multivariate analysis with metabolic syndrome presence/absence-, only fat mass remained as an independent predictor in the model. Resistin concentration increases 0.020 ng/ml (CI95%:0.006–0.038) for each kg of fat mass in female obese subjects. Conclusion: Only fat mass was associated in an independent way. Serum resistin was not associated with the accumulation of MetS factors or the diagnosis of MetS in obese female subjects. © 2011 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction Obesity and insulin resistance are associated with inflammatory markers and adipocytokines [1]. Metabolic syndrome (MetS) is a cluster of abnormalities including central obesity, glucose intolerance or diabetes, hypertension (HT) and dyslipidaemia [high triglycerides (TG) and/or low HDL], which increases the risk of cardio-vascular disease (CVD) [2]. As underlying insulin resistance could be fundamental for this syndrome, MetS factors could be correlated with serum resistin. Resistin has been shown to be inversely correlated with HDL cholesterol in healthy subjects [3] and subjects with mild diabetes, impaired glucose tolerance or normal glucose tolerance with family history of diabetes mellitus type 2 [4]. Resistin is associated with C-reactive protein in an independent way in naïve diabetic patients [5]. In contrast, it has been reported that resistin is not correlated with the number of MetS criteria or any of the individual factors in no diabetic subjects [6]. The adipose tissue is an active secretor organ of adipocytokines, sending out and responding to signals that modulate appetite, insulin sensitivity, energy expenditure, inflammation and immunity [7]. These molecules have been shown to be involved in the pathogenesis of the metabolic syndrome and one of these molecules is the abovementioned resistin. Resistin was identified as a gene whose expression is induced by adipocyte differentiation and inhibited by peroxisome
⁎ Corresponding author at: Institute of Endocrinology and Nutrition, Medicine Schooll, Valladolid University, C/Los perales 16, Simancas 47130, Valladolid, Spain. E-mail address: [email protected] (D.A. de Luis).
proliferators activated receptor ligands in 3T3-L1 cells [8]. In mice, resistin is secreted from adipocytes, and its serum levels are increased in obesity. The over-expression of the resistin gene in the liver increases insulin resistance, whereas its disruption reduces blood glucose [9]. Therefore, high serum resistin levels cause insulin resistance in rodents. In humans, data on the role of this adipocytokine in insulin sensitivity and obesity are controversial. Serum resistin levels are associated with obesity, visceral fat [10] and type 2 diabetes [11], while other groups failed to observe such correlations [12]. Also a sex interaction has been described in serum resistin levels [13]. Considering these previous unclear data, we decide to investigate the association between metabolic syndrome and resistin levels in female obese subjects. Subjects and methods Subjects A sample of 551 female obese subjects (body mass index N30 kg/m 2) was analyzed in a cross-sectional survey. This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving patients were approved by the HURH ethics committee. Written informed consent was obtained from all patients and signed. These patients were recruited in a Nutrition Clinic Unit and signed an informed consent. Exclusion criteria included history of cardiovascular disease or stroke during the previous 36 months, malignant tumor or major surgery during the previous 6 months as well as the use of glucocorticoids, antineoplastic agents, and drinking and/or smoking habit.
0009-9120/$ – see front matter © 2011 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.clinbiochem.2011.09.002
D.A. de Luis et al. / Clinical Biochemistry 44 (2011) 1280–1283
Protocol Weight, blood pressure, fasting glucose, insulin, total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides blood and resistin levels were measured at basal time. To estimate the prevalence of Metabolic Syndrome, the definitions of the ATPIII was considered [14]. The cutoff points for the criteria used are 3 or more of the following; central obesity (waist circumference N 88 cm in women and N102 cm in men), hypertriglyceridemia (triglycerides N150 mg/dL or specific treatment), hypertension (systolic blood pressureN 130 mm Hg or diastolic blood pressure N85 mm Hg or specific treatment) or fasting plasma glucoseN 110 mg/dL or drug treatment for elevated blood glucose. Biochemical assays CRP was measured by immunoturbimetry (Roche Diagnostics GmbH, Mannheim, Germany), analytical sensivity 0.5 mg/dL. Resistin was measured by ELISA (Biovendor Laboratory, Inc., Brno, Czech Republic) with a sensitivity of 0.2 ng/ml with a normal range of 4– 12 ng/ml. Serum total cholesterol and triglyceride concentrations were determined by enzymatic colorimetric assay (Technicon Instruments, Ltd., New York, N.Y., USA), while HDL cholesterol was determined enzymatically in the supernatant after precipitation of other lipoproteins with dextran sulfate–magnesium. LDL cholesterol was calculated using Friedewald formula. Plasma glucose levels were determined by using an automated glucose oxidase method (Glucose analyser 2, Beckman Instruments, Fullerton, California). Insulin was measured by enzymatic colorimetric (Insulin, WAKO Pure-Chemical Industries, Osaka, Japan) and the homeostasis model assessment for insulin resistance (HOMA-IR) was calculated using these values [15]. Anthropometric measurements Waist (narrowest diameter between xiphoid process and iliac crest) and hip (widest diameter over greater trochanters) circumferences to derive waist-to hip ratio (WHR) were measured, too. Body weight was measured to an accuracy of 0.1 kg and body mass index computed as body weight/(height 2). Tetrapolar body electrical bio impedance was used to determine body composition [16] (EFG, Akern, Italy) and applied to the skin using adhesive electrodes placed on right-side limbs. Resistance and reactance were used to calculate total body water, fat and fat-free mass. Blood pressure was measured twice after a 10 minute rest with a random zero mercury sphygmomanometer, and averaged. Dietary intake and habits Patients received prospective serial assessment of nutritional intake with 3 days written food records. All enrolled subjects received instruction to record their daily dietary intake for 3 days including a weekend day. Handling of the dietary data was by means of a personal computer equipped with personal software, incorporating use of food scales and models to enhance portion size accuracy. Records were analyzed with a computer-based data evaluation system. National composition food tables were used as reference [17]. Statistical analysis Sample size was calculated to detect differences over 45% of prevalence of metabolic syndrome with 90% power and 5% significance. The distribution of variables was analyzed with Kolmogorov–Smirnov test. Quantitative variables with normal distribution were analyzed with a two-tailed Student's-t test. Patients were divided by tertiles of resistin in 3 groups and ANOVA test was used where indicated. Non-parametric variables were analyzed with the Mann–Whitney U
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test. Pearson test was used to analyze correlation. Qualitative variables were analyzed with the chi-square test, with Yates correction as necessary, and Fisher's test. A multiple regression analysis was performed involving significant factors from ANOVA and simple regression analysis. A p-value under 0.05 was considered statistically significant. Results 551 patients gave informed consent and were enrolled in the study. The mean age was 56.9 ± 11.6 years. Baseline biochemical and anthropometrical characteristics of female obese subjects were presented in Table 1. Anthropometric measurements showed an average waist circumference (109.7±10.1 cm), waist-to hip ratio (0.90±0.06), BMI (36.6± 6.7) and average weight (92.8±17.7 kg). Serial assessment of nutritional intake with 3 days written food records showed a caloric intake of 1815 ± 340 kcal/day, a carbohydrate intake of 188.2±50.3 g/day, a fat intake of 80.4±30.6 g/day and a protein intake of 84.2±21.5 g/day. Tetrapolar body electrical bio impedance showed the next data; fat free mass (44.6±8.1 kg) and fat mass (45.5±12.3 kg). Patients were divided into three groups by tertiles of resistin value, group I (patients with values, below of 3.2 ng/ml), group II (patients with values, from 3.2 ng/ml till 4.7 ng/ml) and group 3 (patients with the high values, above of 4.7 ng/ml). A total of 255 females had metabolic syndrome (46.3%). Table 2 shows percentages of metabolic syndrome among groups of resistin tertiles. No statistical differences were detected. Table 3 shows the statistical differences among these 3 groups of resistin tertiles in epidemiological and biochemical parameters. Levels of C reactive protein, weight, fat mass and waist circumference were higher in patients in the highest tertile group of resistin than the lowest and middle tertiles of resistin. Table 4 shows dietary intake of three groups (tertiles of resistin). No statistical differences were observed. Table 5 shows levels of resistin according to number of determinant of the metabolic syndrome. The increase in the number of these determinants was not related with resistin levels. Correlation analysis showed a significant correlation among serum resistin levels and the independent variables; weight (r = 0.21; p b 0.05), BMI (r = 0.16; p b 0.05), waist circumference (r = 0.23; p b 0.05), fat mass (r = 0.17; p b 0.05) and C reactive protein (r = 0.24; p b 0.05) (Table 6).
Table 1 Anthropometric and biochemical variables, metabolic syndrome vs no metabolic syndrome in female obese subjects. Parameters
Metabolic syndrome (n = 450)
No metabolic syndrome (n = 101)
BMI Weight (kg) Fat mass (kg) WC (cm) Waist to hip ratio Systolic BP (mm Hg) Diastolic BP (mm Hg) Glucose (mg/dL) Total ch. (mg/dL) LDL-ch. (mg/dL) HDL-ch. (mg/dL) TG (mg/dL) Insulin (mUI/L) HOMA-IR CRP (mg/dL)
37.8 ± 6.7 93.6 ± 17.6 47.5 ± 14.3 112.4 ± 14.5 0.92 ± 0.07 137.3 ± 15.8 86.6 ± 9.5 110.1 ± 26.4 209.6 ± 37.5 128.4 ± 36.2 56.8 ± 15.8 132.6 ± 59.7 16.1 ± 9.3 4.38 ± 2.8 6.29 ± 8.1
35.3 ± 5.7⁎ 90.3 ± 15.6⁎ 41.3 ± 12.2⁎ 105.6 ± 12.9⁎ 0.88 ± 0.07⁎ 121.9 ± 13.3⁎ 78.3 ± 9.4⁎ 91.2 ± 11.2⁎ 196.4 ± 40.5⁎ 118.7 ± 39.5⁎ 56.5 ± 22.6 96.4 ± 40.4⁎ 12.8 ± 6.6⁎ 2.79 ± 1.5⁎ 5.54 ± 8.8
BMI: body mas index. Ch: Cholesterol. TG: Triglycerides. HOMA-IR: Homeostasis model assessment. WC: Waist circumference. ⁎ p b 0.05, between groups.
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Table 2 Percentage of metabolic syndrome in tertiles of resistin in female obese subjects.
Table 4 Dietary intake in tertiles of resistin in female obese subjects.
Tertiles
1 (b3.2 ng/ml)
2 (3.2–4,7 ng/ml)
3 (N4.7 ng/ml)
Tertiles
1 (b3.2 ng/ml)
2 (3.2–4.7 ng/ml)
3 (N4.7 ng/ml)
Metabolic syndrome (%) No metabolic syndrome (%)
52.2% 47.8%
44.8% 55.2%
52.4% 47.6%
Energy (kcal/day) CH (g/day) Fat (g/day) Protein (g/day) Exercise (h/week) Dietary fiber
1855 ± 654 189.3 ± 80.4 81.9 ± 34.3 90.8 ± 26.8 2.0 ± 3.5 15.8 ± 7.1
1888 ± 644 199.9 ± 77.5 86.8 ± 39.1 88.3 ± 21.3 1.5 ± 2.6 15.5 ± 6.7
1932 ± 689 186.5 ± 80.1 88.7 ± 39.5 92.5 ± 30.3 1.7 ± 2.8 14.1 ± 6.2
In the multivariate analysis with metabolic syndrome presence/ absence-, diabetes mellitus presence/absence, age- and weightadjusted basal resistin concentration as a dependent variable, only fat mass remained as an independent predictor in the model (F = 5.5; p b 0.05), with a direct correlation. Resistin concentration increases 0.020 ng/ml (CI95%: 0.006–0.038) for each kg of fat mass in female obese subjects (Table 6). Discussion Our findings showed that serum resistin was correlated with weight, fat mass, waist circumference and C reactive protein in female obese subjects. However in the multivariate analysis, only fat mass remained associated. Serum resistin was not associated with the presence of metabolic syndrome or the accumulation of MetS factors in female obese patients. We have shown that serum resistin was correlated in female obese subjects with weight, wais circumference, and especially with fat mass in the multivariate model, although body mass index itself was not correlated with serum resistin. Actually, the relation between serum resistin and weight has been controversial [18–20]. As the main source of serum resistin in humans is thought to be macrophages [21,22], adiposity itself may not be simply correlated with serum resistin. It has been reported that macrophages infiltrate into adipose tissues in obesity, and secrete cytokines, which induce systemic insulin resistance [23]. The secretion of resistin from these infiltrating macrophages. In our study, serum resistin was positively associated with C reactive protein (CRP). Serum resistin has been reported to be positively associated with CRP [24,25]. In vitro, resistin increases intracellular adhesion molecule-1(ICAM-1) gene expression in vascular endothelial cells, vascular cell adhesion molecule-1 (VCAM-1) and promotes endothelial cell activation by increasing endothelin-1 (ET-1) release [26]. Cell-culture experiments on isolated monocytes demonstrated
Table 3 Anthropometric and biochemical variables in tertiles of resistin in female obese subjects. Tertiles
1 (b 3.2 ng/ml)
2 (3.2–4.7 ng/ml)
3 (N4.7 ng/ml)
BMI Weight (kg) Fat mass (kg) Waist circumference Waist to hip ratio Systolic BP (mm Hg) Diastolic BP (mm Hg) Glucose (mg/dL) Total ch. (mg/dL) LDL-ch. (mg/dL) HDL-ch. (mg/dL) TG (mg/dL) Insulin (mUI/L) HOMA-IR CRP (mg/dL)
35.9 ± 5.9 90.4 ± 16.3 41.9 ± 12.1 108.1 ± 11.4 0.90 ± 0.08 139.5 ± 17.7 85.1 ± 7.9 101.1 ± 17.1 208.2 ± 44.4 124.9 ± 42.7 57.7 ± 14.1 111.7 ± 56.7 13.8 ± 8.4 3.54 ± 2.5 5.30 ± 5.6
36.0 ± 5.7 92.6 ± 16.3+ 43.9 ± 13.3+ 110.5 ± 14+ 0.90 ± 0.07 138.4 ± 21.2 83.8 ± 14.2 101.6 ± 20.9 209.3 ± 43.6 134.7 ± 42.3 55.7 ± 11.1 112.8 ± 59.3 13.7 ± 6.8 3.50 ± 2.1 7.71 ± 8.2+
36.9 ± 8.1* 95.2 ± 19.9* 46.9 ± 12.9* 111.9 ± 13* 0.89 ± 0.1 135.6 ± 19.7 80.1 ± 10.2 96.8 ± 16.6 201.8 ± 37.8 125.6 ± 36.2 56.5 ± 27.2 116.8 ± 51.1 14.4 ± 8.6 3.55 ± 2.4 7.34 ± 7.1*
MS: metabolic syndrome. BMI: body mas index. Ch: Cholesterol. HOMA-IR: Homeostasis model assessment. TG: Triglycerides . WC: Waist circumference. Statistical differences (pb 0.05) between second and first tertile (+). Statistical differences (pb 0.05) between third and first tertile (⁎).
CH: Carbohydrate. No statistical differences.
that resistin regulates proinflammatory cytokine secretion through the nuclear factor-kappa Beta pathway [27], a master controller of the proinflammatory process. However, the relation of resistin and CRP disappeared in multivariate analysis, and this could demonstrate an indirect relation of both molecules with total fat mass of the body and the presence of macrophages in this tissue of female obese subjects. Our findings show that serum resistin was not correlated with cholesterol and triglyceride levels in female obese subjects. In other studies, it has been demonstrated that resistin is associated with low HDL in healthy and T2DM (diabetes mellitus type 2) subjects [28,2]. Mice, of which resistin is over-expressed in the liver by adenovirus, have the characteristics of MetS such as increased insulin resistance, low serum HDL and high triglyceride [29]. Insulin is known to up-regulate lipoprotein lipase, a critical factor for the production of HDL, and the lipolysis of triglyceride, and this relation could be the explanation of this association. Other authors [30] have reported that blood pressure was positively correlated with circulating resistin, which did not remain significant when adjusted by age, gender and BMI in the general population. However, in our female obese subjects, this association has not been reported. Our data did not show an association between resistin and metabolic syndrome. Other authors [30] have shown that serum resistin was positively correlated with the accumulation of MetS factors in patients with diabetes mellitus type 2. Menzaghi et al. also reported that significant genetic correlations were observed between resistin and weight, waist circumference, insulin resistance (HOMA-IR), and the MetS score by analyzing nondiabetic subjects and their adult family members [31]. In contrast, it has been reported that plasma resistin was not correlated with the number of MetS criteria or any of the individual factors in no diabetic subjects [6]. These differences with metabolic syndrome association, lipid or blood pressure levels, could be explained by the studied subjects (diabetic or non diabetic patients), sex distribution, different average of BMI, the sample numbers, type of design (cross-sectional vs. cohort) and potential effect of drugs used by subjects could not be excluded. Prospective studies are required to address this critical question. In summary, serum resistin was correlated with CRP, weight, fat mass and waist circumference. However, only fat mass was associated, in an independent way. Serum resistin was not associated with the accumulation of MetS factors or the diagnosis of MetS in obese female subjects.
Table 5 Levels of resistin according to number of determinant of the metabolic syndrome in female obese subjects. Number of determinant
(RESISTIN levels ng/ml)
0 (n = 101) 1 (n = 93) 2 (n = 102) 3 and 4 (n = 255)
4.51 ± 2.4 (ng/ml) 4.08 ± 2.1 (ng/ml) 4.52 ± 1.3 (ng/ml) 4.41 ± 2.39 (ng/ml)
D.A. de Luis et al. / Clinical Biochemistry 44 (2011) 1280–1283 Table 6 Correlation analysis and multivariate analysis results in female obese subjects. Parameter
(r value with RESISTIN ng/ml)
Weight BMI Waist circumference Fat mass C reactive protein Multivariate analysis Fat mass
(r = 0.21;p b 0.05) (r = 0.16;p b 0.05) (r = 0.23;p b 0.05) (r = 0.17;p b 0.05) (r = 0.24;p b 0.05) Beta coefficient and CI 95% 0.020 ng/ml (0.006–0.038)
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