Introduction: Human Leukocyte Antigen (HLA) matching is a central objective of kidney allocation policies, but current assessment of histocompatibility is inadequate. Building on our previous research, we have now developed a novel computational scoring system to quantify structural and surface electrostatic potential differences between donor and recipient HLA (Electrostatic Mismatch Score; EMS-3D) and applied it to examine long-term graft survival after kidney transplantation in a national patient cohort.

Methods: Data were obtained from the UK Transplant Registry on 10,726 adult, deceased-donor, first, kidney only transplants performed between 2003 and 2012. A multivariate Cox proportional hazards regression model was fitted to investigate the influence of HLA on death-censored graft survival. The model was risk-adjusted for donor, recipient and transplant factors. HLA comparisons were performed using our bioinformatics platform to determine the EMS-3D for each donor-recipient HLA combination.

Results: Patients were followed up for a median (IQR) of 6.5 (4.5-9.5) years. Increasing number of HLA mismatches at the HLA-A, -B, -DR and -DQ loci or increasing HLA mismatch Level (Levels 1 to 4 based on the UK kidney allocation scheme) significantly increased the risk of graft failure (HR: 1.06 per HLA mismatch, 95% CI: 1.02-1.09, p=0.001). The donor-recipient EMS-3D ranged (median, IQR) from 0 to 2.91 (1.07, 0.64-1.44) and correlated with HLA mismatch level (R²: 0.762), but there was wide variation of EMS-3D within each HLA mismatch level. Increasing EMS-3D was strongly and independently associated with an incremental increase in the risk of graft failure (HR: 1.26 per unit increase in EMS-3D, 95% CI: 1.17-1.38, p<0.0001). Notably, for transplants within an HLA mismatch level, EMS-3D was an independent predictor of graft survival [e.g. for Level 3 mismatched grafts (n=2,762) HR: 1.38 per unit increase, 95% CI: 1.11-1.72, p=0.003; for Level 4 mismatched grafts (n=1,016) HR: 1.25 per unit increase, 95% CI: 1.14-1.38, p<0.0001].

Discussion: This study provides strong evidence that our novel HLA matching algorithm enables improved assessment of donor-recipient histocompatibility and may help inform future deceased-donor kidney transplant allocation policies to maximise the benefits of transplantation.

CITATION INFORMATION: Kosmoliaptsis V, Mallon D, Fuggle S, Johnson R, Watson C, Bradley J, Taylor C. A Novel Computational HLA Matching Algorithm for Improving Donor-Recipient Histocompatibility and Graft Outcomes After Kidney Transplantation. Am J Transplant. 2017;17 (suppl 3).

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