Mutations in Hedgehog Acyltransferase (Hhat) Perturb Hedgehog Signaling, Resulting in Severe Acrania-Holoprosencephaly-Agnathia Craniofacial Defects
Bibliographic record
Abstract
Holoprosencephaly (HPE) is a failure of the forebrain to bifurcate and is the most common structural malformation of the embryonic brain. Mutations in SHH underlie most familial (17%) cases of HPE; and, consistent with this, Shh is expressed in midline embryonic cells and tissues and their derivatives that are affected in HPE. It has long been recognized that a graded series of facial anomalies occurs within the clinical spectrum of HPE, as HPE is often found in patients together with other malformations such as acrania, anencephaly, and agnathia. However, it is not known if these phenotypes arise through a common etiology and pathogenesis. Here we demonstrate for the first time using mouse models that Hedgehog acyltransferase (Hhat) loss-of-function leads to holoprosencephaly together with acrania and agnathia, which mimics the severe condition observed in humans. Hhat is required for post-translational palmitoylation of Hedgehog (Hh) proteins; and, in the absence of Hhat, Hh secretion from producing cells is diminished. We show through downregulation of the Hh receptor Ptch1 that loss of Hhat perturbs long-range Hh signaling, which in turn disrupts Fgf, Bmp and Erk signaling. Collectively, this leads to abnormal patterning and extensive apoptosis within the craniofacial primordial, together with defects in cartilage and bone differentiation. Therefore our work shows that Hhat loss-of-function underscrores HPE; but more importantly it provides a mechanism for the co-occurrence of acrania, holoprosencephaly, and agnathia. Future genetic studies should include HHAT as a potential candidate in the etiology and pathogenesis of HPE and its associated disorders.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".