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    A large-scale computational study of inhibitor risk in non-severe haemophilia A

    Shepherd, Adrian J. and Skelton, Stuart and Sansom, Clare E. and Gomez, K. and Moss, David S. and Hart, D.P. (2015) A large-scale computational study of inhibitor risk in non-severe haemophilia A. British Journal of Haematology 168 (3), pp. 413-420. ISSN 0007-1048.

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    Abstract

    Over 500 missense F8 mutations have been reported to cause non-severe haemophilia A. Some F8 genotypes appear to confer a higher risk of inhibitor formation than others and individuals with the same F8 genotype may have differing risks of inhibitor formation. We present an in silico strategy demonstrating the heterogeneity of factor VIII (FVIII)-derived antigen presentation whilst identifying patterns of human leucocyte antigen (HLA) peptide binding that might predict future inhibitor risk. A well-validated computational tool, NetMHCII, enabled large-scale comparison of predicted antigen presentation between endogenous, mutated FVIII-derived peptides and wild-type, therapeutic FVIII-derived peptides spanning all F8 missense mutation positions reported to The Haemophilia A Mutation, Structure and Resource Site (HADB). We identify 40 F8 genotypes to be ‘low risk’ at a 50% inhibitory concentration (IC50)-binding threshold of 300 nmol/l (P = 0·00005), defined as absence of novel peptide-major histocompatibility complex (MHC) surfaces for all 14 common HLA-DR alleles assessed. Analysing each of the possible 7280 F8 genotype/HLA-DR permutations individually at an IC50 threshold of 300 nmol/l, 65% are predicted to not generate a novel peptide-MHC surface that would be necessary to engage T cell help for subsequent anti-FVIII antibody generation. This study demonstrates the future importance of interpreting F8 genotype in the context of an individual's HLA profile to personalize inhibitor risk prediction.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): haemophilia A, antigen presentation, in silico, inhibitor, F8 genotype
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Natural Sciences
    Research Centres and Institutes: Bioinformatics, Bloomsbury Centre for (Closed), Structural Molecular Biology, Institute of (ISMB), Data Analytics, Birkbeck Institute for
    Depositing User: Administrator
    Date Deposited: 23 Sep 2014 13:20
    Last Modified: 02 Aug 2023 17:12
    URI: https://eprints.bbk.ac.uk/id/eprint/10587

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