Hippocampal Malrotation is Associated with Chromosome 22q11.2 Microdeletion
Bibliographic record
Abstract
BACKGROUND: Patients with chromosome 22q11.2 deletion syndrome (22q11DS) are at a seven fold increased risk of developing seizures. However, only a fraction of these patients exhibit structural abnormalities such as polymicrogyria (PMG) and periventricular nodular heterotopia (PNH) that are known to cause seizures and to be associated with 22q11DS. In this study we used a dedicated seizure imaging protocol to look for additional structural abnormalities in these individuals that may explain the elevated risk of seizure disorder in this patient group. METHODS: Nineteen consecutive adult subjects with 22q11DS underwent a 3 Tesla MRI with a dedicated high-resolution seizure protocol. Neurological exam was performed in all patients. Genome-wide analysis excluded the presence of other pathogenic microdeletions or duplications. RESULTS: Structural abnormalities were found in 11 of 14 subjects with sufficient image quality. These included three patients with PNH, one of whom had associated PMG. In addition, there was a surprisingly high prevalence of unilateral hippocampal malrotation (HIMAL), observed in 9 of 14 cases (64%). EEG findings showed interictal epileptiform discharges with focal distribution in four patients and generalized discharges in one patient. CONCLUSION: The results suggest that, in addition to other known structural abnormalities, 22q11DS is associated with HIMAL. It has been suggested that this developmental abnormality of the hippocampus may predispose or otherwise contribute to epileptogenesis. However in this study we observed HIMAL in a large proportion of patients, with and without epilepsy. Therefore, other as yet unknown factors may contribute to the high prevalence of epilepsy in this population.
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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 | 0.001 |
| 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 | 0.000 |
| 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".