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NDT Advance Access published online on March 29, 2007
Nephrology Dialysis Transplantation, doi:10.1093/ndt/gfm067
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Glycated haemoglobin levels are related to chronic subclinical inflammation in renal transplant recipients without pre-existing or new onset diabetes

Esteban Porrini1,2, Maribel Diaz Gomez3, Alejandra Alvarez1, Marian Cobo1, Jose Manuel Gonzalez-Posada1, Lourdes Perez1, Luis Hortal4, José J. García5, María Dolores Checa6, Adelaida Morales7, Domingo Hernández1 and Armando Torres1,2

1Research Unit, Hospital Universitario de Canarias, University of La Laguna, Tenerife, 2Instituto de Investigación Reina Sofía, 3Laboratory Section, Hospital Universitario de Canarias, La Laguna, 4Nephrology Section, Hospital Universitario Doctor Negrin, Las Palmas de Gran Canaria, 5Nephrology Section, Hospital Nuestra Señora de La Candelaria, Tenerife, 6Nephrology Section, Hospital Universitario Insular, Las Palmas de Gran Canaria and 7Hospital General de Lanzarote, Lanzarote, Spain

Correspondence and offprint requests to: Armando Torres, Nephrology Section and Research Unit, Hospital Universitario de Canarias, Ofra S/N, 38320, La Laguna, Tenerife, Spain. Email: atorres{at}ull.es



   Abstract
Top
 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgements
 References
 
Background. C-reactive protein (CRP), a marker of chronic subclinical inflammation (CSI), is related to cardiovascular mortality in the general and renal transplant populations. In the general population, high CRP levels are associated with pre-diabetic glucose homeostasis alterations which may contribute to the proatherogenic effect of CSI.

Methods. We studied 134 consecutive renal transplant recipients without pre-existing or new onset diabetes. CRP, oral glucose tolerance test, insulin sensitivity and HbA1c were measured.

Results. Among CRP tertiles, fasting glucose and glucose after 120 min were not different. However, HbA1c was higher (4.9 ± 0.6; 5.2 ± 0.5; 5.4 ± 0.5; P = 0.005] and insulin sensitivity lower (McAuley index: 7.2 ± 2; 6.8 ± 2; 6.2 ± 1.3; P = 0.042) in the third CRP tertile. In addition, HDL-cholesterol was lower and triglycerides and body mass index (BMI) higher in the third tertile. Consequently, metabolic syndrome was more prevalent in the upper CRP tertiles [11 (25%); 19 (43%); 22 (50%); P = 0.01). In multivariate analyses, HbA1c was related to higher CRP levels (standardized ß coefficient = 0.21, P = 0.013), independently of BMI (standardized ß coefficient = 0.24, P = 0.005) and triglycerides (standardized ß coefficient = 0.18; P = 0.03).

Conclusions. Subclinical glucose homeostasis alterations are related to chronic inflammation in renal transplant recipients without pre-existing or new onset diabetes and may contribute to their high cardiovascular mortality.

Keywords: chronic subclinical inflammation; glycated haemoglobin; insulin resistance; new onset diabetes after transplantation (NODAT)



   Introduction
Top
 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 Acknowledgements
 References
 
C-reactive protein (CRP), a reliable marker of chronic subclinical inflammation (CSI), is independently related to cardiovascular mortality in the general population [1] and in stage 3 and 4 chronic kidney disease [2]. Interestingly, pre-diabetic glucose homeostasis alterations are associated with CSI. First, individuals with insulin resistance and metabolic syndrome (MS) show high CRP levels [3,4]. In addition, CRP levels independently predict the future development of type 2 diabetes in population-based studies [5,6]. Finally, increasing HbA1c in non-diabetic individuals is related to higher CRP levels [7]. Thus, associated glucose homeostasis alterations may, at least in part, explain the proatherogenic effect of CSI.

In renal transplant recipients, slightly elevated CRP levels have been demonstrated to be an independent predictor of coronary heart disease and cardiovascular mortality [8–10]. In a recent and large study involving diabetic and non-diabetic patients, abdominal obesity and current smoking but not fasting glucose were the factors independently associated with CRP levels [11]. Although pre-diabetic glucose homeostasis alterations are novel and modifiable cardiovascular risk factors, their association with CRP levels in renal transplant recipients have only been investigated by means of fasting glucose levels [11]. The aim of this study was to investigate whether glucose homeostasis alterations assessed by fasting glucose, glucose after an oral tolerance test, glycated haemoglobin and parameters of insulin action are related to higher CRP levels.



   Subjects and methods
Top
 Abstract
 Introduction
 Subjects and methods
Results
 Discussion
 Acknowledgements
 References
 
Patients
In this cross-sectional study, we analysed consecutive patients with cadaveric renal transplants performed in our institution from January 1999 to December 2003 that met the following inclusion criteria: no pre-existing or new onset diabetes (NODAT) using the American Diabetes Association (ADA-2005) criteria, at least 12 months of follow-up from transplantation, and stable and acceptable renal function in the last 3 months (creatinine clearance >20 ml/min). Of a total of 517 patients, 171 had diabetes mellitus prior to transplantation, 103 lost their graft or died, 51 patients presented a calculated creatinine clearance <20 ml/min or suffered a recent impairment of renal function, and 28 patients were diagnosed as NODAT. In addition, 30 patients declined to participate. Thus, from 164 eligible recipients we studied 134. In all patients the presence of infection or inflammatory disease was ruled out by physical and clinical examination. Relevant information about donor, recipient and transplant characteristics was extracted from the Canary Islands Renal Transplant Database (CIRTRAD), updated at regular intervals since 1996 [12]. Medical record review was performed in accordance with Spanish law on the protection and confidentiality of clinical data. This study was approved by the Ethics Committee of the Hospital Universitario de Canarias and was conducted in accordance with the provisions of the Declaration of Helsinki.

High-sensitivity CRP, HbA1c, and the other analytes shown in Table 1 were measured in all patients. An oral glucose tolerance test (OGTT) was also performed in all patients. A standard 75 g glucose was given after 10–12 h overnight fast. Blood samples were taken at 0 and 120 min for the measurement of plasma glucose and insulin.


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  		Table 1. Demographic characteristics

 
Definitions
The ADA-2005 [13] criteria were used to exclude NODAT and to define glucose metabolism parameters. Normal fasting glucose (NFG: fasting glucose < 100 mg/dl) and impaired fasting glucose (IFG: fasting glucose ≥100 and ≤125 mg/dl) were defined using multiple data from the CIRTRAD data base. Data from OGTT were used to classify patients as normal: glucose at 120 min <140 mg/dl; impaired glucose tolerance (IGT) as glucose at 120 min between 140–200 mg/dl and provisional diabetes: glucose at 120 min ≥200 mg/dl. A repeated OGTT to confirm the diagnosis of diabetes was not performed in patients with provisional diabetes. MS was diagnosed using the National Cholesterol Education Expert Panel (NCEP-ATP III) definition [14] with a slight modification as previously used in renal transplant recipients [12]. A patient was classified as having MS if at least three of the following criteria were present: (i) body mass index (BMI) ≥ 30 kg/m2; (ii) serum triglycerides (TG) ≥ 150 mg/dl; (iii) HDL-cholesterol <40 mg/dl for men or < 50 mg/dl for women; (iv) blood pressure ≥130/85 mmHg and (v) fasting plasma glucose ≥ 100 mg/dl. Waist circumference was substituted by BMI as per Meigs et al. [15] who showed that this change had little effect on the applicability of the definition. The glycaemia criterion was adapted to the new cut-off point proposed by the ADA [13].

Renal function was assessed using serum creatinine and the Jelliffe formula to estimate creatinine clearance. This formula compares favourably with others in terms of dispersion when compared with inulin clearance in the renal transplant population [16]. Smoking status was defined as current smoking. Mean values of the last two measurements of biochemical parameters and blood pressure from each patient were used for definitions and statistics.

Measurements
High-sensitivity CRP was determined by nephelometry (Image Beckman®). Serum creatinine, triglycerides and glucose levels were measured using a computerized auto-analyzer (Hitachi; Boehringer Manheim, Germany). Total blood "ciclosporin" and tacrolimus levels were quantified by fluorescence polarization immunoassay (FPIA) using a monoclonal antibody (Abbott Laboratories, Abbott, IL, USA). HbA1c was measured by HPLC (ARKRAY® Kyoto, Japan), and normal reference values range from 3.5% to 5.4%. Insulin was determined by enzyme immunoassay of micro particles (MEIA) (Abbott: AxSym Insulin, Germany). Twenty-four hour urinary protein excretion was determined by standard methods. Based on the results of OGTT, two indexes of insulin action validated in the renal transplant population were calculated:

(a) the Insulin Sensitivity Index of Hjelmesæth et al. (ISI-TX) [17]


Formula

and (b) the McAuley index [18]:


Formula

Immunosuppression
Immunosupression consisted of antithymocite globulin (Thimoglobulin® IMTIX-SANGSTAT, Lyon, France) or basiliximab (Simulect®, Novartis, Basel) for induction and prednisone, cyclosporine (Neoral®, Novartis, Basel) or tacrolimus (Prograf® Fujisawa, Japan) and mycophenolate mofetil (Cellcept® Roche, Basel) or azathioprine for maintenance. The dose of prednisone was 0.3 mg/kg bw/day during the first 3 months, and then tapered to 5–10 mg/day by 1 year. Cyclosporine was started at 8 mg/kg bw/day, tacrolimus at 0.2 mg/kg/day, and then adjusted according to total blood levels. Episodes of acute rejection were initially treated with three boluses of 500 mg intravenous methylprednisolone. Resistant episodes were treated with a 7–10 day course of OKT3 (5 mg/day) (Muromonab CD3; Ortho Pharmaceutical, Raritan, NJ, USA).

Statistical analysis
CRP levels were divided into tertiles in order to analyse the characteristics of the population (Table 1) and the results related to glucose homeostasis parameters (Table 2). Quantitative variables with parametric distribution are expressed as mean ± SD. Quantitative variables with non-parametric distribution (e.g. triglycerides, proteinuria and ISI-TX) are expressed as median and interquartile range. To compare different tertiles, we first used the ANOVA or Kruskal–Wallis tests for variables with normal or non-normal distribution, respectively. When significant differences were observed, individual comparisons between groups were done by Tukey's post hoc analysis or Mann–Whitney test, respectively. Diverse bivariate Pearson's or Spearman's correlations between possible factors associated to CRP levels were performed. As a consequence of their non-normal distribution, triglyceride and CRP levels were log-transformed for analysis and back-transformed for result presentation. P-values <0.05 were considered significant.


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  		Table 2. Relationship between the parameters of glucose metabolism and CRP tertiles in patients without NODAT

 
Multiple linear regression analyses with backward selection were carried out for selecting variables related to higher levels of CRP. Co-linearity and the assumption of normality were never violated. The dependent variable was the log10-transformed CRP levels. In model 1, age, gender, smoker status, estimated creatinine clearance, aspirin, statins, angiotensin converting enzyme inhibitors or angiotensin receptor antagonist use, prednisone dose, type of calcineurin inhibitor used (cyclosporine vs tacrolimus) and MS components were introduced as independent variables. In addition, fasting glucose was replaced by glucose levels after OGTT. In model 2, glucose was replaced by HbA1c (Table 3).


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  		Table 3. Linear regression model 2

 
All computations were carried out using the SPSS 12.0 for Windows (Chicago, IL).



   Results
Top
 Abstract
 Introduction
 Subjects and methods
 Results
Discussion
 Acknowledgements
 References
 
Table 1 shows the distribution of demographic, clinical and biochemical data among CRP tertiles. BMI and triglyceride levels were significantly higher and HDL-C significantly lower in the upper tertile (Table 1). Also, MS was more frequent in the upper tertile. Calculated creatinine clearance was significantly lower in the third tertile. No significant differences were observed in patient age, acute rejections, smoker status, immunosuppressive therapy or drugs that can modify CRP levels.

Table 2 shows glucose metabolism parameters among CRP tertiles. The proportion of patients with IFG or IGT, as well as glucose and insulin levels both at baseline and after 120 min of an OGTT, were not different among CRP tertiles. However, glycated haemoglobin increased significantly and insulin-sensitivity indexes decreased significantly in the third tertile (Table 2 and Figure 1).


Figure 1
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  		Fig. 1. (A) McAuley index (mean ± SE) distributed by CRP tertiles. a: T1 vs T3: P = 0.042. (B) HbA1c % (mean ± SE) distributed by CRP tertiles. b: T1 vs T3 P = 0.005.

 
CRP levels correlated directly with glycated haemoglobin (r = 0.33, P < 0.001), BMI (r = 0.27, P = 0.002) and triglycerides (r = 0.26, P = 0.002), and inversely with ISI-TX index (r = –0.23, P = 0.01), McAuley index (r = –0.25, P = 0.004) and HDL-cholesterol (r = –0.23, P = 0.008). Fasting glucose, systolic and diastolic blood pressure showed no correlation with CRP.

Table 3 shows the multiple linear regression analyses. In model 1, BMI (standardized ß coefficient = 0.27; P = 0.002) and triglycerides (standardized ß coefficient = 0.3; P < 0.001) were related to high CRP levels. Remarkably, neither fasting glucose (standardized ß coefficient = 0.07; P = 0.3) nor glucose after OGTT (standardized ß = 0.06; P = 0.9) reached statistical significance. In model 2, HbA1c (standardized ß coefficient = 0.25; P = 0.004), BMI (standardized ß = 0.21; P = 0.008) and triglycerides (standardized ß = 0.18; P = 0.02) were independent factors associated to high CRP levels. The analysis was repeated after excluding the recipients with provisional diabetes and the model did not change significantly (r2 = 0.2; HbA1c: standardized ß = 0.21 and P = 0.03; BMI: standardized ß = 0.28 and P = 0.001; triglycerides: standardized ß = 0.5 and P = 0.001).



   Discussion
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
Acknowledgements
 References
 
This cross-sectional study shows that in stable renal transplant recipients without pre-existing or new onset diabetes, CRP levels are directly related to BMI and triglyceride levels, and inversely related to HDL-C levels and parameters of insulin action. Consequently, MS was more prevalent among recipients with higher CRP levels. Remarkably, HbA1c but not fasting glucose or glucose after an oral glucose tolerance test, was independently related to CSI.

CRP is an acute-phase reactant produced by hepatocytes in response to infection, inflammation, injury and other stimuli. It reflects and amplifies the overall cytokine activation in the organism and proved to be very well correlated to other markers of inflammation [19]. Importantly, CRP has a long half-life, is an exceptionally stable analyte in serum and the assays to measure it are robust, well standardized, reproducible and readily available [19]. Many studies have shown a clear relationship between CRP and cardiovascular disease, including the renal transplant population [8–11].

MS, a cluster of cardiovascular risk factors, was overrepresented in recipients with CRP values in the higher tertile (Table 1). Many studies have linked CSI with MS in the general population [4], and the importance of this relationship prompted some experts to propose CRP as part of the syndrome [20]. Importantly, BMI and triglyceride levels were the components of the syndrome independently associated with CRP levels in our study (Table 3). Obesity is characterized by a broad inflammatory response, and many molecules with immunologic activity are produced in adipocytes including adiponectin, resistin, tumour necrosis factors-{alpha} (TNF-{alpha}), and interleukin-6 and -1. In addition, interleukin-6 stimulates liver production of CRP [21]. Thus, our finding of an association of BMI with CRP levels in renal transplant recipients was not unexpected and has been shown previously [11]. We also observed that triglycerides were another independent factor associated to CRP values (Table 3). Interestingly, the use of specific cut-off points for triglycerides is considered to be a practical approach to identify overweight individuals who are insulin resistant [22,23]. Finally, the American Heart Association has recently characterized individuals with >3 mg/l of CRP as patients at high risk for cardiovascular disease [24]. It is important to note that this cut-off point is similar to the third tertile in our sample (>3.25 mg/l), where cardiovascular risk factors tended to accumulate.

Parameters of insulin action worsened as CRP tertiles increased (Table 2 and Figure 1), and a significant and inverse correlation between both variables was observed. A link between markers or mediators of inflammation and insulin resistance has been clearly shown in several population-based studies [3,25]. Studies looking at the role of inflammation in the pathogenesis of insulin resistance have identified several molecular targets. Interestingly, proinflammatory cytokines such as TNF-{alpha} and Il-1 activate JNK and IKKß/NK-{kappa}B in adipocytes, hepatocytes, and associated macrophages induce the expression of numerous markers that can cause insulin resistance [26]. Thus, insulin resistance and the associated metabolic abnormalities may at least in part explain the proatherogenic effect of chronic inflammation.

Among different parameters of glucose homeostasis, HbA1c, but neither fasting glucose nor glucose levels after the OGTT, was independently related to CRP (Table 2 and Figure 1). A similar relationship has been described in non-diabetic subjects with known coronary atherosclerosis where CRP increases with increasing HbA1c within the normal range [7]. Although some studies have shown a relationship between fasting glucose and CRP values in the general population [27], this has not been the case in other studies [28]. A high intraperson variability in response to an OGTT has been observed. In fact, many patients showing glucose intolerance in the first test may have a normal glucose tolerance on repeated testing [29]. On the other hand, HbA1c represents 2–3 month glucose metabolism (fasting and postprandial) prior to the blood determination and is not subject to the wide variations of fasting plasma glucose. Thus, HbA1c may be an appropriate marker of the relationship between CSI and subclinical homeostasis alterations in renal transplant recipients.

Our study has limitations. The cross-sectional design of the study does not allow us to elucidate the temporal direction of the observed associations between inflammation and insulin resistance and glycated haemoglobin. Future cohort studies should clarify this point. Also, the relatively small number of patients may be considered a general limitation of the study. This may have influenced the lack of correlation between CRP and fasting glucose (type 2 error). Finally, decreasing creatinine clearance has been shown to increase CRP levels in some [30,31] but not in all studies [32]. Although we found a significantly lower creatinine clearance among recipients in the highest CRP tertile (Table 1) it was not an independent factor, and did not change the association between HbA1c and CRP in the multivariate analysis. Thus, in our study the association between inflammation and HbA1c was not altered by creatinine clearance.

In conclusion, renal transplant recipients without pre-existing or new onset diabetes with higher degrees of chronic subclinical inflammation show insulin resistance and higher HbA1c values. Thus, subclinical glucose homeostasis alterations may be an important target to prevent cardiovascular disease in this population.



   Acknowledgements
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgements
References
 
This study was supported by grants FIS 02/1350 and FIS 04/0988, and from the Red Temática de Investigación: C03/03 (Instituto de Salud Carlos III, Spanish Ministry of Health).

We are indebted to Alejandro Jiménez for expertise assistance in statistics, to Mr Michael Lee McLean for English technical assistance and to the staff of the clinical study sites.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgements
 References
 

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Received for publication: 12.11.06
Accepted in revised form: 19. 1.07


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