Assessment of human leukocyte antigen immunogenicity: current methods, challenges and opportunities

Abstract

Purpose of review: Donor-recipient human leukocyte antigen (HLA) matching improves outcomes after solid-organ transplantation, but current assessment of HLA incompatibility is inadequate as it does not consider the relative immunogenicity of individual HLA mismatches. In this article, we review existing strategies for assessing HLA immunogenicity and discuss current challenges and future opportunities in this field.

Recent findings: Current HLA immunogenicity algorithms focus primarily on the humoral component of the alloimmune response and aim to determine a measure of 'dissimilarity' between donor and recipient HLA. This can be achieved by deriving information from comparison of donor and recipient HLA at the amino acid sequence, structural and/or the physicochemical level, accounting for both B-cell and T-cell pathways of alloreactivity. Substantial evidence now supports the superiority of this molecular definition of HLA incompatibility, over conventional enumeration of HLA antigenic differences, for assessing the risk of humoral alloimmunity and for predicting graft outcomes after transplantation.

Summary: Significant progress has been made in developing computational HLA immunogenicity algorithms that offer exciting opportunities for a more rational approach to determining the degree of donor-recipient HLA incompatibility and to defining HLA-related immunological risk. A number of challenges now need to be overcome to enable their implementation into clinical practice.

Box 1

no caption available

FIGURE 1

Correlation between amino acid sequence-based human leukocyte antigen mismatch scoring methods; HLAMatchmaker eplet load vs. number of amino acid mismatches or sequence-based electrostatic mismatch score. This figure depicts analyses of the immunogenic potential of human leukocyte antigen class II mismatches in a large cohort of kidney transplant recipients using HLAMatchmaker and the Cambridge human leukocyte antigen immunogenicity algorithm. The strong correlation between number of eplet mismatches (eplet load), amino acid mismatches and sequence-based electrostatic mismatch score for human leukocyte antigen mismatches within the human leukocyte antigen-DRβ₁, human leukocyte antigen-DRβ_3/4/5, human leukocyte antigen-DQ_α1β1 loci is evident. Reproduced with permission [24^▪].

FIGURE 2

Correlation between predicted indirectly recognizable HLA epitopes and amino acid sequence polymorphism. The figure depicts analysis of HLA (A, B, C, DR, DQ and DP) mismatches in a local cohort of 182 donor–recipient pairs (HLA typed at two-field resolution). HLA mismatches were identified (n = 1615) and scored according to the number of possible peptide epitopes (unique, polymorphic nonameric binding cores) that can be derived from donor HLA (irrespective of predicted binding affinity to recipient HLA-DR), the number of predicted indirectly recognizable HLA epitopes (predicted indirectly recognizable HLA epitopes; defined as polymorphic nonameric binding cores with predicted binding to recipient HLA-DR of IC₅₀ < 1000 nmol/l), and the number of amino acid mismatches (as defined by the Cambridge HLA immunogenicity algorithm). Donor HLA-derived polymorphic nonameric binding cores were defined as those that differed by at least one amino acid compared with the HLA sequences of the recipient. The NetMHCIIpan version 3.1 algorithm was implemented locally to calculate the predicted indirectly recognizable HLA epitopes scores (the predicted indirectly recognizable HLA epitopes algorithm available via https://www.pirche.org implements a previous version of NetMHCIIpan). For the purposes of this analysis, all HLA mismatches were grouped together. There was high correlation between scores (Spearman's Rho), although this correlation varied for mismatches within individual HLA loci (data not shown). HLA, human leukocyte antigen.