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Association of biomarkers of inflammation and oxidative stress with the risk of chronic kidney disease in Type 2 diabetes mellitus in North Indian population
Journal of Diabetes and Its Complications 27 (2013) 548–552
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Association of biomarkers of inflammation and oxidative stress with the risk of chronic kidney disease in Type 2 diabetes mellitus in North Indian population☆ Stuti Gupta, Jasvinder K. Gambhir ⁎, OP Kalra, Amar Gautam, Kirtikar Shukla, Mohit Mehndiratta, Sunil Agarwal, Rimi Shukla Departments of Biochemistry and Medicine, University College of Medical Sciences (University of Delhi) & GTB Hospital, Delhi, 110095 India
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Article history: Received 15 April 2013 Received in revised form 11 July 2013 Accepted 21 July 2013 Available online 6 September 2013 Keywords: Chronic kidney disease Type 2 DM Oxidative stress Inflammation
a b s t r a c t Chronic kidney disease (CKD) is a major cause of morbidity and mortality worldwide. It results from diverse etiologies, diabetes being a frontrunner amongst them. Type 2 diabetes mellitus (DM) is being increasingly recognized as a proinflammatory state with increased oxidative stress which enormously increases the risk of micro and macro vascular diseases. This study was planned to explore the possible association between tumor necrosis factor-alpha (TNF-α), urinary monocyte chemoattractant protein-1 (uMCP-1), highsensitivity C-reactive protein (hsCRP) and parameters of oxidative stress in patients with Type 2 diabetes mellitus (DM) and diabetic chronic kidney disease (DM–CKD). Fifty patients each were recruited in DM, DM–CKD and healthy control groups. Plasma TNF-α, hsCRP and uMCP-1 levels as inflammatory mediators were measured by ELISA, reduced glutathione (GSH), ferric reducing ability of plasma (FRAP) as parameters of antioxidant activity and malondialdehyde (MDA) as marker of oxidative stress, were measured spectrophotometrically. Plasma TNF-α, hsCRP and uMCP-1 were significantly higher in DM–CKD compared to DM and healthy controls. Lipid peroxidation, measured as MDA was significantly higher in patients with DM–CKD as compared to patients with DM and healthy controls. Further, antioxidant capacity of blood measured as FRAP and GSH was found to be significantly lower in patients with DM and DM–CKD as compared to healthy controls (p b 0.001). Plasma TNF-α and uMCP-1 showed a significant positive correlation with HbA1c (r = 0.441, 0.643), hsCRP (r = 0.400, 0.584) and MDA (r = 0.423, 0.759) and significant negative correlation with GSH (R = − 0.370, − 0.800) and FRAP (r = − 0.344, − 0.684) Increased inflammatory markers viz. TNF-α, hsCRP and uMCP-1 and markers of oxidative stress i.e. increased MDA and decreased GSH and FRAP in DM–CKD suggest an important role of inflammation and oxidative stress in the pathogenesis of renal damage in diabetic patients. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Type 2 diabetes mellitus (T2DM) is one of the most challenging health concerns of the 21st century. T2DM is a proinflammatory state with increased oxidative stress, predisposing the patients to macroand micro-vascular complications. Diabetic nephropathy (DN), a microvascular complication of long term uncontrolled DM is the single most frequent cause of end-stage renal disease (ESRD) (Ritz, Rychlik, Locatelli, & Halimi, 1999), accounting for approximately 40% of new cases of ESRD every year (Kramer & Molitch, 2005). Although metabolic and hemodynamic alterations are considered the main cause of renal damage in diabetes, the accumulating
☆ Declaration of interest: The authors alone are responsible for the content and writing of the paper and there is no conflict of interest. ⁎ Corresponding author. Tel.: +91 9811641277. E-mail address: [email protected] (J.K. Gambhir). 1056-8727/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jdiacomp.2013.07.005
evidence now indicates that immunologic and inflammatory mechanisms also play a significant role in its development and progression (Tuttle, 2005; Mora & Navarro, 2006). Diabetics have been shown to produce excessive inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and C-reactive protein (CRP) (Zinman, Hanley, Harris, Kwan, & Fantus, 1999), and few studies have also reported association between inflammatory biomarkers and DN (Navarro, Mora, Muros, & García, 2006; Yeo, Hwang, Park, Choi, Huh, & Kim, 2010; Lu, Randell, Han, Adeli, Krahn, & Meng, 2011; Taslipinar et al., 2011; Fernández-Real, Vendrell, García, Ricart, & Vallès, 2012). Most attention has been focused on the role of TNF-α, which is a pleiotropic proinflammatory cytokine primarily synthesized by monocytes, macrophages and T cells and plays an important role in pathogenesis of DN. Many studies in animal models have shown that intrinsic renal cells, including glomerular, mesangial, endothelial and tubular cells, are also able to produce this cytokine (Jevnikar et al., 1991; Nakamura et al., 1993; Sugimoto, Shikata, Wada, Horiuchi, & Makino, 1999; Dong, Swaminathan, Bachman, Croatt, Nath, & Griffin, 2007; Zhang,
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Ramesh, Norbury, & Reeves, 2007). TNF-α is not only cytotoxic to renal cells (Bertani et al., 1989), but also induces the production of reactive oxygen species (ROS) in diverse cells, including mesangial cells (Raedke, Meier, Topley, Fluge, Habermehl, & Resch, 1990). C-reactive protein (CRP), a member of pentatraxin family is the prototypic marker of inflammation which has been reported to be associated with T2DM and early stages of nephropathy, however its association with DN is not completely understood (Navarro, Mora, Macia, & Garcia, 2003; Navarro et al., 2006; Navarro-González & Mora-Fernandez, 2008). Recent evidence has highlighted the production of monocyte chemoattractant protein-1 (MCP-1) by diabetic kidneys as a major promoter of inflammation, renal injury and fibrosis in diabetic nephropathy (Tesch, 2008). Urinary levels of MCP-1 (uMCP-1) closely reflect kidney MCP-1 production and correlate significantly with levels of albuminuria, serum glycated albumin, urine N-acetylglucosaminidase (NAG) and kidney CD68+ macrophages in human and experimental diabetic nephropathy (Furuta et al., 1993; Gu, Tseng, & Rollins, 1999; Chow, Ozols, Nikolic-Paterson, Atkins, Tesch, et al., 2004). Accumulating evidence, both experimental and clinical, has suggested that there is a close link between hyperglycemia, oxidative stress, inflammation and diabetic complications including nephropathy (Pan et al., 2010). ROS have been shown to cause renal damage via vasoconstriction, vascular smooth muscle cell growth and migration, endothelial dysfunction, modification of extracellular matrix proteins and increased renal tubular reabsorption. Oxidative stress may also be implicated in promoting a low grade systemic inflammation in patients with T2DM (Amalich et al., 2000). Activation of nuclear factor-kappa B (NF-κB) through oxidative stress induced by hyperglycemia increases the concentration of proinflammatory cytokines (Esposito et al., 2002). A study has shown that elevation of TNF-α in turn increases oxidative stress leading to renal injury in streptozotocin induced diabetes in rats (Kuhad & Chopra, 2009). In spite of improvement in our knowledge on DN, from a pathophysiologic point of view, the intricate mechanisms in chronic hyperglycemia leading to the development of renal injury are complex and not yet fully understood. Previous reported studies have not included both inflammatory biomarkers and oxidant– antioxidant parameters in a single setting, in addition, no association between uMCP-1, a marker of renal injury in DN and other parameters has been shown in the aforementioned studies. Therefore, the present work aims to evaluate inflammatory cytokines (TNF-α), inflammatory chemokine (MCP-1), inflammatory marker (hsCRP) and oxidant– antioxidant status in order to investigate the relationship between inflammation and oxidative stress in patients with DN. 2. Methodology 2.1. Subjects The present study included 150 subjects attending Medicine OPD/ Nephrology Outpatient Clinic at the University College of Medical Sciences and Guru Teg Bahadur Hospital, Delhi. The subjects were divided into 3 groups (n = 50) viz; Group I: healthy controls (HC), Group II: patients with Type 2 diabetes mellitus without nephropathy (DM), Group III: patients with Type 2 diabetes mellitus with nephropathy (DM–CKD). Healthy subjects with systolic and diastolic blood pressure 120 mm Hg and 80 mm Hg respectively, and fasting and postprandial plasma glucose less than 100 ml/dL and 140 ml/dL were recruited as controls from volunteers and staff of UCMS and GTB Hospital. Diagnosis of T2DM was made according to revised American Diabetes Association criteria (American diabetic association, 2012). All diabetic subjects with retinopathy and dipstick positive proteinuria and microalbuminuria were clustered in group III. All patients in group III were in pre-dialysis stage. The sensitivity of the dipstick “Urine Test 11 MAU” from Piramal Diagnostic, India is 10–15 mg/dL.
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Further spot urine samples were analyzed for urinary albumin creatinine ratio which was 0.40 ± 0.33 in the DM–CKD group. To avoid potential confounding factors, the patients having acute and chronic infections, fever, malignancy, other renal disorders, cirrhosis of liver and congestive heart failure were excluded. All the patients in group III had retinopathy however patients with macrovascular complications like stroke and CAD were excluded. Patients who were on inhibitors of renin–angiotensin aldosterone system, aspirin and vitamin D analogues were advised to stop these drugs for one week before inclusion in the study. The protocol of this study was approved by the Institutional Ethics Committee for Human Research and informed written consent was taken from all the participants. 2.2. Methods Relevant clinical history and physical examination were recorded. Arterial blood pressure was measured using mercury sphygmomanometer with the patient in the sitting position after 5 min of rest. The glomerular filtration rate was estimated by ‘Modification of Diet in Renal Disease Abbreviated Equation (MDRD)’: [eGFR = 186 × (plasma Cr) −1.154 × (age) −0.203 × (0.742 if female) × (1.210 if African American) (Levey, Bosch, Lewis, Greene, Rogers, & Roth, 1999). Fasting blood sample was withdrawn from ante-cubital vein under aseptic precautions and collected into vacutainers containing salts of fluoride & oxalate for plasma glucose and EDTA vials for various other parameters. For estimation of reduced glutathione 200 μL of whole blood was used and estimated immediately after collection of sample. For glycosylated hemoglobin 200 μL whole blood was kept as aliquot at 4°C–8°C and estimation was carried out within 1 week of collection. Rest of the EDTA blood sample was subjected to centrifugation at 3000 rpm for 10 min to separate the plasma. GST, MDA and FRAP were estimated from plasma immediately after collection. Remaining plasma was stored in aliquots at − 80°C till further use for the estimation of TNF-α and hsCRP. Random mid-stream urine sample was collected for the estimation of the MCP-1 and albumin. Reduced glutathione (GSH) was estimated by the method of Tietze (1969) and the antioxidant capacity of blood was measured as ferric reducing ability of plasma (FRAP) by the method of Benzie and Strain (1996). Plasma malondialdehyde (MDA) was measured according to the method of Satoh (1978). Glycosylated hemoglobin (HbA1C) was measured by ion-exchange resin chromatography using commercially available kits (Fortress, UK). Plasma and urine samples were stored at − 80°C until assayed by ELISA for the measurement of plasma TNF-α (Diaclone, France; sensitivity less than 8 pg/mL), hsCRP (Calbiotech, USA; sensitivity less than 0.005 mg/mL) and uMCP-1 (Weldon, California; sensitivity less than 7.8125 pg/mL). Routine biochemical parameters were assayed in automated analyzer using commercial kits. All these investigations were carried out once at the time of entry into the study. 2.3. Statistical analysis SPSS-17 software was used for statistical analysis. The results were expressed as mean ± standard deviation (SD). Demographic data and routine biochemical parameters were compared among the subject groups using one-way analysis of variance (ANOVA) followed by posthoc Tukey's test. Pearson's correlation analysis was used to determine correlation between different parameters. The mean difference was considered significant at p b 0.05. 3. Results The baseline demographic characteristics and biochemical parameters of both healthy subjects and diabetic groups are shown in Table 1. There were no significant differences between diabetic patients and controls with respect to sex distribution and BMI. The
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Table 1 The baseline demographic characteristics and biochemical parameters in different study groups. Variables
Group I (n = 50)
Group II (n = 50)
Group III (n = 50)
Age (years)
46.0 ± 4.0 (39.6–52.4) 27/23 21.1 ± 1.7 (19.8–23.1) –
56.40 ± 8.5 (46.1–68.2) 26/24 22.1 ± 2.1 (19.2–25.5) 12.6 ± 2.7 (11.8–13.4) 136.0 ± 2.3a (135.3–136.6) 82.6 ± 0.9a (82.3–82.9) 143.5 ± 4.5a (142.3–144.8) 186.7 ± 11.1a (183.5–189.9) 7.3 ± 0.2a (7.2–7.4) 25.7 ± 5.8 (24.1–27.5) 0.95 ± 0.20 (0.89–1.0) 3.4 ± 0.6 (3.2–3.5) 97.4 ± 0.6 (96.5–98.2) –
55.7 ± 8.2 (44.8–65.5) 28/22 22.6 ± 3.4 (19.4–26.1) 9.1 ± 3.3b (8.1–10.1) 136.7 ± 1.8a (136.2–138.2) 82.8 ± 0.8a (82.6–83.1) 187.3 ± 16.2a,b (182.7–191.9) 258.9 ± 31.2a,b (250.1–267.8) 8.1 ± 0.2a,b (8.1–8.2) 91.5 ± 24.8a,b (84.5–98.6) 3.6 ± 1.5a,b (3.24–4.10) 8.5 ± 0.7a,b (8.3–8.7) 56.2 ± 0.9b (55.1–57.9) 0.40 ± 0.33 (0.37–0.49)
Gender (M/F) BMI (kg/m2) Duration of DM (years) SBP (mm Hg) DBP (mm Hg) Fasting glucose (mg/dL) Postprandial glucose (mg/dL) HbA1c (%) Urea (mg/dL) Creatinine (mg/dL) Uric acid (mg/dL) eGFR (mL/min/1.73 m2) Urinary albumin/creatinine
120.1 ± 1.5 (119.7–120.5) 79.2 ± 0.9 (78.9–79.4) 85.4 ± 5.9 (83.6–87.1) 108.2 ± 8.4 (105.8–110.6) 5.2 ± 0.4 (5.0–5.3) 24.5 ± 5.9 (22.8–26.3) 0.85 ± 0.13 (0.81–0.90) 4.6 ± 1.2 (4.2–4.9) 98.1 ± 0.7 (97.3–99.4) –
Data are expressed as mean ± SD. Group I: Healthy control; Group II: Diabetes mellitus without nephropathy; Group III: Diabetic nephropathy. BMI: Body mass index; SBP and DBP: Systolic and diastolic blood pressure; eGFR: estimated glomerular filtration rate. a Significantly different from healthy control at p b 0.001. b Significantly different from diabetic patients without nephropathy at p b 0.001.
patients with diabetes (DM and DM–CKD) were older than healthy controls. Duration of diabetes was longer in DM than DM–CKD group. Significantly higher SBP and DBP were observed in diabetic patients with and without DN (p b 0.001) as compared to healthy controls. Fasting, postprandial plasma glucose and HbA1c were significantly higher (p b 0.001) in DM–CKD as compared to DM. Levels of creatinine, urea, and uric acid were significantly higher (p b 0.001) and estimated glomerular filtration rate (eGFR) was lower (p b 0.001) in DM–CKD as compared to DM group. Table 2 shows levels of inflammatory markers in various study groups. Plasma TNF-α, hsCRP and urinary MCP-1 were significantly higher in DM–CKD cases as compared to DM and HC (p b 0.001). Various oxidative stress parameters in different study groups are shown in Table 3. Antioxidant parameters like reduced GSH and FRAP
Table 2 Plasma levels of inflammatory markers in various study groups. Parameters
Group I (n = 50)
Group II (n = 50)
Group III (n = 50)
TNF-α (pg/mL)
14.5 ± 5.2 (13.1–16.1) 0.74 ± 0.46 (0.61–0.88) 124.1 ± 46.6 (76.3–171.7)
15.3 ± 3.7 (14.3–16.4) 3.6 ± 1.5a (3.3–4.1) 278.5 ± 125.0 (153.1–400.8)
20.6 ± 3.9a,b (19.5–21.8) 8.5 ± 1.7a,b (8.0–9.0) 5632.7 ± 2275.8a,b (3351.5–8001.2)
hsCRP (mg/L) uMCP-1 (pg/mg creatinine)
Data are expressed as mean ± SD. Group I: Healthy control; Group II: Diabetes mellitus without nephropathy; Group III: Diabetic nephropathy. a Significantly different from healthy control at p b 0.001. b Significantly different from diabetic patients without nephropathy at p b 0.001.
Table 3 Plasma levels of oxidative stress markers in various study groups. Parameters
Group I (n = 50)
Group II (n = 50)
Group III (n = 50)
GSH (mg/g Hb)
3.37 ± 0.35 (3.20–3.50) 1.48 ± 0.20 (1.40–1.50) 549.6 ± 49.1 (535.6–563.6)
1.89 ± 0.06a,c (1.70–1.80) 2.60 ± 0.35a (2.50–2.70) 409.0 ± 55.1a,c (399.5–451.8)
0.90 ± 0.01a (0.97–0.98) 5.14 ± 0.39a,b (5.00–5.20) 170.7 ± 142.3a (166.6–231.4)
MDA (nmol/mL) FRAP (μmol/L)
Data are expressed as mean ± SD. Group I: Healthy control; Group II: Diabetes mellitus without nephropathy; Group III: Diabetic nephropathy. a Significantly different from healthy control at p b 0.001. b Significantly different from diabetic patients without nephropathy at p b 0.001. c Significantly different from diabetic patients with nephropathy at p b 0.001.
were lower in DM and DM–CKD cases as compared to HC and maximum depletion of antioxidants was seen in DM–CKD which were significantly lower (p b 0.001) when compared to DM cases. On the other hand, oxidant stress parameter like MDA was raised in DM and DM–CKD groups when compared to HC; however maximum increase was noticed in patients with DM–CKD when compared to patients with DM (p b 0.001) indicating higher oxidative stress in DM–CKD vs DM patients. As shown in Table 4, when all the subjects were grouped together, there was a positive correlation between plasma TNF- α levels and hsCRP (r = 0.400; p b 0.01) and uMCP-1 (r = 0.508; p b 0.01). TNF-α and uMCP-1 also correlated positively with HbA1c (r = 0.441, 0. 643; p b 0.01), however, negative association was observed between TNF-α and antioxidant parameters i.e. GSH and FRAP (r = −0.370, − 0.344; p b 0.01) while a positive association was noticed between TNF-α and MDA levels (r = 0.423; p b 0.01). Similarly uMCP-1 also correlated positively with hsCRP (r = 0.584; p b 0.01) and MDA respectively (r = 0.759; p b 0.01) whereas it correlated negatively with GSH and FRAP (r = − 0.800, − 0.684; p b 0.01). However, this correlation lost significance when calculated in individual groups, probably due to the small sample size, though similar trend was maintained. 4. Discussion Diabetic nephropathy (DN) is a major cause of ESRD in developing countries. Historically, T2DM was not thought to be an immune disease; however there is growing evidence supporting the fact that innate immunity and inflammation are essential contributing factors in the development of renal injury in diabetics (Mora & Navarro, 2005). The current study is the first comprehensive work which highlights the relationship between various markers of inflammation and oxidative stress and DN. Results from our data reveal that plasma levels of TNF-α and hsCRP were significantly higher in patients with diabetes and more so in patients with diabetic nephropathy. These findings are consistent with a previous study which showed that high concentrations of
Table 4 Correlation analysis between inflammatory biomarkers, oxidative stress parameters and other baseline investigations. (all subjects were grouped together). Parameters
TNF-α (r)
uMCP-1 (r)
p value
HbA1c uMCP-1 hsCRP GSH FRAP MDA
0.441 0.508 0.400 −0.370 −0.344 0.423
0.643 1.000 0.584 −0.800 −0.684 0.759
p p p p p p
b b b b b b
0.01 0.001 0.001 0.001 0.001 0.001
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TNF-α and CRP may be risk factors for CKD in Korean patients with T2DM (Yeo et al., 2010). Similarly, a significant association between serum TNF-α and hsCRP in patients with DN has been reported in a study (Navarro et al., 2003). On the other hand, Lin, Hu, Rimm, Rifai, and Curhan (2006) observed that no correlation existed between CRP levels and DN (GFR b60 mL/min/1.73 m 2) (Lin et al., 2006). It has been reported that CRP is associated with glomerular and tubulointerstitial damage in patients with DN (Rivero, Mora, Muros, García, Herrera, & Navarro-González, 2009). The exact mechanism how hsCRP causes renal damage is not completely understood, however a recent study has shown that CRP inhibits endothelial nitric oxide synthase (eNOS) activity by uncoupling (Singh, Devaraj, VasquezVivar, & Jialal, 2007) and leads to endothelial dysfunction in vivo and promotes hypertension which could be a possible mechanism damaging kidney endothelium. uMCP-1 is a potential marker of kidney disease in diabetes and in the present study its levels were highest in patients with DN. Previous experimental studies support our findings that MCP1 plays a crucial role in the progression of diabetic renal injury and uMCP-1 levels reflect the renal injury in diabetes (Kanamori et al., 2007). Hasegawa et al. (1991) have shown that there is good relationship between low grade inflammation and DN in patients with T2DM. Our study further confirms the role of inflammation in the etiopathogenesis of kidney disease in diabetes mellitus. It is well known that hyperglycemia is the causative factor leading to increased production of ROS which may ultimately cause diabetic complications including DN causing increased availability of glycolytic intermediates causing their diversion into other pathways such as polyol pathway, hexosamine pathway, protein kinase C (PKC) pathway and advanced glycation end (AGE) products pathway (Brownlee, 2001). Each of these different pathogenic mechanisms reflects a single hyperglycemia-induced process i.e. overproduction of superoxide by the mitochondrial electron-transport chain. It has also been proposed that reduction of glucose to sorbitol consumes NADPH which is required for regenerating reduced glutathione (GSH), and this could induce or exacerbate intracellular oxidative stress (Brownlee, 2001). Similar results were observed in the present study that antioxidant parameters i.e. reduced GSH, FRAP were maximally decreased and oxidative parameter i.e. MDA was increased in diabetic patients with nephropathy. Our results are in agreement with the study by Kumawat, Pahwa, Gahlaut, and Singh (2009) which showed that there was a significant decrease in reduced GSH and increase in MDA levels in diabetic patients with microvascular complications. A similar study by Kavitha, Ramani, Dhass, and Aruna (2011) showed that levels of MDA were increased and FRAP levels were decreased in patients with DN. Clinical studies correlating both inflammatory markers and oxidative stress together in the pathogenesis of DN are scarce. Few studies have supported the fact that TNF-α is produced by adipose tissue (Trayhurn & Wood, 2005), however in the present study there was no significant difference in BMI between different groups of diabetic patients. Probably the interaction between genetic and environmental factors may result in an inflammatory milieu, eventually leading to synthesis of TNF-α by immune cells and renal cells. Our results also put forward a significant positive correlation between TNF-α, hsCRP and uMCP-1 suggesting that these inflammatory cytokines seem to have a crucial role in the pathogenesis of diabetic nephropathy. Previous studies have shown that TNF-α induces hsCRP synthesis mainly by hepatocytes (McNair et al., 2010). On the other hand, recently Liu, Liu, Ji, Lu, Wang, and Guo (2011) have shown that CRP induces TNF-α via p38MAPK-TLR4 signaling pathway in smooth muscle of rats (Liu et al., 2011). Bain, Elner, Yoshida, and Elner (2004) have reported that TNF-α increases MCP-1 expression via phosphoinositide 3-kinase (PI3K)/AKT signaling pathway. A previous study showed that plasma MCP-1 is positively correlated with MDA in Type 1 diabetics with renal damage (Chiarelli
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et al., 2002), but experimental studies showing association between uMCP-1 and oxidative stress in T2DM with nephropathy are scanty, however our study is the first to demonstrate that uMCP-1 is correlated positively with MDA and negatively with GSH and FRAP. In a previous study Prasad (2004) has reported that CRP increases ROS production by neutrophils, therefore plasma hsCRP might be playing an important role in the pathogenesis of DN and may be a potential risk factor for the development of DN. 5. Conclusions Our study has suggested that increased levels of inflammatory mediators i.e. TNF-α, hsCRP and uMCP-1 may play an independent as well as interdependent role, which via several signaling pathways contributes to hyperglycemia mediated increase in oxidative stress. An increase in oxidative stress may further amplify inflammation, thus setting up a vicious cycle. Therefore, inflammation interlinked with oxidative stress may be major mechanisms in the pathogenesis and progression of nephropathy in susceptible diabetic patients. However, there is a need to carry out these studies in a larger sample size. Acknowledgment We sincerely thank Indian Council of Medical Research and University college of medical sciences, New Delhi for providing partial funding for this study. The authors are also thankful to the Department of Biostatistics and Medical Informatics, University College of Medical Sciences, Delhi for statistical analysis. References Amalich, F., Hernanz, A., Lopez- Maderuelo, D., Pena, J. M., Camacho, J., Madero, R., et al. (2000). Enhanced acute phase response and oxidative stress in older adults with type II diabetes. Hormone and Metabolic Research, 32(10), 407–412. American diabetic association. (2012). Expert committee on the diagnosis and classification of diabetes mellitus. Report. Diabetic Care, 35, S1–S10. Bain, Z. M., Elner, S. G., Yoshida, A., & Elner, V. M. (2004). Differential involvement of phosphoinositide 3-kinase/Akt in human RPE MCP-1 and IL-8 expression. Investigative Ophthalmology & Visual Science, 45(6), 1887–1896. Benzie, I. F., & Strain, J. J. (1996). The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: The FRAP assay. Analytical Biochemistry, 239(1), 70–76. Bertani, T., Abbate, M., Zoja, C., Coma, D., Perico, N., Ghezzi, P., et al. (1989). Tumor necrosis factor induces glomerular damage in rabbit. The American Journal of Pathology, 134(2), 419–430. Brownlee, M. (2001). Biochemistry and molecular cell biology of diabetic complications. Nature, 414(6865), 813–820. Chiarelli, F., Cipollone, F., Mohn, A., Marini, M., Iezzi, A., Fazia, M., et al. (2002). Circulating monocyte chemoattractant protein-1 and early development of nephropathy in type 1 diabetes. Diabetes Care, 25(10), 1829–1834. Chow, F., Ozols, E., Nikolic-Paterson, D. J., Atkins, R. C., Tesch, G. H., et al. (2004). Macrophages in mouse type 2 diabetic nephropathy: Correlation with diabetic state and progressive renal injury. Kidney International, 65(1), 116–128. Dong, X., Swaminathan, S., Bachman, L. A., Croatt, A. J., Nath, K. A., & Griffin, M. D. (2007). Resident dendritic cells are the predominant TNF-secreting cell in early renal ischemia–reperfusion injury. Kidney International, 71(7), 619–628. Esposito, K., Nappo, F., Marfella, R., Giugliano, G., Giugliano, F., Camacho, M., et al. (2002). Inflammatory cytokine concentrations are acutely increased by hyperglycemia in humans: Role of oxidative stress. Circulation, 106(16), 2067–2072. Fernández-Real, J. M., Vendrell, J., García, I., Ricart, W., & Vallès, M. (2012). Structural damage in diabetic nephropathy is associated with TNF-α system activity. Acta Diabetologica, 49(4), 301–305. Furuta, T., Saito, T., Ootaka, T., Soma, J., Obara, K., Abe, K., et al. (1993). The role of macrophages in diabetic glomeruosclerosis. American Journal of Kidney Disease, 21(5), 480–485. Gu, L., Tseng, S. C., & Rollins, B. J. (1999). Monocytes chemoattractant protein-1. Chemical Immunology, 72, 7–29. Hasegawa, G., Nakano, K., Sawada, M., Uno, K., Shibayama, Y., Ienaga, K., et al. (1991). Possible role of tumor necrosis factor and interleukin-1 in the development of diabetic nephropathy. Kidney International, 40(6), 1007–1012. Jevnikar, A. M., Brennan, D. C., Singer, G. G., Heng, J. E., Ivlaslinski, W., Wuthrich, R. P., et al. (1991). Stimulated kidney tubular epithelial cells express membrane associated and secreted TNF alpha. Kidney International, 40(2), 203–211. Kanamori, H., Matsubara, T., Mima, A., Sumi, E., Nagai, K., Takahashi, T., et al. (2007). Inhibition of MCP-1/CCR2 pathway ameliorates the development of diabetic nephropathy. Biochemical and Biophysical Research Communications, 360(4), 772–777.
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Kavitha, G., Ramani, G., Dhass, P. K., & Aruna, R. M. (2011). Oxidative stress, interleukin (IL-6) and atherogenic index of plasma in diabetic nephropathy. International Journal of Applied Biology and Pharmaceutical Technology, 2(2), 211–216. Kramer, H., & Molitch, M. E. (2005). Screening for kidney disease in adults with diabetes. Diabetes Care, 28(7), 1813–1816. Kuhad, A., & Chopra, K. (2009). Attenuation of diabetic nephropathy by tocotrienol: Involvement of NFkB signalling pathway. Life Sciences, 84(9–10), 296–301. Kumawat, M., Pahwa, M. B., Gahlaut, V. S., & Singh, N. (2009). Status of antioxidant enzymes and lipid peroxidation in Type 2 diabetes mellitus with micro vascular complications. The Open Endocrinology Journal, 3, 12–15. Levey, A. S., Bosch, J. P., Lewis, J. B., Greene, T., Rogers, N., & Roth, D. (1999). A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of Diet in Renal Disease Study Group. Annals of Internal Medicine, 130(6), 461–470. Lin, J., Hu, F. B., Rimm, E. B., Rifai, N., & Curhan, G. C. (2006). The association of serum lipids and inflammatory biomarkers with renal function in men with type II diabetes mellitus. Kidney International, 69(2), 336–342. Liu, N., Liu, J., Ji, Y., Lu, P., Wang, C., & Guo, F. (2011). C-reactive protein induces TNF-α secretion by p38 MAPK-TLR4 signal pathway in rat vascular smooth muscle cells. Inflammation, 34(4), 283–290. Lu, J., Randell, E., Han, Y., Adeli, K., Krahn, J., & Meng, Q. H. (2011). Increased plasma methylglyoxal level, inflammation, and vascular endothelial dysfunction in diabetic nephropathy. Clinical Biochemistry, 44(4), 307–311. McNair, E. D., Wells, C. R., Mabood Qureshi, A., Basran, R., Pearce, C., Orvold, J., et al. (2010). Modulation of high sensitivity C-reactive protein by soluble receptor for advanced glycation end products. Molecular and Cellular Biochemistry, 34(1–2), 135–138. Mora, C., & Navarro, J. F. (2005). The role of inflammation as a pathogenic factor in the development of renal disease in diabetes. Current Diabetes Reports, 5(6), 399–401. Mora, C., & Navarro, J. F. (2006). Inflammation and diabetic nephropathy. Current Diabetes Reports, 6(6), 463–468. Nakamura, T., Fukui, M., Ebihara, I., Osada, S., Nagaoka, I., Tomino, Y., et al. (1993). mRNA expression of growth factors in glomeruli from diabetic rats. Diabetes, 42(3), 450–456. Navarro, J. F., Mora, C., Macia, M., & Garcia, J. (2003). Inflammatory parameters are independently associated with urinary albumin in type 2 diabetes mellitus. American Journal of Kidney Disease, 42(1), 53–61. Navarro, J. F., Mora, C., Muros, M., & García, J. (2006). Urinary tumour necrosis factoralpha excretion independently correlates with clinical markers of glomerular and tubulointerstitial injury in type 2 diabetic patients. Nephrology, Dialysis, Transplantation, 21(12), 3428–3434. Navarro-González, J. F., & Mora-Fernandez, C. (2008). The role of inflammatory cytokines in diabetic nephropathy. Journal of the American Society of Nephrology, 19(3), 433–442. Pan, H. Z., Zhang, L., Guo, M. Y., Sui, H., Li, H., Wu, W. H., et al. (2010). The oxidative stress status in diabetes mellitus and diabetic nephropathy. Acta Diabetologica, 47(Suppl 1), 71–76.
Prasad, K. (2004). C-reactive protein increases oxygen radical generation by neutrophils. Journal of Cardiovascular Pharmacology and Therapeutics, 9(3), 203–209. Raedke, H. H., Meier, B., Topley, N., Fluge, J., Habermehl, G. G., & Resch, K. (1990). Interleukin 1-alpha and tumor necrosis factor-alpha induce oxygen radical production in mesangial cells. Kidney International, 37(2), 767–775. Ritz, E., Rychlik, I., Locatelli, F., & Halimi, S. (1999). End-stage renal failure in type 2 diabetes: A medical catastrophe of worldwide dimensions. American Journal of Kidney Disease, 34(5), 795–808. Rivero, A., Mora, C., Muros, M., García, J., Herrera, H., & Navarro-González, J. F. (2009). Pathogenic perspectives for the role of inflammation in diabetic nephropathy. Clinical Sciences, 116(6), 479–492. Satoh, K. (1978). Serum lipid peroxide in cerebrovascular disorders determined by a new colorimetric method. Clinica Chimica Acta, 90(1), 37–43. Singh, U., Devaraj, S., Vasquez-Vivar, J., & Jialal, I. (2007). C-reactive protein decreases endothelial nitric oxide synthase activity via uncoupling. Journal of Molecular and Cellular Cardiology, 43(6), 780–791. Sugimoto, H., Shikata, K., Wada, J., Horiuchi, S., & Makino, H. (1999). Advanced glycation end products-cytokine-nitric oxide sequence pathway in the development of diabetic nephropathy: Aminoguanidine ameliorates the overexpression of tumor necrosis factor-alpha and inducible nitric oxide synthase in diabetic rat glomeruli. Diabetologia, 42(7), 878–886. Taslipinar, A., Yaman, H., Yilmaz, M. I., Demirbas, S., Saglam, M., Taslipinar, M. Y., et al. (2011). The relationship between inflammation, endothelial dysfunction and proteinuria in patients with diabetic nephropathy. Scandinavian Journal of Clinical and Laboratory Investigation, 71(7), 606–612. Tesch, G. H. (2008). MCP-1/CCL2: A new diagnostic marker and therapeutic target for progressive renal injury in diabetic nephropathy. American Journal of Physiology. Renal Physiology, 294(4), F697–F701. Tietze, F. (1969). Enzymic method for quantitative determination of nanogram amounts of total and oxidized glutathione: Applications to mammalian blood and other tissues. Analytical Biochemistry, 27(3), 502–522. Trayhurn, P., & Wood, I. S. (2005). Signalling role of adipose tissue: Adipokines and inflammation in obesity. Biochemical Society Transactions, 33(Pt 5), 1078–1081. Tuttle, K. R. (2005). Linking metabolism and immunology: Diabetic nephropathy is an inflammatory disease. Journal of the American Society of Nephrology, 16(6), 1537–1538. Yeo, E. S., Hwang, J. Y., Park, J. E., Choi, Y. J., Huh, K. B., & Kim, W. Y. (2010). Tumor necrosis factor (TNF-α) AND C-reactive protein (CRP) are positively associated with the risk of chronic kidney disease in patients with type 2 diabetes. Yonsei Medical Journal, 51(4), 519–525. Zhang, B., Ramesh, G., Norbury, C. C., & Reeves, W. B. (2007). Cisplatin-induced nephrotoxicity is mediated by tumor necrosis factor-alpha produced by renal paranchymal cells. Kidney International, 72(1), 37–44. Zinman, B., Hanley, A. J., Harris, S. B., Kwan, J., & Fantus, I. G. (1999). Circulating tumor necrosis factor-alpha concentration in a native Canadian population with high rates of type 2 diabetes mellitus. The Journal of Clinical Endocrinology and Metabolism, 84(1), 272–278.
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Association of biomarkers of inflammation and oxidative stress with the risk of chronic kidney disease in Type 2 diabetes mellitus in North Indian population☆ Stuti Gupta, Jasvinder K. Gambhir ⁎, OP Kalra, Amar Gautam, Kirtikar Shukla, Mohit Mehndiratta, Sunil Agarwal, Rimi Shukla Departments of Biochemistry and Medicine, University College of Medical Sciences (University of Delhi) & GTB Hospital, Delhi, 110095 India
a r t i c l e
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Article history: Received 15 April 2013 Received in revised form 11 July 2013 Accepted 21 July 2013 Available online 6 September 2013 Keywords: Chronic kidney disease Type 2 DM Oxidative stress Inflammation
a b s t r a c t Chronic kidney disease (CKD) is a major cause of morbidity and mortality worldwide. It results from diverse etiologies, diabetes being a frontrunner amongst them. Type 2 diabetes mellitus (DM) is being increasingly recognized as a proinflammatory state with increased oxidative stress which enormously increases the risk of micro and macro vascular diseases. This study was planned to explore the possible association between tumor necrosis factor-alpha (TNF-α), urinary monocyte chemoattractant protein-1 (uMCP-1), highsensitivity C-reactive protein (hsCRP) and parameters of oxidative stress in patients with Type 2 diabetes mellitus (DM) and diabetic chronic kidney disease (DM–CKD). Fifty patients each were recruited in DM, DM–CKD and healthy control groups. Plasma TNF-α, hsCRP and uMCP-1 levels as inflammatory mediators were measured by ELISA, reduced glutathione (GSH), ferric reducing ability of plasma (FRAP) as parameters of antioxidant activity and malondialdehyde (MDA) as marker of oxidative stress, were measured spectrophotometrically. Plasma TNF-α, hsCRP and uMCP-1 were significantly higher in DM–CKD compared to DM and healthy controls. Lipid peroxidation, measured as MDA was significantly higher in patients with DM–CKD as compared to patients with DM and healthy controls. Further, antioxidant capacity of blood measured as FRAP and GSH was found to be significantly lower in patients with DM and DM–CKD as compared to healthy controls (p b 0.001). Plasma TNF-α and uMCP-1 showed a significant positive correlation with HbA1c (r = 0.441, 0.643), hsCRP (r = 0.400, 0.584) and MDA (r = 0.423, 0.759) and significant negative correlation with GSH (R = − 0.370, − 0.800) and FRAP (r = − 0.344, − 0.684) Increased inflammatory markers viz. TNF-α, hsCRP and uMCP-1 and markers of oxidative stress i.e. increased MDA and decreased GSH and FRAP in DM–CKD suggest an important role of inflammation and oxidative stress in the pathogenesis of renal damage in diabetic patients. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Type 2 diabetes mellitus (T2DM) is one of the most challenging health concerns of the 21st century. T2DM is a proinflammatory state with increased oxidative stress, predisposing the patients to macroand micro-vascular complications. Diabetic nephropathy (DN), a microvascular complication of long term uncontrolled DM is the single most frequent cause of end-stage renal disease (ESRD) (Ritz, Rychlik, Locatelli, & Halimi, 1999), accounting for approximately 40% of new cases of ESRD every year (Kramer & Molitch, 2005). Although metabolic and hemodynamic alterations are considered the main cause of renal damage in diabetes, the accumulating
☆ Declaration of interest: The authors alone are responsible for the content and writing of the paper and there is no conflict of interest. ⁎ Corresponding author. Tel.: +91 9811641277. E-mail address: [email protected] (J.K. Gambhir). 1056-8727/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jdiacomp.2013.07.005
evidence now indicates that immunologic and inflammatory mechanisms also play a significant role in its development and progression (Tuttle, 2005; Mora & Navarro, 2006). Diabetics have been shown to produce excessive inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and C-reactive protein (CRP) (Zinman, Hanley, Harris, Kwan, & Fantus, 1999), and few studies have also reported association between inflammatory biomarkers and DN (Navarro, Mora, Muros, & García, 2006; Yeo, Hwang, Park, Choi, Huh, & Kim, 2010; Lu, Randell, Han, Adeli, Krahn, & Meng, 2011; Taslipinar et al., 2011; Fernández-Real, Vendrell, García, Ricart, & Vallès, 2012). Most attention has been focused on the role of TNF-α, which is a pleiotropic proinflammatory cytokine primarily synthesized by monocytes, macrophages and T cells and plays an important role in pathogenesis of DN. Many studies in animal models have shown that intrinsic renal cells, including glomerular, mesangial, endothelial and tubular cells, are also able to produce this cytokine (Jevnikar et al., 1991; Nakamura et al., 1993; Sugimoto, Shikata, Wada, Horiuchi, & Makino, 1999; Dong, Swaminathan, Bachman, Croatt, Nath, & Griffin, 2007; Zhang,
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Ramesh, Norbury, & Reeves, 2007). TNF-α is not only cytotoxic to renal cells (Bertani et al., 1989), but also induces the production of reactive oxygen species (ROS) in diverse cells, including mesangial cells (Raedke, Meier, Topley, Fluge, Habermehl, & Resch, 1990). C-reactive protein (CRP), a member of pentatraxin family is the prototypic marker of inflammation which has been reported to be associated with T2DM and early stages of nephropathy, however its association with DN is not completely understood (Navarro, Mora, Macia, & Garcia, 2003; Navarro et al., 2006; Navarro-González & Mora-Fernandez, 2008). Recent evidence has highlighted the production of monocyte chemoattractant protein-1 (MCP-1) by diabetic kidneys as a major promoter of inflammation, renal injury and fibrosis in diabetic nephropathy (Tesch, 2008). Urinary levels of MCP-1 (uMCP-1) closely reflect kidney MCP-1 production and correlate significantly with levels of albuminuria, serum glycated albumin, urine N-acetylglucosaminidase (NAG) and kidney CD68+ macrophages in human and experimental diabetic nephropathy (Furuta et al., 1993; Gu, Tseng, & Rollins, 1999; Chow, Ozols, Nikolic-Paterson, Atkins, Tesch, et al., 2004). Accumulating evidence, both experimental and clinical, has suggested that there is a close link between hyperglycemia, oxidative stress, inflammation and diabetic complications including nephropathy (Pan et al., 2010). ROS have been shown to cause renal damage via vasoconstriction, vascular smooth muscle cell growth and migration, endothelial dysfunction, modification of extracellular matrix proteins and increased renal tubular reabsorption. Oxidative stress may also be implicated in promoting a low grade systemic inflammation in patients with T2DM (Amalich et al., 2000). Activation of nuclear factor-kappa B (NF-κB) through oxidative stress induced by hyperglycemia increases the concentration of proinflammatory cytokines (Esposito et al., 2002). A study has shown that elevation of TNF-α in turn increases oxidative stress leading to renal injury in streptozotocin induced diabetes in rats (Kuhad & Chopra, 2009). In spite of improvement in our knowledge on DN, from a pathophysiologic point of view, the intricate mechanisms in chronic hyperglycemia leading to the development of renal injury are complex and not yet fully understood. Previous reported studies have not included both inflammatory biomarkers and oxidant– antioxidant parameters in a single setting, in addition, no association between uMCP-1, a marker of renal injury in DN and other parameters has been shown in the aforementioned studies. Therefore, the present work aims to evaluate inflammatory cytokines (TNF-α), inflammatory chemokine (MCP-1), inflammatory marker (hsCRP) and oxidant– antioxidant status in order to investigate the relationship between inflammation and oxidative stress in patients with DN. 2. Methodology 2.1. Subjects The present study included 150 subjects attending Medicine OPD/ Nephrology Outpatient Clinic at the University College of Medical Sciences and Guru Teg Bahadur Hospital, Delhi. The subjects were divided into 3 groups (n = 50) viz; Group I: healthy controls (HC), Group II: patients with Type 2 diabetes mellitus without nephropathy (DM), Group III: patients with Type 2 diabetes mellitus with nephropathy (DM–CKD). Healthy subjects with systolic and diastolic blood pressure 120 mm Hg and 80 mm Hg respectively, and fasting and postprandial plasma glucose less than 100 ml/dL and 140 ml/dL were recruited as controls from volunteers and staff of UCMS and GTB Hospital. Diagnosis of T2DM was made according to revised American Diabetes Association criteria (American diabetic association, 2012). All diabetic subjects with retinopathy and dipstick positive proteinuria and microalbuminuria were clustered in group III. All patients in group III were in pre-dialysis stage. The sensitivity of the dipstick “Urine Test 11 MAU” from Piramal Diagnostic, India is 10–15 mg/dL.
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Further spot urine samples were analyzed for urinary albumin creatinine ratio which was 0.40 ± 0.33 in the DM–CKD group. To avoid potential confounding factors, the patients having acute and chronic infections, fever, malignancy, other renal disorders, cirrhosis of liver and congestive heart failure were excluded. All the patients in group III had retinopathy however patients with macrovascular complications like stroke and CAD were excluded. Patients who were on inhibitors of renin–angiotensin aldosterone system, aspirin and vitamin D analogues were advised to stop these drugs for one week before inclusion in the study. The protocol of this study was approved by the Institutional Ethics Committee for Human Research and informed written consent was taken from all the participants. 2.2. Methods Relevant clinical history and physical examination were recorded. Arterial blood pressure was measured using mercury sphygmomanometer with the patient in the sitting position after 5 min of rest. The glomerular filtration rate was estimated by ‘Modification of Diet in Renal Disease Abbreviated Equation (MDRD)’: [eGFR = 186 × (plasma Cr) −1.154 × (age) −0.203 × (0.742 if female) × (1.210 if African American) (Levey, Bosch, Lewis, Greene, Rogers, & Roth, 1999). Fasting blood sample was withdrawn from ante-cubital vein under aseptic precautions and collected into vacutainers containing salts of fluoride & oxalate for plasma glucose and EDTA vials for various other parameters. For estimation of reduced glutathione 200 μL of whole blood was used and estimated immediately after collection of sample. For glycosylated hemoglobin 200 μL whole blood was kept as aliquot at 4°C–8°C and estimation was carried out within 1 week of collection. Rest of the EDTA blood sample was subjected to centrifugation at 3000 rpm for 10 min to separate the plasma. GST, MDA and FRAP were estimated from plasma immediately after collection. Remaining plasma was stored in aliquots at − 80°C till further use for the estimation of TNF-α and hsCRP. Random mid-stream urine sample was collected for the estimation of the MCP-1 and albumin. Reduced glutathione (GSH) was estimated by the method of Tietze (1969) and the antioxidant capacity of blood was measured as ferric reducing ability of plasma (FRAP) by the method of Benzie and Strain (1996). Plasma malondialdehyde (MDA) was measured according to the method of Satoh (1978). Glycosylated hemoglobin (HbA1C) was measured by ion-exchange resin chromatography using commercially available kits (Fortress, UK). Plasma and urine samples were stored at − 80°C until assayed by ELISA for the measurement of plasma TNF-α (Diaclone, France; sensitivity less than 8 pg/mL), hsCRP (Calbiotech, USA; sensitivity less than 0.005 mg/mL) and uMCP-1 (Weldon, California; sensitivity less than 7.8125 pg/mL). Routine biochemical parameters were assayed in automated analyzer using commercial kits. All these investigations were carried out once at the time of entry into the study. 2.3. Statistical analysis SPSS-17 software was used for statistical analysis. The results were expressed as mean ± standard deviation (SD). Demographic data and routine biochemical parameters were compared among the subject groups using one-way analysis of variance (ANOVA) followed by posthoc Tukey's test. Pearson's correlation analysis was used to determine correlation between different parameters. The mean difference was considered significant at p b 0.05. 3. Results The baseline demographic characteristics and biochemical parameters of both healthy subjects and diabetic groups are shown in Table 1. There were no significant differences between diabetic patients and controls with respect to sex distribution and BMI. The
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Table 1 The baseline demographic characteristics and biochemical parameters in different study groups. Variables
Group I (n = 50)
Group II (n = 50)
Group III (n = 50)
Age (years)
46.0 ± 4.0 (39.6–52.4) 27/23 21.1 ± 1.7 (19.8–23.1) –
56.40 ± 8.5 (46.1–68.2) 26/24 22.1 ± 2.1 (19.2–25.5) 12.6 ± 2.7 (11.8–13.4) 136.0 ± 2.3a (135.3–136.6) 82.6 ± 0.9a (82.3–82.9) 143.5 ± 4.5a (142.3–144.8) 186.7 ± 11.1a (183.5–189.9) 7.3 ± 0.2a (7.2–7.4) 25.7 ± 5.8 (24.1–27.5) 0.95 ± 0.20 (0.89–1.0) 3.4 ± 0.6 (3.2–3.5) 97.4 ± 0.6 (96.5–98.2) –
55.7 ± 8.2 (44.8–65.5) 28/22 22.6 ± 3.4 (19.4–26.1) 9.1 ± 3.3b (8.1–10.1) 136.7 ± 1.8a (136.2–138.2) 82.8 ± 0.8a (82.6–83.1) 187.3 ± 16.2a,b (182.7–191.9) 258.9 ± 31.2a,b (250.1–267.8) 8.1 ± 0.2a,b (8.1–8.2) 91.5 ± 24.8a,b (84.5–98.6) 3.6 ± 1.5a,b (3.24–4.10) 8.5 ± 0.7a,b (8.3–8.7) 56.2 ± 0.9b (55.1–57.9) 0.40 ± 0.33 (0.37–0.49)
Gender (M/F) BMI (kg/m2) Duration of DM (years) SBP (mm Hg) DBP (mm Hg) Fasting glucose (mg/dL) Postprandial glucose (mg/dL) HbA1c (%) Urea (mg/dL) Creatinine (mg/dL) Uric acid (mg/dL) eGFR (mL/min/1.73 m2) Urinary albumin/creatinine
120.1 ± 1.5 (119.7–120.5) 79.2 ± 0.9 (78.9–79.4) 85.4 ± 5.9 (83.6–87.1) 108.2 ± 8.4 (105.8–110.6) 5.2 ± 0.4 (5.0–5.3) 24.5 ± 5.9 (22.8–26.3) 0.85 ± 0.13 (0.81–0.90) 4.6 ± 1.2 (4.2–4.9) 98.1 ± 0.7 (97.3–99.4) –
Data are expressed as mean ± SD. Group I: Healthy control; Group II: Diabetes mellitus without nephropathy; Group III: Diabetic nephropathy. BMI: Body mass index; SBP and DBP: Systolic and diastolic blood pressure; eGFR: estimated glomerular filtration rate. a Significantly different from healthy control at p b 0.001. b Significantly different from diabetic patients without nephropathy at p b 0.001.
patients with diabetes (DM and DM–CKD) were older than healthy controls. Duration of diabetes was longer in DM than DM–CKD group. Significantly higher SBP and DBP were observed in diabetic patients with and without DN (p b 0.001) as compared to healthy controls. Fasting, postprandial plasma glucose and HbA1c were significantly higher (p b 0.001) in DM–CKD as compared to DM. Levels of creatinine, urea, and uric acid were significantly higher (p b 0.001) and estimated glomerular filtration rate (eGFR) was lower (p b 0.001) in DM–CKD as compared to DM group. Table 2 shows levels of inflammatory markers in various study groups. Plasma TNF-α, hsCRP and urinary MCP-1 were significantly higher in DM–CKD cases as compared to DM and HC (p b 0.001). Various oxidative stress parameters in different study groups are shown in Table 3. Antioxidant parameters like reduced GSH and FRAP
Table 2 Plasma levels of inflammatory markers in various study groups. Parameters
Group I (n = 50)
Group II (n = 50)
Group III (n = 50)
TNF-α (pg/mL)
14.5 ± 5.2 (13.1–16.1) 0.74 ± 0.46 (0.61–0.88) 124.1 ± 46.6 (76.3–171.7)
15.3 ± 3.7 (14.3–16.4) 3.6 ± 1.5a (3.3–4.1) 278.5 ± 125.0 (153.1–400.8)
20.6 ± 3.9a,b (19.5–21.8) 8.5 ± 1.7a,b (8.0–9.0) 5632.7 ± 2275.8a,b (3351.5–8001.2)
hsCRP (mg/L) uMCP-1 (pg/mg creatinine)
Data are expressed as mean ± SD. Group I: Healthy control; Group II: Diabetes mellitus without nephropathy; Group III: Diabetic nephropathy. a Significantly different from healthy control at p b 0.001. b Significantly different from diabetic patients without nephropathy at p b 0.001.
Table 3 Plasma levels of oxidative stress markers in various study groups. Parameters
Group I (n = 50)
Group II (n = 50)
Group III (n = 50)
GSH (mg/g Hb)
3.37 ± 0.35 (3.20–3.50) 1.48 ± 0.20 (1.40–1.50) 549.6 ± 49.1 (535.6–563.6)
1.89 ± 0.06a,c (1.70–1.80) 2.60 ± 0.35a (2.50–2.70) 409.0 ± 55.1a,c (399.5–451.8)
0.90 ± 0.01a (0.97–0.98) 5.14 ± 0.39a,b (5.00–5.20) 170.7 ± 142.3a (166.6–231.4)
MDA (nmol/mL) FRAP (μmol/L)
Data are expressed as mean ± SD. Group I: Healthy control; Group II: Diabetes mellitus without nephropathy; Group III: Diabetic nephropathy. a Significantly different from healthy control at p b 0.001. b Significantly different from diabetic patients without nephropathy at p b 0.001. c Significantly different from diabetic patients with nephropathy at p b 0.001.
were lower in DM and DM–CKD cases as compared to HC and maximum depletion of antioxidants was seen in DM–CKD which were significantly lower (p b 0.001) when compared to DM cases. On the other hand, oxidant stress parameter like MDA was raised in DM and DM–CKD groups when compared to HC; however maximum increase was noticed in patients with DM–CKD when compared to patients with DM (p b 0.001) indicating higher oxidative stress in DM–CKD vs DM patients. As shown in Table 4, when all the subjects were grouped together, there was a positive correlation between plasma TNF- α levels and hsCRP (r = 0.400; p b 0.01) and uMCP-1 (r = 0.508; p b 0.01). TNF-α and uMCP-1 also correlated positively with HbA1c (r = 0.441, 0. 643; p b 0.01), however, negative association was observed between TNF-α and antioxidant parameters i.e. GSH and FRAP (r = −0.370, − 0.344; p b 0.01) while a positive association was noticed between TNF-α and MDA levels (r = 0.423; p b 0.01). Similarly uMCP-1 also correlated positively with hsCRP (r = 0.584; p b 0.01) and MDA respectively (r = 0.759; p b 0.01) whereas it correlated negatively with GSH and FRAP (r = − 0.800, − 0.684; p b 0.01). However, this correlation lost significance when calculated in individual groups, probably due to the small sample size, though similar trend was maintained. 4. Discussion Diabetic nephropathy (DN) is a major cause of ESRD in developing countries. Historically, T2DM was not thought to be an immune disease; however there is growing evidence supporting the fact that innate immunity and inflammation are essential contributing factors in the development of renal injury in diabetics (Mora & Navarro, 2005). The current study is the first comprehensive work which highlights the relationship between various markers of inflammation and oxidative stress and DN. Results from our data reveal that plasma levels of TNF-α and hsCRP were significantly higher in patients with diabetes and more so in patients with diabetic nephropathy. These findings are consistent with a previous study which showed that high concentrations of
Table 4 Correlation analysis between inflammatory biomarkers, oxidative stress parameters and other baseline investigations. (all subjects were grouped together). Parameters
TNF-α (r)
uMCP-1 (r)
p value
HbA1c uMCP-1 hsCRP GSH FRAP MDA
0.441 0.508 0.400 −0.370 −0.344 0.423
0.643 1.000 0.584 −0.800 −0.684 0.759
p p p p p p
b b b b b b
0.01 0.001 0.001 0.001 0.001 0.001
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TNF-α and CRP may be risk factors for CKD in Korean patients with T2DM (Yeo et al., 2010). Similarly, a significant association between serum TNF-α and hsCRP in patients with DN has been reported in a study (Navarro et al., 2003). On the other hand, Lin, Hu, Rimm, Rifai, and Curhan (2006) observed that no correlation existed between CRP levels and DN (GFR b60 mL/min/1.73 m 2) (Lin et al., 2006). It has been reported that CRP is associated with glomerular and tubulointerstitial damage in patients with DN (Rivero, Mora, Muros, García, Herrera, & Navarro-González, 2009). The exact mechanism how hsCRP causes renal damage is not completely understood, however a recent study has shown that CRP inhibits endothelial nitric oxide synthase (eNOS) activity by uncoupling (Singh, Devaraj, VasquezVivar, & Jialal, 2007) and leads to endothelial dysfunction in vivo and promotes hypertension which could be a possible mechanism damaging kidney endothelium. uMCP-1 is a potential marker of kidney disease in diabetes and in the present study its levels were highest in patients with DN. Previous experimental studies support our findings that MCP1 plays a crucial role in the progression of diabetic renal injury and uMCP-1 levels reflect the renal injury in diabetes (Kanamori et al., 2007). Hasegawa et al. (1991) have shown that there is good relationship between low grade inflammation and DN in patients with T2DM. Our study further confirms the role of inflammation in the etiopathogenesis of kidney disease in diabetes mellitus. It is well known that hyperglycemia is the causative factor leading to increased production of ROS which may ultimately cause diabetic complications including DN causing increased availability of glycolytic intermediates causing their diversion into other pathways such as polyol pathway, hexosamine pathway, protein kinase C (PKC) pathway and advanced glycation end (AGE) products pathway (Brownlee, 2001). Each of these different pathogenic mechanisms reflects a single hyperglycemia-induced process i.e. overproduction of superoxide by the mitochondrial electron-transport chain. It has also been proposed that reduction of glucose to sorbitol consumes NADPH which is required for regenerating reduced glutathione (GSH), and this could induce or exacerbate intracellular oxidative stress (Brownlee, 2001). Similar results were observed in the present study that antioxidant parameters i.e. reduced GSH, FRAP were maximally decreased and oxidative parameter i.e. MDA was increased in diabetic patients with nephropathy. Our results are in agreement with the study by Kumawat, Pahwa, Gahlaut, and Singh (2009) which showed that there was a significant decrease in reduced GSH and increase in MDA levels in diabetic patients with microvascular complications. A similar study by Kavitha, Ramani, Dhass, and Aruna (2011) showed that levels of MDA were increased and FRAP levels were decreased in patients with DN. Clinical studies correlating both inflammatory markers and oxidative stress together in the pathogenesis of DN are scarce. Few studies have supported the fact that TNF-α is produced by adipose tissue (Trayhurn & Wood, 2005), however in the present study there was no significant difference in BMI between different groups of diabetic patients. Probably the interaction between genetic and environmental factors may result in an inflammatory milieu, eventually leading to synthesis of TNF-α by immune cells and renal cells. Our results also put forward a significant positive correlation between TNF-α, hsCRP and uMCP-1 suggesting that these inflammatory cytokines seem to have a crucial role in the pathogenesis of diabetic nephropathy. Previous studies have shown that TNF-α induces hsCRP synthesis mainly by hepatocytes (McNair et al., 2010). On the other hand, recently Liu, Liu, Ji, Lu, Wang, and Guo (2011) have shown that CRP induces TNF-α via p38MAPK-TLR4 signaling pathway in smooth muscle of rats (Liu et al., 2011). Bain, Elner, Yoshida, and Elner (2004) have reported that TNF-α increases MCP-1 expression via phosphoinositide 3-kinase (PI3K)/AKT signaling pathway. A previous study showed that plasma MCP-1 is positively correlated with MDA in Type 1 diabetics with renal damage (Chiarelli
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et al., 2002), but experimental studies showing association between uMCP-1 and oxidative stress in T2DM with nephropathy are scanty, however our study is the first to demonstrate that uMCP-1 is correlated positively with MDA and negatively with GSH and FRAP. In a previous study Prasad (2004) has reported that CRP increases ROS production by neutrophils, therefore plasma hsCRP might be playing an important role in the pathogenesis of DN and may be a potential risk factor for the development of DN. 5. Conclusions Our study has suggested that increased levels of inflammatory mediators i.e. TNF-α, hsCRP and uMCP-1 may play an independent as well as interdependent role, which via several signaling pathways contributes to hyperglycemia mediated increase in oxidative stress. An increase in oxidative stress may further amplify inflammation, thus setting up a vicious cycle. Therefore, inflammation interlinked with oxidative stress may be major mechanisms in the pathogenesis and progression of nephropathy in susceptible diabetic patients. However, there is a need to carry out these studies in a larger sample size. Acknowledgment We sincerely thank Indian Council of Medical Research and University college of medical sciences, New Delhi for providing partial funding for this study. The authors are also thankful to the Department of Biostatistics and Medical Informatics, University College of Medical Sciences, Delhi for statistical analysis. References Amalich, F., Hernanz, A., Lopez- Maderuelo, D., Pena, J. M., Camacho, J., Madero, R., et al. (2000). Enhanced acute phase response and oxidative stress in older adults with type II diabetes. Hormone and Metabolic Research, 32(10), 407–412. American diabetic association. (2012). Expert committee on the diagnosis and classification of diabetes mellitus. Report. Diabetic Care, 35, S1–S10. Bain, Z. M., Elner, S. G., Yoshida, A., & Elner, V. M. (2004). Differential involvement of phosphoinositide 3-kinase/Akt in human RPE MCP-1 and IL-8 expression. Investigative Ophthalmology & Visual Science, 45(6), 1887–1896. Benzie, I. F., & Strain, J. J. (1996). The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: The FRAP assay. Analytical Biochemistry, 239(1), 70–76. Bertani, T., Abbate, M., Zoja, C., Coma, D., Perico, N., Ghezzi, P., et al. (1989). Tumor necrosis factor induces glomerular damage in rabbit. The American Journal of Pathology, 134(2), 419–430. Brownlee, M. (2001). Biochemistry and molecular cell biology of diabetic complications. Nature, 414(6865), 813–820. Chiarelli, F., Cipollone, F., Mohn, A., Marini, M., Iezzi, A., Fazia, M., et al. (2002). Circulating monocyte chemoattractant protein-1 and early development of nephropathy in type 1 diabetes. Diabetes Care, 25(10), 1829–1834. Chow, F., Ozols, E., Nikolic-Paterson, D. J., Atkins, R. C., Tesch, G. H., et al. (2004). Macrophages in mouse type 2 diabetic nephropathy: Correlation with diabetic state and progressive renal injury. Kidney International, 65(1), 116–128. Dong, X., Swaminathan, S., Bachman, L. A., Croatt, A. J., Nath, K. A., & Griffin, M. D. (2007). Resident dendritic cells are the predominant TNF-secreting cell in early renal ischemia–reperfusion injury. Kidney International, 71(7), 619–628. Esposito, K., Nappo, F., Marfella, R., Giugliano, G., Giugliano, F., Camacho, M., et al. (2002). Inflammatory cytokine concentrations are acutely increased by hyperglycemia in humans: Role of oxidative stress. Circulation, 106(16), 2067–2072. Fernández-Real, J. M., Vendrell, J., García, I., Ricart, W., & Vallès, M. (2012). Structural damage in diabetic nephropathy is associated with TNF-α system activity. Acta Diabetologica, 49(4), 301–305. Furuta, T., Saito, T., Ootaka, T., Soma, J., Obara, K., Abe, K., et al. (1993). The role of macrophages in diabetic glomeruosclerosis. American Journal of Kidney Disease, 21(5), 480–485. Gu, L., Tseng, S. C., & Rollins, B. J. (1999). Monocytes chemoattractant protein-1. Chemical Immunology, 72, 7–29. Hasegawa, G., Nakano, K., Sawada, M., Uno, K., Shibayama, Y., Ienaga, K., et al. (1991). Possible role of tumor necrosis factor and interleukin-1 in the development of diabetic nephropathy. Kidney International, 40(6), 1007–1012. Jevnikar, A. M., Brennan, D. C., Singer, G. G., Heng, J. E., Ivlaslinski, W., Wuthrich, R. P., et al. (1991). Stimulated kidney tubular epithelial cells express membrane associated and secreted TNF alpha. Kidney International, 40(2), 203–211. Kanamori, H., Matsubara, T., Mima, A., Sumi, E., Nagai, K., Takahashi, T., et al. (2007). Inhibition of MCP-1/CCR2 pathway ameliorates the development of diabetic nephropathy. Biochemical and Biophysical Research Communications, 360(4), 772–777.
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