GPC3 mutation analysis in a spectrum of patients with overgrowth expands the phenotype of Simpson-Golabi-Behmel syndrome
Bibliographic record
Abstract
Simpson-Golabi-Behmel syndrome (SGBS) is an X-linked overgrowth syndrome caused by deletions in glypican 3 (GPC3). SGBS is characterized by pre- and postnatal overgrowth, a characteristic facial appearance, and a spectrum of congenital malformations which overlaps that of other overgrowth syndromes. We performed GPC3 deletion screening on 80 male patients with somatic overgrowth in the following categories: SGBS (n = 19), possible SGBS (n = 26), including families in which individuals had previously been diagnosed with other overgrowth syndromes, and Wiedemann-Beckwith syndrome (WBS) (n = 35). Using exon-specific PCR and Southern blot analysis, we identified seven GPC3 deletions. In most cases a clear X-linked family history was not present. In two cases, GPC3 deletions were identified in patients belonging to pedigrees published previously as other overgrowth syndromes: one with a diagnosis of Sotos syndrome and the other Perlman syndrome with nephroblastomatosis. A third patient developed hepatoblastoma, a tumor type not previously described in SGBS. No GPC3 deletions were identified among the WBS patients. Direct sequencing of all GPC3 exons in the remaining 13 SGBS patients without GPC3 deletions did not identify any further mutations, raising the possibility of alternative silencing mechanisms and/or other genes in the pathogenesis of SGBS. Our results validate the clinical specificity of the facial appearance, skeletal/hand anomalies, and supernumerary nipples in patients with GPC3 deletions. Our data also suggest that nephroblastomatosis and hepatoblastoma are included in the phenotypic spectrum of GPC3 deletions and SGBS, underscoring the importance of tumor surveillance in these children.
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 | 0.001 |
| 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) | 0.001 | 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".