Werida et al. 2013
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Correlations between adipocytokines and insulin resistance in obese and
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non obese type 2 diabetic patients
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Hoda A. El-Bahrawya, Sahar K. Hegazyb, Wael F. Farragc, Rehab H. Weridad
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a
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Egypt
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b
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Egypt
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c
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Egypt
Biochemistry Department, Faculty of Pharmacy, Tanta University, El-Gharbia, 31527,
Clinical Pharmacy Department, Faculty of Pharmacy, Tanta University, El-Gharbia, 31527,
Internal Medicine Department, Faculty of Medicine, Tanta University, El-Gharbia, 31527,
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d
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Egypt, rehab_werida@hotmail.com
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Tel. No.: 002 01005359968
Drug Information Center, Faculty of Pharmacy, Tanta University, El-Gharbia, 31527,
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002 0403349180
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Fax No.: 002 0403335466
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Abstract
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Aim: This study aimed to investigate the association between body mass index BMI,
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adipocytokines and insulin resistance in obese and non obese type 2 diabetics.
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Method: Eighty diabetic patients aged 40-60 years old were divided into 2 groups: Obese
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diabetic group (BMI>25 kg/m2) and Non obese diabetic group (BMI ≤ 25 kg/m2). Serum
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leptin, adiponectin, tumor necrosis factor-alpha (TNF-α) and visfatin were measured by
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enzyme-linked immunosorbent assay (ELISA). Serum fasting glucose, glycated hemoglobin
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%, C-peptide, total cholesterol, high-density lipoprotein (HDL-C) and low-density lipoprotein
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cholesterol (LDL-C) and triglycerides levels were measured. Insulin resistance was estimated
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by homeostasis model assessment (HOMA2-IR).
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Results: A positive association between BMI with fasting glucose, glycated hemoglobin %,
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C-peptide, TNF-α, visfatin, total cholesterol, LDL-C, triglycerides and HOMA2-IR, and a
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negative association with HDL-C and adiponectin were revealed (p < 0.05).
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Conclusions: The higher levels of visfatin, TNF-α and atherogenic lipids and the lower level
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of adiponectin in obese diabetics, suggested that different adipocytokines may play different
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roles of insulin resistance which may increase susceptibility for more complications in case
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of obesity and type 2 diabetes.
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Keywords
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Visfatin; Adiponectin; Leptin; TNF-α; HOMA2-IR; T2DM.
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Abbreviations
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OD: Obese diabetics group; NOD: None obese diabetics group; FBG: fasting blood glucose;
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HbA1c %: glycated hemoglobin percent; TNF-α: tumor necrosis alpha; HOMA2-IR:
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homeostasis model assessment for insulin resistance; TC: total cholesterol; LDL-C: low
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density lipoprotein; HDL-C: high density lipoprotein; TGs: Triglyceride; T2DM: type 2
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diabetes mellitus; ELISA: enzyme-linked immunosorbent assay.
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Introduction
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Research of the past decade has increased our understanding about the role of adipose tissue
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plays in health and disease. Adipose tissue is now recognized as a highly active metabolic
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and endocrine organ. Adipocytes are of importance in buffering the daily influx of dietary fat
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and exert autocrine, paracrine and/or endocrine effects by secreting a variety of
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adipocytokines [1].
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Obesity can affect beta cells through the influence of elevated levels of free fatty acids (FFA),
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and/or through the adipocytokines that are secreted by adipose tissues. The direct effect of
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free fatty acids, termed lipotoxicity, is leading to apoptosis and reduced insulin secretion. The
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effect of obesity is thought to be mediated by adipokines such as TNF-α, leptin, adiponectin,
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omentin, visfatin, adipsin, resistin, apelin and retinol binding protein (rbp4) [2].
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The normal function of adipose tissue is disturbed in obesity, and there is accumulating
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evidence to suggest that adipose tissue dysfunction plays a prominent role in the development
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and/or progression of insulin resistance [1]. Type 2 diabetes (T2DM) is thought to be a
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culmination of two seemingly distinct processes, insulin resistance and beta cell failure, both
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of which have been closely linked to obesity [2]. Previous studies revealed that weight gain
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results in lipid accumulation and adipocyte stress-factors known to disrupt the balance of
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systemic cell signaling (adipokines and cytokines) [3,4]. This bioactive substance may
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directly contribute to the pathogenesis of conditions associated with obesity [5], and
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inflammation [4].
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So, the proposal of this research is to investigate the effect of obesity in diabetic patients on
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the promotion of the secretion of pro- inflammatory adipocytokines (TNF-α, visfatin, leptin,
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and adiponectin) and insulin resistance.
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Patients and methods
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Patients
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The study was carried on 40 obese and non-obese diabetic patients recruited from Outpatient
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Clinics of Internal Medicine Department, Tanta University Hospitals, Tanta, Egypt. All
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participants were asked to sign on an informed consent prior to inclusion in the study. The
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diabetic patients were divided according to their body mass index (BMI) into two groups
Werida et al. 2013
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(n=40 each): Obese diabetic group (OD) (BMI >25 kg/m2). Non obese diabetic group (NOD)
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(BMI ≤ 25 kg/m2). The protocol was approved by the Tanta University Ethical Committee.
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Anthropometric evaluations
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Body weights were measured without shoes and in light clothing and recorded to the nearest
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0.5 kg. Body heights were measured without shoes and/or caps and recorded to the nearest
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centimeter. BMI was expressed as weight (kg) per height (m) squared [6].
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Biochemical assays
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All blood samples were obtained after a 10-12 hours fasting period. Blood samples were
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centrifuged and separated immediately, then collected in tubes and stored at -20 oc until
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assayed.
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glucometer (Roche Diagnostics, Indianapolis, IN) [7]. Glycated hemoglobin (HbA1c %) was
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determined by ion exchange method (Stanbio Laboratory Company, USA) [8]. Triglycerides
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(TGs) [9], Total cholesterol (TC) and High density lipoprotein (HDL-C) [10] were
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measured colorimetery using kits obtained from Elitech Diagnostics Company, France.
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Low density lipoprotein (LDL-C) was calculated [11].
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Serum visfatin [12], TNF-alpha [13] and
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ELISA (Enzyme-Linked Immunosorbent Assay) kits from RayBiotech Company, USA.
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Serum C-peptide quantified using Immunoenzymometric assay kit (Monobind Inc. Company,
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USA) [15]. Leptin serum level was determined using ELISA Kit from (Diagnostics Biochem
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Company, Canada) [16]. Homeostasis model assessment for insulin resistance (HOMA2-IR)
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was calculated using HOMA Calculator version 2.2, where, C-peptide values are used [17].
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Statistical analysis
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All values are expressed as mean ± SD and the differences between the two groups were
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calculated by Student’s t test. The correlation was done between different parameters using
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Pearson correlation. All P values were two-tailed and P < 0.05 was considered significant.
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All analyses were carried out using SPSS version 17.
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Results
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Data and the difference between OD group and NOD group regarding BMI showed a highly
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significant difference (p < 0.001) between the two studied groups noting that OD group
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recorded the higher values Table (1). The levels of pro-inflammatory adipocytokines (TNF-α,
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visfatin) were increased significantly in OD group than that in NOD group (p < 0.0001). The
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anti-inflammatory adiponectin has also, shown a very high significant decrease in OD group
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as compared to NOD group (p < 0.0001), the pro-inflammatory adipocytokine serum leptin
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levels showed insignificant difference in OD group in comparison to NOD group (p > 0.05).
Fasting glucose determined using glucose oxidase method by an Accu-Chek
adiponectin levels [14] were determined using
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Table (1) Comparison between OD and NOD group regarding the studied parameters.
Group (F/M)
NOD (20/20)
OD (21/19)
F
P
46.65
+6.02
49.65
+6.07
4.93
0.03
33.02
+1.78
184.10
+15.42
8.06
+0.48
1.94
+0.31
544.14
0.000
34.81
0.000
56.33
0.000
80.963
0.000
Parameters
Age (years)
107
109
FBG (mg/dl)
110
HbA1c %
111
C-peptide
(ng/ml)
24.11
+1.20
162.70
+16.98
7.25
+0.48
1.26
+0.36
112
Adiponectin
(pg/ml)
1.10
+0.24
0.56
+0.10
147.052
0.000
Visfatin (ng/ml)
62.38
+9.88
91.39
+14.32
111.248
0.000
Leptin (ng/ml)
12.46
+3.07
12.07
+2.79
0.367
0.547
TNF-α (pg/ml)
1.24
+0.25
1.92
+0.37
92.013
0.000
118
HOMA2-IR
1.11
+0.33
1.79
+0.29
90.687
0.000
119
TC
(mg\dl)
153.78
+14.72
195.25
+17.00
136.09
0.000
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LDL-C
(mg/dl)
89.45
+14.49
127.85
+16.54
122.02
0.000
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HDL-C
(mg/dl)
33.71
+1.31
32.78
+1.24
10.65
0.002
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TGs
(mg/dl)
151.30
+11.59
173.04
+15.12
52.13
0.000
108
113
114
115
116
117
120
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BMI (kg/m2)
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Data are presented as Mean+SD; F: female; M: male; OD: Obese diabetics group; NOD: None obese
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diabetics group; FBG: Fasting blood glucose; HbA1c %: Glycated hemoglobin percent; TNF-α: tumor
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necrosis alpha; HOMA2-IR: homeostasis model assessment for insulin resistance; TC: total
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cholesterol; LDL-C: low density lipoprotein; HDL-C: high density lipoprotein; TGs: Triglyceride.
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p < 0.0001 = very highly significant difference.
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Table (2) illustrated a significant positive correlation between BMI with FBG, HbA1c % and
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C-peptide (r = 0.59, r = 0.68 and r = 0.67, p = 0.01) respectively. BMI showed a positive
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correlation with TC, LDL-C and TGs (r = 0.74, r = 0.73 and r = 0.58, p = 0.01) respectively,
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on the other hand a negative correlation was found between BMI and HDL-C (r=-0.33,
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P=0.01) Figure (1). The obtained results revealed a significant positive correlation between
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BMI with the pro-inflammatory cytokines TNF-α and visfatin (r = 0.73, p = 0.01 and
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r = 0.69, p = 0.01) respectively Figure (2).
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Figure (1) Association between BMI and fasting blood glucose, glycated hemoglobin, serum c-
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peptide and Lipid profile. Plot 1: A positive correlation between BMI and FBG, HbA1C % and C-
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peptide. Plot 2: A positive correlation between BMI and TCH, LDL-C and TGs. Negative correlation
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between BMI and HDL-C.
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Table (2) Correlation between measured BMI, Adipocytokines, HOMA2-IR and lipid profile
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parameters.
FBG HbA1c% C-peptide Adiponectin Visfatin Leptin TNF-α
BMI 0.59
FBG
**
0.68
**
0.83
**
HbA1c %
0.67
**
0.52
**
0.61**
C-peptide
-0.74
**
-0.39
**
0.69
**
0.42
**
-0.08 0.73
**
0.03 0.42
**
TC
0.74
**
0.45
**
LDL-C HDL-C TGs HOMA2-IR
0.73** -0.33** 0.58**
0.44
**
-0.09 0.34
0.70**
**
0.60**
-0.51**
0.44**
0.09 0.48** 0.51** 0.49** -0.19 0.46**
0.66**
-0.60**
0.52**
0.09 0.50** 0.59** 0.58** -0.27* 0.45**
0.99**
-0.62** -0.01 -0.62** -0.66** -0.64** 0.31** -0.57**
-0.61**
-0.09 0.53** 0.67** 0.65** -0.19 0.50**
0.53**
Adiponectin
Visfatin
-0.09 -0.02 -0.03
Leptin
0.53
TNF-α
TC
LDL-C
HDL-C
TGs
**
-0.08
-0.02
*
**
0.51**
0.99** -0.22* 0.60**
0.60**
-0.27* 0.51**
0.59**
-0.16
-0.27*
0.51
**
-0.23
0.48
0.06
0.47**
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** Pearson Correlation is significant at the 0.01 level (2-tailed).
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* Pearson Correlation is significant at the 0.05 level (2-tailed).
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BMI: body mass index; FBG: fasting blood glucose; HbA1c %: Glycated hemoglobin percent, LDL-
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C: low density lipoprotein, HDL-C: high density lipoprotein, TNF-α: tumor necrosis alpha, TC: total
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cholesterol, TGs: triglyceride, HOMA2-IR: homeostasis model assessment for insulin resistance.
Werida et al. 2013
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Figure (2) Association between BMI and Measured adipocytokines. Plot 3: Negative correlation
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between BMI and Adiponectin. Plot 4: A positive correlation between BMI and Visfatin. Plot 5:A
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positive correlation between BMI and TNF-alpha. Plot 6: Insignificance correlation between BMI
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and Leptin.
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155
156
157
158
159
160
161
162
163
164
165
166
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Figure (3) Association between BMI and calculated HOMA2-IR.
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BMI: body mass index; HOMA2-IR: homeostasis model assessment of insulin resistance.
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A significant negative correlation was found between BMI with the anti-inflammatory
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adiponectin (r = -0.74, p = 0.01) Figure (2). In addition an insignificant correlation was found
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between BMI and leptin (r = -0.08, p > 0.05) Figure (2). BMI showed a significant positive
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correlation with insulin resistance index HOMA2-IR (r=0.70, P=0.01) Figure (3).
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Discussion
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Obesity results in a pro-inflammatory state starting within the metabolic cells (adipocyte,
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hepatocyte, or monocyte) [18, 19]. The response becomes more intense and the resolution is
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less efficient. These signals accumulate over time and may reach a level where the
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professional immune cells are recruited and activated leading to an unresolved inflammatory
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response within the tissue [20, 21], where the pro-inflammatory cytokines are overexpressed
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[22]. The present results revealed a reduction in adiponectin levels in obese subjects than that
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in non obese subjects, which accords with a study done by Matsuzawa et al. [23] that
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revealed a substantial proportion of adipocytokines are involved in the inflammatory
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stimulation and response, as either pro-inflammatory or anti-inflammatory adipocytokines.
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Trujillo and Scherrer [24] stated that adiponectin levels were inversely correlated with
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visceral adiposity, in addition Halleux et al. [25], revealed that a co-culture with visceral fat
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inhibits adiponectin secretion from subcutaneous adipocytes, which suggests that some
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inhibiting factors for adiponectin synthesis or secretion are released from visceral adipose
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tissue. Maeda and his colleagues [26] found that TNF-α is a strong inhibitor of adiponectin
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promoter activity, which was supported by the present findings about the negative correlation
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between TNF-α and adiponectin. This is in consistence with Ouchi et al. [27] and was
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attributed to the role of adiponectin in reducing the degree of macrophages transformation to
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foam cell and decreasing the expression of TNF-α in macrophages and adipose tissue, which
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may lead to reduced lipotoxicity and counteract inflammation [28]. It has been shown by Ho
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et al. [29] that adipose plasma TNF-α protein are increased in obesity, both in animals and
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humans. Leptin the inflammatory adipocytokine [30], is secreted primarily by fat cells and
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acts centrally particularly in the hypothalamus to reduce food intake and body weight [31].
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An excess of leptin in the circulation was found in obesity and overweight [32]. Our results
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showed that serum leptin insignificantly correlated to BMI. The results on the relationship
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between body fat and serum leptin concentration per unit of fat mass published in the
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literature are conflicting, this can be attributed to variations in the physiological
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characteristics of the research subjects of each study, such as adiposity, age, and gender, may
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partly account for the discrepancy. Kamińska et al. [33] found significantly higher visfatin
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levels in the obese subjects compared to the lean subjects. On the other hand, Pagano et al.
Werida et al. 2013
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[34] found that obese subjects had a significantly lower visfatin levels compared to
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subjects with normal body weight. Consistence with our results García-Fuentes et al. [35]
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found that patients with morbid obesity are characterized by significantly higher visfatin
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levels compared to lean individuals but only when obesity is associated with glucose
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metabolism abnormalities.
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The present study showed that obesity in T2DM patients is associated with atherogenic lipid
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profile, which is characterized by overproduction of LDL-C, TGs, total cholesterol as well as
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low production of HDL-C, in agreement with Jeusette et al. [36] who proposed that insulin
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resistance in obese subjects may be responsible for high serum levels of TGs and total
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cholesterol concentrations as a result of enhanced overproduction of TGs and cholesterol rich
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lipoprotein by liver. This atherogenic lipid profile is the most deleterious metabolic
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derangement of obesity. The obtained results showed, in agreement with Gokalp et al [6], a
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significant decrease in HOMA2-IR index, the indicator of insulin resistance, in NOD group
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compared to OD group.
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Conclusions
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This study revealed the positive correlation between obesity and the inflammatory status as
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represented by increased levels of inflammatory adipocytokines in type 2 diabetic patients.
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The higher levels of visfatin, TNF-α and atherogenic lipids and the lower level of adiponectin
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in obese diabetics, suggested that different adipocytokines may play different roles of insulin
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resistance which may increase susceptibility of obese T2DM subjects to more complications.
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Conflict of interest The authors declared that there are no conflicts of interest.
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