Allele-Specific Suppression of Mutant Huntingtin Using Antisense Oligonucleotides: Providing a Therapeutic Option for All Huntington Disease Patients
Bibliographic record
Abstract
Huntington disease (HD) is an inherited, fatal neurodegenerative disorder caused by a CAG repeat expansion in the huntingtin gene. The mutant protein causes neuronal dysfunction and degeneration resulting in motor dysfunction, cognitive decline, and psychiatric disturbances. Currently, there is no disease altering treatment, and symptomatic therapy has limited benefit. The pathogenesis of HD is complicated and multiple pathways are compromised. Addressing the problem at its genetic root by suppressing mutant huntingtin expression is a promising therapeutic strategy for HD. We have developed and evaluated antisense oligonucleotides (ASOs) targeting single nucleotide polymorphisms that are significantly enriched on HD alleles (HD-SNPs). We describe our structure-activity relationship studies for ASO design and find that adjusting the SNP position within the gap, chemical modifications of the wings, and shortening the unmodified gap are critical for potent, specific, and well tolerated silencing of mutant huntingtin. Finally, we show that using two distinct ASO drugs targeting the two allelic variants of an HD-SNP could provide a therapeutic option for all persons with HD; allele-specifically for roughly half, and non-specifically for the remainder.
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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) | 0.001 | 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".