Relationship between plasma adipokines, inflammation, insulin resistance and subclinical atherosclerosis in newly diagnosed type 2 diabetes
Razvan Vasilescu, Silvi Ifrim, Constantin Ionescu-Tirgoviste
DOI: 10.4236/jdm.2011.12004   PDF    HTML     4,061 Downloads   9,017 Views   Citations

Abstract

Background: The aim of this study was to investigate the occurrence of subclinical atherosclerosis, evaluated by carotid artery intima-media thickness (CIMT) in subjects with newly diagnosed type 2 diabetes. Methods: A total of 167 subjects, 50 newly diagnosed type 2 diabetic subjects and 117 non-diabetic subjects were included in the study. Obese and overweight newly diagnosed type 2 diabetic patients were matched for age and BMI with obese and overweight non-diabetic subjects. Only postmenopausal women were selected. The following biomarkers were analyzed: fasting glucose, HbA1c, fasting insulin, fasting proinsulin, total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides, adiponectin, leptin, hs-CRP, urine albumin/creatinine ratio. 75 g oral glucose tolerance test was performed in all subjects. Ultrasound imaging was used to evaluate IMT of the common carotid artery. Results: CIMT was greater in newly diagnosed type 2 patients compared to non-diabetic subjects. When analyzed by BMI, the difference regarding CIMT between diabetic and non-diabetic subjects was significant only in overweight subjects, in both sexes. In univariate analysis in men with newly diagnosed type 2 diabetes, CIMT was positively correlated with age, SBP, triglycerides, leptin and negatively correlated with HDL-cholesterol and in women CIMT was positively correlated with SBP and leptin. Independent determinants of CIMT in patients with newly diagnosed type 2 diabetes were in men age (β = 0.556, p = 0.0028) and log leptin (β = 0.393, p = 0.049) and in women systolic blood pressure (β = 0.48, p = 0.026). Conclusions: Subclinical atherosclerosis is present in newly diagnosed type 2 diabetic subjects. Body fat accumulation in men and hypertension in postmenopausal women have a primary role in increase carotid intima-media thickness.

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Vasilescu, R. , Ifrim, S. and Ionescu-Tirgoviste, C. (2011) Relationship between plasma adipokines, inflammation, insulin resistance and subclinical atherosclerosis in newly diagnosed type 2 diabetes. Journal of Diabetes Mellitus, 1, 17-25. doi: 10.4236/jdm.2011.12004.

1. INTRODUCTION

Diabetes is one of the main risk factors for cardiovascular disease [1]. An increase in the carotid intima-media thickness (CIMT), examined by B-mode ultrasonography, is generally considered an early marker of atherosclerosis [2-6]. Previous studies have shown an association of increased CIMT with cardiovascular risk factors [7,8] and future cerebrovascular and cardiovascular events [9,10]. It has also been demonstrated that CIMT is increased in type 2 diabetic patients [11-14]. In subjects with established diabetes, traditional risk factors such as hypertension, dyslipidemia (high LDL-cholesterol, triglycerides and apoB levels and low HDL-cholesterol levels), obesity as well as lower plasma adiponectin, inflammation markers and insulin resistance are associated with CIMT [15-21]. We noticed large differences between the studies which evaluated the correlation of cardiovascular risk factors with measures of subclinical atherosclerosis, both in diabetic and non-diabetic subjects, mainly because of the wide variations of the populations included. Few studies showed that early atherosclerosis, evaluated by CIMT or arterial stiffness, is present in newly diagnosed type 2 diabetic subjects [22-25]. In the present study we evaluated CIMT in newly diagnosed type 2 diabetic patients, in comparison with nondiabetic subjects, matched for age and sex. In addition we analyzed the influence of traditional cardiovascular risk factors, adipokines (adiponectin and leptin), inflammation markers (fibrinogen and hs-CRP), insulin resistance and albuminuria on CIMT in patients with newly diagnosed type 2 diabetes without cardiovascular disease.

2. METHODS

2.1. Subjects

A total of 167 subjects were included in this study: 50 newly diagnosed type 2 diabetes (25 men and 25 women) and 117 control, non-diabetc (64 men and 53 women). Subjects were recruited at the Department of Diabetes, Nutrition and Metabolic Diseases, Clinical Hospital Colentina, from February 2009 to January 2010. All participants gave written informed consent. Subjects with established diabetes, currently smoking, history of cardiovascular disease, use of drugs for dyslipidemia and hypertension, fasting glucose ≥ 250mg/dl, systolic blood pressure ≥ 170 mmHg, total cholesterol ≥ 300 mg/dl, triglycerides ≥ 300 mg/dl, presence of viral hepatitis, renal disease or thyroid dysfunction were excluded. Women included in the study were post menopause. Subjects were classified by BMI into: lean (18.5 < BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30kg/m2) and obese (BMI ≥ 30 kg/m2). According to BMI newly diagnosed type 2 diabetic subjects were classified into two groups: overweight, 20 subjects (10 men and 10 women) and obese, 30 subjects (15 men and 15 women) and non-diabetic subjects into three groups: lean, 18 subjects (9 men and 9 women), overweight, 43 subjects (24 men and 19 women) and obese, 56 subjects (31 men and 25 women).

2.2. Carotid Artery Ultrasound

CIMT was determined using a B-mode ultrasound scanner (Siemens Sonoline Sienna) and a 7.5 MHz linear probe with subjects in the supine position, by a trained specialist with no knowledge of the subjects clinical characteristics. Longitudinal scan of both the right and left common carotid artery was recorded. Measurement of IMT was made on the near (anterior) and far (posterior) wall of the common carotid artery at 1 cm proximal to the bifurcation, in segments that were free of plaque, plaque being defined as the presence of wall thickening at least 50% greater than the adjacent thickness. For each individual, the CIMT was determined as the average of near and far-wall measurements of both the left and right arteries.

2.3. Laboratory Assay

The samples of blood were taken after 12 hours of overnight fasting. Total adiponectin, leptin, hs-CRP, insulin and proinsulin were measured by ELISA (DRG International, Inc.) on a Dynex analyzer. Low-density lipoprotein (LDL) cholesterol was calculated using the Friedewald formula. Total cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and glucose were measured using standard techniques. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as the product of the fasting plasma insulin value (in microunits per liter) and the fasting plasma glucose value (in mg per deciliter) divided by 405. Urine albumin/cretinine ratio (UACR) was calculated from a single spot urine specimen collected in the morning. Microalbuminuria was defined as UACR 30 - 300 mg/g. Percent body fat (%) was measured using a bioelectrical impedance analyzer (Omron BF 500). All participants underwent standard oral glucose tolerance test (OGTT) with 75 g glucose. To diagnose type 2 diabetes we used the following criteria: fasting plasma glucose (FPG) ≥ 126 mg/dl and/or a 2-h plasma glucose in OGTT ≥ 200 mg/dl.

2.4. Statistical Analysis

Statistical analyse was performing using GraphPad Instat version 3.0 and NCSS/2004. Continuous variables were tested for normality of distribution with the use of the Wilk-Shapiro test. Data normally distributed were expressed as mean ± standard deviation (SD) and data skewed distributed were expressed as median (interquartile range). Normally distributed variables were compared by unpaired t-test and not normally distributed variables were compared by Mann-Whitney test. Variables not normally distributed (insulin, proinsulin, proinsulin to insulin ratio, HOMA-IR, adiponectin, leptin, leptin to adiponectin ratio, hs-CRP, UACR) were log transformed before evaluating the correlations. Associations between CIMT and the variables evaluated, in subjects with newly diagnosed type 2 diabetes, were examined using linear regression analysis. P-value < 0.05 was considered statistically significant for all analyses.

3. RESULTS

3.1. Characteristics of Study Subjects

The clinical and biochemical characteristics of the subjects included in this study are presented in Table 1. Obese and overweight newly diagnosed type 2 diabetic patients were matched for age, sex and BMI with obese and overweight non-diabetic subjects. Systolic blood pressure (SBP), triglycerides, fibrinogen, hs-CRP, insu

Table 1. Clinical and biochemical characteristics of diabetic patients and control subjects.

lin, proinsulin, leptin and UACR were significantly higher and adiponectin and HDL-cholesterol were significantly lower in obese subjects, both newly diagnosed diabetic and non diabetic, compared to non diabetic, lean subjects. There were no significant differences between obese non diabetic and obese newly diagnosed type 2 diabetic subjects for waist, systolic blood pressure, diastolic blood pressure, total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, fibrinogen, hs-CRP, adiponectin, leptin, leptin/adiponectin ratio, proinsulin/ insulin ratio and UACR. Similarly, there were no significant differences between overweight non-diabetic and overweight newly diagnosed type 2 diabetic subjects for waist, systolic blood pressure, diastolic blood pressure, total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, fibrinogen, hs-CRP, adiponectin, leptin, leptin/adiponectin ratio, proinsulin/insulin ratio and UACR. Fasting glucose and HBA1c were higher in newly diagnosed type 2 diabetic, both in obese and overweight, compared to non-diabetic subjects. Fasting insulin, proinsulin and HOMA-R were significantly higher in obese type 2 newly diagnosed diabetic vs.

obese non-diabetic. In non-diabetic subjects BMI, waist and triglycerides were higher in obese vs. overweight. In newly diagnosed type 2 diabetic patients BMI, waist, insulin, HOMA-R and proinsulin were higher in obese vs. overweight. None of the subjects had macroalbuminuria, 7 subjects (5 subjects from the non-diabetic group and 2 subjects from the diabetic group) had microalbuminuria and the rest of the participants had low grade albuminuria.

CIMT was greater in obese and overweight, both in newly diagnosed type 2 diabetic (obese vs. lean, pmen < 0.0001, pwomen < 0.0001; overweight vs. lean, pmen < 0.0001, pwomen < 0.0001) and non-diabetic subjects (obese vs. lean, pmen < 0.0001, pwomen < 0.0001; overweight vs. lean, pmen = 0.0041, pwomen < 0.0001), compared to non-diabetic lean subjects. CIMT was greater in obese subjects, both in newly diagnosed type 2 diabetic and non diabetic subjects, compared to overweight subjects, but the difference was statistically significant only for non-diabetic subjects (non-diabetic, obese vs. overweight, pmen = 0.0005, pwomen = 0.003). There was no significant difference between CIMT in obese, newly diagnosed diabetic patients and CIMT in obese, nondiabetic subjects. CIMT was greater in overweight newly diagnosed diabetic patients compared to overweight, non-diabetic subjects (pmen = 0.008, pwomen = 0.027) (Table 2).

3.2. Univariate Analysis between CIMT and Various Variables in Newly Diagnosed Type 2 Diabetic Subjects

In univariate analysis in men with type 2 diabetes newly diagnosed CIMT was positively correlated with age (CIMT = 0.0122 × age + 0.3033, r2 = 0.35, p = 0.002), systolic blood pressure (CIMT = 0.0044 × SBP + 0.3233, r2 = 0.14, p = 0.046), triglycerides (CIMT = 0.0011 × triglycerides + 0.7018, r2 = 0.2, p = 0.026), leptin (CIMT = 0.2038 × log (leptin) + 0.6764, r2 = 0.19, p = 0.025) and negatively correlated with HDL-cholesterol (CIMT = –0.0082 × HDL-cholesterol + 1.2381, r2 = 0.15, p = 0.044) (Table 3). In univariate analysis in women with type 2 diabetes newly diagnosed CIMT was positively correlated with systolic blood pressure (CIMT = 0.005 × SBP + 0.211, r2 = 0.2, p = 0.021) and leptin (CIMT = 0.1666 × log (leptin) + 0.6053, p = 0.037) (Table 3).

3.3. Multiple Regression Analysis in Subjects with Newly Diagnosed Type 2 Diabetic Subjects

In men, in a model with CIMT as a dependent variable and age, systolic blood pressure, triglycerides, log leptin and HDL-cholesterol as covariates, age (β = 0.556, p = 0.0028) and log leptin (β = 0.393, p = 0.0488) were independent determinant of CIMT (Tabel 4). In a model with age (β = 0.619, p = 0.0002) and log leptin (β = 0.482, p = 0.0021) the coefficient of determination (R2) was 0.578 and the adjusted value was 0.539.

In women, in a model with CIMT as a dependent variable and age, systolic blood pressure, leptin, triglycerides and HDL-cholesterol as covariates, systolic blood pressure (β = 0.48, p = 0.026) was the only independent predictor of CIMT (Table 5).

4. DISCUSSION

In this study we show that patients with newly diagnosed type 2 diabetes have an increase CIMT compared to non-diabetic, lean subjects matched for age. In obese subjects we found no difference in CIMT between newly diagnosed type 2 diabetes and non-diabetic, in both sexes and in overweight subjects CIMT was significantly greater in newly diagnosed type 2 diabetes compared to non-diabetic, in both sexes.

Temelkova et al. [22] showed in 71 newly diagnosed type 2 diabetes, aged 40 - 70 years, 67.61% male with mean HbA1c of 6.33 ± 0.11% and mean BMI of 28.8 ± 0.4 kg/m2 that newly detected type 2 diabetic patients, compared to normal glucose tolerance subjects matched for age and sex, with mean BMI of 27.4 ± 0.4 kg/m2, exhibit a higher degree of early atherosclerosis, evaluated by measurement of the common carotid artery IMT (men, diabetic vs control, 1 ± 0.03 vs.0.88 ± 0.03 mm;

Table 2. Carotid intima-media thickness (CIMT) in newly diagnosed type 2 diabetic patients and non-diabetic subjects.

Table 3. Correlation between CIMT and all the other parameters evaluated.

Tabel 4. Multiple regression analysis with CIMT as the dependent variable in men with newly diagnosed type 2 diabetes.

Tabel 5. Multiple regression analysis with CIMT as the dependent variable in women with newly diagnosed type 2 diabetes.

female, diabetic vs. control, 0.94 ± 0.04 vs. 0.79 ± 0.02 mm). Also, the authors showed that in diabetic patients triglycerides and the total-to-HDL cholesterol ratio were significantly correlated to IMT after adjustment for age and sex, but in multivariate analysis no independent determinants of carotid IMT were found. Sigurdardottir et al. [23] showed in 271 men, 61 year old (50 with established diabetes, mean HbA1c of 6.66 ± 1.53% and mean BMI of 29.6 ± 4.7 kg/m2; 24 newly diagnosed diabetes with mean HbA1c of 5.94 ± 1.54% and mean BMI of 29.8 ± 2.9 kg/m2 and 197 healthy control subjects with mean BMI of 25.5 ± 4.3 kg/m2) increased preclinical atherosclerotic changes (evaluated by carotid IMT and plaque size) and increased inflammation (hsCRP) both in men with newly diagnosed and established diabetes compared with healthy control subjects. In this study waist-to-hip ratio, diabetes onset status (newly diagnosed versus established) and triglycerides were independent correlates of carotid IMT in men with diabetes.

We found that in patients with newly diagnosed type 2 diabetes, without cardiovascular diseases and treatment for hypertension or dyslipidemia, there are sex differences in the risk of subclinical atherosclerosis. In men, in univariate analysis age, SBP, triglycerides and leptin correlated positively with CIMT and HDL-cholesterol correlated negatively with CIMT and in multivariate analysis, age and leptin were independent predictors of CIMT and in women, in univariate analysis SBP and leptin correlated positively with CIMT and in multivariate analysis, SBP was an independent predictor of CIMT. Leptin, a hormone produce by white adipose tissue, is primarily involved in the regulation of food intake and energy expenditure. Plasma leptin concentration is increased in obese subjects and reflects increased adiposity and leptin resistance [26-28]. In vitro and in vivo assays demonstrated that leptin has multiple atherogenic effects such as induction of endothelial dysfunction [29,30], stimulation of migration and proliferation of vascular smooth cells [31], production of reactive oxygen species (ROS) [32] stimulation of inflammatory reaction [33], platelet aggregation [34], sympathetic activation [35]. Inhibition of leptin signaling may be a promising strategy to slow the progression of atherosclerosis in hyperleptinemic obese subjects. According to the concept of selective leptin resistance, there is resistance to the effects of leptin on appetite and thermogenic metabolism, whereas its other actions are maintained [36]. There are studies which have shown that serum leptin is lower in subjects with established diabetes mellitus [37,38].

In recent years many studies evaluated the cardiovascular effects of leptin [39-41]. Wallace et al. [42] showed in a large prospective study (the West of Scotland Coronary Prevention Study – WOSCOPS) that leptin is an independent risk factor for coronary heart disease. Reilly et al. [43] found an association between plasma leptin levels and coronary artery calcification (CAC), a measure of coronary atherosclerosis, in type 2 diabetes mellitus patients (age, median – 61.3 year in men and 56.9 year in women, duration of diabetes, mean – 7 year in men and 7.5 year in women and BMI, mean – 31.5 kg/m2 in men and 31.2 kg/m2 in women), after controlling for traditional measures of obesity and plasma CRP. Qasim et al. [44] found in 860 (457 men and 403 women) healthy, nondiabetic, with family histories of premature cardiovascular disease, participants in the SIRCA (Study of Inherited Risk of Coronary Atherosclerosis) a strong association between leptin and CAC. Ciccone et al. [45] showed in 120 healthy subjects (52 men and 68 women), aged 28.1 ± 7 years in men and 28.8 ± 7.8 years in women and with a wide range of BMI (31.2 ± 9.4 kg/m2 in men and 29.4 ± 8.1 kg/m2 in women), that plasma leptin concentrations are independently associated with CIMT. Van den Beld et al. [46] found no association between plasma leptin levels and CIMT in 403 elderly men (aged 73 - 94 years). Bountoris et al. [47] found that plasma leptin levels were decreased in symptomatic patients undergoing carotid endarterectomy. Stork et al. [48] show in 142 non-diabetic postmenopausal women, aged 59.1 ± 4.3 years and with mean BMI 26.4 ± 4.6kg/m2, that low levels of adiponectin are associated with CIMT progression and increased risk of arterial stiffness progression. The authors found no association for leptin.

In the present study we show that SBP, triglycerides, fibrinogen, hs-CRP, insulin, proinsulin, leptin and UACR were significantly higher and adiponectin and HDL-cholesterol were significantly lower in obese subjects, both newly diagnosed diabetic and non-diabetic, compared to non-diabetic, lean subjects. We found no difference in the plasma concentration of total cholesterol, LDL-cholesterol, HDL-cholesterol, fibrinogen, hsCRP, leptin and adiponectin, systolic blood pressure and diastolic blood pressure between the diabetic and nondiabetic subjects, irrespective of BMI (obese or overweight). Plasma triglycerides were higher in both obese and overweight newly diagnosed type 2 diabetes, compared to obese and overweight non-diabetic subjects. Insulin, HOMA-R and proinsulin were higher in obese type 2 diabetic subjects compared to obese non-diabetic subjects. Insulin, proinsulin and HOMA-R were higher in obese type 2 diabetic subjects compared to overweight type 2 diabetic subjects. These data sustained our view[49] that the main pathogenic link of type 2 diabetes with vascular disease is close related with obesity. Hansen and colab.[50] showed in a total of 60 males (20 healthy, non-obese subjects, 20 non-obese and 20 obese (BMI >35 kg/m2) type 2 diabetes patients that elevated plasma leptin, hsCRP, IL-6 and free fatty acid (FFA) are associated with obesity and not necessarily with the type 2 diabetic state.

5. CONCLUSION

Subclinical atherosclerosis is present in patients with newly diagnosed type 2 diabetes. Body fat accumulation in men and hypertension in women have primary roles in development of subclinical atherosclerosis in newly diagnosed type 2 diabetic patients.

Conflicts of Interest

The authors declare no conflicts of interest.

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