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Published ahead of print on March 22, 2006
Clin J Am Soc Nephrol 1: 575-582, 2006
© 2006 American Society of Nephrology
doi: 10.2215/CJN.01471005
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Renal Transplantation

Hypoadiponectinemia Is Associated with Insulin Resistance and Glucose Intolerance after Renal Transplantation: Impact of Immunosuppressive and Antihypertensive Drug Therapy

Jøran Hjelmesæth*,{dagger}, Allan Flyvbjerg{ddagger}, Trond Jenssen*,§, Jan Frystyk{ddagger}, Thor Ueland||, Monica Hagen*, and Anders Hartmann*

* Department of Medicine and || Research Institute of Internal Medicine, Rikshospitalet University Hospital, Oslo, Norway; {dagger} Medical Department, the Hospital in Vestfold, Tønsberg, Norway; {ddagger} The Medical Research Laboratories, Clinical Institute and Medical Department M (Diabetes and Endocrinology), Aarhus University Hospital, Aarhus, Denmark; and § Institute of Clinical Medicine, University of Tromsø, Tromsø, Norway

Address correspondence to: Dr. Jøran Hjelmesæth, Medical Department, Hospital in Vestfold, Boks 2168, 3103 Tønsberg, Norway. Phone: +47-40-21-73-49; Fax: +47-33-34-39-38; E-mail: joran{at}online.no


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 References
 
The objectives of this analysis were (1) to assess whether low serum adiponectin concentrations are associated with insulin resistance, metabolic syndrome, and new-onset posttransplantation diabetes mellitus (PTDM) and (2) to examine the possible effects of immunosuppressive and antihypertensive therapies on circulating adiponectin levels after renal transplantation. A total of 172 consecutive previously nondiabetic renal transplant recipients were examined 3 mo after transplantation, the majority (n = 167) with an oral glucose tolerance test. Serum adiponectin was measured by an in-house time-resolved immunofluorometric assay. Insulin secretion and insulin sensitivity were estimated by previously validated oral glucose tolerance test–derived indexes. One- and 6-yr follow-up data were available in subgroups of patients. Lower adiponectin levels were significantly associated with insulin resistance but not with insulinopenia. Patients with low adiponectin levels (first quartile) had significantly higher odds of PTDM (odds ratio [OR] 3.6; 95% confidence interval [CI] 1.1 to 12.7; P = 0.049) and metabolic syndrome (OR 3.9; 95% CI 1.6 to 9.5; P = 0.003) than patients in the upper (fourth) quartile. The increased risk for PTDM in patients with low adiponectin levels remained significant after adjustment for age, steroid dose, and family history of diabetes. Treatment with ß blockers was independently associated with lower serum adiponectin levels, and total steroid dose was associated with higher serum adiponectin levels. Low baseline adiponectin levels were also associated with significantly higher odds of PTDM at 6 yr (OR 6.9; 95% CI = 1.1 to 41.8; P = 0.037). Serum adiponectin levels correlate with posttransplantation insulin sensitivity and glucose tolerance. Glucocorticoids and ß blockers seem to have opposite effects on circulating adiponectin levels.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Conclusions
 References
 
Adiponectin is a fat-derived hormone that is produced and secreted exclusively by adipocytes (1,2). Beneficial effects of adiponectin have been reported on insulin sensitivity (IS), blood glucose, lipids, and cardiovascular disease (CVD) (1,2). Recently, a possible relationship between low adiponectin levels and pancreatic ß cell dysfunction was suggested (3,4). A negative correlation between body mass index (BMI) and adiponectin levels has been established both in the general population and in patients with renal disease (5–8).

Renal transplant recipients are insulin resistant when compared with age- and gender-matched control subjects (9). This may be explained partly by immunosuppressive therapy (10), in particular steroids (11). Inhibition of endogenous calcineurin activity with tacrolimus or cyclosporine A (CsA) may lead to enhanced adipogenesis, which may explain the metabolic disturbances that are associated with these drugs (12). Some studies have reported linear relationships between doses or blood trough concentrations of CsA and lipids (inverse relationship with HDL) (13,14), but the potential impact of calcineurin inhibitors on serum adiponectin is unknown.

Two previous studies addressed posttransplantation adiponectin levels (5,15), and the former reported a positive relationship between steroid dose and adiponectin levels (5). Recently, low pretransplantation adiponectin levels were shown to be associated with increased risk for posttransplantation diabetes mellitus (PTDM) (7).

A large proportion of renal transplant recipients receive antihypertensive drug therapy, and both diuretics and ß blockers have been correlated with insulin resistance in renal transplant patients (16). Recently, it was hypothesized that hypoadiponectinemia may be related to insulin resistance in essential hypertension and that renin-angiotensin system blockade ameliorates IS through increased serum adiponectin levels (17). To our knowledge, the possible relationship between adiponectin and other antihypertensive drugs, such as ß blockers, {alpha} blockers, and calcium channel blockers has not been addressed.

This analysis was undertaken to (1) assess the influence of adiponectin on IS and the occurrence of posttransplantation glucose intolerance and the metabolic syndrome (MS) and (2) to examine the possible effects of immunosuppressive and antihypertensive therapies on circulating adiponectin levels early after renal transplantation. In addition, the predictive effect of early posttransplantation adiponectin levels on long-term (1 and 6 yr posttransplantation) cumulative incidence of PTDM and metabolic parameters was addressed.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Conclusions
 References
 
We previously examined risk factors and pathogenesis of PTDM in a cross-sectional study of a total of 173 consecutive pretransplantation patients who did not have diabetes (before transplantation) and received a kidney transplant between 1995 and 1996 (16,18,19). The study population, the immunosuppressive protocol, and laboratory analyses have been described in detail (16,18).

Briefly, all patients were treated with steroids, and the majority (86%) received a combination of CsA, prednisolone, and azathioprine. An oral glucose tolerance test (OGTT) was performed in 167 recipients 10 wk after transplantation. All patients completed a questionnaire that addressed smoking habits, present or pretransplantation diabetes, and symptoms of CVD (20). Patients with repeated BP values in the sitting or recumbent position above systolic BP 140 mmHg or diastolic BP 90 mmHg and those who were being treated with antihypertensive medication were classified as hypertensive. The patients were divided into categories of glucose tolerance according to the American Diabetes Association/World Health Organization criteria (20–22): New-onset PTDM, impaired glucose tolerance (IGT), impaired fasting glucose (IFG), or normal glucose tolerance (NGT). Informed consent was obtained, and the study was approved by the local ethics committee and performed in accordance with the Declaration of Helsinki (23).

Estimates of IS and Insulin Secretion
IS was estimated by the OGTT-derived IS index (ISI) ISITX = 0.208 – 0.0032 x BMI – 0.0000645 x Ins120 – 0.00375 x Gluc120 (16) and the ISI suggested by McAuley et al. (24): ISIMcAuley = [Exp (2.63 – 0.28 x ln [insulin] – 0.31 x ln [triglycerides])] (25). These indexes have been validated in renal transplant patients and correlate well with IS as assessed by euglycemic glucose clamp studies (16,25). First-phase insulin release was estimated by the use of an equation that was documented by Stumvoll et al. (26) to correlate well with insulin secretion as assessed by hyperglycemic clamp studies in patients with varying degrees of glucose tolerance: Secr1.phase = 1194 + 4.724 x Ins0 – 117.0 x Gluc60 + 1.414 x Ins60.

The product of the estimates of IS and insulin release, known as the disposition index (DI), is a constant in normoglycemic individuals, whereas the development of glucose intolerance is associated with a decline of the DI (19,27,28). Accordingly, the DI describes the ability of the pancreatic ß cell to compensate for various degrees of insulin resistance and therefore may represent a more appropriate measure of ß cell function than the absolute insulin release. In our analysis, the product of Secr1.phase and ISITX was used as a surrogate measure of DI as described previously (19).

MS
A slightly modified version of the World Health Organization definition of the MS was implemented (excluding microalbuminuria). Previous reports have demonstrated that this definition of MS may be appropriate to identify individuals who are at increased risk for future CVD (reviewed in [29]). Insulin resistance was defined as IS (ISITX) below the lowest quartile for the background population under investigation (16,22). A person with PTDM or IFG/IGT or an insulin-resistant individual with NGT has the MS when two of the following criteria are fulfilled (22): (1) hypertension (treatment or systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg), (2) dyslipidemia (triglycerides ≥1.7 mmol/L or HDL <0.9/1.0 mmol/L [M/F]), and (3) obesity (BMI >30 kg/m2).

Laboratory Analyses
Blood samples were drawn in the fasting state, and immediately after centrifugation, serum was used for determination of glucose, creatinine, and lipids or frozen for later analysis of insulin, adiponectin, and high-sensitivity C-reactive protein (hsCRP; –40°C). In addition, blood samples were drawn after 1 and 2 h for analysis of glucose and insulin. See previous publications for details on analytical methods (16,18,20). Frozen sera were available for analysis of adiponectin and hsCRP from 172 of 173 patients. hsCRP was measured as described by others (30).

Serum adiponectin was determined by a novel in-house time-resolved immunofluorometric assay based on two antibodies and recombinant human adiponectin (R&D Systems, Abingdon, UK) as recently described (31,32). Adiponectin has a molecular weight of 30 to 36 kD, depending on the degree of glycosylation, but the molecule is known to form a wide range of polymers in vivo. The predominant polymers include trimers, hexamers, and highly congregated multimers of 300 kD. Both of these antibodies were able to detect several adiponectin polymers in serum, including the three major molecular forms (data not shown). Within and between assay coefficients of variation of standards and unknown samples averaged <5 and 10%, respectively.

Follow-Up at 1 and 6 Yr after Transplantation
The first 109 of 172 consecutive patients in the baseline study were evaluated for inclusion in a follow-up study at a median of 1 yr after transplantation; 12 patients declined to participate, and two patients died, leaving 95 patients to be included (33). Five years later, these 95 patients were evaluated for inclusion in a second follow-up study; 18 had died, two had received another transplant, two had returned to hemodialysis, and 10 were unwilling to participate, leaving 63 recipients to be included (34).

The majority of patients in both follow-up studies underwent an OGTT, and the patients were divided into three groups—PTDM, IGT/IFG, or NGT—according to current guidelines (21). Body weight, BMI, and blood glucose concentrations were registered in both studies, and more detailed information on waist circumference, insulin sensitivity, lipid parameters, and metabolic risk factors were collected in the 6-yr follow-up study. Further detailed information on the patients and methods has been given previously (33,34).

Statistical Analyses
Data are given as mean (SD), median (interquartile range), or proportions. {chi}2 statistics and binary logistic regression were used to assess the relationship between adiponectin (independent) and IGT/IFG, PTDM, and MS (dependents). We used ANOVA and independent samples t test to assess the association of various levels of adiponectin with continuous variables. Nonparametric tests were used for nonnormal distributed data. Bivariate associations of adiponectin with explanatory variables corresponding to P < 0.1 were included in a multiple linear regression analysis, and their relative influence on adiponectin (dependent) levels was addressed. Skewly distributed variables (adiponectin and hsCRP) were ln transformed to meet the assumptions of the linear regression analyses. We chose a 5% statistical significance level. The analyses were implemented using SPSS 12.0 (SPSS, Inc., Chicago, IL).


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Conclusions
 References
 
At baseline, serum adiponectin levels were measured in 172 patients: 119 men and 53 women, the majority being white (n = 165). Median fasting serum adiponectin concentration was 19.6 mg/L (interquartile range 14.6 to 24.6). The patients had a mean age of 47 ± 16 yr, a BMI of 23.5 ± 3.8 kg/m2, serum creatinine of 145 ± 44 µmol/L, daily prednisolone dose of 15 ± 7 mg, daily CsA dose of 342 ± 114 mg, and whole-blood CsA trough concentration of 242 ± 60 µg/L. More than 80% of the recipients were hypertensive (n = 146).

Relationship between Adiponectin (Independent) and PTDM, MS, Glucose, and Insulin Parameters
Table 1 illustrates that the proportion of patients with either new-onset PTDM (versus NGT) or IGT/IFG (versus NGT) was significantly higher in the lower (first) than in the upper (fourth) adiponectin quartile. Using NGT as reference, the odds ratio (OR) for PTDM for patients in the lower quartile was 3.6 (95% confidence interval [CI] 1.0 to 12.7; P = 0.049) and for IGT/IFG was 3.9 (95% CI 1.4 to 11.0; P = 0.010), as compared with patients in the upper quartile. Because age and daily prednisolone dose predict posttransplantation glucose intolerance (18), multiple logistic regression models were used to calculate adjusted OR; patients with lower adiponectin levels had significantly greater odds of PTDM and IGT/IFG (OR 6.1 [95% CI 1.4 to 26.9; P = 0.017] and OR 7.6 [95% CI 2.4 to 24.5; P = 0.001], respectively) even after adjustments for age and daily steroid dose. Further adjustment for a family history of diabetes did not alter the odds for developing PTDM significantly (data not shown).


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  		Table 1. Relationship between adiponectin quartiles and PTDM, IGT/IFG, metabolic syndrome, serum glucose, IS, and insulin secretiona

 
The proportions of patients with MS differed significantly between quartiles (Table 1). Patients in the lower adiponectin quartile had an approximately four-fold greater odds of MS as compared with patients in the upper quartile (OR 3.9; 95% CI = 1.6 to 9.5; P = 0.003). These results were essentially unaltered by adjustments for age and gender (OR 4.3; 95% CI 1.7 to 10.8; P = 0.002).

Estimated IS was significantly lower in the first adiponectin quartile (Table 1), and a significant linear relationship was found between adiponectin quartiles and ISITX (r = 0.25, P = 0.001). The positive relationship between adiponectin and ISITX (dependent) remained significant after adjustment for ß blocker therapy and total steroid dose (P = 0.002) but not after further adjustment for BMI (P = 0.114). Estimated first-phase insulin release did not differ significantly between quartiles, whereas a trend toward a lower median DI was observed in the lower adiponectin quartile (Table 1).

Variables (Independents) Associated with Adiponectin (Dependent)
Adiponectin was negatively correlated with BMI and daily dose of CsA and positively correlated with total steroid dose (Table 2). Of note, no significant relationships were found between adiponectin and hsCRP or between adiponectin and serum creatinine.


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  		Table 2. Adiponectin (ln) as the dependent variable and relationships with potential independent continuous and categorical variablesa

 
On average, ß blocker therapy, male gender, and current smoking were associated with lower levels of adiponectin, whereas rejections were associated with higher levels of adiponectin (Table 2). A trend toward lower mean adiponectin concentrations in patients who were treated with {alpha} blockers was also observed. Treatment with angiotensin-converting enzyme (ACE) inhibitors, calcium channel blockers, or furosemide did not influence adiponectin levels significantly.

Variables that were associated with adiponectin (Table 2) with P < 0.1 were included in a standard multiple linear regression analysis. For avoiding multicollinearity, rejection was not included; a high correlation was found between rejection and total steroid dose (r = 0.90). The multiple regression analysis revealed that BMI and use of ß blockers were independent predictors of decreased adiponectin levels, whereas total steroid dose independently predicted increased levels of adiponectin (Table 3). This model explained 22% (R2 = 0.22) of the variance in adiponectin. Total steroid dose explained approximately 7%, ß blocker therapy 5%, and BMI 5% of the variance in serum adiponectin concentrations (squared partial correlation coefficients).


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  		Table 3. Predictors of serum adiponectin level (standard multiple linear regression analysis, n = 171)a

 
One- and 6-Yr Follow-Up Studies
At 1 yr, the distribution of patients with PTDM did not differ significantly in the various quartiles of adiponectin (data not shown). In contrast, the proportion of patients with PTDM at 6 yr was higher in the first than in the fourth adiponectin quartile: 8 (53%) of 15 versus two (14%) of 14 patients (P = 0.050). Accordingly, the OR of PTDM for patients in the lower quartile was 6.9 (95% CI 1.1 to 41.8; P = 0.037), as compared with patients in the upper quartile. Patients with transient PTDM (n = 6) had significantly higher baseline adiponectin levels than patients with persistent PTDM (n = 7) after 6 yr (28 ± 10 versus 15 ± 5 mg/L; P = 0.013).

Patients in the first adiponectin quartile had significantly lower median HDL cholesterol levels (1.1 versus 1.5 mmol/L; P = 0.006) at 6 yr. In contrast, lower baseline adiponectin levels were not significantly associated with any other anthropometric (BMI, weight, waist circumference, and waist-to-hip ratio) or metabolic parameter (blood glucose, IS, insulin secretion, total cholesterol, and triglycerides) at 6 yr or with changes in these parameters during the study period (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Conclusions
 References
 
The major novel findings of our analysis are (1) that hypoadiponectinemia is associated with insulin resistance, glucose intolerance, and the MS in the early posttransplantation period and (2) that early posttransplantation adiponectin levels may predict both long-term persistence and new-onset of PTDM. In addition, to our knowledge, this is the first study to suggest that treatment with ß blockers is associated with lower serum adiponectin concentrations.

Adiponectin: Relationship with Posttransplantation Glucose Intolerance and MS
Patients with low adiponectin levels 3 mo after transplantation had an approximately four-fold higher odds of glucose intolerance (PTDM or IFG/IGT). In addition, low baseline adiponectin levels were associated with a higher long-term (6 yr) risk for PTDM, and patients with transient PTDM had higher baseline adiponectin levels than those with persistent PTDM. Although the relationship between posttransplantation adiponectin levels and PTDM was not examined previously, our findings add some support to one previous study that showed that low pretransplantation adiponectin levels predict PTDM (7). An inverse relationship between adiponectin and IGT/IFG has been described in the general population (35) but has not been reported in transplant patients.

Lower adiponectin levels were significantly associated with insulin resistance, and although we were unable to demonstrate any significant effect of adiponectin on ß cell function, a trend toward reduced insulin secretion (measured as DI) was revealed. These results indicate that the main mechanism by which decreased adiponectin may worsen glucose tolerance is by inducing insulin resistance, although an additional effect on pancreatic ß cell function cannot be excluded.

Patients with MS had significantly lower levels of adiponectin than those without, which is in concert with published data in the general population (1). However, whether this finding translates into increased long-term risk for cardiovascular events in renal transplant recipients remains to be determined.

Antihypertensive Drugs and Adiponectin
The mechanisms of the possible detrimental effect of ß blockers on adiponectin levels are unknown. ß Blockers may decrease total energy expenditure by 5 to 10%, induce weight gain, inhibit lipolysis, and promote the accumulation of abdominal fat (36). Weight gain may partly explain the negative association between ß blockers and adiponectin, but, importantly, the negative correlation between ß blocker therapy and adiponectin persisted after adjustment for BMI. Because ß blocker treatment has been associated with insulin resistance (36,37), an alternative explanation may be that ß blocker–induced insulin resistance leads to decreased adiponectin levels.

Furuhashi et al. (17) reported that 2 wk of treatment with either the ACE inhibitor temocapril or the angiotensin II type 1 receptor blocker candesartan was associated with a 15 to 30% increase in adiponectin levels in humans with essential hypertension. Beneficial effects of losartan and ramipril on adiponectin also have been reported (38,39). We were unable to demonstrate any significant relationship between treatment with ACE inhibitors and adiponectin levels in renal transplant recipients. The majority of patients in our study received lisinopril, and the relationship between this ACE inhibitor and adiponectin has not been evaluated previously. Therefore, our findings do not directly contradict previous reports suggesting a relationship between adiponectin and other ACE inhibitors.

Immunosuppressive Drugs and Adiponectin
In view of the widely known adverse effect of steroids on IS, glucose tolerance, and lipid profile (10,11,16,18), the positive relationship between glucocorticoid dose and adiponectin concentration may seem unexpected and difficult to explain. However, a number of previous studies support a possible positive relationship between steroids and adiponectin both in humans (5,40,41) and in rodents (42). Moreover, in accordance with our findings, Chudek et al. (5) found a significant positive correlation between the dose of prednisone or total steroid dose and plasma adiponectin concentrations in renal transplant recipients who were examined the first few weeks after renal transplantation. In contrast, others have shown that both exogenously administered glucocorticoids and endogenous cortisol hyperproduction are associated with lower adiponectin levels (43), whereas no significant change in adiponectin level was observed despite a decline in plasma cortisol after successful surgery for Cushing’s syndrome (44). Although the promoter region of the human adipose most abundant gene transcript-1 gene contains consensus sequences for glucocorticoid receptor binding (45), the mechanism of a potential relationship between steroids and adiponectin is unknown. However, TNF-{alpha} is known to inhibit adipose most abundant gene transcript-1 gene expression (46), and steroids may increase adiponectin levels indirectly by suppressing TNF-{alpha} (47).

Surprisingly, higher adiponectin levels were observed in patients who had experienced one or more rejections. This probably may be explained by the standard high-dose glucocorticoid treatment of rejections as indicated by the highly positive correlation between rejections and total steroid dose (r = 0.90).

Increasing daily dose of cyclosporine was negatively correlated with adiponectin in the univariate analysis but failed to reach statistical significance in the multivariate regression model. No significant association between CsA trough concentrations and adiponectin was found. However, whole-blood CsA measurement 2 h after drug administration may be a more appropriate measure of drug exposure and side effects, but this analysis was not implemented in our study. Therefore, the hypothesis of a possible negative effect of CsA on adiponectin levels needs further evaluation.

Renal Function and Adiponectin
An inverse relationship between renal function and adiponectin has been described in populations with normal or impaired renal function (2,48). We did not find any significant association between serum creatinine and adiponectin in renal transplant recipients, which is in accordance with the study by Chudek et al. (5) but in contrast with the findings of Malyszko et al. (15). Although the lack of association between creatinine and adiponectin in these two studies does not definitely exclude any such relationship, other parameters seem to have a greater impact on serum adiponectin in the first months after transplantation.

Limitations
This analysis has limitations. First, the cross-sectional design of the baseline study makes it difficult to discern any definitive cause–effect relationships. Second, all patients received glucocorticoids, and the results may be less relevant for transplant recipients who do not receive steroids. Because the majority of patients were treated with different combinations of antihypertensive drugs, the possible independent effect of ß blocker therapy on adiponectin levels must be interpreted with care. Furthermore, the majority of patients were white, and the results may not be generalized to nonwhite populations. Finally, the possibility of selection bias should be taken into account in the interpretation of the follow-up data.


   Conclusions
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
References
 
Adiponectin is associated with beneficial effects on posttransplantation IS and glucose tolerance. Glucocorticoids and ß blockers seem to have opposite effects on circulating adiponectin levels. These findings need confirmation in future studies.


   Acknowledgments
 
J.H. has received an educational grant from the Norwegian Foundation for Health and Rehabilitation. A.F. is supported by a research grant from the Danish Medical Research Council. J.F. is supported by research grants from the Danish Medical Research Council and the Danish Diabetes Association.

We acknowledge the laboratory assistance of Hanne Petersen, Anette Mengel, and Joan Hansen, Medical Research Laboratories, Aarhus University Hospital (Aarhus, Denmark), and Kirsten Lund, Jannicke Narverud, Els Breistein, and Jean Stenstrøm, Laboratory of Renal Physiology Rikshospitalet University Hospital (Oslo, Norway). Thanks to Marijke Veenstra, Biostatistics, Rikshospitalet University Hospital, for valuable statistical advice.


   Footnotes
 
Published online ahead of print. Publication date available at www.cjasn.org.

Received October 26, 2005. Accepted January 19, 2006.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 References
 

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