Deep Phenotyping of the Broader Autism Phenotype in Epilepsy: A Transdiagnostic Marker of Epilepsy and Autism Spectrum Disorder
Bibliographic record
Abstract
ABSTRACT Objective We conducted deep and minimal phenotyping of the broader autism phenotype (BAP) in people with epilepsy (PWE) and compared its expression with published rates in the general population and relatives of individuals with autism spectrum disorder (ASD‐relatives). We then examined the association of clinical epilepsy variables with BAP expression to explore its underpinnings in PWE. Methods 103 adults with seizures (Mage = 37.37, SD = 12.50; 47% males; 51 temporal lobe epilepsy, 40 genetic generalized epilepsy, 12 other) and 58 community members (Mage = 39.59, SD = 14.56; 35% males) underwent deep phenotyping using the observer‐rated Autism Endophenotype Interview and minimal phenotyping with the Broader Autism Phenotype Questionnaire (BAPQ). Published rates of the BAP were ascertained from large randomly selected samples (n > 100) of the general population and ASD‐relatives based on BAPQ data. Results There was a higher rate of BAP in PWE (15% males, 27% females) compared with the general population (5% males, 7% females) and a similar rate to ASD‐relatives (9% males, 20% females). Deep phenotyping identified an additional 22 males and 10 females, with the combined measures indicating elevated rates of the BAP in PWE (44% males, 36% females). Only a shorter duration of epilepsy was weakly correlated with BAP trait expression in males (r = − 0.21, p = 0.05). Interpretation PWE have a high rate of BAP, largely unrelated to secondary clinical epilepsy effects. The BAP may provide a trans‐diagnostic marker of shared etiological mechanisms of epilepsy and ASD and partly account for psychosocial difficulties faced by PWE with childhood or adult onset of seizures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".