Evidence of shared genetic risk factors for migraine and rolandic epilepsy
Bibliographic record
Abstract
PURPOSE: Evidence for a specific association between migraine and rolandic epilepsy (RE) has been conflicting. Children with migraine frequently have electroencephalographic (EEG) abnormalities, including rolandic discharges, and approximately 50% of siblings of patients with RE exhibit rolandic discharges. We assessed migraine risk in RE probands and their siblings. METHODS: We used cohort and reconstructed cohort designs to respectively assess the relative risk of migraine in 72 children with RE and their 88 siblings using International Classification of Headache Disorders (ICHD-2) criteria. Incidences were compared in 150 age and geographically matched nonepilepsy probands and their 188 siblings. We used a Cox proportional hazards model, using age as the time base, adjusting hazard ratios (HRs) for sex in the proband analysis, and for sex and proband migraine status in the sibling analysis. RESULTS: Prevalence of migraine in RE probands was 15% versus 7% in nonepilepsy probands, and in siblings of RE probands prevalence was 14% versus 4% in nonepilepsy siblings. The sex-adjusted HR of migraine for an RE proband was 2.46 [95% confidence interval (CI) 1.06-5.70]. The adjusted HR of having > or =1 sibling with migraine in an RE family was 3.35 (95% CI 1.20-9.33), whereas the HR of any one sibling of a RE proband was 2.86 (95% CI 1.10-7.43). DISCUSSION: Migraine is strongly comorbid in RE and independently clusters in their siblings. These results suggest shared susceptibility to migraine and RE that is not directly mediated by epileptic seizures. Susceptibility gene variants for RE may be tested as risk factors for migraine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".