Researchers at Weil Cornell Medicine in New York have developed a novel DNA-based scoring system to predict matches between kidney donors and recipients, thereby potentially improving transplant success. The study – which was published in the journal, PLOS Computational Biology – uses a genetic matching program incorporating many genes to help physicians predict long-term transplantation success.
Doctors currently use DNA sequence data to compare organ donors to their prospective recipients. The more similarities in key genes between the patients, the greater the chance that a transplant will be a success. Unfortunately, up to 50 percent of all kidney transplants still fail within a decade of surgery, suggesting other areas of genomic compatibility are important to consider.
“There is a striking shortage of kidneys for transplantation worldwide, and a major contributor to the shortage are patients with a failed kidney transplant who return to the transplant wait list,” said Dr. Manikkam Suthanthiran, Professor of Medicine at Weil Cornell Medicine, and one of the study’s co-authors. “Should our novel scoring system be validated in future clinical trials, a real opportunity could emerge for minimizing the disparity between organ supply and demand.”
By collecting DNA data from a broader selection of genes from 53 sets of kidney donors and recipients, the researchers studied the influence of many genes on transplant success. Based on mismatches in the exome of the transplant donor and recipient, the researchers developed a computation method to allocate a score to each pair.
In order to test the applicability of these scores to patient outcomes, the researchers followed-up with kidney donors and recipients for many years after the initial transplant surgery. The score generated from the whole exome sequencing program was found to be a significant predictor of the transplant kidney’s functionality after surgery.
“Future studies will be able to build on this new concept to confirm the initial observations,” said Dr. Fabien Campagne, Assistant Professor of Research in Computational Biomedicine at Weil Cornell Medicine, and the senior author on the study. “They may lead to using this new concept in the clinic to optimize the matching of donor and recipients before transplantation.”