Matrix Metalloproteinase Gene Polymorphisms and New-Onset Diabetes After Kidney Transplantation in Korean Renal Transplant Subjects

Genetic and Epigenetic Associations with Post-Transplant Diabetes Mellitus

Post-transplant diabetes mellitus (PTDM) is a common complication of solid organ transplantation. PTDM prevalence varies due to different diabetes definitions. Consensus guidelines for the diagnosis of PTDM have been published based on random blood glucose levels, glycated hemoglobin (HbA1c), and oral glucose tolerance test (OGTT). The task of diagnosing PTDM continues to pose challenges, given the potential for diabetes to manifest at different time points after transplantation, thus demanding constant clinical vigilance and repeated testing. Interpreting HbA1c levels can be challenging after renal transplantation. Pre-transplant risk factors for PTDM include obesity, sedentary lifestyle, family history of diabetes, ethnicity (e.g., African-Caribbean or South Asian ancestry), and genetic risk factors. Risk factors for PTDM include immunosuppressive drugs, weight gain, hepatitis C, and cytomegalovirus infection. There is also emerging evidence that genetic and epigenetic variation in the organ transplant recipient may influence the risk of developing PTDM. This review outlines many known risk factors for PTDM and details some of the pathways, genetic variants, and epigenetic features associated with PTDM. Improved understanding of established and emerging risk factors may help identify people at risk of developing PTDM and may reduce the risk of developing PTDM or improve the management of this complication of organ transplantation.

Association between Genetic Polymorphisms and Risk of Kidney Posttransplant Diabetes Mellitus: A Systematic Review and Meta-Analysis

OBJECTIVES

The purpose of this study was to clarify the role of genetic factors on posttransplant diabetes mellitus (PTDM) risk.

METHODS

Relevant publications were systematically retrieved from PubMed, EMBASE, and the Cochrane Library up to December 2020. Data from eligible case-control and cohort studies were extracted for qualitative and quantitative analyses. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the association between gene polymorphisms and PTDM in the quantitative meta-analysis.

RESULTS

A total of 43 eligible articles were identified, and 16 studies on 9 DNA variants from 8 genes were included in the meta-analysis. TCF7L2 rs7903146 was significantly associated with PTDM risk in 5 genetic models (OR (95% CI): allelic: 1.59 (1.17-2.16), P=0.003; dominant recessive: 1.62 (1.14, 2.31), P=0.007; recessive: 1.87 (1.18, 2.94), P=0.007; homozygote: 2.21 (1.23, 3.94), P=0.008; and heterozygote 1.50 (1.08, 2.10), P=0.017). KCNQ1 rs2237892 was significantly correlated with PTDM risk in 3 genetic models (allelic: 0.68 (0.58, 0.81), P < 0.001; dominant: 0.6 (049, 0.74), P < 0.001; and heterozygote: 0.61 (0.48, 0.76), P < 0.001). KCNJ11 rs5219 was significantly linked with PTDM in the recessive genetic model (1.59 (1.01, 2.50), P=0.047). No significant correlations of PTDM with TCF7L2 rs12255372, SLC30A8 rs13266634, PPARγ rs1801282, CDKN2A/B rs10811661, HHEX rs1111875, and IGF2BP2 rs4402960 polymorphisms were found.

CONCLUSIONS

The gene polymorphisms of TCF7L2 rs7903146, KCNQ1 rs2237892, and KCNJ11 rs5219 may predispose kidney transplant recipients to PTDM. Large sample size studies on diverse ethnic populations were warranted to confirm our findings.

Genetic Variants Associated With Immunosuppressant Pharmacokinetics and Adverse Effects in the DeKAF Genomics Genome-wide Association Studies

BACKGROUND

The immunosuppressants tacrolimus and mycophenolate are important components to the success of organ transplantation, but are also associated with adverse effects, such as nephrotoxicity, anemia, leukopenia, and new-onset diabetes after transplantation. In this report, we attempted to identify genetic variants which are associated with these adverse outcomes.

METHODS

We performed a genome-wide association study, using a genotyping array tailored specifically for transplantation outcomes containing 722 147 single nucleotide polymorphisms, and 2 cohorts of kidney allograft recipients-a discovery cohort and a confirmation cohort-to identify and then confirm genetic variants associated with immunosuppressant pharmacokinetics and adverse outcomes.

RESULTS

Several genetic variants were found to be associated with tacrolimus trough concentrations. We did not confirm variants associated with the other phenotypes tested although several suggestive variants were identified.

CONCLUSIONS

These results show that adverse effects associated with tacrolimus and mycophenolate are complex, and recipient risk is not determined by a few genetic variants with large effects with but most likely are due to many variants, each with small effect sizes, and clinical factors.

Risk factors for new-onset diabetes mellitus after kidney transplantation (NODAT): a Brazilian single center study

OBJECTIVES

This study aims to verify the new-onset diabetes after kidney transplant (NODAT) incidence in recipients within 1 year after kidney transplantation from a single center in Southern Brazil and to assess the associated conditions.

SUBJECTS AND METHODS

A retrospective study of 258 post-renal transplant patients was performed. Demographic (gender, age, ethnic background) and clinical (origin of graft, associated infections, body mass index (BMI) at transplant time and 6 and 12 months after, causes of renal failure, and comorbidities) data were analyzed. All patients were on tacrolimus, mycophenolate mofetil, and prednisone treatment. Patients with and without NODAT were compared.

RESULTS

A NODAT incidence of 31.2% was noted 1 year post transplantation. In the univariate analysis, patients with NODAT were older (p = 0.001), mostly had African-American ethnic background (p = 0.02), and had renal failure secondary to high blood pressure (HBP) (p = 0.001). The group of patients with NODAT also had more incidence of post-transplant HBP (p = 0.01), heart failure (p = 0.02), and dyslipidemia (p = 0.001). Logistic regression showed that African-American ethnic background, post-transplant HBP, and dyslipidemia were independently associated with NODAT.

CONCLUSION

This study shows a NODAT incidence that is greater in patients with African-American ethnic background and that is associated with HBP and dyslipidemia.

Matrix metalloproteinase-2 gene polymorphisms are associated with ischemic stroke in a Hainan population

Ischemic stroke is a complex vascular disease, which has become 1 of the major causes of morbidity and mortality worldwide. More and more data showed that matrix metalloproteinases (MMPs), in particular, MMP-2 are deleterious after ischaemic stroke. This study investigated the relationship between MMP-2 and stroke risk in the Southern Chinese population.We evaluated single nucleotide polymorphisms (SNP) of MMP-2 in stroke patients in an association study using a case-control design. Six SNPs of MMP2 were selected and genotyped by Agena MassARRAY. SNPStats, Haploview was used to analyze genetic data.Two SNPs in the MMP-2 gene were significantly associated with stroke risk.For rs1132896 (C versus G allele), the C allele was significantly reduced stroke risk (OR = 0.56, 95% confidence intervals [95% CI] = 0.39-0.81, P = .002). The effect of the T allele of rs243849 was IS risk according to an additive genetic model (OR = 0.67, 95% CI = 0.47-0.96, P = .028). We did not found any strong linkage between the six SNPs (rs1132896, rs1053605, rs243849, rs243847, rs243832, rs7201)The results presented strongly indicate that MMP-2 genetic variants are an important mediator of stroke risk.

Drug-induced hyperglycaemia and diabetes: pharmacogenomics perspectives

Drug-induced diabetes is widely reported in clinical conditions, and it is becoming a global issue because of its potential to increase the risk of severe cardiovascular complications. However, which drug mechanisms exert their diabetogenic effects and why the effects present significant inter-individual differences remain largely unknown. Pharmacogenomics, which is the study of how genomic variation influences drug responses, provides an explanation for individual differences in drug-induced diabetes. We highlight that pharmacogenomics can be involved in regulating the expression of genes in signaling pathways related to the pharmacokinetics or pharmacodynamics of drugs or the pathogenesis of diabetes, contributing to the differences in drug-induced glucose impairment. The pharmacogenomics studies of the major diabetogenic drugs are reviewed, including calcineurin inhibitors, antipsychotics, hormones, and antihypertensive drugs. We intend to elucidate the genetic basis of drug-induced diabetes and pave the way for the precise use of these drugs in the clinic.