Global Seroprevalence of Pre-existing Immunity Against AAV5 and Other AAV Serotypes in People with Hemophilia A
Bibliographic record
Abstract
Adeno-associated virus (AAV)-mediated gene therapy may provide durable protection from bleeding events and reduce treatment burden for people with hemophilia A (HA). However, pre-existing immunity against AAV may limit transduction efficiency and hence treatment success. Global data on the prevalence of AAV serotypes are limited. In this global, prospective, noninterventional study, we determined the prevalence of pre-existing immunity against AAV2, AAV5, AAV6, AAV8, and AAVrh10 among people ≥12 years of age with HA and residual FVIII levels ≤2 IU/dL. Antibodies against each serotype were detected using validated, electrochemiluminescent-based enzyme-linked immunosorbent assays. To evaluate changes in antibody titers over time, 20% of participants were retested at 3 and 6 months. In total, 546 participants with HA were enrolled at 19 sites in 9 countries. Mean (standard deviation) age at enrollment was 36.0 (14.87) years, including 12.5% younger than 18 years, and 20.0% 50 years of age and older. On day 1, global seroprevalence was 58.5% for AAV2, 34.8% for AAV5, 48.7% for AAV6, 45.6% for AAV8, and 46.0% for AAVrh10. Considerable geographic variability was observed in the prevalence of pre-existing antibodies against each serotype, but AAV5 consistently had the lowest seroprevalence across the countries studied. AAV5 seropositivity rates were 51.8% in South Africa ( n = 56), 46.2% in Russia ( n = 91), 40% in Italy ( n = 20), 37.2% in France ( n = 86), 26.8% in the United States ( n = 71), 26.9% in Brazil ( n = 26), 28.1% in Germany ( n = 89), 29.8% in Japan ( n = 84), and 5.9% in the United Kingdom ( n = 17). For all serotypes, seropositivity tended to increase with age. Serostatus and antibody titer were generally stable over the 6-month sampling period. As clinical trials of AAV-mediated gene therapies progress, data on the natural prevalence of antibodies against various AAV serotypes may become increasingly important.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".