Tacrolimus decreases insulin sensitivity without reducing fasting insulin concentration: a 2-year follow-up study in kidney transplant recipients

Abstract

New Onset Diabetes after Transplantation (NODAT) is defined as sustained hyperglycemia developing in patients without diabetes history before transplantation. A cohort study was performed to access the effects of tacrolimus on insulin secretion and insulin sensitivity and consequently in the development of NODAT in kidney transplant recipients. Then, we further investigated the association between NODAT and single-nucleotide polymorphisms of IRS-1 and IRS-2 in renal allograft recipients. One hundred and fifty-eight kidney transplant patients, receiving tacrolimus as the base immunosuppressant, were divided into two groups: with or without NODAT. Plasma levels of fasting insulin concentration (FINS) and C-peptide were determined by enhanced chemiluminescence immunoassay and ADVIA Centaur C peptide assay, respectively. The genotypes of Gly1057Asp in IRS-2 and Gly972Arg in IRS-1 were detected through polymerase chain reaction fragment length polymorphism in NODAT and non-NODAT patients. It was found that the concentrations of fasting plasma insulin and C-peptide in NODAT and non-NODAT patients treated with tacrolimus were higher than that in healthy volunteers (p < 0.05). Fasting plasma insulin concentration in NODAT was significantly elevated compared with than that in non-NODAT group (p < 0.05). But there are no statistical differences in fasting plasma C-peptide concentrations between NODAT and non-NODAT groups. The allele and genotype frequencies of IRS-2 Gly1057Asp and IRS-1 Gly972Arg in NODAT patients were not significantly different from non-NODAT patients (p > 0.05). In conclusion, insulin resistance is the primary cause of tacrolimus-induced NODAT. The IRS-2 Gly1057Asp and IRS-1 Gly972Arg genotypes are not related to NODAT.

• IRS-1
• IRS-2
• PTDM
• SNP
• TAC

Introduction

New Onset Diabetes after Transplantation (NODAT) is defined as sustained hyperglycemia developing in patients without history of diabetes before transplantation that meets the current diagnostic criteria published by the American Diabetes Association or the World Health Organization.1 The incidence of NODAT ranges from 2% to 50% in the first year after transplant.2 NODAT can lead to chronic renal allograft dysfunction, infections, and increased incidence of cardiovascular and cerebrovascular diseases, which seriously affect long-term survival of kidney transplant recipient.3–5 Studies6–8 have suggested that some factors may be responsible for the initiation of NODAT such as recipient’s age, race, family history of diabetes, impaired glucose tolerance, Hepatitis C virus (HCV) infection, and immunosuppression with high dose of cyclosporine or tacrolimus. Furthermore, the U.S. study3 demonstrated that tacrolimus was an independent risk factor for NODAT occurred in renal transplant patients. However, there is still no consensus among those studies about the risk factors of NODAT in renal transplant recipients.

The pathophysiology of NODAT closely mimics that of Type2 DM, which is characterized by a progressive decline in pancreatic β-cell function and worsening insulin resistance. Whether NODAT results from the decreased insulin secretion or increased insulin resistance and which of them is more important are not clearly defined in the clinical studies.9–13

It is thus possible that nongenetic and genetic variants increase susceptibility of NODAT in kidney transplant recipients. Kido et al.14 confirmed the single nucleotide polymorphism (SNP) of insulin receptor substrate (IRS), Gly972Arg (rs1801278) in IRS-1 and Gly1057Asp (rs1805097) in IRS-2, play important roles in the development of Type2 DM. However, it is unknown whether these genetic polymorphisms are associated with NODAT.

The aims of this study were: (1) to identify the risk factors for the development of NODAT; (2) to perform a cohort study to examine the effects of tacrolimus on insulin secretion and insulin sensitivity in renal transplant recipients with NODAT, and (3) to evaluate the relationship between IRS-1 Gly972Arg and IRS-2 Gly1057Asp polymorphisms and NODAT.

Materials and methods

Patient population and immunosuppressive treatment

Patients are underwent renal transplantation in the Third Xiangya Hospital Organ Transplant Center. All patients were provided with written informed consent in accordance with the guidelines of the declaration of Helsinki to collect the data. Under the laws of organ donation from a living or dead person in China, the donor himself must sign the voluntary consent of human organ donation, and then immediate family must sign it when deceased donor’s renal transplant is performed. Finally, the certificate of the consent of human organ donation will be made by the ethics committee of Xiangya Third Hospital.

Patients, older than 18 years who underwent renal transplantation in the Third Xiangya Hospital Organ Transplant Center were enrolled between January 2007 and October 2011. Patients were excluded from our study for the following reasons: diabetes mellitus before the transplant (n = 14), multiorgan transplant, super acute rejection related to transplantation, serious infections, and calcineurin inhibitor toxicity. Four-hundred and thirteen patients were included in the follow-up study to analyze the risk factors of NODAT. One-hundred and sixty-three patients had deceased donors’ renal transplantation and 250 patients had living donor renal transplantation. Renal transplant recipients, treated with triple immunosuppressive scheme: tacrolimus or cyclosporine (CSA), mycophenolate mofetil or mizoribine, and steroid were brought into the study. All patients received the same prophylactic steroid regimen: the steroid was administered as 500 mg methylprednisolone for 3 days, followed by prednisone 80 mg daily from day 4 to 7, then treated with prednisone at a reduction rate of 2.5 mg every 2 weeks from 80 mg daily till maintenance dose 5 mg per day. Diltiazem was used as a regimen to increase the blood concentration of tacrolimus.

One-hundred and fifty-eight of 293 patients treated with tacrolimus as the base immunosuppressant were enrolled to evaluate the effects of tacrolimus on insulin secretion and insulin sensitivity in the development of NODAT. Tacrolimus was orally administered with a loading dose of 0.075 mg/kg twice-daily within 12 h of surgery.

Insulin was administered to the patients with NODAT. According to the handbook of kidney transplantation in China, the target tacrolimus whole-blood trough concentrations are as follows: 8–10 ng/mL in the first month after renal transplantation, 6–8 ng/mL from months 1 to 3, and 3–7 ng/mL thereafter. Routine therapeutic drug monitoring was performed to confirm whether the target concentration of tacrolimus was achieved. Dose adjustments and monitoring of oral study medication were performed by a clinical pharmacist and nephrologist outside the collaborative group of investigators. The patients were divided into two groups: patients with NODAT (n = 78) and without NODAT group (n = 80), to investigate the impact of insulin secretion and insulin sensitivity in the development of NODAT. The level of FINS, C-peptide, and the allele and genotype frequencies of IRS-1 Gly972Arg and IRS-2 Gly1057Asp polymorphisms were measured.

Definition of diabetes mellitus

NODAT was defined according to the diagnostic criteria published by the World Health Organization. All patients who showed random plasma glucose concentration ≥11.1 mmol/L or fasting plasma glucose (FPG) ≥ 7.0 mmol/L or 2-h plasma glucose level ≥ 11.1 mmol/L following oral glucose tolerance test (OGTT) on two consecutive days were confirmed to be diabetic. The remaining patients were assigned to the non-NODAT group. Fasting glycemia was routinely performed during hospitalization and at the outpatient clinic department.

The concentration of tacrolimus

The trough blood concentrations of tacrolimus were determined using a microparticle enzyme immunoassay performed on the IMx analyzer from Abbott Diagnostics (Wiesbaden, Germany) with the Emit 2000 Tacrolimus Assay (Siemens Healthcare Diagnostics Inc., Erlangen, Germany). The details are described in our previous report.15

Determination of FINS and C-peptide concentration

FINS was determined by enhanced chemiluminescence immunoassay. The log (X)–log (Y) linear fitting method was selected to calculate the content of insulin in the sample. ADVIA Centaur C peptide assay (Siemens Healthcare Diagnostics Inc.) was used to measure the concentration of C-peptide.

Genotyping

Genomic DNA was extracted from 500 μL of whole-blood samples using the commercially available DNA isolation kit. Software Primer premier 5.0 was used to design polymerase chain reaction (PCR) primers. For IRS-2 Gly1057Asp (G1057A) SNP, the upstream primer sequence is 5′-CTCCCCGTCGTCGTCTCT-3′ and the downstream primer sequence is 5′-CTCGACTCCCGACACCTG-3′. PCR products were digested with 2 μL Fast Digest HaeII for 10 min at 37 °C before separation on a 2.5% agarose gel. Allele G was detected as a 185 and 10 bp fragment and allele A as 287 bp fragments. For IRS-1 Gly972Arg (G972C) SNP primer sequences, the upstream primer is 5′-CTTCTGTCAGGTGTCCATCC-3′; and the downstream primer sequence is 5′-TGGCGAGGTGTCCACGTAGC-3′. PCR products were digested with 2 μL BstNI for one night at 37 °C. The digested products were separated on a 2.5% agarose gel. Allele G was detected as a 159, 81, and 22 bp fragment and allele C as 108 and 51 bp fragments.

Statistical analysis

All continuous data were shown as mean values ± standard deviations (x ± SD). Using multivariate logistic regression to analyze the risk factors associated with NODAT. t-Test and nonparametric test (Mann–Whitney U) of two independent samples were implemented in the analysis of differences in insulin and C-peptide concentration between the NODAT group and the non-NODAT group, and were also used in the comparison of genotype frequencies in the IRS-2 Gly1057Asp and IRS-1Gly972Arg and the incidence of diabetes between the two groups. The level of statistical significance was set at p < 0.05.

Results

Risk factors of NODAT

There were 413 renal transplant recipients, and 120 of them were treated with CSA and 293 with tacrolimus; 24 of 120 patients treatment with CSA were NODAT patients (22%). And, the incidence of NODAT among patients who take tacrolimus was 59%.

The significant difference in characteristics between NODAT and non-NODAT patients was age at surgery time (42.7 ± 10.4 vs 36.2 ± 8.6, p = 0.000), body mass index (BMI) (22.8 ± 5.5 vs 20.9 ± 3.4 kg/m², p = 0.000), FPG (7.65 ± 3.63 vs 4.39 ± 0.74 mmol/L, p = 0.004), hepatitis C virus infection rate (10.8% vs 2.9%, p = 0.001), the incidence of acute rejection (46.3% vs 22.9%, p = 0.000), and tacrolimus usage (89.1% vs 61.9%, p = 0.000). The above factors were significantly higher in NODAT than in non-NODAT group. Independent risk factors of NODAT, evaluated by logistic regression, were as follows: age > 50 (p = 0.000), HCV infection (p = 0.004), acute rejection episodes (p = 0.015), and tacrolimus usage (p = 0.000) (Table 1).

Table 1. Multivariate logistic regression analysis of potential risk factors for NODAT.

	Wald	OR (95% CI)	p
Age > 50 years	22.58	1.07 (1.04–1.10)	0.000
HCV infection	8.20	4.66 (1.62–13.35)	0.004
Acute rejection episodes	5.94	1.94 (1.14–3.30)	0.015
Tacrolimus	16.77	4.45 (2.18–9.10)	0.000

Clinical characteristics of renal transplant patients treated with tacrolimus

The proportion of NODAT associated with tacrolimus was 33.4% (n = 293). One-hundred and fifty-eight of 293 patients who had complete hospitalization information and follow-up data entered into the next analysis. Table 2 shows the characteristics of the 158 renal transplant patients treated with tacrolimus. There were no significant differences in gender, age, BMI values, blood pressure, serum creatinine, follow-up time of the postoperation and dosage, and blood concentration of tacrolimus between NODAT and non-NODAT patients.

Table 2. Characteristics of the renal transplant patients treatment with tacrolimus.

Characteristic	NODAT (n = 78)	Non-NODAT (n = 80)	p
Sex (male/female)	58/20	59/21	0.930
Age (x ± SD)	40.4 ± 9.4	38.7 ± 8.2	0.239
BMI at transplantation (kg/m^2, x ± SD)	22.4 ± 2.7	21.7 ± 2.8	0.184
FPG before transplantation (mmol/L, x ± SD)	4.56 ± 0.58	4.36 ± 0.60	0.717
FPG at 1 month after transplantation (mmol/L, x ± SD)	7.40 ± 3.14	4.88 ± 0.67	0.001*
SBP (mmHg, x ± SD)	129.2 ± 12.4	128.4 ± 14.6	0.814
DBP (mmHg, x ± SD)	81.6 ± 9.8	80.8 ± 10.2	0.588
Serum creatinine (μmol/L, x ± SD)	109.3 ± 29.5	99.5 ± 35.2	0.095
Acute rejection (%)	22.2	30.3	0.257
HCV infection (%)	3.6	3.0	0.841
Tacrolimus dosage (mg, x ± SD)
At 1 month after transplantation	5.4 ± 2.1	4.7 ± 1.6	0.306
At 3 months after transplantation	4.2 ± 1.3	3.4 ± 1.0	0.088
At 6 months after transplantation	4.0 ± 1.5	3.1 ± 1.0	0.139
At 12 months after transplantation	3.9 ± 1.5	3.0 ± 1.0	0.288
Tacrolimus blood concentration (x ± SD)
At 1 month after transplantation	8.4 ± 1.8	8.3 ± 1.8	0.987
At 3 months after transplantation	7.2 ± 1.5	7.8 ± 1.9	0.095
At 6 months after transplantation	6.6 ± 2.0	6.5 ± 1.4	0.993
At 12 months after transplantation	6.5 ± 2.0	6.0 ± 2.6	0.194
Pred (%)	98.6	97.3	0.584
MMF (%)	84.6	91.3	0.587
Diltiazem (%)	87.2	87.5	0.952
follow-up time (months, x ± SD)	40 ± 12.4	39 ± 14.8	0.675

Notes: Data are means ± SD or n (%); p values are calculated from t test or Mann–Whitney U by comparing the values between the NODAT and the non-NODAT, *p < 0.05; BMI, body mass index; FPG, fasting plasma glucose; SBP, systolic blood pressure; DBP, diastolic blood pressure; FK506, tacrolimus; Pred, prednisone; MMF, mycophenolate mofetil.

Insulin and C-peptide concentrations

At about 40 months of follow-up time, fasting plasma concentrations of insulin and C-peptide were determined. Table 3 shows that fasting plasma insulin concentration in NODAT group was significantly higher than that in non-NODAT group and C-peptide level was similar in both groups. Compared to healthy volunteers (n = 20), levels of FINS and C-peptide in both NODAT and non-NODAT group were statistically higher (p < 0.05).

Table 3. Fasting insulin and C-peptide level in 158 renal transplant patients treatment with tacrolimus.

	NODAT (n = 78)	Non-NODAT (n = 80)
Fasting insulin (μU/mL, x ± SD)	19.40 ± 14.00*	15.80 ± 10.03
C-peptide (ng/mL, x ± SD)	1.66 ± 1.39	1.57 ± 0.65

Notes: Data are means ± SD or n (%).

*p = 0.046 NODAT versus non-NODAT group.

Genotyping analysis and allelic frequencies

As shown in Tables 4 and 5, allele and genotype frequency of IRS-2 Gly1057Asp and IRS-1 Gly972Arg polymorphism of NODAT have no significant differences compared with the control group. The allele and genotype frequencies of IRS-2 Gly1057Asp and IRS-1 Gly972Arg of the control come from the study of Chan16 and Baba.17 Genotype distribution of IRS-2 Gly1057Asp and IRS-1 Gly972Arg SNPs matched with the Hardy–Weinberg equilibrium (p > 0.05). Furthermore, there were no significant differences in the distribution of genotypes between the two groups (p < 0.05) (Table 6).

Table 4. Allele and genotype frequency of IRS-2 Gly1057Asp polymorphism of NODAT.

	Genotype frequency [number of individuals (%)]
Allele	Control (n = 340)	NODAT (n = 158)	p Value
GLy	186 (54.7%)	93 (58.9%)
Asp	154 (45.3%)	65 (41.1%)	0.438
	Genotype frequency [number of individuals (%)]
Genotype	Control (n = 170)	NODAT (n = 158)	p Value
Gly/Gly + Gly/Asp	126 (71.4%)	124 (79.7%)
Asp + Asp	44 (25.9%)	32 (20.3%)	0.295

Table 5. Allele and genotype frequency of IRS-1 Gly972Arg polymorphism of NODAT.

	Genotype frequency [number of individuals (%)]
Allele	Control (n = 380)	NODAT (n = 158)	p Value
GLy	370 (97.3%)	156 (98.7%)
Arg	10 (2.6%)	2 (1.3%)	0.523
	Genotype frequency [number of individuals (%)]
Genotype	Control (n = 380)	NODAT (n = 158)	p Value
Gly/Gly	362 (95.3%)	154 (97.5%)
Gly/Arg	17 (4.5%)	4 (2.5%)
Arg/Arg	1 (0.3%)	0 (0)	0.461

Table 6. Allele and genotype frequencies of polymorphisms in IRS gene.

Polymorphisms	Allele	NODAT, n (%)	Non-NODAT, n (%)	p*	Genotype	NODAT, n (%)	p	Non-NODAT, n (%)	p	p*
IRS-2 Gly1057Asp	G	96 (61.5)	90 (56.2)	0.340	GG	32 (41.0)	0.750	28 (35.0)	0.677	0.670
	A	60 (38.5)	70 (43.8)		GA	32 (41.0)		34 (42.5)
					AA	14 (18.0)		18 (22.5)
IRS-1 Gly972Arg	G	154 (98.7)	158 (98.8)	0.971	GG	76 (97.4)	1.000	78 (97.5)	1.000	0.980
	C	2 (1.3)	2 (1.2)		GC	2 (2.6)		2 (2.5)
					CC	0 (0)		0 (0)

Notes: Data are n (%). p Value was assessed by Hardy–Weinberg equilibrium x² test. NODAT, post-transplantation diabetes mellitus.

*p Value was assessed by Fisher test between the NODAT and non-NODAT genotypes.

Discussion

This study showed that the incidence of NODAT at 24 months was 28.6%, which was consistent with the previous meta-analysis report that the rates of NODAT in the first post-transplantation year range from 2% to 50 %2 and 24% at 36 months post-transplant.3 Age, HCV infection, acute rejection episodes, and tacrolimus usage denoted higher risk of NODAT at 2 years after transplantation. These risk factors for NODAT in this study confirmed the earlier findings.3

One of the strongest risk factors for NODAT was the use of tacrolimus (Table 1), which is consistent with several retrospective, single-center and observational studies.3^,7 It is known to all that both insulin deficiency and insulin resistance are involved in the pathogenesis of NODAT, but the relative importance of the two different mechanisms is still under dispute. Some clinical studies show that impaired insulin secretion and relative insulin resistance seem to be the dominant mechanism in the development of NODAT,9–13 and the effects of tacrolimus on insulin secretion are both dose dependent and reversible. However, Sui et al.18 reported that obesity or overweight and tacrolimus (especially when its blood concentration was high) were risk factors resulting in insulin resistance in kidney transplant recipients. A 6-year prospective study18 demonstrates that a decline in insulin secretion seems to be the most important factor for the development of long-term NODAT. Boots et al.10 prospectively evaluated glucose metabolism by intravenous glucose tolerance test in 15 white stable, renal transplant recipients without diabetes, and showed that tacrolimus trough level reduction resulted in an improved pancreatic β-cell secretion capacity. The OGTT in 77 patients11 with normal glucose tolerance (NGT) was performed at 1 week before transplantation and repeated at 1 and 7 years after transplantation, and revealed that impaired insulin secretion may be the main mechanism for the development of NODAT. The above studies exhibit that β-cell dysfunction rather than insulin resistance seems to be a greater contributing factor in the development of NODAT.

However, our study showed that fasting plasma insulin concentrations in NODAT group were markedly higher than non-NODAT group and those of both groups were higher than that of healthy subjects. C-peptide level was similar in both groups, and was statistically higher than healthy volunteers. We found that despite no difference in the C-peptide level comparing NODAT to non NODAT subjects, there was an upward trend in the C-peptide level in NODAT than non-NODAT. This may be explained by individual difference and comparatively small sample size of our study. These results indicate that the major mechanism of NODAT associated with tacrolimus is insulin resistance. Both FINS and C-peptide level determination in our study and the Homeostasis Model Assessment-Insulin Resistance in Sui’s study18 are used to reflect insulin resistance level. Therefore, the outcome in our study is consistent with Sui’s report.18

Glucose tolerance test is used to assess insulin release and insulin sensitivity. Boots et al.10 and Hur et al.11 presented the impaired insulin secretion induced by tacrolimus via OGTT. However, these two studies did not show whether a decrease in insulin release induced by tacrolimus results in increase in fasting glucose. It is still unclear whether tacrolimus plays as a regulator of human β-cell survival. Probably, tacrolimus only affected the rhythm of insulin release and then caused the decline in postprandial insulin level. To be sure, we revealed that at about 40 months post-transplant, it is not the impaired islet β-cell but insulin resistance associated with tacrolimus lead to NODAT in renal transplant recipients.

Renal allograft recipients are at high risk for developing diabetes mellitus due to a number of factors including aging, acute rejection episodes, HCV infection, and immunosuppressive medication use. But in the same above conditions where tacrolimus used as the main immunosuppressant, the incidence of NODAT is different among different renal transplant populations. Genetic factors may have important roles in the development of NODAT.

Study14 confirms that IRS SNPs are associated with the susceptibility diabetes. Several studies14^,19 have shown that IRS-2 and IRS-1 genotypes are associated with C-peptide levels and insulin sensitivity. IRS-2 Gly1057Asp and IRS-1 Gly972Arg genotype are the major polymorphic loci of IRS. It has been reported14^,20–22 that the Gly1057Asp of IRS-2 and GLy972Arg of IRS-1 can affect islet-β cell function and levels of insulin and C-peptide, thus increasing the susceptibility to Type2 DM. Our study compared GLy972Arg genotypes in IRS-1 and Gly1057Asp genotypes in IRS-2 between patients with and without diabetes after renal transplantation and found that there was no significant difference (p > 0.05), suggesting that the mutations may not be the important genetic factors of NODAT related to tacrolimus. Because of the low frequency of GLy972Arg allele in IRS-1 a large sample still need to be carried out to confirm this effect.

In conclusion, tacrolimus decreases insulin sensitivity without impairing islet β-cell and reducing FINS in NODAT patients treated with tacrolimus-based immunosuppressant at about 2 years post-transplant evaluation. Insulin resistance is the main cause of NODAT associated with tacrolimus. The IRS-2 Gly1057Asp and IRS-1 Gly972Arg genotypes are not related to NODAT.

Acknowledgements

We are grateful to doctors in the Department of Transplantation of the third Xiangya hospital of Central South University.

Declaration of interest

This study was funded by the National Natural Science Foundation of China (Nos. 81102512, 81273594), the Doctoral Fund of the Ministry of Education of China (No. 20110162120023), Hunan Provincial Health Department Project of China (No. B2010-034) and Program for New Century Excellent Talents in University (NCET-13-0605).