Summary The occurrence of alloantibodies against Factor VIII (FVIII) is the main iatrogenic complication in haemophilia A (HA). Anti‐FVIII autoantibodies may also spontaneously appear in non‐HA patients, leading to acquired haemophilia A. In both contexts, the antibody response against FVIII is complex and difficult to analyse due to the lack of suitable tools. Our purpose was to comprehensively map, at the amino acid level, discontinuous epitopes of the C2 domain of FVIII targeted by patients’ antibodies. We synthesized 33 synthetic peptides, which were predicted by the bioinformatic algorithm PEPOP to mimic C2 domain discontinuous epitopes. Using an inhibition assay based on the x‐MAP technology, we evaluated their ability to block the binding to the C2 domain of anti‐C2 domain antibodies from pooled plasma samples. Nine peptides were thus selected and tested again in individual plasma samples. Our results support the view that C2 domain epitopes are organized as an epitopic mosaic distributed around the molecule, showed that each patient displayed a specific anti‐C2 epitopic profile, and confirmed the complexity and variability of the immune response against the C2 domain of FVIII. This ability to finely map epitopes could be further used to follow the antibody specificity modifications over time.
Summary. Background: Acquired hemophilia A (AHA) is a severe life‐threatening autoimmune disease due to the development of autoantibodies that neutralize the procoagulant activity of factor VIII (FVIII). In rare cases, AHA occurs in the postpartum period as a serious complication of an otherwise normal pregnancy and delivery. Due to its rarity, little is known about the features of the antibody response to FVIII in AHA. Objectives: Our study wanted to (i) determine the epitope specificity and the immunoglobulin (Ig) subclasses of anti‐FVIII autoantibodies in plasma samples from a large cohort of AHA patients, and (ii) compare the epitope specificity of anti‐FVIII autoantibodies in plasma samples from postpartum AHA and other AHA patients. Patients/Methods: Seventy‐three plasma samples from patients with postpartum AHA (n = 10) or associated with malignancies (n = 16) or autoimmune diseases (n = 11) or without underlying disease (n = 36) were analyzed with three multiplexed assays. Results and Conclusions: Our results showed a stronger response against the A1a1‐A2a2‐B fragments of FVIII and more specifically against the A1a1 domain in patients with postpartum AHA than in the other AHA groups (P < 0.01). Moreover, although IgG4 was the predominant IgG subclass in all groups, anti‐A1a1‐A2a2‐B and anti‐A1a1 domain autoantibodies of the IgG1 and IgG3 subclasses were more frequently detected in postpartum AHA than in the other AHA groups. These findings support the involvement of the Th1‐driven response in the generation of autoantibodies in women with postpartum AHA compared with the other groups of AHA patients in whom production of Th2‐driven IgG4 was predominant.
Development of antibodies (Abs) against factor VIII (FVIII) is a severe complication of haemophilia A treatment. Recent publications suggest that domain specificity of anti-FVIII antibodies, particularly during immune tolerance induction (ITI), might be related to the outcome of the treatment. Obtaining suitable tools for a fine mapping of discontinuous epitopes could thus be helpful. The aim of this study was to map discontinuous epitopes on FVIII A2 domain using a new epitope prediction functionality of the PEPOP bioinformatics tool and a peptide inhibition assay based on the Luminex technology. We predicted, selected and synthesized 40 peptides mimicking discontinuous epitopes on the A2 domain of FVIII. A new inhibition assays using Luminex technology was performed to identify peptides able to inhibit the binding of anti-A2 Abs to A2 domain. We identified two peptides (IFKKLYHVWTKEVG and LYSRRLPKGVKHFD) able to block the binding of anti-A2 allo-antibodies to this domain. The three-dimensional representation of these two peptides on the A2 domain revealed that they are localized on a limited region of A2. We also confirmed that residues 484-508 of the A2 domain define an antigenic site. We suggest that dissection of the antibody response during ITI using synthetic peptide epitopes could provide important information for the management of patients with inhibitors.
In clinical practice, differentiating Bipolar Disorder (BD) from unipolar depression is a challenge due to the depressive symptoms, which are the core presentations of both disorders. This misdiagnosis during depressive episodes results in a delay in proper treatment and a poor management of their condition. In a first step, using A-to-I RNA editome analysis, we discovered 646 variants (366 genes) differentially edited between depressed patients and healthy volunteers in a discovery cohort of 57 participants. After using stringent criteria and biological pathway analysis, candidate biomarkers from 8 genes were singled out and tested in a validation cohort of 410 participants. Combining the selected biomarkers with a machine learning approach achieved to discriminate depressed patients (n = 267) versus controls (n = 143) with an AUC of 0.930 (CI 95% [0.879–0.982]), a sensitivity of 84.0% and a specificity of 87.1%. In a second step by selecting among the depressed patients those with unipolar depression (n = 160) or BD (n = 95), we identified a combination of 6 biomarkers which allowed a differential diagnosis of bipolar disorder with an AUC of 0.935 and high specificity (Sp = 84.6%) and sensitivity (Se = 90.9%). The association of RNA editing variants modifications with depression subtypes and the use of artificial intelligence allowed developing a new tool to identify, among depressed patients, those suffering from BD. This test will help to reduce the misdiagnosis delay of bipolar patients, leading to an earlier implementation of a proper treatment.
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