Preclinical evaluation of lentiviral gene therapy for adenosine deaminase 2 deficiency (DADA2): engraftment efficiency and biodistribution in humanised NBSGW mice
Bibliographic record
Abstract
Adenosine deaminase type 2 deficiency (DADA2) is caused by bi-allelic loss-of-function mutations in ADA2. While anti-TNF therapy is effective for the autoinflamatory and vasculitic components of the disease it does not correct marrow failure or immunodeficiency. Allogeneic stem cell transplantation (HSCT) offers a potential cure but is limited by challenges such as graft-versus-host-disease and donor availability. We previously demonstrated that lentiviral-mediated ADA2 gene therapy could restore ADA2 enzyme activity in patient-derived cells, correct macrophage inflammatory activation and reduce endothelial activation in vitro. Here, we evaluated the biodistribution and engraftment potential of lentivirally transduced healthy donor and patient-derived haematopoietic stem cells (HSC) in vivo using a humanised NBSGW mouse model. Transduced healthy HSC retained multilineage differentiation and engraftment capacity, without functional impairment. PCR analysis confirmed the absence of viral integration in non-haematopoietic organs, and histology showed no abnormal tissue changes, underscoring the safety and precision of this approach. In DADA2 patient-derived HSC, ADA2 transduction restored protein expression and enzyme activity, supporting improved cellular function and enhanced engraftment potential. These findings provide a strong foundation for advancing ADA2 gene therapy as a therapeutic strategy for DADA2, bringing it closer to clinical application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 teacher head, 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".