Kidney transplant teams currently rely on donor age and a visual score of a biopsy to decide whether to use a marginal organ—but these tools often fail to predict which kidneys will work well long-term. This project aims to build a better prediction system by combining donor data with deeper molecular analysis of the biopsy tissue itself. The core problem is organ shortage. To expand the donor pool, surgeons increasingly accept kidneys from older or less healthy donors, but up to a third of these organs function poorly after transplant, leaving patients back on dialysis. Current decision-making tools are too crude to reliably distinguish a usable kidney from one that will fail. If successful, the research will deliver a free online risk calculator that gives transplant teams a more accurate, real-time prediction of graft outcome. It will also identify specific genes and immune cell patterns in the biopsy that signal future failure, pointing toward new drug targets to protect the kidney. The ultimate impact is straightforward: more transplants that last longer, fewer patients returning to dialysis, and a more efficient use of every donated organ.
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Research question: Can we identify biomarkers and mechanistic pathways to improve organ utilisation and kidney transplant outcomes? Background: End stage renal failure (ESRF) is a devastating condition that has a significant impact on patient's quality and quantity of life. Kidney transplantation is the optimal form of renal replacement therapy for most patients with ESRF, but organ shortage is a major problem. In an attempt to meet this shortfall, there has been increased utilisation of kidneys from older, more marginal donors. However, these organs have higher rates of delayed graft function and some organs do not provide good kidney function in the longer term. Basic donor demographic data and histological scoring of pre-implantation biopsies have been used to assist clinicians in the decision to use an organ, but these parameters do not provide an accurate prediction of whether a transplant will ultimately have good function. Aims and objectives: We have two overarching aims: Aim 1: To increase the utility of histopathological and demographic data to predict kidney transplant outcome, and to deliver an on-line risk calculator to assist clinical decision-making at the time of transplant. Aim 2: To identify novel biomarkers and mechanistic pathways that predict, or are associated with, kidney graft outcome to improve clinical decision making and reveal novel therapeutic targets. Specific Objectives and Methods: 1. To determine if the predictive value of the histological score generated on a pre-implantation biopsy can be improved by modeling the impact of adjusting the importance assigned to score parameters. 2. To ascertain if the combination of donor characteristics (as per the UK Donor risk index) and biopsy score (the standard Remuzzi score) can better predict outcomes using biostatistics to generate an on-line risk calculator. 3. To determine if bulk transcriptomic analysis (RNA sequencing) of pre-implantation biopsies can be used to identify a gene signature that predicts graft function. 4. To assess whether the use of second harmonics in two-photon microscopy can provide a rapid and accurate assessment of fibrosis in a pre-transplant kidney biopsy. 5. To investigate kidney biopsies using single cell RNA sequencing and mass cytometry to identify immune cell subsets and mechanistic pathways associated with poor graft outcome. Timelines for delivery: The discovery phase of Objective 1 (O1) will be delivered in year 1, the validation by year 3. O2 will be delivered by year 4, and O3-5 during year 5. Anticipated impact and dissemination: This project will generate an open access tool for the transplant community to assist clinical decision-making in organ utilisation. It will also provide mechanistic insights into the pathogenesis of DGF and chronic kidney disease. Ultimately, this will lead to more kidney transplants that last longer, keeping patients off dialysis. We will disseminate our findings via presentations at local and international scientific meetings and in journal publications. We will inform the patients and public of our research in the Cambridge Science Festival and at local NIHR Cambridge BRC open days and evenings.
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