Eradication of neutralizing antibodies to factor VIII in canine hemophilia A after liver gene therapy
Bibliographic record
Abstract
Inhibitory antibodies to factor VIII (FVIII) are a major complication in the treatment of hemophilia A, affecting approximately 20% to 30% of patients. Current treatment for inhibitors is based on long-term, daily injections of large amounts of FVIII protein. Liver-directed gene therapy has been used to induce antigen-specific tolerance, but there are no data in hemophilic animals with pre-existing inhibitors. To determine whether sustained endogenous expression of FVIII could eradicate inhibitors, we injected adeno-associated viral vectors encoding canine FVIII (cFVIII) in 2 strains of inhibitor hemophilia A dogs. In 3 dogs, a transient increase in inhibitor titers (up to 7 Bethesda Units [BU]) at 2 weeks was followed by continuous decline to complete disappearance within 4-5 weeks. Subsequently, an increase in cFVIII levels (1.5%-8%), a shortening of clotting times, and a reduction (> 90%) of bleeding episodes were observed. Immune tolerance was confirmed by lack of antibody formation after repeated challenges with cFVIII protein and normal protein half-life. A fourth dog exhibited a strong early anamnestic response (216 BU), with slow decline to 0.8 BU and cFVIII antigen detection by 18 months after vector delivery. These data suggest that liver gene therapy has the potential to eradicate inhibitors and could improve the outcomes of hemophilia A patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".