Kidney transplant (KTx) biopsies showing transplant glomerulopathy (TG) (glomerular basement membrane double contours (cg) > 0)) and microvascular inflammation (MVI) in the absence of C4d staining and donor-specific antibodies (DSA)s do not fulfill the criteria for chronic active antibody-mediated rejection (CA-AMR) diagnosis and do not fit into any other Banff category. To investigate this, we initiated a multicenter intercontinental study encompassing 36 cases, comparing the immunomic and transcriptomic profiles of 14 KTx biopsies classified as cg+MVI DSA^-/C4d^- with 22 classified as CA-AMR DSA⁺/C4d⁺ through novel transcriptomic analysis using the NanoString Banff-Human Organ Transplant (B-HOT) panel and subsequent orthogonal subset analysis using two innovative 5-marker multiplex immunofluorescent panels. Nineteen genes were differentially expressed between the two study groups. Samples diagnosed with CA-AMR DSA⁺/C4d⁺ showed a higher glomerular abundance of natural killer cells and higher transcriptomic cell type scores for macrophages in an environment characterized by increased expression of complement-related genes (i.e., C5AR1) and higher activity of angiogenesis, interstitial fibrosis tubular atrophy, CA-AMR, and DSA-related pathways when compared to samples diagnosed with cg+MVI DSA^-/C4d^-. Samples diagnosed with cg+MVI DSA^-/C4d^- displayed a higher glomerular abundance and activity of T-cells (CD3⁺, CD3⁺CD8⁺, and CD3⁺CD8^-). Thus, we show that using novel multiomic techniques, KTx biopsies with cg+MVI DSA^-/C4d^- have a prominent T-cell presence and activity, putting forward the possibility that these represent a more T-cell-dominant phenotype.

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.

Hypothermic machine perfusion(HMP) is considered the gold standard in kidney preservation. Despite this, grafts from extended criteria donors(ECD-DBD) and donation after circulatory death(DCD) remain at high risk of delayed graft function(DGF). Normothermic machine perfusion(NMP) during the preservation process could alternatively preserve physiological activity. We investigated the value of additional NMP to HMP in ECD-DBD and DCD kidney transplantation. This is a single-centre, open-label, superiority, randomized controlled trial. Patients were randomized to receive a kidney that was either preserved on HMP and two hours of end-ischemic HMP+NMP(intervention group) or HMP only(control group). Primary outcome was the incidence of immediate graft function(IGF). A total of 80 patients were included in the intention-to-treat analysis, of which 41 received a kidney that was preserved on HMP and HMP+NMP and 39 received a graft that was preserved on HMP alone. Incidence of IGF was 16/41(39%) in HMP+NMP group compared to 19/39(49%) in the HMP group, with no significant difference between both groups(OR: 0.68, 95% CI: 0.28-1.64, p=0.38). There was no statistically significant difference in any of the secondary outcomes. The addition of two hours end-ischemic NMP does not improve early graft outcomes in kidney transplantation compared to HMP alone.

Background: Human donor kidneys release (pro)renin, erythropoietin (EPO), active vitamin D, and urodilatin during normothermic machine perfusion (NMP). However, whether the endocrine function of donor kidneys is associated with post‐transplant kidney function is unclear.Methods: We studied 28 donor kidneys, including seven from donation after brain death (DBD) donors and 21 from donation after circulatory death (DCD) donors. Prior to transplantation, we measured levels of (pro)renin, EPO, 1,25(OH)₂D in the perfusate, and urodilatin in urine during NMP. Hormone release rates were compared between kidneys with and without delayed graft function (DGF), and correlations were assessed between hormone release rates and donor characteristics and transplant outcome, including DGF duration, serum creatinine levels at 1‐week post‐transplant, and estimated glomerular filtration rate at 1‐month post‐transplant.Results: DBD kidneys secreted significantly less EPO and more active vitamin D than DCD kidneys. Kidneys with DGF exhibited significantly higher release rates of active vitamin D and lower release rates of urodilatin compared to those without DGF. In addition, EPO release rate was positively correlated with serum creatinine levels at 1‐week post‐transplant. Finally, urodilatin release rates were negatively correlated with DGF duration and positively correlated with urine output.Conclusions: Urodilatin release in urine and EPO and active vitamin D release in perfusate during NMP may serve as potential biomarkers for predicting early post‐transplant outcomes.Trial Registration: ClinicalTrials.gov identifier: NCT04882254

Molecular classifiers are a promising tool to refine the diagnosis of antibody-mediated rejection (ABMR) and T-cell–mediated rejection (TCMR) after kidney transplantation. Despite this potential, the integration of molecular classifiers in transplant clinics has been slow, in part because of the complexity of current assays and lack of a consensus platform. Herein, we aimed to develop and validate sparse molecular classifiers for ABMR and TCMR using allograft tissue. In a discovery cohort of 224 kidney transplant biopsies, lasso regression was applied on microarray gene expression data to derive a molecular classifier for ABMR and TCMR, respectively. A 2-gene classifier for ABMR (PLA1A, GNLY) and a 2-gene classifier for TCMR (IL12RB1, ARPC1B) were identified. External validation (n = 403 biopsies) demonstrated preserved diagnostic accuracy for ABMR (area under the receiver operating characteristic curve [ROC-AUC]: 0.80, 95% confidence interval [CI]: 0.75–0.85) and TCMR (ROC-AUC: 0.83, 95% CI: 0.77–0.89), with the possibility to discriminate between pure and mixed rejection phenotypes. Complementary to their diagnostic potential, the molecular classifiers associated with accelerated graft loss in a second validation cohort (n = 282 biopsies) and identified allografts at risk for failure with histological lesions that did not reach the Banff thresholds for rejection. The computational approach was further validated using the Banff Human Organ Transplant (B-HOT) gene panel in 2 independent biopsy cohorts that were analyzed on the Nanostring nCounter platform (n = 66 and n = 80, respectively). Rigid variable selection strategies can yield sparse molecular classifiers for allograft rejection phenotypes with preserved accuracy and prognostic value across different molecular diagnostic platforms, which may facilitate their interpretation and clinical implementation.

Visual exploration of complex data helps interpretation, especially in the case of omics data analysis in life sciences and clinical research. Generating and analysing omics data requires bioinformatic skills, while they are interpreted by domain experts, for whom parsing large and complex data structures may be challenging. However, outcomes of visual analytics are often difficult to quantify, which emphasises precision and reproducibility, especially for research on human diseases. Here, we propose a workflow combining a reproducible computational environment with a dedicated visualisation functionality for systems biology diagrams. By linking the Galaxy with the MINERVA Platform, we visualise and explore COVID-19 transcriptomic data to demonstrate the utility of our workflow. Visualised data recapitulate findings of the original publication and offer new insights about the COVID-19 pathology. Our results offer a blueprint for quick prototyping of computational workflows that facilitate communication and exploration of complex data in biomedical research.