Incidence and Risk Factors for Post–Renal Transplant Diabetes Mellitus

Donor and recipient polygenic risk scores influence the risk of post-transplant diabetes

Post-transplant diabetes mellitus (PTDM) reduces allograft and recipient life span. Polygenic risk scores (PRSs) show robust association with greater risk of developing type 2 diabetes (T2D). We examined the association of PTDM with T2D PRS in liver recipients (n = 1,581) and their donors (n = 1,555), and kidney recipients (n = 2,062) and their donors (n = 533). Recipient T2D PRS was associated with pre-transplant T2D and the development of PTDM. T2D PRS in liver donors, but not in kidney donors, was an independent risk factor for PTDM development. The inclusion of a combined liver donor and recipient T2D PRS significantly improved PTDM prediction compared with a model that included only clinical characteristics: the area under the curve (AUC) was 67.6% (95% confidence interval (CI) 64.1-71.1%) for the combined T2D PRS versus 62.3% (95% CI 58.8-65.8%) for the clinical characteristics model (P = 0.0001). Liver recipients in the highest quintile of combined donor and recipient T2D PRS had the greatest risk of PTDM, with an odds ratio of 3.22 (95% CI 2.07-5.00) (P = 1.92 × 10^-7) compared with those in the lowest quintile. In conclusion, T2D PRS identifies transplant candidates with high risk of PTDM for which pre-emptive diabetes management and donor selection may be warranted.

Diabetogenic Effects of Immunosuppression: An Integrative Analysis. Transplantation. 2020;104:211-221. [PMID: 31283677 DOI: 10.1097/tp.0000000000002815]

BACKGROUND

Posttransplant diabetes mellitus (PTDM) affects up to 50% of solid organ transplant recipients and compromises long-term outcomes. The goal of this study was to investigate how immunosuppressants affect gene expression in a manner that increases diabetes risk, by performing integrative analysis on publicly available, high-throughput gene expression data.

METHODS

All high-throughput gene expression datasets of solid organ transplant recipients were retrieved from the Gene Expression Omnibus. Significantly dysregulated genes and pathways were determined, and those in common with type 2 diabetes were identified. THP-1 and HepG2 cells were exposed in vitro to tacrolimus, and validation of genes involved in insulin signaling and glucose metabolism was performed using specific arrays. These cells were then treated with the hypoglycemic agents, metformin, and insulin to assess for appropriate reversion of specific diabetogenic genes.

RESULTS

Insulin signaling and secretion were the most commonly dysregulated pathways that overlapped with diabetes in transplant recipients. KRAS, GRB2, PCK2, BCL2L1, INSL3, DOK3, and PTPN1 were among the most significantly upregulated genes in both immunosuppression and diabetes subsets and were appropriately reverted by metformin as confirmed in vitro.

CONCLUSIONS

We discovered that the significantly dysregulated genes in the context of immunosuppression are implicated in insulin signaling and insulin secretion, as a manifestation of pancreatic β-cell function. In vitro validation confirmed key diabetes-related genes in the context of immunosuppression. Further analysis and in vitro validation revealed that metformin optimally reverts diabetogenic genes dysregulated in the context of immunosuppression. The optimal therapeutic management of posttransplant diabetes mellitus needs to be further investigated, taking into account the mechanistic impact of immunosuppressants.

Management of metabolic alterations in adult kidney transplant recipients: A joint position statement of the Italian Society of Nephrology (SIN), the Italian Society for Organ Transplantation (SITO) and the Italian Diabetes Society (SID)

Chronic metabolic alterations such as post-transplant diabetes mellitus (PTDM), dyslipidaemias and overweight/obesity significantly impact on kidney transplant (KT) outcomes. This joint position statement is based on the evidence on the management of metabolic alterations in KT recipients (KTRs) published after the release of the 2009 KDIGO clinical practice guideline for the care of KTRs. Members of the Italian Society of Nephrology (SIN), the Italian Society for Organ Transplantation (SITO) and the Italian Diabetes Society (SID) selected to represent professionals involved in the management of KTRs undertook a systematic review of the published evidence for the management of PTDM, dyslipidaemias and obesity in this setting. The aim of this work is to provide an updated review of the evidence on the prevention, diagnosis and treatment of metabolic alterations in KTRs, in order to support physicians, patients and the Healthcare System in the decision-making process when choosing among the various available options.

Serum magnesium, hepatocyte nuclear factor 1β genotype and post-transplant diabetes mellitus: a prospective study

BACKGROUND

Retrospective studies suggest that tacrolimus-induced hypomagnesaemia is a risk factor for post-transplant diabetes mellitus (PTDM), but prospective studies are lacking.

METHODS

This was a prospective study with measurements of serum magnesium and tacrolimus at pre-specified time points in the first year after living donor kidney transplantation (KT). The role of single nucleotide polymorphisms (SNPs) in hepatocyte nuclear factor 1β (HNF1β) was also explored because HNF1β regulates insulin secretion and renal magnesium handling. Repeated measurement and regression analyses were used to analyse associations with PTDM.

RESULTS

In our cohort, 29 out of 167 kidney transplant recipients developed PTDM after 1 year (17%). Higher tacrolimus concentrations were significantly associated with lower serum magnesium and increased risk of hypomagnesaemia. Patients who developed PTDM had a significantly lower serum magnesium trajectory than patients who did not develop PTDM. In multivariate analysis, lower serum magnesium, age and body mass index were independent risk factors for PTDM. In recipients, the HNF1β SNP rs752010 G > A significantly increased the risk of PTDM [odds ratio (OR) = 2.56, 95% confidence interval (CI) 1.05-6.23] but not of hypomagnesaemia. This association lost significance after correction for age and sex (OR = 2.24, 95% CI 0.90-5.57). No association between HNF1β SNPs and PTDM was found in corresponding donors.

CONCLUSIONS

A lower serum magnesium in the first year after KT is an independent risk factor for PTDM. The HNF1β SNP rs752010 G > A may add to this risk through an effect on insulin secretion rather than hypomagnesaemia, but its role requires further confirmation.

Linagliptin plus insulin for hyperglycemia immediately after renal transplantation: A comparative study

AIMS

Post-renal-transplanted patients frequently present hyperglycemia immediately after the procedure. The goal of this work was to evaluate the effect of linagliptin + insulin in post-renal-transplanted patients with hyperglycemia.

METHODS

Retrospective comparative study in post-renal transplanted patients with hyperglycemia after transplantation who were treated with linagliptin 5 mg daily plus insulin vs insulin alone for 5 days after renal transplantation with hyperglycemia. Main outcomes were glucose levels, insulin dose and severity of hypoglycemia.

RESULTS

There were 14 patients treated with linagliptin + insulin and 14 patients treated only with insulin. Glucose levels and insulin doses were lower in the linagliptin + insulin group in comparison with the insulin alone group, 131.0 ± 15.1 vs 191.1 ± 22.5 mg/dl (7.27 ± 0.84 vs 10.61 ± 1.25 mmol/l) and 37.5 ± 6.3 vs 24.2 ± 6.6 U, respectively (p < 0.05). Hypoglycemia was less severe in the linagliptin + insulin group, 65.1 ± 2.2 vs 54.2 ± 3.3 mg/dl (3.61 ± 0.12 vs 3.00 ± 3.3 ± 0.18 mmol/l), p 0.036.

CONCLUSIONS

The combination of linagliptin + insulin provided better glycemic control with a lower insulin dose and less severe hypoglycemia in comparison to insulin alone in patients with hyperglycemia immediately after renal transplantation.

New-Onset Diabetes and Preexisting Diabetes Are Associated With Comparable Reduction in Long-Term Survival After Liver Transplant: A Machine Learning Approach

OBJECTIVE

To identify key predictors and survival outcomes of new-onset diabetes after transplant (NODAT) in liver transplant (LT) recipients by using the Scientific Registry of Transplant Recipients.

PATIENTS AND METHODS

Data of all adult LT recipients between October 1, 1987, and March 31, 2016, were analyzed using various machine learning methods. These data were divided into training (70%) and validation (30%) data sets to robustly determine predictors of NODAT. The long-term survival of patients with NODAT relative to transplant recipients with preexisting diabetes and those without diabetes was assessed.

RESULTS

Increasing age (odds ratio [OR], 1.01; 95% CI, 1.00-1.02; P≤.001), male sex (OR, 1.09; 95% CI, 1.05-1.13; P=.03), and obesity (OR, 1.13; 95% CI, 1.08-1.18; P<.001) were significantly associated with NODAT. Sirolimus as a primary immunosuppressant carried a 33% higher risk of NODAT than did tacrolimus (OR, 1.33; 95% CI, 1.22-1.45; P<.001) at 1 year after LT. Patients with NODAT had significantly decreased 10-year survival than did those without diabetes (63.0% vs 74.9%; P<.001), similar to survival in patients with diabetes before LT (58.9%).

CONCLUSION

Using a machine learning approach, we found that older, male, and obese recipients are at especially higher risk of NODAT. Donor features do not affect risk. In addition, sirolimus-based immunosuppression is associated with a significantly higher risk of NODAT than other immunosuppressants. Most importantly, NODAT adversely affects long-term survival after LT in a manner similar to preexisting diabetes, indicating the need for more aggressive care and closer follow-up.

Association of Body Mass Index and the Risk of New-Onset Diabetes After Kidney Transplantation: A Meta-analysis

OBJECTIVE

To comprehensively examine the correlation between body mass index (BMI) and the risk of new-onset diabetes after kidney transplantation (NODAT).

METHODS

The electronic databases Pubmed, Embase, and Cochrane Library, updated in December 2016, were searched, and a literature review was conducted as well to identify relevant research studies. With the use of R 3.12 software, the association between BMI and NODAT risk was analyzed by means of a meta-analysis, with the mean differences (MDs) and their 95% confidence intervals (CIs) as effect indexes. Publication bias was assessed with the use of the Egger test. A sensitivity analysis was performed by excluding 1 study at a time. And the overall morbidity of NODAT was calculated.

RESULTS

In the meta-analysis, 55 eligible studies involving 15,458 kidney transplantation cases were included. After the heterogeneity test, the random-effects model was used to calculate the pooled results of the effect indexes. The results of the meta-analysis showed that BMI was an independent risk factor of NODAT (MD, 1.88; 95% CI, 1.48-2.27). No publication bias was found among the included studies (t = 0.3417; P = 0.7339). The sensitivity analysis revealed that the pooled MD did not reverse after ignoring 1 study at a time. In addition, the overall morbidity of NODAT was 21% (95% CI, 21%-23%).

CONCLUSIONS

Our results suggest that BMI is an independent risk factor for NODAT.

Impact of Immunosuppression on the Metagenomic Composition of the Intestinal Microbiome: a Systems Biology Approach to Post-Transplant Diabetes

Solid organ transplantation (SOT) outcomes have continued to improve, although long-term use of immunosuppressants can lead to complications such as diabetes, compromising post-transplant outcomes. In this study, we have characterized the intestinal microbiome (IM) composition at the metagenomic level in the context of hyperglycemia induced by immunosuppressants. Sprague-Dawley rats were subjected to doses of tacrolimus and sirolimus that reliably induce hyperglycemia and an insulin-resistant state. Subsequent exposure to probiotics resulted in reversal of hyperglycemia. 16S rRNA and metagenomic sequencing of stool were done to identify the bacterial genes and pathways enriched in immunosuppression. Bacterial diversity was significantly decreased in sirolimus-treated rats, with 9 taxa significantly less present in both immunosuppression groups: Roseburia, Oscillospira, Mollicutes, Rothia, Micrococcaceae, Actinomycetales and Staphylococcus. Following probiotics, these changes were reversed to baseline. At the metagenomic level, the balance of metabolism was shifted towards the catabolic side with an increase of genes involved in sucrose degradation, similar to diabetes. Conversely, the control rats had greater abundance of anabolic processes and genes involved in starch degradation. Immunosuppression leads to a more catabolic microbial profile, which may influence development of diabetes after SOT. Modulation of the microbiome with probiotics may help in minimizing adverse long-term effects of immunosuppression.

New-Onset Diabetes After Kidney Transplantation and Pretransplant Hypomagnesemia

AIM

Hypomagnesemia is a frequent finding in kidney transplant patients and plays a causal role in insulin resistance and diabetes. The aim of this study was to investigate whether the pretransplant magnesium (Mg) level is a risk factor for the development of new-onset diabetes after kidney transplantation (NODAT) and the presence of relationship between pretransplant hypomagnesemia and the development period of NODAT.

METHODS

Four hundred and nineteen nondiabetic renal transplant recipients were evaluated retrospectively. The patients were divided into NODAT and non-NODAT groups. The time of diagnosis of patients with NODAT was divided into 0 to 3, 3 to 6, 6 to 12 months, and after 12 months. Patients' characteristics and pretransplant Mg levels in NODAT were compared with non-NODAT, and it was investigated whether pretransplant hypomagnesemia was a risk factor for the development of NODAT.

RESULTS

Totally 70 (16.6%) patients (36 female [F], mean age 51.7 ± 8.2 years) were diagnosed with NODAT. Three hundred and forty-nine patients (115 F, mean age 43.2 ± 12.5 years) did not have NODAT. Pretransplant mean Mg level was 1.97 ± 0.40 mg/dL in patients with NODAT, while it was 2.5 ± 0.45 mg/dL in non-NODAT patients (P < .001). Serum Mg level was found to be similar in subgroups according to the development period of NODAT (P = .07). When patients were stratified according to quartiles of Mg level, the frequency of NODAT was significantly higher in patients in the lower quartile (Mg < 2.1 mg/dL; P < .001). Older age, high body mass index, and low pretransplant serum Mg levels were established as risk factors for developing NODAT. According to the quartile of Mg level, the risk of developing NODAT was highest in the lowest quartile.

CONCLUSION

Pretransplant hypomagnesemia is an independent risk factor of NODAT. Therefore, it is necessary to closely monitor the Mg levels in the posttransplant period.

Risk factors of metabolic syndrome after liver transplantation

BACKGROUND

Liver transplantation is a treatment of choice for both acute and chronic liver failure. Accompanied with the increase of long-term survival rates of recipients, metabolic syndrome and its individual components, including obesity, hyperglycemia, hypertension and hyperlipidemia, have become more frequent post liver transplantation. Here we reviewed the literature concerning the risk factors for the development of metabolic complications in liver recipients.

DATA SOURCES

PubMed was searched for English-language articles published from January 2000 to June 2015. The search criteria focused on risk factors for metabolic syndrome after liver transplantation.

RESULT

The risk factors of metabolic syndrome in liver recipients include older age, obesity, pre-transplantation diabetes mellitus, hepatitis C virus infection, certain genetic polymorphisms and the use of immunosuppressive drugs.

CONCLUSION

Active intervention of the risk factors will reduce the occurrence rate of metabolic syndrome after liver transplantation and improve the recipients' quality of life.

The incidence of posttransplantation diabetes mellitus during follow-up in kidney transplant recipients and relationship to Fok1 vitamin D receptor polymorphism

BACKGROUND

Posttransplantation diabetes mellitus (PTDM) is a common, serious complication of kidney transplantation. The purpose of this study was to investigate the incidence of and risk factors for PTDM in relationship to Fok1 vitamin D receptor (VDR) polymorphisms.

METHODS

One hundred five kidney transplant recipients with normal glucose values before transplantation were recruited for this study. All patients underwent fasting plasma glucose (FPG) determinations followed by oral glucose tolerance tests (OGTTs) among normal FPG recipients. Every recipient underwent Fok1 VDR polymorphism analysis using polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP).

RESULTS

Among 105 recipients, 16 (15.24%) developed new-onset PTDM within 6 months after kidney transplantation. Compared with 89 non-PTDM recipients, the mean age was significantly higher among recipients with PTDM: 47.81 ± 15.54 vs 36.62 ± 11.43 years (P = .001). Patients treated with tacrolimus were more susceptible to PTDM (56.25% vs 28.09%; P = .027). The distribution frequencies of Fok1 genotypes in this cohort followed the Hardy-Weinberg equilibrium. The frequencies of 3 genotypes (FF/Ff/ff; P = .040) and 2 alleles (F/f; P = .009) differed between the 2 groups. Multivariate analysis by logistic regression showed age older than 40 years (odds ratio, 7.774; P = .005), VDR Fok1 f allele (odds ratio, 11.765; P = .012), and tacrolimus therapy (odds ratio, 7.499; P = .007) to be related to the development of PTDM.

CONCLUSIONS

The incidence of newly diagnosed PTDM in this study was 15.24%. Fok1 VDR polymorphism was a genetic marker predicting PTDM risk. Age older than 40 years and tacrolimus were independent risk factors for PTDM.