Pretransplant Transcriptome Profiles Identify among Kidneys with Delayed Graft Function Those with Poorer Quality and Outcome

Abstract

Robust biomarkers are needed to identify donor kidneys with poor quality associated with inferior early and longer-term outcome. The occurrence of delayed graft function (DGF) is most often used as a clinical outcome marker to capture poor kidney quality. Gene expression profiles of 92 preimplantation biopsies were evaluated in relation to DGF and estimated glomerular filtration rate (eGFR) to identify preoperative gene transcript changes associated with short-term function. Patients were stratified into those who required dialysis during the first week (DGF group) versus those without (noDGF group) and subclassified according to 1-month eGFR of >45 mL/min (eGFR hi ) versus eGFR of ≤45 mL/min (eGFR lo ). The groups and subgroups were compared in relation to clinical donor and recipient variables and transcriptome-associated biological pathways. A validation set was used to confirm target genes. Donor and recipient characteristics were similar between the DGF versus noDGF groups. A total of 206 probe sets were significant between groups (P < 0.01), but the gene functional analyses failed to identify any significantly affected pathways. However, the subclassification of the DGF and noDGF groups identified 283 probe sets to be significant among groups and associated with biological pathways. Kidneys that developed postoperative DGF and sustained an impaired 1-month function (DGF lo group) showed a transcriptome profile of significant immune activation already preimplant. In addition, these kidneys maintained a poorer transplant function throughout the first-year posttransplant. In conclusion, DGF is a poor marker for organ quality and transplant outcome. In contrast, preimplant gene expression profiles identify "poor quality" grafts and may eventually improve organ allocation.

Prediction of kidney graft failure using clinical scoring tools

“…The key variables common in most scoring systems are donor age, history of hypertension and kidney function. The predictive weight of these clinical variables is biologically meaningful and corroborates the key importance of organ quality as defined by nephron supply, extent of established injury and repair capacity, on long‐term graft performance .…”

“…However, it also suggests the need for large patient numbers to see an effect of DGF on long‐term outcome. It stresses differences in the relative weight of risk factors to predict DGF vs. long‐term graft function and underlines that DGF does not necessarily translate into poor long‐term outcome, at least in our patient group .…”

“…However, significance in graft survival curves based on categorized score levels is not sufficient for truly individualized organ allocation and patient management. Given the inherent interdependence of clinical variables such as age and co‐morbidities the addition of molecular diagnostics or histopathology readings may potentially improve the algorithms and increase the predictive accuracy in the future .…”

Identification of Biomarkers to Assess Organ Quality and Predict Posttransplantation Outcomes

“…We recently reported the identification of a subset of delayed graft function (DGF) kidney graft with increased expression of a number of genes involved in antigen processing and presentation and selection/activation of T-cell mediated cytotoxicity in pre-implantation biopsies (10). Although, these patients recovered function, first year post-transplant eGFR remained nearthe 45 mL/min/1.73m 2 cut-off and did not significantly improve.…”

“…We also identified a subset of non-DGF patients with similar graft performance during the same period of time. Here, we expand on our previously published results (10), by increasing the number of subjects as well as length of clinical follow-up and investigate the molecular basis behind this occurrence in order to identify potential molecular biomarkers for use in pre-transplant donor quality assessment.…”