The effect of genetic polymorphism in complement proteins on clinical renal transplant outcome

The number of people with kidney failure is increasing, with a 7% per year rise in patients on dialysis. For the majority of these patients the best treatment is kidney transplantation. Unfortunately the demand for transplant kidneys exceeds the number available and the transplant waiting list increases yearly. This situation is made worse by a steady rate of transplant failure requiring a return to dialysis or another transplant.
There is increasing evidence that modifying drug treatment can slow the progression of damage to a transplanted kidney. Unfortunately we are often late to recognise that damage is occurring at which point there may already be significant irreversible renal damage. Ideally we would be able to identify patients at risk at an early stage, prior to the development of significant damage, and alter treatments at this point. The main objective of this proposal is to develop a method by which risk of later problems can be predicted at the time of transplantation.
Studies have shown that differences between individuals at a genetic level can influence the outcome after transplantation. However, this work has yet to translate into improvements in patient care. We plan to use these genetic differences to predict the course of patients following kidney transplantation and to identify those patients at high or low risk of problems leading to graft damage. This would allow us to alter the intensity of monitoring and even use drug treatments to prevent damage developing. The work proposed in this application will define how powerful this type analysis can be and therefore form the basis of future clinical trials in this area.

Transplantation is the best treatment for patients with stage 5 chronic kidney disease, but is limited by the availability of donor organs and by failure of the kidney after transplantation. Chronic allograft injury (CAI) is the main cause of kidney loss after the first year. The aetiology of CAI is incompletely understood but is likely to be multifactorial including immune and non-immune factors. There is increasing recognition that complement activation causes graft injury at several stages post transplant and that complement proteins synthesised within the kidney may be most important.
We have recently shown in a study of over 600 kidney transplant donor?recipient pairs that a single polymorphism of C3, the pivotal component of the complement cascade, strongly influences the incidence of CAI and long-term transplant outcome. The polymorphism C364G, designated C3F, when present in the donor kidney, is associated both with better graft function and survival. The next phase of this work is to translate this important observation into a clinically useful system that can screen donor and recipient DNA pre-transplantation to help predict long term graft outcome. In this way risk of CAI could be stratified, identifying high-risk individuals allowing treatment regimes to be altered to increase graft survival.
Specifically we propose to:
1. Develop a robust system for screening for multiple SNPs complement genes that can be applied to clinical material.
2. Use this system to identify other SNPs and SNP haplotypes in the main complement proteins that independently affect kidney allograft outcome. These may modify the predictive value of C345G allowing more accurate stratification of CAN risk. This may also increase our understanding of the mechanism by which these SNPs alter graft outcome.
3. Combine this data with other factors known to influence graft outcome to further stratify patients into levels of risk of graft loss.
4. Establish a prospective study to use the screening system developed to demonstrate the feasibility of grouping transplants into risk categories that may influence graft outcome.
At the end of this study period we would expect to have a method for identifying complement SNPs that influence graft outcome, know the magnitude of their effect and be able to use this data to predict clinical outcome. We would expect to demonstrate that this can be used in clinical transplantation and form the basis of a major prospective study including alteration of treatment regimes.