A novel adeno-associated virus capsid with enhanced neurotropism corrects a lysosomal transmembrane enzyme deficiency
Bibliographic record
Abstract
Recombinant adeno-associated viruses (AAVs) are popular in vivo gene transfer vehicles. However, vector doses needed to achieve therapeutic effect are high and some target tissues in the central nervous system remain difficult to transduce. Gene therapy trials using AAV for the treatment of neurological disorders have seldom led to demonstrated clinical efficacy. Important contributing factors are low transduction rates and inefficient distribution of the vector. To overcome these hurdles, a variety of capsid engineering methods have been utilized to generate capsids with improved transduction properties. Here we describe an alternative approach to capsid engineering, which draws on the natural evolution of the virus and aims to yield capsids that are better suited to infect human tissues. We generated an AAV capsid to include amino acids that are conserved among natural AAV2 isolates and tested its biodistribution properties in mice and rats. Intriguingly, this novel variant, AAV-TT, demonstrates strong neurotropism in rodents and displays significantly improved distribution throughout the central nervous system as compared to AAV2. Additionally, sub-retinal injections in mice revealed markedly enhanced transduction of photoreceptor cells when compared to AAV2. Importantly, AAV-TT exceeds the distribution abilities of benchmark neurotropic serotypes AAV9 and AAVrh10 in the central nervous system of mice, and is the only virus, when administered at low dose, that is able to correct the neurological phenotype in a mouse model of mucopolysaccharidosis IIIC, a transmembrane enzyme lysosomal storage disease, which requires delivery to every cell for biochemical correction. These data represent unprecedented correction of a lysosomal transmembrane enzyme deficiency in mice and suggest that AAV-TT-based gene therapies may be suitable for treatment of human neurological diseases such as mucopolysaccharidosis IIIC, which is characterized by global neuropathology.
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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) | 0.001 | 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 | 0.001 |
| 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".