Defining a Methylation Signature Associated With Operational Tolerance in Kidney Transplant Recipients

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.

An exome-wide study of renal operational tolerance

Background

Renal operational tolerance is a rare and beneficial state of prolonged renal allograft function in the absence of immunosuppression. The underlying mechanisms are unknown. We hypothesized that tolerance might be driven by inherited protein coding genetic variants with large effect, at least in some patients.

Methods

We set up a European survey of over 218,000 renal transplant recipients and collected DNAs from 40 transplant recipients who maintained good allograft function without immunosuppression for at least 1 year. We performed an exome-wide association study comparing the distribution of moderate to high impact variants in 36 tolerant patients, selected for genetic homogeneity using principal component analysis, and 192 controls, using an optimal sequence-kernel association test adjusted for small samples.

Results

We identified rare variants of HOMER2 (3/36, FDR 0.0387), IQCH (5/36, FDR 0.0362), and LCN2 (3/36, FDR 0.102) in 10 tolerant patients vs. 0 controls. One patient carried a variant in both HOMER2 and LCN2. Furthermore, the three genes showed an identical variant in two patients each. The three genes are expressed at the primary cilium, a key structure in immune responses.

Conclusion

Rare protein coding variants are associated with operational tolerance in a sizable portion of patients. Our findings have important implications for a better understanding of immune tolerance in transplantation and other fields of medicine.ClinicalTrials.gov, identifier: NCT05124444.

"Transplantomics" for predicting allograft rejection: real-life applications and new strategies from Network Medicine

Although decades of the reductionist approach achieved great milestones in optimizing the immunosuppression therapy, traditional clinical parameters still fail in predicting both acute and chronic (mainly) rejection events leading to higher rates across all solid organ transplants. To clarify the underlying immune-related cellular and molecular mechanisms, current biomedical research is increasingly focusing on "transplantomics" which relies on a huge quantity of big data deriving from genomics, transcriptomics, epigenomics, proteomics, and metabolomics platforms. The AlloMap (gene expression) and the AlloSure (donor-derived cell-free DNA) tests represent two successful examples of how omics and liquid biopsy can really improve the precision medicine of heart and kidney transplantation. One of the major challenges in translating big data in clinically useful biomarkers is the integration and interpretation of the different layers of omics datasets. Network Medicine offers advanced bioinformatic-molecular strategies which were widely used to integrate large omics datasets and clinical information in end-stage patients to prioritize potential biomarkers and drug targets. The application of network-oriented approaches to clarify the complex nature of graft rejection is still in its infancy. Here, we briefly discuss the real-life clinical applications derived from omics datasets as well as novel opportunities for establishing predictive tests in solid organ transplantation. Also, we provide an original "graft rejection interactome" and propose network-oriented strategies which can be useful to improve precision medicine of solid organ transplantation.

Longitudinal Epigenome-Wide Analysis of Kidney Transplant Recipients Pretransplant and Posttransplant

Introduction

Kidney transplantation remains the gold standard of treatment for end-stage renal disease (ESRD), with improved patient outcomes compared with dialysis. Epigenome-Wide Association Analysis (EWAS) of DNA methylation may identify markers that contribute to an individual's risk of adverse transplant outcomes, yet only a limited number of EWAS have been conducted in kidney transplant recipients. This EWAS aimed to interrogate the methylation profile of a kidney transplant recipient cohort with minimal posttransplant complications, exploring differences in samples pretransplant and posttransplant.

Methods

We compared differentially methylated cytosine-phosphate-guanine sites (dmCpGs) in samples derived from peripheral blood mononuclear cells of the same kidney transplant recipients, collected both pretransplant and posttransplant (N = 154), using the Infinium MethylationEPIC microarray (Illumina, San Diego, CA). Recipients received kidneys from deceased donors and had a mean of 17 years of follow-up.

Results

Five top-ranked dmCpGs were significantly different at false discovery rate (FDR) adjusted P ≤ 9 × 10^-8; cg23597162 within JAZF1, cg25187293 within BTNL8, cg17944885, located between ZNF788P and ZNF625-ZNF20, cg14655917 located between ASB4 and PDK4 and cg09839120 located between GIMAP6 and EIF2AP3.

Conclusion

Five dmCpGs were identified at the generally accepted EWAS critical significance level of FDR adjusted P (P _FDRadj) ≤ 9 × 10^-8, including cg23597162 (within JAZF1) and cg17944885, which have prior associations with chronic kidney disease (CKD). Comparing individuals with no evidence of posttransplant complications (N = 105) demonstrated that 693,555 CpGs (89.57%) did not display any significant difference in methylation (P _FDRadj ≥ 0.05), thereby this study establishes an important reference for future epigenetic studies that seek to identify markers of posttransplant complications.

Epigenetic Regulation in Kidney Transplantation

Kidney transplantation is a standard care for end stage renal disease, but it is also associated with a complex pathogenesis including ischemia-reperfusion injury, inflammation, and development of fibrosis. Over the past decade, accumulating evidence has suggested a role of epigenetic regulation in kidney transplantation, involving DNA methylation, histone modification, and various kinds of non-coding RNAs. Here, we analyze these recent studies supporting the role of epigenetic regulation in different pathological processes of kidney transplantation, i.e., ischemia-reperfusion injury, acute rejection, and chronic graft pathologies including renal interstitial fibrosis. Further investigation of epigenetic alterations, their pathological roles and underlying mechanisms in kidney transplantation may lead to new strategies for the discovery of novel diagnostic biomarkers and therapeutic interventions.

The applications of DNA methylation as a biomarker in kidney transplantation: a systematic review

BACKGROUND

Although kidney transplantation improves patient survival and quality of life, long-term results are hampered by both immune- and non-immune-mediated complications. Current biomarkers of post-transplant complications, such as allograft rejection, chronic renal allograft dysfunction, and cutaneous squamous cell carcinoma, have a suboptimal predictive value. DNA methylation is an epigenetic modification that directly affects gene expression and plays an important role in processes such as ischemia/reperfusion injury, fibrosis, and alloreactive immune response. Novel techniques can quickly assess the DNA methylation status of multiple loci in different cell types, allowing a deep and interesting study of cells' activity and function. Therefore, DNA methylation has the potential to become an important biomarker for prediction and monitoring in kidney transplantation.

PURPOSE OF THE STUDY

The aim of this study was to evaluate the role of DNA methylation as a potential biomarker of graft survival and complications development in kidney transplantation. MATERIAL AND METHODS: A systematic review of several databases has been conducted. The Newcastle-Ottawa scale and the Jadad scale have been used to assess the risk of bias for observational and randomized studies, respectively.

RESULTS

Twenty articles reporting on DNA methylation as a biomarker for kidney transplantation were included, all using DNA methylation for prediction and monitoring. DNA methylation pattern alterations in cells isolated from different tissues, such as kidney biopsies, urine, and blood, have been associated with ischemia-reperfusion injury and chronic renal allograft dysfunction. These alterations occurred in different and specific loci. DNA methylation status has also proved to be important for immune response modulation, having a crucial role in regulatory T cell definition and activity. Research also focused on a better understanding of the role of this epigenetic modification assessment for regulatory T cells isolation and expansion for future tolerance induction-oriented therapies.

CONCLUSIONS

Studies included in this review are heterogeneous in study design, biological samples, and outcome. More coordinated investigations are needed to affirm DNA methylation as a clinically relevant biomarker important for prevention, monitoring, and intervention.