Systemic delivery of mutant huntingtin lowering antisense oligonucleotides to the brain using apolipoprotein A-I nanodisks for Huntington disease
Bibliographic record
Abstract
Efficient delivery of therapeutics to the central nervous system (CNS) remains a major challenge for the treatment of neurological diseases. Huntington disease (HD) is a dominantly inherited neurodegenerative disorder caused by a CAG trinucleotide expansion mutation in the HTT gene which codes for a toxic mutant huntingtin (mHTT) protein. Pharmacological reduction of mHTT in the CNS using antisense oligonucleotides (ASO) ameliorates HD-like phenotypes in rodent models of HD, with such therapies being investigated in clinical trials for HD. In this study, we report the optimization of apolipoprotein A-I nanodisks (apoA-I NDs) as vehicles for delivery of a HTT-targeted ASO (HTT ASO) to the brain and peripheral organs for HD. We demonstrate that apoA-I wild type (WT) and the apoA-I K133C mutant incubated with a synthetic lipid, 1,2-dimyristoyl-sn-glycero-3-phosphocholine, can self-assemble into monodisperse discoidal particles with diameters <20 nm that transmigrate across an in vitro blood-brain barrier model of HD. We demonstrate that apoA-I NDs are well tolerated in vivo, and that apoA-I K133C NDs show enhanced distribution to the CNS and peripheral organs compared to apoA-I WT NDs following systemic administration. ApoA-I K133C conjugated with HTT ASO forms NDs (HTT ASO NDs) that induce significant mHTT lowering in the liver, skeletal muscle and heart as well as in the brain when delivered intravenously in the BACHD mouse model of HD. Furthermore, HTT ASO NDs increase the magnitude of mHTT lowering in the striatum and cortex compared to HTT ASO alone following intracerebroventricular administration. These findings demonstrate the potential utility of apoA-I NDs as biocompatible vehicles for enhancing delivery of mutant HTT lowering ASOs to the CNS and peripheral organs for HD.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".