Assessing Precision Antisense Oligonucleotide Therapy Eligibility for Infantile Genetic Epilepsies
Bibliographic record
Abstract
Abstract Importance The highest incidence of pediatric epilepsy is in the first year of life. Most infantile epilepsies have presumed genetic etiologies and timely precision genetic diagnosis is increasingly possible. However, treatment remains largely symptomatic and outcomes poor due to a gap from precision diagnoses to precision therapies. Antisense oligonucleotide therapies are a precision therapy approach that holds promise for transforming outcomes. Objective To determine the proportion of infants with genetic epilepsies eligible for precision antisense oligonucleotide therapy approaches. Design This cohort study assessed eligibility for antisense oligonucleotide therapy approaches for 160 infants with epilepsy enrolled in the Gene-STEPS study from September 2021 to March 2025 with diagnostic genome sequencing. Clinical data were collected through October 2025. Setting Four pediatric referral centers. Participants Participants with infantile epilepsy and diagnostic genome sequencing. Exposure(s) Assessment for antisense oligonucleotide therapy eligibility using established guidelines and multidisciplinary review. Main Outcome(s) and Measure(s) Primary: proportion eligible for antisense oligonucleotide therapy approaches based on variant assessment; Secondary: proportion remaining eligible after considering general disease factors and patient-specific phenotypes. Results We assessed 160 infants with genetic epilepsies (86 male (54%)), 39 with neonatal seizure onset (<44 weeks postmenstrual age, 24%)), for eligibility for precision antisense oligonucleotide therapy approaches. Of 152 unique variants, 133 were single nucleotide variants or small insertions-deletions (74 missense, 23 frameshift, 26 nonsense, 8 intronic, 2 in-frame indels), 17 copy number variants (4 intragenic), and 2 repeat expansions. Twenty-four unique variants from 25 infants (15.6%) were in principle eligible for an exon-skipping, knockdown, splice correction, or existing upregulation antisense oligonucleotide therapy approach. Taking into account general disease factors and patient-specific phenotypes, 16/25 infants (64%) could be currently considered for these approaches and an additional 5/25 (20%) could have been considered at seizure onset. Conclusions and Relevance A substantial proportion of infants with genetic epilepsies may be eligible for precision antisense oligonucleotide therapy approaches. Our findings highlight the potential of these emerging therapies to narrow the gap from precision diagnoses to precision therapies for this population. Key Points Question What proportion of infants with genetic epilepsies are eligible for precision antisense oligonucleotide therapy approaches? Findings In this cohort study of 160 infants with genetic epilepsies, 25/160 infants (15.6%) had variants that are, in principle, eligible for antisense oligonucleotide therapy approaches. Taking into account both general disease factors and patient-specific phenotypes, 16/25 infants (64%) could be currently considered for these approaches and an additional 5/25 (20%) could have been considered at seizure onset. Meaning A substantial proportion of infantile genetic epilepsies may be eligible for precision antisense oligonucleotide therapy approaches.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".