An uncommon finding of Menke-Hennekam syndrome 1 associated with congenital diaphragmatic hernia and autism-like features
Bibliographic record
Abstract
Introduction: Menke-Hennekam syndrome 1 (MKHK1) is a congenital disorder resulting from mutations associated with CREBBP pathogenic variants mapped to 16p13.3. This ubiquitously expressed gene is involved in the transcription of several transcription factors that have key roles in embryonic development, homeostasis, and growth control. Interestingly, although mutations in this gene are classically associated with Rubinstein-Taybi syndrome (RTS), individuals with MKHK1 do not share the distinct facial features of RTS or other dysmorphisms. Case Presentation: In this case report, we present the case of an individual who presented antenatally with congenital diaphragmatic hernia and was subsequently found to have a pathogenic heterozygous de novo variant in the CREBBP gene associated with MKHK1 (c.5599C > T; p.Arg1867Trp). We present the clinical manifestations and discuss the novelty of congenital diaphragmatic hernia in this condition and the developmental profile associated with the condition. Conclusion: We report a case of a child with antenatally detected CDH and normal CMA who was later found to have a de novo variant consistent with Menke-Hennekam syndrome on WES. This highlights the value of considering WES when CMA is normal, and the importance of close developmental follow-up to enable early intervention and family support.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".