Computational Assessment of T-cell and B-cell Allorecognition to Predict Donor HLA Immunogenicity
1Department of Surgery, University of Cambridge and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospital, Cambridge, United Kingdom, 2University of Cambridge and NIHR Cambridge Biomedical Research Centre, Cambridge University Hospital & NIHR Blood and Transplant Research Unit in Organ Donation and Transplantation at the University of Cambridge, Cambridge, UK., Cambridge, United Kingdom
Meeting: 2019 American Transplant Congress
Abstract number: 163
Keywords: Allorecognition, HLA antibodies, HLA matching, Immunogenicity
Session Information
Date: Sunday, June 2, 2019
Session Name: Concurrent Session: Histocompatibility and Immunogenetics
Session Time: 4:30pm-6:00pm
Presentation Time: 5:18pm-5:30pm
Location: Room 309
*Purpose: Donor-specific alloantibody (DSA) development after solid-organ transplantation is a major cause of graft loss, and limits future transplant options. We have previously shown that recipient B-cell allorecognition of donor HLA can be assessed by quantification of electrostatic potential differences at the tertiary level between donor and recipient HLA (electrostatic mismatch score, EMS3D). Humoral alloresponses require CD4+ T-cell help (the indirect pathway of allorecognition) through recognition of donor HLA-derived peptides presented by recipient HLA class-II. We used in silico prediction of CD4+ T-cell epitopes to assess the risk of DSA development in a unique HLA sensitisation model.
*Methods: We examined DSA alloresponses in 179 healthy female patients (HLA-typed at two-field resolution) undergoing standardised subcutaneous lymphocyte injection, purified from their partner, as treatment for infertility (lymphocyte immunotherapy). DSA were detected using Luminex single-antigen-beads. Binding of high affinity (<50nM) donor HLA-derived 15-mer peptides to recipient HLA-DR/DQ/DP were assessed using a neural network approach (NetMHCIIpan3.1 programme).
*Results: Donor T-cell epitope numbers ranged (mean, SD) from 0-10 (1.53, 1.94) for HLA class-I and from 0-28 (3.15, 4.92) for HLA class-II mismatches. Increasing T-cell epitope number was associated with higher risk of DSA development (HLA Class-I: OR 1.08 per peptide increase, 95%CI: 1.00-1.17, p=0.05; Class-II: OR 1.21 per peptide increase, 95%CI: 1.16-1.28, p<0.01). Prediction of HLA class-II DSA (the most clinically significant alloresponse in transplantation) conformed best to the model with ROC area-under-curve (AUC) of 0.73 which was similar to the predictive ability of the EMS3D model. Notably, simple combination of the T-cell epitope score with the EMS3D score (the two scores were not correlated) improved prediction of HLA class-II DSA development (AUC 0.8).
*Conclusions: Assessment of recipient T-cell help for development of humoral alloimmunity may help predict the immunogenic potential of donor HLA. Further investigation of a combined B-cell and T-cell model of humoral alloreactivity is needed to fully assess the utility of this approach to quantify HLA immunogenicity.
To cite this abstract in AMA style:
Copley HC, Elango M, Kosmoliaptsis V. Computational Assessment of T-cell and B-cell Allorecognition to Predict Donor HLA Immunogenicity [abstract]. Am J Transplant. 2019; 19 (suppl 3). https://atcmeetingabstracts.com/abstract/computational-assessment-of-t-cell-and-b-cell-allorecognition-to-predict-donor-hla-immunogenicity/. Accessed February 19, 2020.« Back to 2019 American Transplant Congress