Predicting Kidney Transplant Survival using Multiple Feature Representations for HLAs

Kidney transplantation can significantly enhance living standards for people suffering from end-stage renal disease. A significant factor that affects graft survival time (the time until the transplant fails and the patient requires another transplant) for kidney transplantation is the compatibility of the Human Leukocyte Antigens (HLAs) between the donor and recipient. In this paper, we propose new biologically-relevant feature representations for incorporating HLA information into machine learning-based survival analysis algorithms. We evaluate our proposed HLA feature representations on a database of over 100,000 transplants and find that they improve prediction accuracy by about 1%, modest at the patient level but potentially significant at a societal level. Accurate prediction of survival times can improve transplant survival outcomes, enabling better allocation of donors to recipients and reducing the number of re-transplants due to graft failure with poorly matched donors

Low Hydrophobic Mismatch Scores Calculated for HLA-A/B/DR/DQ Loci Improve Kidney Allograft Survival

We evaluated the impact of human leukocyte antigen (HLA) disparity (immunogenicity; IM) on long-term kidney allograft survival. The IM was quantified based on physicochemical properties of the polymorphic linear donor/recipient HLA amino acids (the Cambridge algorithm) as a hydrophobic, electrostatic, amino acid mismatch scores (HMS\AMS\EMS) or eplet mismatch (EpMM) load. High-resolution HLA-A/B/DRB1/DQB1 types were imputed to calculate HMS for primary/re-transplant recipients of deceased donor transplants. The multiple Cox regression showed the association of HMS with graft survival and other confounders. The HMS integer 0-10 scale showed the most survival benefit between HMS 0 and 3. The Kaplan-Meier analysis showed that: the HMS=0 group had 18.1-year median graft survival, a 5-year benefit over HMS\u3e0 group; HMS ≤ 3.0 had 16.7-year graft survival, a 3.8-year better than HMS\u3e3.0 group; and, HMS ≤ 7.8 had 14.3-year grafts survival, a 1.8-year improvement over HMS\u3e7.8 group. Stratification based on EMS, AMS or EpMM produced similar results. Additionally, the importance of HLA-DR with/without -DQ IM for graft survival was shown. In our simulation of 1,000 random donor/recipient pairs, 75% with HMS\u3e3.0 were re-matched into HMS ≤ 3.0 and the remaining 25% into HMS≥7.8: after re-matching, the 13.5 years graft survival would increase to 16.3 years. This approach matches donors to recipients with low/medium IM donors thus preventing transplants with high IM donors