High levels of anti-factor VIII immunoglobulin G4 and immunoglobulin G total are associated with immune tolerance induction failure in people with congenital hemophilia A and high-responding inhibitors.

Background: Immune tolerance induction (ITI) is the treatment of choice to eradicate neutralizing anti-factor (F)VIII alloantibodies (inhibitors) in people with inherited hemophilia A. However, it is not successful in 10% to 40% of the cases. The biological mechanisms and biomarkers associated with ITI outcome are largely unknown. Objectives: The aim of this study was to investigate the association of plasma cytokines (interferon-γ, tumor necrosis factor, interleukin [IL]-2, IL-4, IL-5, IL-6, IL-10, and IL-17A), chemokines (IL-8/CXCL8, RANTES/CCL5, MIG/CXCL9, MCP-1/CCL2, and IP-10/CXCL10), and anti-FVIII immunoglobulin (Ig) G total, IgG1, and IgG4 with ITI outcome. Methods: In this cross-sectional analysis of the Brazilian Immune Tolerance Study, we assessed plasma levels of anti-FVIII IgGs using an enzyme-linked immunosorbent assay with plasma-derived FVIII and recombinant FVIII as target antigens, immobilized in microplates. Results: We assayed 98 plasma samples of moderately severe and severe (FVIII activity, <2%) people with hemophilia A after completion of a first ITI course. Levels of anti-recombinant FVIII IgG total and IgG4 were higher in people with hemophilia A who failed ITI (IgG total optical density [OD], 0.37; IQR, 0.15-0.73; IgG4 OD, 2.19; IQR, 0.80-2.52) than in those who had partial (IgG total OD, 0.03; IQR, 0.00-0.14; IgG4 OD, 0.39; IQR, 0.09-1.11; P < .0001 for both) or complete success (IgG total OD, 0.04; IQR, 0.00-0.07; IgG4 OD, 0.07; IQR, 0.06-0.40; P < .0001 for both). Plasma cytokines, chemokines, and anti-FVIII IgG1 were not associated with ITI outcome. Conclusion: Our results show that high levels of plasma anti-FVIII IgG4 and IgG total are associated with ITI failure.

Prediction of inhibitor development in previously untreated and minimally treated children with severe and moderately severe hemophilia A using a machine-learning network.

BACKGROUND: Prediction of inhibitor development in patients with hemophilia A (HA) remains a challenge. OBJECTIVES: To construct a predictive model for inhibitor development in HA using a network of clinical variables and biomarkers based on the individual similarity network. METHODS: Previously untreated and minimally treated children with severe/moderately severe HA, participants of the HEMFIL Cohort Study, were followed up until reaching 75 exposure days (EDs) without inhibitor (INH-) or upon inhibitor development (INH+). Clinical data and biological samples were collected before the start of factor (F)VIII replacement (T0). A predictive model (HemfilNET) was built to compare the networks and potential global topological differences between INH- and INH+ at T0, considering the network robustness. For validation, the "leave-one-out" cross-validation technique was employed. Accuracy, precision, recall, and F1-score were used as evaluation metrics for the machine-learning model. RESULTS: We included 95 children with HA (CHA), of whom 31 (33%) developed inhibitors. The algorithm, featuring 37 variables, identified distinct patterns of networks at T0 for INH+ and INH-. The accuracy of the model was 74.2% for CHA INH+ and 98.4% for INH-. By focusing the analysis on CHA with high-risk F8 mutations for inhibitor development, the accuracy in identifying CHA INH+ increased to 82.1%. CONCLUSION: Our machine-learning algorithm demonstrated an overall accuracy of 90.5% for predicting inhibitor development in CHA, which further improved when restricting the analysis to CHA with a high-risk F8 genotype. However, our model requires validation in other cohorts. Yet, missing data for some variables hindered more precise predictions.

Time between inhibitor detection and start of immune tolerance induction: Association with outcome in the BrazIT study.

BACKGROUND: Immune tolerance induction (ITI) is the treatment of choice for eradication of anti-factor VIII (FVIII) neutralizing alloantibodies (inhibitors) in people with inherited hemophilia A and high-responding inhibitor (PwHA-HRi). The association between ITI outcome and time elapsed between inhibitor detection and start of ITI (∆tinhi-ITI ) is debatable. OBJECTIVE: The aim of this study was to evaluate this association among a large cohort of severe PwHA-HRi. METHODS: Severe (factor VIII activity level <1%) PwHA-HRi on ITI (n = 142) were enrolled in 15 hemophilia treatment centers. PwHA-HRi were treated according to the Brazilian ITI Protocol. ITI outcomes were defined as success (i.e., recovered responsiveness to exogenous FVIII) and failure (i.e., no responsiveness to exogenous FVIII and requirement of bypassing agents to control bleeding). RESULTS: Median ages at inhibitor detection and at ITI start were 3.2 years (interquartile range [IQR], 1.6-8.1) and 6.9 years [IQR, 2.6-20.1), respectively. PwHA-HRi were stratified according to ∆tinhi-ITI quartiles: first (0.0-0.6 year), second (>0.6-1.7 year), third (>1.7-9.2 years), and fourth quartile (>9.2-24.5 years). The overall success rate was 65.5% (93/142), with no difference among first, second, third, and fourth quartiles (62.9%, 69.4%, 58.3%, and 71.4%, respectively) even after adjusting the analyses for potential confounders. CONCLUSION: In conclusion, delayed ITI start is not associated with failure of ITI in PwHA-HRi. Therefore, ITI should be offered for these patients, regardless of the time elapsed between the detection of inhibitor and the ITI start.

Effect of the First Factor VIII Infusions on Immunological Biomarkers in Previously Untreated Patients with Hemophilia A from the HEMFIL Study.

Hemophilia A (HA) is an inherited bleeding disorder which requires continuous replacement with factor (F) VIII concentrate. The main complication of HA is the development of neutralizing alloantibodies which inhibit FVIII activity (inhibitors). The objective of this study was to investigate the effect of the first FVIII infusions on immunological biomarkers in previously untreated patients with HA. Plasma samples were collected at enrollment before any FVIII infusion (T0) and at inhibitor development (INB +/T1) or up to 35 exposure days without inhibitors (INB -/T1). Anti-FVIII antibodies (immunoglobulin M, immunoglobulin G [IgG] 1, IgG3, and IgG4), chemokines (CCL2, CCL5, CXCL8, CXCL9, and CXCL10), and cytokines (interleukin [IL]-2, IL-4, IL-6, IL-10, interferon-γ, tumor necrosis factor, and IL-17) were assessed. A total of 71 children with severe HA were included, of whom 28 (39.4%) developed inhibitors. Plasma levels of anti-FVIII IgG4, IL-6, and CXCL8 were higher at INB +/T1 when compared with INB -/T1. This group presented a mixed cytokine profile and higher plasma levels of CXCL9 and CXL10 when compared with INB +/T1. We conclude that exposure to FVIII triggers a proinflammatory response mediated by IL-6 and CXCL8 in patients with HA who developed inhibitors. Regardless of inhibitor status, the immune system of all HA patients is stimulated after infusions of FVIII.