Pre-Transplant CDKN2A Expression in Kidney Biopsies Predicts Renal Function and Is a Future Component of Donor Scoring Criteria

Abstract

CDKN2A is a proven and validated biomarker of ageing which acts as an off switch for cell proliferation. We have demonstrated previously that CDKN2A is the most robust and the strongest pre-transplant predictor of post- transplant serum creatinine when compared to “Gold Standard” clinical factors, such as cold ischaemic time and donor chronological age. This report shows that CDKN2A is better than telomere length, the most celebrated biomarker of ageing, as a predictor of post-transplant renal function. It also shows that CDKN2A is as strong a determinant of post-transplant organ function when compared to extended criteria (ECD) kidneys. A multivariate analysis model was able to predict up to 27.1% of eGFR at one year post-transplant (p = 0.008). Significantly, CDKN2A was also able to strongly predict delayed graft function. A pre-transplant donor risk classification system based on CDKN2A and ECD criteria is shown to be feasible and commendable for implementation in the near future.

A molecular signature for delayed graft function

“…Further analysis of an additional model (DGF pre‐ vs. postperfusion and IGF pre‐ vs. postperfusion, Model 2) revealed that the transcriptional response to reperfusion injury was similar for allografts, irrespective of their post‐transplant outcome. Resolution of transplant‐related stresses and restoration of physiological homeostasis were, however, exacerbated in those that manifested DGF (Supporting Information Tables S5–S10 in Data S5) suggesting, that donor‐organ resilience to stress may be a key determinant of DGF, which is congruent with recent findings linking organ function to biological age (Gingell‐Littlejohn et al, 2013; McGuinness et al, 2016). Significantly, this is supported by the observation that the transcriptional amplitude of change in DGF signature genes following reperfusion was significantly larger than in IGF.…”

“…From a clinical perspective, this also suggests that these effects are driven by donor characteristics, which may therefore be even more discriminating than reperfusion injury itself. Correspondingly, BioAge in the preperfusion biopsy analyses appeared to be a significant determinant of post‐transplant allograft function, in keeping with previous observations centring on the CDKN2 and CDKN1 loci (Gingell‐Littlejohn et al, 2013; McGuinness et al, 2016). Furthermore, it suggests strongly that increased allograft biological age is contributory to less successful outcomes in renal transplantation and poorer post‐transplant performance.…”

“…However, each factor was independently associated with unique transcript expression (Figure 1d). CDKN2A/p16 ink4a expression correlated with DGF occurrence and long‐term allograft function post‐transplantation, when used as a composite BioAge (pretransplant donor risk classification system using CDKN2A and ECD criteria) (Gingell‐Littlejohn et al, 2013; McGuinness et al, 2016). No common targets were associated with BioAge and DGF risk factors.…”

“…It is possible that this inability to sufficiently resolve inflammatory responses manifests as DGF and could be attributed to a differential response to reperfusion injury by biologically older allografts and decreased resilience to stress (Gingell‐Littlejohn et al, 2013; McGuinness et al, 2016; O'Neill et al, 2015; Salvadori, Rosso, & Bertoni, 2015). Such a scenario is supported by the reperfusion signature associated with cellular events (metabolic shift, autophagy, RNA metabolism, ribosomal biogenesis, protein synthesis) activated in response to environmental stress (ischaemic damage, nutrient deprivation and hypoxia), which facilitates cellular repair after insult, or induces apoptosis if the damage is too severe.…”

“…We have previously developed the use of renal allografts as an in vivo model to study healthy tissue ageing in humans, whose physiological function can be tracked longitudinally to demonstrate that allograft biological age is more important than chronological age in prognostication of post‐transplant allograft performance (Gingell‐Littlejohn et al, 2013; McGuinness et al, 2016). …”