Association between Pro‐oxidant‐Antioxidant balance and high‐sensitivity C‐reactive protein in type 2 diabetes mellitus: A Study on Postmenopausal Women

Abstract Introduction Oxidative stress known as a predictive marker for cardiovascular and metabolic diseases could be measured through pro‐oxidant antioxidant balance (PAB). The present study aimed to evaluate PAB and its association with high‐sensitivity C‐reactive protein (hs‐CRP) in the serum of postmenopausal women with diabetes mellitus. Methods In this case–control study, 99 diabetic and 100 healthy postmenopausal women without diabetes mellitus were recruited. Serum PAB values, hs‐CRP, lipid profile, insulin, and vitamin D levels were measured. Moreover, insulin resistance (HOMA‐IR, HOMA‐β and QUICKI), waist circumference (WC), waist‐to‐hip ratio (WHR), waist‐to‐height ratio (WHtR), and body mass index (BMI) were calculated. Results Serum PAB, hs‐CRP, insulin resistance, HOMA‐β, QUICKI, low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), and triglycerides (TG) levels were significantly higher in the postmenopausal women with diabetes mellitus, while there was no significant difference in the total cholesterol (TC), serum insulin, WC, WHR, WHtR and vitamin D levels between the groups. Pearson correlation coefficient showed that HDL‐C and insulin levels were directly correlated with serum PAB. Also, there was a significant direct relationship between LDL‐C and insulin levels and hs‐CRP. There was no meaningful relationship between serum insulin and vitamin D levels and other assessed parameters. Backward logistic regression showed a positive relationship between diabetes mellitus and serum PAB and an inverse relationship with serum HDL levels. Conclusions Serum PAB, hs‐CRP concentration, and lipid profile were significantly different between postmenopausal women with and without diabetes mellitus. These differences may contribute to the development of coronary complications.


| Anthropometric parameters and blood collection
After overnight fasting, 5 ml of venous blood was drawn into EDTA and plain tubes, centrifuged at 2500 rpm for 15 min at room temperature, and serum was allocated to several microtubes and stored at −70°C until analysis. Furthermore, body weight, height, waist circumference (WC), and hip circumference (HC) were measured to calculate the waist-to-hip ratio (WHR), waist-to-height (WHtR), and body mass index (BMI) (kg/m 2 ).

| Biochemical analysis processing
Fasting glucose and lipid profile indices, including total cholesterol (TC), triglyceride (TG), and HDL-C, were measured by enzymatic methods and commercial kits using the BT-3000 Auto-analyser (Biotechnica). Moreover, LDL-C was indirectly evaluated in participants with the Friedewald formula.
The levels of insulin were assessed using commercial kits using a radioimmunoassay from the Immuno Nuclear Corporation

| Measurements of hs-CRP
The PEG (polyethylene glycol)-enhanced immuno-turbidometry method and commercially available kits on an Alcyon® analyser (Abbott) were used to measure hs-CRP levels.

| Assessment of PAB
Serum PAB values were measured in all subjects as previously described by Alamdari et al. 10 In the first step, we added horseradish peroxidase enzyme and chloramine-T as oxidizing agents to TMB.
Redox index resulted in the combined activity of a colour cation (by oxidants) or reduced to a colourless compound (by antioxidants). In standard solutions, various proportions (0%-100%) of 250 μM hydrogen peroxide (as an oxidizing substance) were mixed with 3 mM uric acid (in 10 mM NaOH) (as an antioxidant

| Statistical methods
The normality of the data was assessed by the Kolmogorov-Smirnov test. The mean and SD (for normal distribution) and median and interquartile range (IQR) (for non-normal distribution) were used to describe the study variables. The independent student t-test (for variable normality distribution) was used to compare the mean of study variables between case and control groups. A logistic regression method was used to determine the variables related to diabetes, in- were added to the final model and analysed using multiple logistic regressions. We used SPSS for Windows software (version 18 software package SPSS Inc). A p-value less than .05 was considered statistically significant.

| Participants' characteristics and demographic findings
All data showed a normal distribution. Demographic data, including age, BMI, SYSp and DIAp, were not significantly different between the two groups. Except for serum TC, insulin, vitamin D, WC, WHR and WHtR, other laboratory findings in diabetic subjects were significantly different from the non-diabetic subjects (p < .05). Table 1 shows the features of the two groups.

| PAB values, hs-CRP concentration and insulin resistance among postmenopausal women
Serum PAB levels in the diabetic subjects were significantly higher than in the control group (p < .001) ( Table 1). Also, serum hs-CRP concentrations were statistically different in the two groups (p = .002) ( Table 1). Unsurprisingly, in diabetic women, there was a statistically significant difference in insulin resistance, HOMAβ and QUICKI compared to non-diabetic women (all p < .05), whereas no considerable difference was demonstrated between diabetic patients and healthy participants in serum insulin concentrations (p = .335).

| The relationship between serum PAB values, BMI, and hs-CRP concentrations and other laboratory parameters
As shown in Table 2, the Pearson correlation coefficient analysis was performed to evaluate the correlation between serum PAB values, BMI, hs-CRP concentrations and other laboratory parameters.  respectively. Among the other study factors, a significant association was observed between serum PAB values and LDL-C levels (r = .209, p = .038) and a negative correlation with HDL-C levels (r = −0.224 and p = .026). Moreover, a comparison of the relationship between BMI and other values showed a significant correlation between BMI and TG levels (r = .207 and p = .042). In addition, we did not find any association between vitamin D levels and other laboratory parameters listed in this study.

| Multiple logistic regressions
Logistic regression in the backward approach explained that InsulinR  Table 3). Moreover, these results showed that diabetes had an inverse association with HDL-C (OR: −0.932; p < .001).

| DISCUSS ION
To our knowledge, this is the first case-control study to report PAB duce the production of free radicals. 15 The present study showed that serum hs-CRP levels were positively associated with serum PAB values in diabetic women. Moreover, earlier reports support the presence of high OS and hs-CRP levels in stroke, cardiovascular and beta-thalassemia patients. 16,17 There is strong evidence of the correlation between inflammation and OS because both factors contribute to the pathogenesis of diabetes. 18 Moreover, diabetic postmenopausal women also had higher levels of blood glucose and HOMA-IR index. In correlation with previous studies, dysregulated lipid metabolism in diabetics has been reported, which could be attributed to increased lipolysis due to impaired insulin function in adipose tissue. In addition, the accumulation of free fatty acids in the liver leads to the high hepatic synthesis of TGs and results in hypertriglyceridemia. 11,19 In this study, as shown by Barrett-Connor et al., 20 no relationship was observed in total cholesterol between diabetic and non-diabetic subjects. We did not find any significant difference between serum hs-CRP, glucose, TG, LDL-C levels, and BMI. These results were inconsistent with those of Yang et al. 21 The reason may be due to the menopause subjects and the changes in the oestrogen hormone and its function in the liver. Moreover, parallel to our report, earlier reports have suggested that OS plays a major role in developing insulin resistance. 22,23 Consistent with many studies, 23,24 we can suggest that diabetic women have significantly altered lipid profiles than healthy postmenopausal subjects. Contrary to our work, many studies have reported that increased BMI values were strongly associated with hs-CRP and OS levels. 25 We suggest that independent of BMI, OS may also be an essential determinant of hs-CRP levels in diabetic people. Therefore, the link between OS and hs-CRP levels may involve pathways unrelated to BMI. In line with the study by Goodarzi et al., 7 there was no significant difference in BMI between the two groups. Moreover, consistent with Zaman et al., the patient and control groups were overweight but not obese. 26 Overweight women are not necessarily diabetic, and diabetes mellitus is not the only reason for the BMI increase in overweight type 2 diabetics; other factors may be involved. In addition, in line with our study, many studies have shown that people with diabetes also have a low BMI, and some have a very low BMI. 26,27 On the contrary, unlike some studies, 28 our study found that diabetes Due to this controversy with the prior investigation, we think that diabetes in postmenopausal women can cause these outcomes.

TA B L E 3 Association between study variables and diabetes using multiple logistic regressions
Our finding was in agreement with that of Kahn et al., 35,36 indicating that diabetic postmenopausal women were characterized by insulin resistance. Moreover, it has been noted that insulin has a significantly negative relationship with higher hs-CRP levels and PAB values. However, in Table 3, PAB values showed a positive correlation with LDL-C levels and an irreversible association with HDL-C levels. Therefore, the evidence supporting these results is that HDL cholesterol is the major lipoprotein carrier of antioxidant enzymes, and LDL is the main factor correlated with oxidative markers.
Our study had a few limitations. The present work focused only on PAB values. However, several other factors can affect these biochemical parameters in OS, including sex hormones. Another limitation was the small sample size.  Writing -review and editing (equal). Naser Mobarra: Conceptualization (lead); supervision (lead); writing -review and editing (equal).

ACK N O WLE D G E M ENTS
The authors are particularly grateful to the patients and their family members who volunteered to participate in this study.

FU N D I N G I N FO R M ATI O N
This study is funded by Mashhad University of Medical Sciences (Grant No: 981826)

CO N FLI C T O F I NTE R E S T
The authors declared no conflicts of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

E TH I C A L A PPROVA L
The Ethics Committee of Mashhad University of Medical Sciences approved the study (IR.MUMS.REC.1399.533).