Efficacy of gene delivery to the brain using AAV and ultrasound depends on serotypes and brain areas
Bibliographic record
Abstract
Focused ultrasound combined with intravenously injected microbubbles (FUS) is known to non-invasively, locally, and transiently increase the permeability of the blood-brain barrier (BBB). A promising approach for non-invasive gene delivery to the brain is to administer recombinant adeno-associated viruses (AAVs) intravenously and allow them to cross the BBB at precise FUS-targeted brain regions. FUS-AAV delivery has been achieved in animal models; however, the key elements influencing, guiding, and monitoring the success of FUS-AAV delivery to the brain remain largely unknown. We systematically compared the ability of AAV1, AAV2, AAV5, AAV8, AAV9, and AAVrg to enter four specific brain regions and transduce two main cell types: neurons and astrocytes. Our results demonstrate that the AAV serotype, the extent of FUS-induced BBB permeability, and the intrinsic properties of the targeted brain tissue influence the observed biodistribution, diffusion and transduction of AAV to cells of the cerebrovasculature and brain parenchyma. Non-invasive contrast-enhanced MR imaging was found to predict the efficacy of FUS-AAV delivery. Notably, we also found that AAVs with high biodistribution to peripheral organs result in low gene delivery to the brain when combined with FUS. Gene delivery by AAV1, AAV2, AAV5, AAV8 and AAV9 was highly and selectively localized to FUS-targeted brain areas. To obtain non-invasive gene delivery to multiple brain regions with one area of FUS-BBB modulation, we combined a modified AAV2 vector harboring enhanced retrograde transport properties (AAVrg) with FUS-mediated brain delivery. This allowed for gene delivery from the FUS-targeted site to multiple connected brain regions. This study demonstrates that MR imaging can be used as a non-invasive indication of AAV delivery to the brain, and that the properties of AAV serotypes influence the efficacy of gene delivery to the brain with FUS. AAVs that have minimal peripheral biodistribution are ideal candidates for enhanced, and perhaps exclusive with future serotypes, delivery to the brain with FUS. The characterization of parameters influencing FUS-AAV delivery to the brain are critical to the design of safe and efficient gene therapies, from preclinical studies to future clinical applications.
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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 | 0.001 | 0.001 |
| 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".