Deep phenotyping of the neuroimaging and skeletal features in KBG syndrome: a study of 53 patients and review of the literature
Bibliographic record
Abstract
Background KBG syndrome is caused by haploinsufficiency of ANKRD11 and is characterised by macrodontia of upper central incisors, distinctive facial features, short stature, skeletal anomalies, developmental delay, brain malformations and seizures. The central nervous system (CNS) and skeletal features remain poorly defined. Methods CNS and/or skeletal imaging were collected from molecularly confirmed individuals with KBG syndrome through an international network. We evaluated the original imaging and compared our results with data in the literature. Results We identified 53 individuals, 44 with CNS and 40 with skeletal imaging. Common CNS findings included incomplete hippocampal inversion and posterior fossa malformations; these were significantly more common than previously reported (63.4% and 65.9% vs 1.1% and 24.7%, respectively). Additional features included patulous internal auditory canal, never described before in KBG syndrome, and the recurrence of ventriculomegaly, encephalic cysts, empty sella and low-lying conus medullaris. We found no correlation between these structural anomalies and epilepsy or intellectual disability. Prevalent skeletal findings comprised abnormalities of the spine including scoliosis, coccygeal anomalies and cervical ribs. Hand X-rays revealed frequent abnormalities of carpal bone morphology and maturation, including a greater delay in ossification compared with metacarpal/phalanx bones. Conclusion This cohort enabled us to describe the prevalence of very heterogeneous neuroradiological and skeletal anomalies in KBG syndrome. Knowledge of the spectrum of such anomalies will aid diagnostic accuracy, improve patient care and provide a reference for future research on the effects of ANKRD11 variants in skeletal and brain development.
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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) | 0.001 | 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".