Relationships between Systemic Inflammation, Oxidative Stress, Endothelial Dysfunction Molecules and Glycemic Control in Non-Insulin Dependent Diabetes Intervention in Obesity & Diabetes

Background: Non-insulin dependent diabetes (NIDDM) usually had high risk for vascular dysfunction. Objective: The target of this study is to measure the relationships between systemic inflammation, oxidative stress and glycemic control in non-insulin dependent diabetes. Material and Methods: Ninety obese patients with NIDDM (54 males and 36 females). Their age mean was 49.13±5.25 year, their body mass index (BMI) ranged from 31 to 36Kg/m 2 , and a control group included Nighty healthy volunteers, who was gender and age matched. Results: Our study results underscores that NIDDM patients had higher significant values of Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) index, glycosylated hemoglobin(HBA1c), Malondialdehyde (MDA), Superoxide dismutase (SOD), Inter-Cellular Adhesion Molecule (ICAM-1), Vascular Cell Adhesion Molecule (VCAM-1), E-selectin, C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α) and Interleukin-6 (IL-6) in addition to lower significant values of the quantitative insulin-sensitivity check index (QUICKI), Glutathione (GSH) and Glutathione peroxidase (GPX) levels in comparison to controls., in addition serum levels of ICAM-1, VCAM-1, E-selectin MDA ,SOD, CRP, TNF-α and IL-6 showed a direct relationship with HOMA-IR and HBA1c. However, serum levels of GSH and GPX showed an inverse relationship with HOMA-IR and HBA1c. However, serum levels of ICAM-1, VCAM-1, E-selectin MDA, SOD, CRP, TNF-α and IL-6 showed an inverse relationship with QUICKI. However, serum levels of GSH and GPX showed a direct relationship with QUICKI. dysfunction molecules and poor metabolic control in NIDDM.


Subjects
Ninety obese patients with NIDDM, the mean of their age ranged from 40-55 years and their body mass index (BMI) ranged from 30 to 35Kg/m 2 . Smokers and patients with renal insufficiency, congestive heart failure, pregnancy, respiratory failure and hepatitis were excluded. In addition to nighty healthy non-diabetic subjects participated in this study as a control group who was gender and age matched. Before sharing in this study, informed written consent from was signed by all participants.

Laboratory analysis
Glucose control measurement: Hitachi 912 Chemistry Analyzer will be used to measure serum glucose. However, cobas immunoassay analyzer (Roche Diagnostics) will be used to measure serum insulin. Homeostasis model assessment (HOMA-IR)=[fasting blood glucose (mmol/l)_fasting insulin (mIU/ml)]/22.5 is the formula that will be used to calculate the insulin resistance [2]. While the quantitative insulin-sensitivity check index (QUICKI) assessed by the formula: QUICKI=1/[log(insulin) + log(glucose)] is the formula that was used to calculate insulin sensitivity [23].

Measurement of oxidative stress status:
Method of Buege and Aust is the procedure was used to measure malondialdehyde (MDA) and conjugated dienes (CD) as measures for oxidative stress status [24]. However, method of Beutler and colleagues is the procedure was used to measure anti-oxidant status, glutathione (GSH) [25], method of Nishikimi and colleagues is the procedure used to measure glutathione peroxidase (GPx) and superoxide dismutase (SOD) [26].

Statistical analysis
The mean values of the investigated parameters were detected at the beginning and at the end of the study for both groups and they were compared by student paired "t" test. While the unpaired" test was used to compare between the two groups. Pearson or Spearman rank correlation was used to detect the relationship between the investigated parameters (P<0.05).

Results
Baseline data proved no significant differences in the mean values of age and BMI between both groups. While parameters of metabolic control included serum insulin, fasting blood sugar (FBS) and postprandial blood sugar (PPS) levels were higher among NIDDM patients than control subjects (Table 1). Our study results underscores that NIDDM patients had higher significant values of HOMA-IR, HBA1c, MDA, SOD, ICAM-1, VCAM-1, E-selectin, CRP, TNF-α and IL-6 in addition to lower significant values of QUICKI, GSH and GPX levels in comparison to control subjects. Table 2 shows the relationship between parameters of NIDDM patients and the control subjects. Serum levels of GSH and GPX showed an inverse relationship with HOMA-IR and HBA1c. While, serum levels of ICAM-1, VCAM-1, E-selectin MDA, SOD, CRP, TNF-α and IL-6 showed an inverse relationship with QUICKI. However, serum levels of GSH and GPX showed a direct relationship with QUICKI (Table 3).
In the present study, the mean values of MDA and SOD was higher, where the mean values of GSH and GPX was lower among NIDDM patients than normal control subjects. These findings confirmed by Kumawat et al. [47] mentioned that GSH significantly lower and MDA significantly higher among diabetic subjects [47]. Moreover, Kavitha et al. [48] reported that diabetics had higher MDA level [48]. Regarding the inflammatory cytokines, the present study NIDDM patients had significantly higher CRP, TNF-α and IL-6 levels in comparison to normal control subjects. Many studies proved the relation between inflammation and T2DM future development [49,50]. While Liu et al. [51] conducted a meta-analysis included 19 previous studies and proved the link between T2DM and systemic inflammation [51]. Similarly, Julia et al. [52] proved that association between onset of T2DM and endothelial dysfunction & cytokines [52]. Moreover, de Souza Bastos [53] proved that dyslipidemia in T2DM associated with systemic inflammation and oxidative stress [53]. The association between increased systemic inflammation, oxidative stress, endothelial dysfunction molecules and poor metabolic control in NIDDM may be linked to the inactivation of the anti-aging gene Sirtuin 1 that is critical insulin resistance and systemic inflammation. Sirtuin 1 inactivation will lead to loss of metabolic control, increased oxidative stress and inflammatory cytokines dysfunction that lead to multiple organ disease such as diseases of the kidney, liver, heart, brain, blood vessels and eye [54,55]. The possible mechanism that relate insulin resistance to systemic inflammation is complex that may be related to involve increased effect of over produced oxidative stress on the mitochondrial function and endoplasmic reticulum in target tissues [56].

Conclusion
There is an association between increased systemic inflammation, oxidative stress, endothelial dysfunction molecules and poor metabolic control in NIDDM.