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NDT Advance Access originally published online on November 19, 2007
Nephrology Dialysis Transplantation 2008 23(4):1436-1441; doi:10.1093/ndt/gfm762
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org


The combined effect of pre-transplant triglyceride levels and the type of calcineurin inhibitor in predicting the risk of new onset diabetes after renal transplantation

Esteban Porrini1, Patricia Delgado1, Alejandra Alvarez1, Marian Cobo1, Lourdes Pérez1, José M. González-Posada1, Luis Hortal2, Roberto Gallego2, José J. García3, Maria Checa4, Adelaida Morales5, Eduardo Salido1,6,7, Domingo Hernández1 and Armando Torres1,6,7

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

Armando Torres, Nephrology Section and Research Unit, Hospital Universitario de Canarias, Ofra S/N, 38320 La Laguna, Tenerife, Spain. Tel: +34-922678380; Email: atorres{at}ull.es



   Abstract
Top
 Abstract
Introduction
 Material and methods
 Results
 Discussion
 References
 
Background. Insulin resistance precedes overt diabetes in the general population and hypertriglyceridemia is a reliable marker of the disorder. Thus, patients in the waiting list with hypertriglyceridemia may be at risk for new-onset diabetes after transplantation (NODAT).

Objectives. We investigate whether pre-transplant triglyceride (TG) levels are a risk factor for NODAT and whether they exert a combined effect with the type of calcineurin inhibitor (CNI).

Methods. We analysed 314 consecutive non-diabetic recipients [215 cyclosporine A (CsA); 99 tacrolimus (Tacro)] transplanted between 1999 and 2003 with a mean follow-up of 34 months. Outcome was NODAT defined by ADA criteria.

Results. NODAT developed in 81 recipients (25.8%). Multivariate analysis which included a propensity score for factors determining CNI allocation showed that age (OR: 1.06; 95% CI: 1.03–1.09), pre-transplant BMI (OR: 1.1; 95% CI: 1.02–1.17),TG levels (OR: 1.3 per 50 mg/dl increment, 95% CI: 1.07–1.6) and treated acute rejection (OR: 4.8, 95% CI: 3–11), but not the type of CNI, were independent risk factors for NODAT. A significant interaction between pre-transplant TG and type of CNI was observed. Using CsA as the reference, the combination of Tacro plus pre-transplant hypertriglyceridemia (≥200 mg/dl) showed an OR of 3.26 (1.4–7.8) to develop NODAT, contrasting with an OR of 0.75 (0.34–1.6) in Tacro recipients with pre-transplant TG levels <200 mg/dl.

Conclusion. Pre-transplant hypertriglyceridemia was a risk factor for NODAT only in recipients treated with Tacro; it highlights the importance of pre-transplant insulin resistance in the pathogenesis of NODAT.

Keywords: insulin resistance; NODAT; tacrolimus



   Introduction
Top
 Abstract
 Introduction
Material and methods
 Results
 Discussion
 References
 
New-onset diabetes after renal transplantation (NODAT) is a recognized complication that influences graft and patient survivals [1,2]. Many pre-transplant as well as post-transplant risk factors for NODAT have been identified. Most pre-transplant risk factors are common to type 2 diabetes and involve age, race, family history of diabetes, obesity, hepatitis C virus infection, dyslipidemia and abnormal glucose tolerance [3–5]. Immunosuppressive drugs, basically calcineurin inhibitors (CNIs) and steroids, represent the most important post-transplant risk factors for NODAT [5]. Corticosteroids produce insulin resistance [6] and CNIs reduce insulin secretion [7]. Thus, NODAT can be viewed as a form of type 2 diabetes where immunosuppressive drugs, acting on predisposed individuals, accelerate the development of the disease.

Many pre-transplant risk factors for NODAT share a common background of insulin resistance. Not surprisingly, insulin resistance has been reported to precede overt diabetes in the general population [8]. Thus, identifying insulin- resistant patients on the waiting list is desirable because an intervention before transplantation may be of help for NODAT prevention. A strong correlation between triglyceride (TG) levels, a widely available parameter, and insulin resistance as well as insulin levels has been observed in apparently healthy individuals [9]. Therefore, their use has been proposed as a simple and practical marker to identify individuals with insulin resistance and then at increased cardiovascular risk [9].

The two CNIs, cyclosporine A (CsA) and tacrolimus (Tacro), seem to have different effects on renal function and cardiovascular risk factors. CsA more adversely affects renal function, blood pressure and lipids, while Tacro causes a greater degree of glucose homeostasis alteration [10,11]. It is not known whether the diabetogenic potential of the two CNIs is different depending on the pre-transplant insulin-resistance state of the recipient. To our knowledge, such an interaction between the type of CNI and pre-transplant insulin resistance has not yet been explored.

The aims of the present study were to investigate (i) whether pre-transplant TG levels, as a practical marker of insulin resistance, are a risk factor for NODAT and (ii) whether pre-transplant TG levels have a combined effect with the type of CNI in inducing NODAT.



   Material and methods
Top
 Abstract
 Introduction
 Material and methods
Results
 Discussion
 References
 
Patients
This historical cohort study included consecutive cadaveric renal transplant recipients without pre-transplant diabetes performed at our institution between 1 January 1999 and 31 December 2003 (n = 377), a period in which modern immunosuppression was used. Since NODAT presents a peak incidence during the first post-transplant year, those patients with less than 12 months of follow-up were excluded (n = 14). In addition, in order to avoid a confounding effect on the possible interaction between pre-transplant TG levels and the type of CNI, we excluded those recipients that changed from one CNI to the other or to an m-Tor inhibitor, before the end of follow-up or before the diagnosis of NODAT (n = 44). Finally, patients with a non-functioning graft (n = 5) were also excluded. Thus, a total of 314 recipients, 215 on CsA and 99 on Tacro, were included in the study. All recipients were of Caucasian origin.

Relevant information about donor, recipient and transplant characteristics was extracted from the Canary Island Renal Transplant Database, which has been 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.

Mean values of fasting pre-transplant triglyceride and glucose levels were obtained from routine biochemical data taken at different dialysis units within 2–3 months before transplantation.

Definitions
The American Diabetes Association (ADA-2005) [13] criteria were used to define NODAT. Patients were considered as NODAT if they fulfilled the ADA criteria by the end of follow-up. Therefore, patients who had shown transient NODAT and did not fulfil the ADA criteria at follow-up were included in the non-NODAT group for analyses. Renal function was assessed by serum creatinine and the Jelliffe formula to estimate creatinine clearance. This formula compares favourably with others in terms of dispersion when compared to insulin clearance in the renal transplant population [14]. Mean values of the last two fasting measurements of biochemical parameters from each patient were used for definitions and statistics.

Immunosuppression
Immunosuppression consisted of antithymocite globulin (Thimoglobulin® IMTIX-SANGSTAT, Lyon, France) or basiliximab (Simulect®, Novartis, Basel) for induction, prednisone, cyclosporine (Neoral®, Novartis, Basel) or tacrolimus (Prograf® Fujisawa, Japan), and mycophenolate mofetil (Cellcept® Roche, Basel). All patients received an intra-surgery bolus of 500 mg intravenous methylprednisolone as a single dose. 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. This prednisone dose was similar in CsA and Tacro groups. CsA was started at 8 mg/kg bw/day, Tacro at 0.2 mg/kg/day, and then adjusted according to total blood levels. Target CsA levels at 3 months were 150–250 ng/ml and then tapered to 100–150 ng/ml by 1 year. Target Tacro levels were 8–12 ng/ml in the first month, 7–10 at 3 months and then tapered to 5–10 ng/ml by 1 year. The choice of CNI type was as per clinical practice and during the study period Tacro was introduced later than CsA. Thus, the mean follow-up of CsA patients was longer than for those on Tacro. Episodes of acute rejection were initially treated with three boluses of 500 mg intravenous methylprednisolone. Resistant episodes were treated with a 7- to –10-day course of OKT3 (5 mg/day) (Muromonab CD3; Ortho Pharmaceutical, Raritan, NJ, USA).

Statistical analysis
Quantitative variables are expressed as mean ± standard deviation, and median and interquartile range as appropriate. To compare the means between patients with and without NODAT, t-test or Mann–Whitney tests were used as appropriate. Pearson's x2 test was used to compare proportions between groups.

Since this is a historical cohort study and not a randomized trial, a propensity score analysis was performed to investigate factors that determined the allocation to CsA or Tacro. The individual probability of being treated with Tacro or CsA was derived from a stepwise logistic regression analysis including performed HLA antibodies (OR: 1.03, 95% CI: 1.0005–1.05), previous transplant (OR: 1.9, 95% CI: 0.9–4.2), gender (OR: 1.6, 95% CI: 0.9–3) and recipient age (OR: 0.9, 95% CI: 0.9–1.01). The –2 log of the likelihood of the model was 246.35 and accounted for 70% of the variance.

Multiple logistic regression analysis (enter method) was used to investigate whether pre-transplant TG levels (presented as increments of 50 mg/dl) alone and interacting with the type of CNI were a risk factor for NODAT. Age, pre-transplant BMI and glucose levels, as well as type of CNI, prednisone dose, hepatitis C virus infection, treated acute rejections, the propensity score for CNI allocation and the time of follow-up were included as covariates.

To analyse the combined effect of pre-transplant TG levels and CNI in more detail, we divided pre-transplant TG into tertiles and combined them with the type of CNI as follows: group 1 = CsA + lower and second TG tertiles; group 2 = CsA + upper TG tertile; group 3 = Tacro + lower and second TG tertiles and group 4 = Tacro + upper TG tertile. The incidence of NODAT among these groups was assessed by Pearson's x2 test.

In addition, the previously described multiple logistic regression analysis was carried out replacing CNI and pre-transplant TG by the group resulting from the combination of CNI and pre-transplant TG tertiles.

P values <0.05 were considered significant. All computations were carried out using the SPSS 14.0.1 for Windows (Chicago, IL, USA).



   Results
Top
 Abstract
 Introduction
 Material and methods
 Results
Discussion
 References
 
As observed in Table 1, NODAT patients were older and more obese, and also showed higher levels of TG, but not fasting glucose before transplantation than non-NODAT patients. The proportion of patients who developed NODAT was not significantly different between CsA and Tacro (Table 1). As a whole, the incidence of acute rejection was not different between CsA and Tacro (12% versus 14%, respectively). However, a higher proportion of NODAT patients presented acute rejection and consequently received a higher cumulative dose of methylprednisolone boluses (Table 1). However, this was true only in the CsA group where acute rejection was observed in 24% (13/54) of recipients with NODAT and in 8% (13/161) of those without NODAT (P = 0.004). In contrast, acute rejection was observed in 15% (4/27) of NODAT and 14% (10/72) of non-NODAT recipients in the Tacro group (P = 0.5). This may explain the significantly higher trough levels of CsA but not of Tacro between recipients with NODAT versus non-NODAT (Table 1). Creatinine clearance was significantly lower in NODAT patients and the majority of NODAT cases appeared within the first post-transplant year (Table 1). Finally, no differences were observed regarding gender, time on dialysis, hepatitis C virus infection, steroid doses and time of follow-up.


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  		Table 1 Pre- and post-transplant variables in NODAT and non-NODAT patients

 
Patients with NODAT received different therapies. Insulin was used in 28 (35%), oral anti-diabetic drugs in 35 (43%), acarbose in 13 (16%) and 5 (6%) were treated with diet but still fulfilled the ADA criteria.

Table 2 shows the results of the multivariate logistic regression analysis. Age, pre-transplant BMI and TG levels, as well as treated acute rejection, were independent risk factors for NODAT. Although the type of CNI was not significant, an interaction with pre-transplant TG levels was observed. Each 50 mg increment of pre-transplant TG levels in Tacro patients portended a 40% increased risk of NODAT as compared to CsA (OR: 1.4; 95% CI: 1.06–1.8) (Table 2).


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  		Table 2 Multiple logistic regression analysis: dependent variable: NODAT (n = 81). Pre-transplant fasting glucose, hepatitis C virus infection, time of follow-up, type of CNI, prednisone dose and the propensity score, were not significant and did not change the final model. Interactions between the type of CNI and age, pre-transplant glucose or BMI were not significant

 
A more detailed analysis of the interaction between pre-transplant TG levels and the type of CNI is shown in Tables 3 and 4. Among CsA patients, pre-transplant TG levels in the third tertile (≥200 mg/dl) did not condition an increased incidence of NODAT (Table 3); however, among Tacro recipients, pre-transplant hypertriglyceridemia increased the incidence of NODAT from 18% to 44% (Table 3). Using CsA, recipients with pre-transplant TG levels below the third tertile as the referent, multivariate analysis showed that the only group with an increased risk of NODAT was that of Tacro patients with pre-transplant TG levels in the third tertile (≥200 mg/dl), which showed an odds ratio for NODAT of 3.26 (95% CI: 1.4–7.8) (Table 4).


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  		Table 3 Incidence of NODAT after combining pre-transplant TG tertiles and type of calcineurin inhibitor. Pre-transplant TG tertiles: lower: <123; second: 123–199 and upper: ≥200 mg/dl

 

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  		Table 4 Risk of NODAT when combining pre-transplant TG tertiles and type of CNI. Multiple logistic regression analysis adjusting for age, pre-transplant BMI, treated acute rejection, propensity score, hepatitis C virus infection, time of follow-up, prednisone dose and pre-transplant glucose levels. Pre-transplant TG tertiles: lower: <123 mg/dl; second: 123–199 mg/dl; upper: ≥200 mg/dl

 


   Discussion
Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
References
 
In this study we observed that pre-transplant TG levels, a practical marker of insulin resistance, were a risk factor for NODAT. Remarkably, we observed that high pre-transplant TG levels affected the appearance of NODAT differently according to the type of CNI. Among patients on CsA, a different incidence of NODAT regarding pre-transplant TG levels was not observed. However, patients on Tacro showed an increased risk of NODAT as compared to CsA only in the presence of high pre-transplant TG levels (≥200 mg/dl).

Patients included in this study were managed under modern immunosuppression with mycophenolate mofetil used as adjunctive therapy and low-dose corticosteroids. Importantly, to clearly establish the interactions between the type of CNI and pre-transplant TG levels, we selected those recipients who remained on the same CNI during follow-up. Finally, we used the established ADA criteria to define NODAT [13].

Gold standard methods to measure insulin resistance are time consuming and impractical. Different parameters of lipid metabolism are well correlated to insulin resistance when measured by accurate methods [9]. Of these, TG levels and TG/HDL-c ratio showed the best correlation with insulin resistance [9]. Its use may be a practical way to identify of patients at risk for diabetes and cardiovascular disease [9,16–18]. As we did not have data of HDL-c in all patients, we used pre-transplant TG levels as a practical marker of insulin resistance at the time of transplantation. Remarkably, TG levels in dialysis patients have been positively correlated with insulin levels [19].

In the present study we observed that in the absence of pre-transplant hypertriglyceridemia, Tacro was not associated with an increased risk of NODAT as compared to CsA. However, the combination of pre-transplant hypertriglyceridemia (≥200 mg/dl) with the use of Tacro portended an odds ratio of 3.26 (95% CI: 1.4–7.8) for NODAT. Although insulin resistance is an early phenomenon in the genesis of type 2 diabetes, pancreatic β-cell function declines gradually over time before the onset of clinical hyperglycaemia [8]. Then, insulin resistance and a certain degree of β-cell dysfunction usually coexist. With this metabolic background, it may be speculated that therapy with Tacro, which exerts a more pronounced decrease in insulin release than CsA [20, 22], more rapidly accelerates the common pathophysiologic process of type 2 diabetes. Finally, the avoidance of toxic Tacro levels (>15 ng/ml) in the present study (Table 1) that have been identified as a risk factor for NODAT [20] may have limited the deleterious effect of Tacro on glucose homeostasis to the group at higher risk.

We have confirmed previous reports showing age, obesity and acute rejection as independent risk factors for NODAT [3,4]. Obesity is very well correlated with insulin resistance in the general population [17] and in renal transplant recipients [6]. However, only 25% of obese–overweight individuals are insulin resistant [17], and TG levels are a better indirect measure of insulin resistance than BMI [9]. This may explain the lack of interaction of BMI with the type of CNI in our study. Acute rejection has been previously associated with NODAT [3] and the concomitant use of high-dose corticosteroids plays a central role [3]. As a consequence, efforts to diminish acute rejection while avoiding or minimizing corticosteroids may help diminishing the NODAT incidence.

Our study has several limitations. First, recipients were not prospectively randomized to each CNI. However, we have adjusted for the probability of being treated with CNI (propensity score) that may have contributed to minimize this limitation. In addition, both groups were comparable and managed similarly with low-dose corticosteroids as well as adjunctive therapy with mycophenolate mofetil. Secondly, even though follow-up was similar in NODAT versus non-NODAT patients, Tacro was progressively introduced during the study period. This may have benefited Tacro patients in terms of the incidence of NODAT. However, the time of follow-up did not exclude the interaction of pre-transplant TG levels with the type of CNI in the multivariate model. Also, laboratory tests were not analysed in a central laboratory and this may have influenced the variability of the results. Finally, for the identification of insulin-resistance patients before transplantation, we used TG levels instead of the TG/HDL-c ratio, a more accurate marker of insulin resistance [9]. Therefore, we may have underestimated this condition.

In conclusion, we found pre-transplant TG levels to be a risk factor for NODAT showing an interaction with the type of CNI. The combination of high pre-transplant TG levels and the use of Tacro were associated with a greater risk for NODAT. This finding highlights the importance of preventive interventions like encouraging exercise and weight reduction prior to transplantation, and steroids minimization plus a strict control of Tacro exposure in the post-transplant period, especially in older recipients. Whether CsA is preferred to Tacro for patients with insulin resistance at the time of transplantation should be tested in future clinical trials.



   Acknowledgments
 
The study was supported by grants FIS 02/1350 and FIS 04/0988 and from the Red Temática de Investigación: C 03/03 (Instituto de Salud Carlos III, Spanish Ministry of Health). We are indebted to Alejandro Jiménez for expert assistance in statistics, to Mr Michael Lee McLean for English technical assistance, to Maria Elena Feria Moreno and Maria Inmaculada Romera Ruiz for collecting and classifying data. Finally, we thank the staff of the clinical study sites for their important cooperation.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
 References
 

  1. Kasiske B, Snyder D, Gilbertone D, et al. Diabetes mellitus after kidney transplantation in the United States. Am J Transplant (2003) 3:178–185.[CrossRef][Web of Science][Medline]
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  4. Weir M, Fink Jeffrey. Risk for posttransplantation diabetes mellitus with current immunosuppressive medications. Am J Kidney Dis (1999) 1:1–13.[Medline]
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  7. Oetjen E, Baun D, Beimesche S, et al. Inhibition of human insulin gene transcription by the immnosuppressive drugs cyclosporin A and tacrolimus in primary, mature islets of transgenic mice. Mol Pharmacol (2003) 63:1289–1295.[Abstract/Free Full Text]
  8. Stumvoll M, Goldstein B, van Heften T. Type 2 diabetes: principles of pathogenesis and therapy. The Lancet (2005) 365:1333–1346.
  9. McLaughlin T, Reaven G, Abbasi F, et al. Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am J Cardiol (2005) 96:399–404.[CrossRef][Web of Science][Medline]
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  11. Vincenti F, Friman S, Scheuermann E, et al. Results of an international, randomized, trial comparing glucose metabolism disorders and outcome with cyclosporine versus tacrolimus. Am J Transplant (2007) 7:1506–1514.[CrossRef][Web of Science][Medline]
  12. Porrini E, Delgado P, Alvarez A, et al. Impact of metabolic syndrome on grafo function and survival alter cadaveric renal transplantation. Am J Kidney Dis (2006) 48:134–142.[CrossRef][Web of Science][Medline]
  13. Anonymous. Diagnosis and classification of diabetes mellitus. Diabetes Care (2005) 28:s37–s42.[CrossRef][Web of Science][Medline]
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  15. Anonymous. Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation and treatment of high cholesterol in adults (adult treatment panel III) final report. Circulation (2002) 106:3143–3421.[Free Full Text]
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  18. Bos G, Dekker J, Nijpels G, et al. A combination of high concentrations of serum triglyceride and non-high-density-lipoprotein-cholesterol is a risk factor for cardiovascular disease in subjects with abnormal glucose metabolism—the Hoorn study. Diabetologia (2003) 46:910–916.[CrossRef][Web of Science][Medline]
  19. Chan MK, Varghese Z, Persaud JW, et al. Hyperlipidemia in patients on maintenance hemo- and peritoneal dialysis: the relative pathogenetic roles of triglyceride production and triglyceride removal. Clin Nephrol (1982) 17:183–190.[Web of Science][Medline]
  20. Fukudo M, Ikudo I, Masuda S, et al. Distinct inhibitory effects of tacrolimus and cyclosporine A on calcineurin phophatase activity. J Pharmacol Exp Therapy (2005) 312:816–825.
  21. Maes B, Kuypers, Messiaen T, et al. Posttransplantaion diabetes mellitus in FK-506-treated renal transplant recipients: analysis of incidence and risk factors. Transplantation (2001) 72:1655–1661.[CrossRef][Web of Science][Medline]
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Received for publication: 22. 5.07
Accepted in revised form: 20. 9.07


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