Prognostic Value of Proinflammatory Markers in Patients After Kidney Transplantation in Relation to the Presence of Diabetes

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.

Genome-wide post-transcriptional regulation of bovine mammary gland response to Streptococcus uberis

MicroRNAs (miRNAs) as post-transcriptionally regulators of gene expression have been shown to be critical regulators to fine-tuning immune responses, besides their criteria for being an ideal biomarker. The regulatory role of miRNAs in responses to most mastitis-causing pathogens is not well understood. Gram-positive Streptococcus uberis (Str. uberis), the leading pathogen in dairy herds, cause both clinical and subclinical infections. In this study, a system biology approach was used to better understand the main post-transcriptional regulatory functions and elements of bovine mammary gland response to Str. uberis infection. Publicly available miRNA-Seq data containing 50 milk samples of the ten dairy cows (five controls and five infected) were retrieved for this current research. Functional enrichment analysis of predicted targets revealed that highly confident responsive miRNAs (4 up- and 19 downregulated) mainly regulate genes involved in the regulation of transcription, apoptotic process, regulation of cell adhesion, and pro-inflammatory signaling pathways. Time series analysis showed that six gene clusters significantly differed in comparisons between Str. uberis-induced samples with controls. Additionally, other bioinformatic analysis, including upstream network analysis, showed essential genes, including TP53 and TGFB1 and some small molecules, including glucose, curcumin, and LPS, commonly regulate most of the downregulated miRNAs. Upregulated miRNAs are commonly controlled by the most important genes, including IL1B, NEAT1, DICER1 enzyme and small molecules including estradiol, tamoxifen, estrogen, LPS, and epigallocatechin. Our study used results of next-generation sequencing to reveal key miRNAs as the main regulator of gene expression responses to a Gram-positive bacterial infection. Furthermore, by gene regulatory network (GRN) analysis, we can introduce the common upregulator transcription factor of these miRNAs. Such milk-based miRNA signature(s) would facilitate risk stratification for large-scale prevention programs and provide an opportunity for early diagnosis and therapeutic intervention.

Diabetes and Cardiovascular Risk in Renal Transplant Patients

End-stage kidney disease (ESKD) is a main public health problem, the prevalence of which is continuously increasing worldwide. Due to adverse effects of renal replacement therapies, kidney transplantation seems to be the optimal form of therapy with significantly improved survival, quality of life and diminished overall costs compared with dialysis. However, post-transplant patients frequently suffer from post-transplant diabetes mellitus (PTDM) which an important risk factor for cardiovascular and cardiovascular-related deaths after transplantation. The management of post-transplant diabetes resembles that of diabetes in the general population as it is based on strict glycemic control as well as screening and treatment of common complications. Lifestyle interventions accompanied by the tailoring of immunosuppressive regimen may be of key importance to mitigate PTDM-associated complications in kidney transplant patients. More transplant-specific approach can include the exchange of tacrolimus with an alternative immunosuppressant (cyclosporine or mammalian target of rapamycin (mTOR) inhibitor), the decrease or cessation of corticosteroid therapy and caution in the prescribing of diuretics since they are independently connected with post-transplant diabetes. Early identification of high-risk patients for cardiovascular diseases enables timely introduction of appropriate therapeutic strategy and results in higher survival rates for patients with a transplanted kidney.

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.

Inflammatory and related biomarkers are associated with post-transplant diabetes mellitus in kidney recipients: a retrospective study

In this study, we investigate the association between selected inflammatory-related biomarkers and post-transplant hyperglycemia in kidney transplant recipients. This retrospective analysis comprises 852 patients receiving a kidney transplant at the Norwegian national transplant center between 2007 and 2012, all having a normal oral glucose tolerance test (OGTT) before transplantation. A diagnostic OGTT was performed 10 weeks post-transplant to examine the association between inflammation-related biomarkers and two-hour plasma glucose (2HPG) by multivariable linear regression models adjusting for BMI, age, graft function, fasting insulin levels, dosage of prednisolone, and concentration of calcineurin inhibitors. Six of 20 biomarkers were significantly associated with 2HPG in multivariate analyses showing strong associations with soluble tumor necrosis factor type 1 (P = 0.027), Pentraxin 3 (P = 0.019), macrophage migration inhibitory factor (P = 0.024), and endothelial protein C receptor (P = 0.001). These associated markers reflect several distinct but also overlapping pathways including activation of tumor necrosis factor, macrophages, and endothelial cells. The multinomial logistic regression model showed a clear association between the inflammatory biomarkers and post-transplant diabetes mellitus (PTDM). The association between a range of inflammation markers and PTDM suggests that these markers may be target for future studies on pathogenesis and perhaps also treatment of PTDM.

miR-155 regulates high glucose-induced cardiac fibrosis via the TGF-β signaling pathway

Cardiac fibrosis, as a pathological process, plays an important role in various cardiac diseases. microRNA-155 (miR-155) is one of the most important miRNAs, and previous studies have shown that it is a regulatory factor in various fibrotic diseases. However, the mechanism by which miR-155 affects myocardial fibrosis remains unclear. In this study, we aim to establish the biological function of miR-155 in myocardial fibrosis induced by diabetes in mice. We used normal C57BL/6 wild type (WT) and miR-155 knockout (KO) mice to establish the diabetic model by intraperitoneal injection of streptozotocin, and we utilized echocardiography to evaluate the cardiac function at 30 and 60 days post-modeling. Hematoxylin-eosin (HE) and sirius-red (SR) staining were used to evaluate the degree of myocardial lesions. Furthermore, we extracted cardiac fibroblasts (CFs) from the WT mice and transfected them with miR-155 inhibitors, mimics and negative control siRNAs to analyze the specific mechanism involved in the development of myocardial fibrosis. The results showed that miR-155 deficiency could prevent cardiac fibrosis induced by diabetes in mice and also that attenuated collagen synthesis is induced by high glucose (HG) in CFs. We found that miR-155 regulated cardiac fibrosis via the TGF-β1-Smad 2 signaling pathway. These findings suggest that miR-155 may be a therapeutic target for preventing cardiac fibrosis induced by diabetes.