Molecular analysis expands the spectrum of phenotypes associated with GLI3 mutations
Bibliographic record
Abstract
A range of phenotypes including Greig cephalopolysyndactyly and Pallister-Hall syndromes (GCPS, PHS) are caused by pathogenic mutation of the GLI3 gene. To characterize the clinical variability of GLI3 mutations, we present a subset of a cohort of 174 probands referred for GLI3 analysis. Eighty-one probands with typical GCPS or PHS were previously reported, and we report the remaining 93 probands here. This includes 19 probands (12 mutations) who fulfilled clinical criteria for GCPS or PHS, 48 probands (16 mutations) with features of GCPS or PHS but who did not meet the clinical criteria (sub-GCPS and sub-PHS), 21 probands (6 mutations) with features of PHS or GCPS and oral-facial-digital syndrome, and 5 probands (1 mutation) with nonsyndromic polydactyly. These data support previously identified genotype-phenotype correlations and demonstrate a more variable degree of severity than previously recognized. The finding of GLI3 mutations in patients with features of oral-facial-digital syndrome supports the observation that GLI3 interacts with cilia. We conclude that the phenotypic spectrum of GLI3 mutations is broader than that encompassed by the clinical diagnostic criteria, but the genotype-phenotype correlation persists. Individuals with features of either GCPS or PHS should be screened for mutations in GLI3 even if they do not fulfill clinical criteria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".