Genome‐wide association study: Exploring the genetic basis for responsiveness to ketogenic dietary therapies for drug‐resistant epilepsy
Bibliographic record
Abstract
OBJECTIVE: With the exception of specific metabolic disorders, predictors of response to ketogenic dietary therapies (KDTs) are unknown. We aimed to determine whether common variation across the genome influences the response to KDT for epilepsy. METHODS: We genotyped individuals who were negative for glucose transporter type 1 deficiency syndrome or other metabolic disorders, who received KDT for epilepsy. Genotyping was performed with the Infinium HumanOmniExpressExome Beadchip. Hospital records were used to obtain demographic and clinical data. KDT response (≥50% seizure reduction) at 3-month follow-up was used to dissect out nonresponders and responders. We then performed a genome-wide association study (GWAS) in nonresponders vs responders, using a linear mixed model and correcting for population stratification. Variants with minor allele frequency <0.05 and those that did not pass quality control filtering were excluded. RESULTS: , odds ratio [A] = 13.5, 95% confidence interval [CI] 4.07-44.8). Although analysis of regional linkage disequilibrium around rs12204701 did not strengthen the likelihood of CDYL being the candidate gene, additional bioinformatic analyses suggest it is the most likely candidate. SIGNIFICANCE: CDYL deficiency has been shown to disrupt neuronal migration and to influence susceptibility to epilepsy in mice. Further exploration with a larger replication cohort is warranted to clarify whether CDYL is the causal gene underlying the association signal.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".