Delivery of mutant huntingtin-lowering antisense oligonucleotides to the brain by intranasally administered apolipoprotein A-I nanodisks
Bibliographic record
Abstract
Lowering mutant huntingtin (mHTT) in the central nervous system (CNS) using antisense oligonucleotides (ASOs) is a promising approach currently being evaluated in clinical trials for Huntington disease (HD). However, the therapeutic potential of ASOs in HD patients is limited by their inability to cross the blood-brain barrier (BBB). In non-human primates, intrathecal infusion of ASOs results in limited brain distribution, with higher ASO concentrations in superficial regions and lower concentrations in deeper regions, such as the basal ganglia. To address the need for improved delivery of ASOs to the brain, we are evaluating the therapeutic potential of apolipoprotein A-I nanodisks (apoA-I NDs) as novel delivery vehicles for mHTT-lowering ASOs to the CNS after intranasal administration. Here, we have demonstrated the ability of apoA-I nanodisks to bypass the BBB after intranasal delivery in the BACHD model of HD. Following intranasal administration of apoA-I NDs, apoA-I protein levels were elevated along the rostral-caudal brain axis, with highest levels in the most rostral brain regions including the olfactory bulb and frontal cortex. Double-label immunohistochemistry indicates that both the apoA-I and ASO deposit in neurons. Most importantly, a single intranasal dose of apoA-I ASO-NDs significantly reduces mHTT levels in the brain regions most affected in HD, namely the cortex and striatum. This approach represents a novel non-invasive means for improving delivery and brain distribution of oligonucleotide therapies and enhancing likelihood of efficacy. Improved ASO delivery to the brain has widespread application for treatment of many other CNS disorders.
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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) | 0.000 | 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 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".