The Immunogenicity of HLA Class II Mismatches: The Predicted Presentation of Nonself Allo-HLA-Derived Peptide by the HLA-DR Phenotype of the Recipient Is Associated with the Formation of DSA (2017)

Author of Publication: Vadim Jucaud.

Appeared in: Journal of Immunology Research (February 2017)

Read more…

Abstract

The identification of permissible HLA class II mismatches can prevent DSA in mismatched transplantation. The HLA-DR phenotype of recipients contributes to DSA formation by presenting allo-HLA-derived peptides to T-helper cells, which induces the differentiation of B cells into plasma cells. Comparing the binding affinity of self and nonself allo-HLA-derived peptides for recipients’ HLA class II antigens may distinguish immunogenic HLA mismatches from nonimmunogenic ones. The binding affinities of allo-HLA-derived peptides to recipients’ HLA-DR and HLA-DQ antigens were predicted using the NetMHCIIpan 3.1 server. HLA class II mismatches were classified based on whether they induced DSA and whether self or nonself peptide was predicted to bind with highest affinity to recipients’ HLA-DR and HLA-DQ. Other mismatch characteristics (eplet, hydrophobic, electrostatic, and amino acid mismatch scores and PIRCHE-II) were evaluated. A significant association occurred between DSA formation and the predicted HLA-DR presentation of nonself peptides (P=0.0169; accuracy = 80%; sensitivity = 88%; specificity = 63%). In contrast, mismatch characteristics did not differ significantly between mismatches that induced DSA and the ones that did not, except for PIRCHE-II (P=0.0094). This methodology predicts DSA formation based on HLA mismatches and recipients’ HLA-DR phenotype and may identify permissible HLA mismatches to help optimize HLA matching and guide donor selection.

Vadim Jucaud, “The Immunogenicity of HLA Class II Mismatches: The Predicted Presentation of Nonself Allo-HLA-Derived Peptide by the HLA-DR Phenotype of the Recipient Is Associated with the Formation of DSA,” Journal of Immunology Research, vol. 2017, Article ID 2748614, 12 pages, 2017. doi:10.1155/2017/2748614

Matthias Niemann

Matthias Niemann

Matthias holds a Masters degree in Computer Science with a major in software engineering and a minor in Bioinformatics from Berlin University (Freie Universität). While working at Charité University Hospital in Berlin, he developed a database for kidney transplantation data and worked on various laboratory information systems and research databases. His research at Charité focused on epitope matching models and machine learning. He was instrumental in the implementation methods to increase data quality.
Since fall 2014 he focuses at PIRCHE on further improving the PIRCHE algorithm and investigating the technology's power in new domains.
Matthias Niemann