The present study was conducted in the Department of Biochemistry, Sri Venkateswara Institute of Medical Sciences (SVIMS), Tirupati, Andhra Pradesh, India. All subjects were informed about the study and written informed consent was obtained from the patients enrolled. The study was approved by the Institutional ethical committee (IEC).

Patients attending the Department of Nephrology, SVIMS hospital, with established diagnosis of CKD were subjects of the study. A total of (n=120) CKD patients were included in the study. Patients were classified into three groups based on glomerular filtration rate (GFR) calculated from serum creatinine, using Cockcroft-Gault (CG) equation. Group I (n=40) consists of patients with mild kidney damage with a GFR between 60 and 119 ml/min/1.73m² (stage I, II CKD). Group II (n=40) consists of patients with moderate to severe kidney damage and GFR between 15 and 59 ml/min/1.73m² (stage III, IV CKD). Group III (n=40) consists of patients with ESRD (stage V CKD) patients with GFR <15 ml/min/1.73m². Forty healthy subjects served as controls. Adult patients with stage I-V CKD were included. Patients undergoing haemodialysis, peritoneal dialysis, patients with organ transplantation, with active or chronic infections, using anti-inflammatory or immunosuppressive drugs and of paediatric age group were excluded.

Following an overnight fasting, 5ml of blood samples were drawn from the ante cubital vein of all the study subjects. Two (2) ml of blood drawn was transferred into a plain tube and 3ml was transferred into heparinized tubes. The plain tube samples were allowed to stand for 30 min, centrifuged at 3000 rpm for 15 minutes and the serum was separated. The heparinized tube samples were centrifuged immediately and the plasma was separated. The serum, plasma and haemolysate samples were aliquoted and stored in separate vials at -80⁰C in deep freezer (Thermo Fischer Scientific) until analysis. Plasma was used for the estimations of adiponectin, leptin, IL-6, IL-10, TNF-α, high sensitivity C-reactive protein (hsCRP) and NO. Serum samples were used for estimations of urea and creatinine.

Demographic characteristics, metabolic factors and laboratory data were collected. Biochemical analysis which includes adipokines and cytokines such as adiponectin, leptin, IL-10, IL-6 and TNF-α was done by solid phase sandwich Enzyme Linked Immunosorbent Assay (ELISA) technique using ELISA commercial test kits purchased for human adiponectin, leptin, IL-10, from AviBion (Orgenium Laboratories Division, Vantaa, FINLAND), human Interleukin-6 (DIA Source, Belgium), human TNF-α (Assay Pro, Belgium) on Chemwell fully automated analyser. The level of hsCRP was estimated by Immunoturbidimetry method using commercial kit on Beckman Synchron DxC 600 fully automated analyser, USA. NO was estimated as nitrates on UV/VIS spectrophotometer, USA using Griess reaction [14].

All the analysis was performed using statistical software, SPSS software for Windows 11.5 program (SPSS Inc, Chicago, IL, USA). Comparisons of means between controls and CKD patients were analysed using nonparametric Mann-Whitney test. Comparisons of means among CKD stages were analysed using nonparametric one-way analysis of variance (ANOVA), Kruskalwallis test. Correlation among the variables in CKD patients was performed using Spearman’s rank correlation. Contribution of ED in CKD patients was performed using simple univariate linear regression analysis. A p-value of less than 0.05 was considered as statistically significant.

The base-line and biochemical characteristics of controls and CKD patients studied were shown in [Table/Fig-1]. Among the 120 patients, 86 (71.66%) were males and 34 (28.33%) were females. Co-morbidity conditions included 63 (52.5%) patients with diabetic nephropathy, 18 (15.0%) patients with chronic glomerulo nephritis, 27 (22.5%) patients with chronic interstitial nephritis, 09 (7.5%) patients with hypertensive nephropathy and 03 (2.5%) patients with other conditions. There was an increase in urea, creatinine and decrease in eGFR levels in CKD patients. No change in BMI was observed between controls and CKD patients.

The levels were assessed between controls and CKD patients and are presented in [Table/Fig-2]. Adiponectin and NO were significantly lower whereas, IL-6, IL-6/IL-10 ratio and hsCRP were higher in CKD patients when compared to control group. The changes observed among CKD patients from group I to group III are shown in [Table/Fig-3]. Adiponectin, leptin, IL-6, IL-6/IL-10 ratio and TNF-α were significantly increased whereas IL-10 levels were significantly decreased across the three groups of CKD. Although hsCRP was increased and NO was decreased, the difference was not statistically significant.

The associations observed among the parameters studied are presented in [Tables/Fig-4,5]. In CKD patients, adiponectin showed a significant positive correlation with leptin (r=+0.207; p=0.027, IL-6 (r=+0.449; p<0.001), IL-6/IL-10 ratio (r=+0.612; p<0.001) and a significant negative correlation with IL-10 (r=-0.480; p<0.001). Leptin showed a significant positive correlation with IL-6 (r=+0.357; p<0.001), and IL-6/IL-10 ratio (r=+0.329; p=0.001). IL-6 showed a significant positive correlation with TNF-α (r=+0.374; p<0.001), IL-6/IL-10 ratio (r=+0.872; p<0.001) and a significant negative correlation with IL-10 (r=-0.327; p=0.001) and NO (r=-0.557; p=0.005). TNF-α showed a significant positive correlation with IL-6/IL-10 ratio (r=+0.368; p<0.001). Creatinine had a significant positive correlation with adiponectin (r=+0.649; p<0.001), leptin (r=+0.222; p=0.017), IL-6 (r=+0.553; p<0.001), TNF-α (r=+0.262; p=0.006), IL-6/IL-10 ratio (r=+0.736; p=0.017) and negative correlation with IL-10 (r=-0.562; p<0.001).

Univariate linear regression analysis to assess the principal determinants of ED showed that IL-6 (β=-0.038; p=0.002), was independently associated with ED [Table/Fig-6]. Other adipokines adiponectin, leptin, IL-10 and TNF-α were not associated with ED. Also, there was no significant association between inflammatory marker hsCRP and ED marker NO (p=0.514).

In the present study, adiponectin levels were significantly lower in CKD patients than healthy controls (p=0.037). However, the levels were significantly elevated as the renal function deteriorates and the levels were higher in group III (stage V). A possible explanation for this can be decreased renal adiponectin clearance in patients with CKD [10,15–17]. Further, adiponectin directly correlated with serum creatinine (r=0.649; p<0.001), in CKD patients which indicates an increase in adiponectin with decreasing renal function. In the present study, adiponectin showed a positive correlation with leptin, IL-6 and TNF-α in CKD patients (r=0.207; p=0.027, r=0.449; p<0.001 and r=0.305; p=0.001) and thus, it is possible that adiponectin may play a compensatory role in the presence of an inflammatory milieu as an anti-inflammatory factor [17,18].

Similarly, a significant increase in leptin was observed in comparison with preceding group in CKD patients and the levels were higher in group III (p<0.001). Leptin is cleared by kidney. Increased levels in CKD patients (p=0.004) may be due to deficient renal metabolism and also possibly by increased leptin production which in turn may result from increased IL-6 and TNF-α levels in the state of enhanced systemic inflammatory milieu [19,20]. In the present study, leptin was positively correlated with increased IL-6 and IL-6/IL-10 ratio (r=0.357; p<0.001; r=0.329; p<0.001) in CKD patients, suggesting that inflammation and hyperleptinaemia are associated in CKD [21].

In the present study, IL-6 was significantly elevated in CKD patients compared to healthy controls (p<0.001). Also, IL-6 was significantly higher in group III (stage V) compared to group I (stage I&II) and II (stage III&IV) CKD patients. Similarly, TNF-α levels were elevated in group III (stage V) CKD patients compared to group I (stage I&II) and II (stage III&IV) (p<0.001). These observations are in agreement with previous reports [2,13,16,22–24]. The elevated plasma IL-6 and TNF-α level in CKD patients may be related to loss of kidney function, and activated monocytes and macrophages [11]. Further, it is possible that an increased IL-6 production is an early response to renal disease rather than a mere accumulation phenomenon attributable to loss of renal function [24]. Both IL-6 and TNF-α were directly correlated with serum creatinine (r=0.553; p<0.001 and r=0.262; p=0.006), indicating that reduced GFR could lead to their defective clearance from the plasma [22]. A strong positive correlation between IL-6 and TNF-α was observed (r=0.374; p<0.001). This indicates both could be responsible for production of each other [23].

The levels of IL-10 were increased in CKD patients compared to controls. In contrast to the above result, in CKD patients, there was a decrease in IL-10 levels from group I to group III CKD patients and the levels were significant in comparison with preceding group (p<0.001). A significant negative correlation of IL-10 with IL-6 and IL-6/IL-10 ratio was observed in CKD patients (r=-0.327; p=0.001 and r=-0.722; p<0.001) Further, a significant negative correlation with renal function (serum creatinine) was observed in CKD patients (r=-0.562; p<0.001). These findings suggest that beneficial effects of IL-10 plasma levels are restricted in patients with CKD by elevated plasma levels of IL-6, TNF-α and hsCRP, which is an indication of an enhanced systemic inflammatory response [25].

The IL-6/IL-10 ratio may reflect a proinflammatory/anti-inflammatory balance. Therefore, we examined IL-6/IL-10 ratio in CKD patients and found that there was a significant increase in CKD patients compared to controls (p=0.002). Moreover, the IL-6/IL-10 ratio significantly increased among the CKD patients with progression of disease (p<0.001) indicating a systemic pro-inflammatory state in these patients. The altered IL-6/IL-10 ratio in CKD patients may be due to decreased IL-10 secretion, especially at high CRP levels observed thereby, accentuating the inflammatory process by inhibiting IL-10 and stimulating IL-6, TNF-α [26].

In the present study, the inflammation was assessed by hsCRP which was significantly increased in CKD patients when compared to controls (p<0.001). A similar observation has been reported previously [19,27]. Circulating hsCRP levels elevated in CKD patients may be due to renal function deterioration as well as increase in IL-6 which stimulates production of CRP in the liver [5]. However, there was no change among the three CKD groups. This could be due to that CRP levels fluctuate over time, being mainly influenced by co-morbidity and subclinical infections [28].

In the present study, ED was analysed by estimating plasma NO levels. In accordance with the earlier reports [29–31] in the present study also, NO levels were significantly lower in CKD patients than controls (p<0.001). NO is decreased in renal disease due to impaired endothelial and renal NO production. Many mechanisms are likely to be responsible, including substrate limitation due to decreased renal synthesis of L-arginine, utilization by arginase, and loss of renal NO production due to reduced renal neuronal NO synthase α (nNOS-α) activity [32]. However, no significant change was observed among the CKD groups. This decline in NO can lead to elevated levels of proinflammatory components (IL-6 and TNF-α) in CKD resulting in attenuated prothrombotic potential of endothelial cells which may lead to the development of ED [33].

In the present study, adiponectin, leptin, IL-10 and TNF-α did not show significant correlation with NO which is contrary to our expectations.

A negative correlation of IL-6 with NO was observed in group III (stage V CKD) (r=-0.557; p=0.005). Further, in regression analysis also IL-6 was independently associated with NO in CKD patients, which implies adipokines may contribute to ED in CKD.

Apart from adipokines, inflammatory marker hsCRP showed a negative correlation with NO in group II (stage III, IV) and group III (stage V) CKD patients (r=-0.422; p=0.057 and r=-0.411; p=0.051). This supports a direct role of pro inflammatory state in the development of ED [34].

In conclusion, the present study demonstrates that, CKD leads to the abnormal concentration change of adipokines due to renal function deterioration. The concentration changes were more pronounced at advanced stages of CKD compared with earlier stages of CKD. There is a substantial increase in inflammation and a pro inflammatory/anti-inflammatory imbalance from initial stages to advanced stages of CKD. The ED was accelerated from earlier to final stages of CKD. Moreover, a significant association was observed for adipokines with inflammation and ED in CKD patients. Thus, CKD leads to disruption in levels for adipokines which in association with an exaggerated inflammation may contribute to the ED and an excess of CV risk in pre dialysis patients from initial to advanced stages of CKD.