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Human proteome and hemophilia A inhibitor risk
where within the human proteome. Such cross-matching peptides are the basis for protection against inhibitor development because of presumed T-cell tolerance mech- anisms. Here we focused on the surfaces formed by tFVIII peptides that span the locations of known disease-caus- ing F8 missense mutations and are predicted to bind to the MHC molecules for 25 common HLA class II alleles. Given a conservative binding threshold of 1000 nM, the number of F8 missense mutation/HLA isoform combina- tions associated with a risk of developing inhibitors was predicted to fall by more than a third – from 49% to 31% – when cross-matches to the proteome are taken into account. These results were shown to be statistically sig- nificant with a dataset derived from the Factor VIII Gene Variant Database of patients with missense mutation hemophilia A.
Although our proteome scanning approach reduces the number of patients predicted to be at risk of developing inhibitors, that number remains higher than, albeit closer to, the number of patients that have – at least to date – developed inhibitors. This is inevitable for a model based entirely on a consideration of MHC/TCR interactions, as a range of downstream factors may militate against inhibitor development. These include: the absence of suf- ficient T cells capable of binding to a given pMHC surface for reasons other than self-tolerance; the lack of co-stimu- latory signaling; or the level of exposure to tFVIII being below the threshold necessary for inhibitor formation (only cursory information about a patient’s degree of exposure to tFVIII is available in the Factor VIII Gene Variant Database).
There are a number of ways in which this analysis could be refined. Firstly, we took no account of potential F8 genotype mismatches between tFVIII products (derived from common F8 genotypes H1 and H2 that differ only in the B domain) and rare genotypes H3-8, such as the M2238V found in approximately 23% of black people.26 Nor did we consider the antigenic impact of different link- ers used in B-domain-modified tFVIII products. Secondly, proteome scanning was performed against a single refer- ence proteome. It is likely that additional cross-matches will be found if allelic variants are taken into account, adding further to the potential advantages of personalized risk assessment. Scanning against an individual’s own pro- teome would be the optimal predictive strategy. The impact of proteome variability will be assessed in future work using data from IGSR: The International Genome Sample Resource.27
There are several more challenging issues. Our model of peptide-MHC binding is imperfect, for example: we do not take into account the impact of cathepsin cleavage on the availability of FVIII peptides for MHC class II binding (there are no established computational methods for pre- dicting cleavage by cathepsins, and different sets of cathepsins occur in different professional antigen-present-
ing cells28); peptide differences at anchoring positions,29 or outside the binding core,30 are known to affect the forma- tion of pMHC surface in specific cases (but the prevalence of such effects is poorly understood); and a given TCR may not be in contact with all TCR-facing residues (but the binding angle and register of individual TCR is cur- rently unpredictable).31
Validating the accuracy of inhibitor risk prediction for patients with non-severe hemophilia is also particularly problematic. In practice, the current, clinical gold standard for inhibitor detection is a functional, clotting-based Bethesda assay. However, heat treatment modifications in the presence of residual FVIII:C (i.e. non-severe hemophilia A) are often omitted, resulting in reduced sensitivity of detection.32 More importantly, a purely “functional” clot- ting assay does not detect the totality of antibody respons- es against a protein therapeutic. The absence of a more “neutral” screening assay (e.g. based on enzyme-linked immunosorbence) to pick up any anti-tFVIII antibody response first, and subsequently for the functional assay (Bethesda) to determine its inhibitory potential and clinical relevance, compromises our knowledge of the totality of anti-tFVIII responses in our cohorts of patients. It is also evident that the screening practice for antibody responses in non-severe hemophilia A, in contrast to that for severe hemophilia A, is often opportunistic and passive, further reducing the likelihood of detecting the totality of anti- tFVIII antibody responses by missing the optimal immuno- logical windows for screening after tFVIII exposure.9 Given the life-long risk of inhibitor formation in non-severe hemophilia A, we have concerns that true negatives (i.e. patients confirmed to have a zero risk of inhibitor develop- ment) are impossible to identify in a clinical study of non- severe hemophilia A, even when factors such as age and exposure are taken into account.
Notwithstanding these limitations, this study provides compelling evidence of the importance of HLA class II genotyping for analyzing the inhibitor risk of patients with missense mutation hemophilia A. Moreover, we have demonstrated that an innovative computational pipeline incorporating proteome scanning predicts that a large proportion of F8 missense mutation/HLA isoform combinations afford a negligible risk of inhibitor develop- ment, with a low error rate when evaluated using the largest available dataset of patients with F8 missense mutations and conservative MHC binding thresholds. This represents an important step forward, as it closes part of the gap between predicted/potential inhibitor risk and observed inhibitor rates. These insights may ultimately contribute to the design of future clinical studies (with HLA typing of missense mutation hemophilia A patients) that are of direct translational relevance.
Acknowledgments
DPH received funding from the British Society of Haematology.
References
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