Renal Transplant Program, University Medical Center Groningen, Groningen, The Netherlands
Correspondence and offprint requests to: Stephan J. L. Bakker, MD PhD, Department of Medicine, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, the Netherlands. Email: s.j.l.bakker{at}int.umcg.nl
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Abstract |
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Methods. Between August 2001 and July 2003, renal transplant recipients with a functioning graft for more than 1 year (n = 847) were eligible for investigation at their next visit to the outpatient clinic. A total of 606 patients (55% male, aged 51±12 years) participated at a median (interquartile range) time of 6.0 (2.611.4) years post-transplant.
Results. Median CRP concentration was 2.0 (0.804.8) mg/l and mean 24 h creatinine clearance was 62±22 ml/min. CRP was significantly associated with body mass index, waist circumference and waist-to-hip ratio (P-value<0.0001). None of the transplant characteristics except creatinine clearance was associated with CRP. In multiple regression analysis, waist circumference, log sICAM-1 concentration, gender, creatinine clearance and current smoking were independently associated with CRP.
Conclusions. In renal transplant recipients waist circumference and smoking are the two most important modifiable independent determinants of CRP. Furthermore, CRP is independently associated with the endothelial function parameter sICAM-1 and, in univariate analyses, associated with multiple cardiovascular risk factors. CRP is not associated with any of the transplant-related factors, except for renal transplant function.
Keywords: C-reactive protein; cardiovascular risk; chronic allograft nephropathy; obesity; renal transplantation; smoking
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Introduction |
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In renal transplant recipients, slightly elevated levels of CRP have recently been demonstrated to be an independent predictor of coronary heart disease and total mortality [7,8]. Importantly, an even more recent study has also identified post-transplant CRP as a predictor of chronic allograft nephropathy [9].
In renal transplant patients it is not known what factors determine plasma CRP concentrations. Complicating factors in comparison with the general population might, for instance, be a chronic low-grade immunologic response to the renal allograft, pro-inflammatory effects of various degrees of uraemia [10] and potential anti-inflammatory effects of immunosuppressive therapy. In this study, we aimed to investigate whether levels of CRP are associated with cardiovascular risk factors and transplant-related factors including creatinine clearance. We also aimed to investigate the influence of measures of obesity on putative associations.
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Materials and methods |
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Measurements
The body mass index (BMI) was calculated as weight in kilograms (kg) divided by height in metres squared (measured to the nearest 0.5 kg and 0.5 cm respectively). Waist circumference was measured on bare skin midway between the 10th rib and the iliac crest. Hip circumference was measured at the maximum circumference of the buttocks. Blood pressure was measured as the average of three automated (Omron M4; Omron Europe B.V., The Netherlands) measurements with 1 min intervals after a 6 min rest in supine position. Diabetes mellitus was diagnosed if the fasting plasma glucose concentration was 7.0 mmol/l or anti-diabetic medication was used.
High sensitivity CRP was measured using a double plated ELISA assay as described before [13]; the lowest limit of detection was 0.002 mg/l. Total cholesterol was determined using the CHOD PAP method (MEGA AU 510; Merck Diagnostica, Darmstadt, Germany). Low density lipoprotein (LDL) was calculated using the Friedewald formula. High density lipoprotein cholesterol (HDLc) was determined using the CHOD PAP method on a Technikon RA-1000 (Bayer Diagnostics b.v., Mijdrecht, The Netherlands). Soluble intercellular adhesion molecule type 1 (sICAM-1), soluble vascular cellular adhesion molecule type 1 (sVCAM-1) and sE-selectin concentrations were measured by enzyme-linked immunosorbent assay (ELISA) kits (Diaclone Research, Besançon, France). Plasma glucose was determined by the glucose-oxidase method (YSI 2300 Stat plus; Yellow Springs, OH, USA). Cytomegalovirus (CMV) IgG was assessed by routine ELISA assay as described previously [14]. Total protein concentration was analysed using the Biuret reaction (MEGA AU 510; Merck Diagnostica, Darmstadt, Germany).
Recipient and transplant characteristics
Relevant donor, recipient and transplant characteristics were extracted from the Groningen Renal Transplant Database. This database holds information of all renal transplantations that have been performed at our centre since 1968. Extracted were donor and recipient age and gender, date of transplantation, CMV status, delayed graft function (days of oliguria), weight, renal function at baseline, type of acute rejection treatment and use of aspirin. Smoking status and prior history of cardiovascular disease were obtained from a self-report questionnaire that had been sent to participants by mail.
Standard immunosuppression consisted of the following: from 1968 until 1989, prednisolone and azathioprine (100 mg/day); from January 1989 to February 1993, cyclosporine standard formulation (Sandimmune, Novartis; 10 mg/kg; trough levels of 175200 µg/l in first 3 months, 150 µg/l between 3 and 12 months post-transplant, and 100 µg/l thereafter) combined with prednisolone (starting with 20 mg/day, rapidly tapered to 10 mg/day). From March 1993 to May 1996, cyclosporine microemulsion (Neoral; Novartis Pharma b.v., Arnhem, The Netherlands; 10 mg/kg; trough levels idem) and prednisolone. From May 1997 to date, mycophenolate mofetil (Cellcept; Roche b.v., Woerden, The Netherlands; 2 g/day) was added. Current medication was extracted from the medical record.
Statistical analysis
Analyses were performed with SPSS version 12.0 (SPSS Inc., Chicago, IL). Parametric variables are expressed as mean±standard deviation, whereas non-parametric variables are given as median (interquartile range). Skewed data were normalized by logarithmic transformation in all analyses.
First, in order to investigate which demographic variables, cardiovascular risk factors and transplant-related factors were associated with CRP concentrations, we analysed these factors over quartiles of CRP concentrations. P for trend was determined with -square for trend and JonckheereTerpstra tests for nominal and ordinal variables, respectively, and by univariate linear regression analyses with log-transformed CRP concentrations as dependent variable for continuous variables. A two-sided P
0.05 was considered to indicate statistical significance.
Second, to investigate which cardiovascular risk factors and transplant-related factors were significantly associated with levels of CRP independent of age, gender and measures of obesity, linear regression analyses were performed with log-transformed CRP as dependent variable. The effect of adjustments can be judged by comparing (standardized) regression coefficients and P-values of an association before and after adjustment. Strengths of associations of different variables can be compared with standardized regression coefficients. To allow for these comparisons standardized regression coefficients and P-values of all recipient and transplant characteristics that showed at least a tendency (P 0.1) to be associated with CRP in univariate analyses are shown in Model 1. The associations were subsequently adjusted for age and gender (Model 2) and additionally for the measure of obesity with the strongest association to CRP (Model 3). Further adjustments for smoking status were performed in Model 4 (results not shown in tables).
Third, to determine which of the factors in Model 3 were independently associated with CRP, a backward multivariate linear regression analysis was performed with log CRP concentration as dependent variable. Co-variables with a P-value 0.1 in Model 3 were included.
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Results |
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Recipient and transplant characteristics over quartiles of CRP are shown in Tables 1 and 2. The following interquartile ranges were calculated: 1st quartile (<0.80 mg/ml, n = 151), 2nd quartile (0.802.0 mg/ml, n = 152), 3rd quartile (2.14.8 mg/ml, n = 152) and 4th quartile (>4.9 mg/ml, n = 151).
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Table 3 shows the standardized regression coefficients (ß) and P-values of the univariate linear regression analyses of the variables that showed at least a tendency (P 0.1) to be associated with higher CRP in the first table (Model 1). Age (standardized ß = 0.16, P<0.0001) and gender (standardized ß = 0.15, P = 0.0002) were both significantly associated with CRP levels (Table 3). All body composition measurements showed a significant positive association with CRP (Table 3). Waist circumference was associated strongest with CRP (standardized ß = 0.28, P<0.0001). BMI and WHR were also associated with higher CRP (standardized ß = 0.26 and 0.19, respectively, P<0.0001). Adjustment for age and gender had no significant effect on these associations (Model 2). The associations of CRP with BMI and WHR were dependent on waist circumference, since neither remained significantly associated with CRP after adjustment for waist circumference. Current smoking (standardized ß = 0.12, P = 0.002) was positively associated with CRP (Table 3). This association remained statistically significant after adjustment for age, gender and waist circumference.
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There was a significant positive association of the endothelial function parameters, log sICAM-1 (standardized ß = 0.28, P<0.0001), log sVCAM-1 (standardized ß = 0.11, P = 0.006) and log sE-selectin (standardized ß = 0.096, P = 0.02) with CRP (Table 3). Adjustment for age, gender and subsequently waist circumference did not materially change these associations.
Log triglyceride concentration (standardized ß = 0.12, P = 0.003) showed a positive significant association with CRP, whereas log HDLc (standardized ß = 0.079, P = 0.05) concentration showed a significant negative association with CRP (Table 3). Both associations virtually disappeared after adjustment for waist circumference.
Further adjustment for smoking status (Model 4) did not importantly affect any of the above-mentioned associations. Results of Model 4 are therefore not shown.
None of the transplant characteristics, except creatinine clearance, was significantly associated with CRP (Table 3). The association of creatinine clearance (standardized ß = 0.15, P = 0.0002) did not materially change after adjustment for age, gender and waist circumference (Table 3).
To determine which variables were independently associated with CRP, we performed a backward linear regression analysis with log CRP concentration as dependent variable (Table 4). Included co-variables were from Model 3 (Table 3), if the P-value was 0.1. Because log serum creatinine concentration and creatinine clearance are considered mutually exclusive, we did not include log serum creatinine concentration in the multivariate analysis. In multivariate analyses, CRP was independently associated with waist circumference (standardized ß = 0.30, P<0.0001), log sICAM-1 concentration (standardized ß = 0.21, P<0.0001), gender (standardized ß = 0.18, P<0.0001), creatinine clearance (standardized ß = 0.13, P = 0.0004) and current smoking (standardized ß = 0.09, P = 0.02).
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Discussion |
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Several epidemiological studies have documented associations between CRP and obesity markers in the general population [5,6]. The same is true for patients with various degrees of renal insufficiency [15]. To our knowledge, our study is the first to document the existence of the same relationship in renal transplant recipients. Obesity is a state in which there is an increased storage of fatty acids in the form of triglycerides in adipose tissue [16]. A mass effect of these stored triglycerides on lipolysis results in a continuously increased release of fatty acids into the circulation. This mass effect on lipolysis is especially pronounced in adipocytes in the intra-abdominal cavity [17]. The increased release of fatty acids in case of abdominal obesity causes the liver to produce increased amounts of triglyceride-rich lipoproteins, and underlies the association of abdominal obesity with high fasting triglyceride concentrations and low levels of HDLc [18]. The fatty acids also drive increased gluconeogenesis in the liver, and importantly underlie fasting hyperglycaemia when pancreatic ß-cells fail to fully compensate for the prevailing insulin resistance [19]. Recent studies also implicate the increased release of fatty acids from abdominal adipose tissue into the portal circulation as a cause of sympathetic activation and hypertension [20]. Even more recent is the recognition that adipose tissue is not merely an inert place where triglycerides are stored, but a very active endocrine organ, which secretes numerous hormones and pro-inflammatory cytokines, including tumour necrosis factor- and IL-6 into the circulation [21]. Approximately 25% of basal circulating IL-6 originates in human adipose tissue [2], with production in intra-abdominal fat three times that of subcutaneous fat [3]. These pro-inflammatory cytokines stimulate the liver in synthesis and secretion of CRP. Abdominal obesity may therefore be considered an important causal link connecting cardiovascular risk factors, such as fasting triglycerides, HDLc, blood pressure, fasting glucose concentrations and diabetes to CRP.
Atherosclerosis is nowadays considered to be a chronic inflammatory process in the arterial wall [22]. Many epidemiological studies have documented that levels of CRP predict the occurrence myocardial infarction, stroke and cardiovascular mortality in the general population [23]. In renal transplant recipients, slightly elevated levels of CRP have recently been demonstrated to be an independent predictor of coronary heart disease and total mortality [7,8]. Atherosclerosis and chronic low grade inflammation are strongly linked to endothelial dysfunction. We found significant associations between CRP and the endothelial function markers sICAM-1, sVCAM-1 and sE-selectin, which were independent of age, gender and waist circumference. Our finding of an association between sICAM-1, sVCAM-1 and sE-selectin and CRP is consistent with findings in other populations [24]. The increased expression of these endothelial function parameters to the endothelial surface could be an early event in atherogenesis [25]. However, the increased expression of these endothelial function parameters could also be transplant derived through inflammatory processes such as rejection episodes [26]. In multivariate analysis, it appeared that the associations of the endothelial function parameters with CRP were strongly interdependent, with log sICAM-1 as strongest variable, remaining significant after adjustment of the endothelial function parameters for each other.
Renal function was also associated with CRP levels in renal transplant patients. The association between CRP level and diminished creatinine clearance has been shown in several other populations, including chronic pre-dialytic patients and healthy people [27,28]. There are several possible explanations for the association between CRP levels and diminished filtration. First, uraemia has been demonstrated to be a microinflammatory state [10]. Second, it might be that CRP is a marker of a chronic low-grade immune-mediated response to the graft. A third possible explanation for the association between CRP and diminished glomerular filtration could be the result of a decreased renal clearance of CRP. However, the major determinant of CRP levels is the rate of synthesis by the liver, and not the excretion through the kidney [29].
Smoking is a major modifiable risk factor for CVD [30]. Several studies have documented a significant positive association between CRP and smoking [31,32]. In general, CRP concentrations increase among smokers with increased cigarette consumption [31]. In this study current smoking status was independently associated with CRP levels, which supports the suggestion of Bazzano et al. [31] that inflammation may be an important mechanism by which smoking promotes atherosclerotic disease.
The present study has several limitations. First, the study was cross-sectional in design. Such a design cannot establish causality, it can only establish an association. Second, because the study population almost entirely consisted of patients of Caucasian ethnicity, the applicability of our results to more racially diverse renal transplant populations remains limited. Third, in this renal transplant population there was little variation in the use of immunosuppressive medication or in the use of steroids. Therefore, it cannot be excluded that a higher variation in the use of these medications might have any influence on CRP level. Fourth, our study was a single centre study. One way to overcome the problem of little variation in the use of immunosuppressive drugs could be a multi-centre study with more variation in immunosuppressive drugs.
In conclusion, in renal transplant recipients waist circumference and smoking are the two most important modifiable independent determinants of CRP. Furthermore, CRP is independently associated with the endothelial function parameter sICAM-1 and, in univariate analyses, associated with multiple cardiovascular risk factors. CRP is not associated with any of the transplant-related factors, except for renal transplant function.
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Acknowledgments |
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Conflict of interest statement. None declared.
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References |
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