Improving long-term kidney allograft survival by rethinking HLA compatibility: from molecular matching to non-HLA genes

Front Genet. 2024 Oct 2:15:1442018. doi: 10.3389/fgene.2024.1442018. eCollection 2024.

Abstract

Optimizing immunologic compatibility in organ transplantation extends beyond the conventional approach of Human Leukocyte Antigen (HLA) antigen matching, which exhibits significant limitations. A broader comprehension of the roles of classical and non-classical HLA genes in transplantation is imperative for enhancing long-term graft survival. High-resolution molecular HLA genotyping, despite its inherent challenges, has emerged as the cornerstone for precise patient-donor compatibility assessment. Leveraging understanding of eplet biology and indirect immune activation, eplet mismatch calculators and the PIRCHE-II algorithm surpass traditional methods in predicting allograft rejection. Understanding minor histocompatibility antigens may also present an opportunity to personalize the compatibility process. While the application of molecular matching in deceased donor organ allocation presents multiple technical, logistical, and conceptual barriers, rendering it premature for mainstream use, several other areas of donor-recipient matching and post-transplant management are ready to incorporate molecular matching. Provision of molecular mismatch scores to physicians during potential organ offer evaluations could potentially amplify long-term outcomes. The implementation of molecular matching in living organ donation and kidney paired exchange programs is similarly viable. This article will explore the current understanding of immunologic matching in transplantation and the potential applications of epitope and non-epitope molecular biology and genetics in clinical transplantation.

Keywords: HLAMatchmaker; PIRCHE-II; eplet; eplet registry; kidney paired exchange; kidney transplant; non-HLA genes; non-classical HLA.

Publication types

  • Review

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Ian Jaffe was supported by the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number UL1TR001445.