An integrative algorithm combining HLA epitope registry, PIRCHE-T2, and PIRCHE-B outcomes to improve immunological risk stratification in kidney transplantation.

Zhao, H., Kakodkar, P., Wang, E., Zhang, D., Niemann, M., Webster, D., Pearce, T., Shoker, A., Keown, P., Sherwood, K., Wu, F., Lewis, C., & Mostafa, A. (2025). An integrative algorithm combining HLA epitope registry, PIRCHE-T2, and PIRCHE-B outcomes to improve immunological risk stratification in kidney transplantation.. Frontiers in Immunology, 16, 1718506.

Abstract

AIM: Kidney transplantation remains the most effective treatment for end-stage kidney disease. Still, the development of de novo donor-specific antibodies (dnDSA) increases the risk of rejection and allograft failure. While molecular matching algorithms assess B-cell and T-cell epitope mismatches, no single method fully captures rejection risk across immune pathways. This study combines the HLA Epitope Registry (Epregistry), PIRCHE-T2, and PIRCHE-B scores to enhance risk stratification, allowing for early intervention in high-risk recipients and improving long-term outcomes.

METHODS: A retrospective study of 594 kidney transplant recipients in Saskatchewan (1981-2021), Canada, was conducted, tracking de novo donor-specific antibodies (dnDSA) development until January 2024. Epitope mismatch scores were calculated using Epregistry, PIRCHE-T2, and PIRCHE-B, and receiver operating characteristic (ROC) curve analysis determined the optimal cutoff values for predicting dnDSA formation. Patients were categorized into high-risk (all scores > cutoff), intermediate-risk (one algorithm > cutoff), and low-risk (all scores < cutoff) groups. Kaplan-Meier survival analysis evaluated dnDSA-free survival across risk categories.

RESULTS: Among 594 recipients, 104 individuals (17.5%) developed de novo DSA; of these, 29 patients developed more than one, resulting in a total of 146 dnDSA events. The most frequently targeted locus was HLA-DQ (72/146, 49.3%), followed by HLA-DR (25/146, 17.1%) and HLA-A (24/146, 16.4%). The optimal cutoff values for predicting dnDSA were 22.5 (Epregistry), 30.5 (PIRCHE-T2), and 5.5 (PIRCHE-B) for Class I, and 15.5 (Epregistry), 17.5 (PIRCHE-T2), and 5.5 (PIRCHE-B) for Class II (all p < 0.05). Across all molecular mismatch load metrics, Kaplan-Meier analysis demonstrated significantly lower dnDSA-free and antibody-mediated rejection (ABMR)-free survival among high-risk recipients compared with low-risk recipients (log-rank p < 0.001). In addition, both the PIRCHE-T2 score at HLA Class I loci and the overall PIRCHE-T2 score were significantly associated with T-cell mediated rejection (TCMR) (p < 0.01).

CONCLUSION: Integrating Epregistry, PIRCHE-T2, and PIRCHE-B enhances risk stratification for kidney transplant recipients. Epregistry and PIRCHE-B evaluate HLA antibody epitope mismatches, and PIRCHE-T2 focuses on T-cell mismatches. Applied in conjunction, the methods show improved predictive accuracy, making this multi-algorithm approach more effective in identifying high-risk patients. By enabling earlier interventions and personalized immunosuppressive strategies, this model has the potential to improve long-term transplant success.

Last updated on 04/01/2026
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