Assessing the role of rare genetic variants in drug-resistant, non-lesional focal epilepsy
Bibliographic record
Abstract
OBJECTIVE: Resistance to antiseizure medications (ASMs) is one of the major concerns in the treatment of epilepsy. Despite the increasing number of ASMs available, the proportion of individuals with drug-resistant epilepsy remains unchanged. In this study, we aimed to investigate the role of rare genetic variants in ASM resistance. METHODS: We performed exome sequencing of 1,128 individuals with non-familial non-acquired focal epilepsy (NAFE) (762 non-responders, 366 responders) and were provided with 1,734 healthy controls. We undertook replication in a cohort of 350 individuals with NAFE (165 non-responders, 185 responders). We performed gene-based and gene-set-based kernel association tests to investigate potential enrichment of rare variants in relation to drug response status and to risk for NAFE. RESULTS: We found no gene or gene set that reached genome-wide significance. Yet, we identified several prospective candidate genes - among them DEPDC5, which showed a potential association with resistance to ASMs. We found some evidence for an enrichment of truncating variants in dominant familial NAFE genes in our cohort of non-familial NAFE and in association with drug-resistant NAFE. INTERPRETATION: Our study identifies potential candidate genes for ASM resistance. Our results corroborate the role of rare variants for non-familial NAFE and imply their involvement in drug-resistant epilepsy. Future large-scale genetic research studies are needed to substantiate these findings.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".