Pleiotropy in FOXC1-attributable phenotypes involves altered ciliation and cilia-dependent signaling
Bibliographic record
Abstract
Alterations to cilia are responsible for a wide range of severe disease; however, understanding of the transcriptional control of ciliogenesis remains incomplete. In this study we investigated whether altered cilia-mediated signaling contributes to the pleiotropic phenotypes caused by the Forkhead transcription factor FOXC1. Here, we show that patients with FOXC1-attributable Axenfeld-Rieger Syndrome (ARS) have a prevalence of ciliopathy-associated phenotypes comparable to syndromic ciliopathies. We demonstrate that altering the level of Foxc1 protein, via shRNA mediated inhibition, CRISPR/Cas9 mutagenesis and overexpression, modifies cilia length in vitro. These structural changes were associated with substantially perturbed cilia-dependent signaling [Hedgehog (Hh) and PDGFRα], and altered ciliary compartmentalization of the Hh pathway transcription factor, Gli2. Consistent with these data, in primary cultures of murine embryonic meninges, cilia length was significantly reduced in heterozygous and homozygous Foxc1 mutants compared to controls. Meningeal expression of the core Hh signaling components Gli1, Gli3 and Sufu was dysregulated, with comparable dysregulation of Pdgfrα signaling evident from significantly altered Pdgfrα and phosphorylated Pdgfrα expression. On the basis of these clinical and experimental findings, we propose a model that altered cilia-mediated signaling contributes to some FOXC1-induced phenotypes.
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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 | 0.001 |
| Research integrity | 0.001 | 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".