Advances in overgrowth syndromes: clinical classification to molecular delineation in Sotos syndrome and Beckwith-Wiedemann syndrome
Bibliographic record
Abstract
PURPOSE OF REVIEW: The clinical importance of overgrowth syndromes in the pediatric patient population has been increasingly recognized during the past decade, but clinical overlap among overgrowth syndromes often makes diagnostic categorization difficult. Advances in the molecular delineation of overgrowth syndromes in recent years have furthered our knowledge of the phenotypic spectrum of this group of conditions. This review focuses on developments in our understanding of the molecular mechanisms and phenotype-genotype correlations in the two most common overgrowth syndromes, Beckwith-Wiedemann syndrome and Sotos syndrome. The implications of these findings with respect to clinical diagnosis, medical management, and genetic counseling are discussed. RECENT FINDINGS: Recent reports have redefined the cardinal clinical features of Sotos syndrome, and the identification of two distinct types of molecular alterations in patients with this syndrome has enabled assessment of phenotype-genotype correlations. Recent studies in patients with Beckwith-Wiedemann syndrome have further expanded our understanding of the causative molecular mechanisms of this condition and provide evidence for specific genotype-phenotype correlations, most notably with respect to tumor risk. SUMMARY: Recognition of childhood overgrowth and investigation of diagnostic causes is important in anticipating appropriate medical management and facilitating the provision of genetic counseling. New developments in our understanding of the molecular basis and phenotypic expression of overgrowth syndromes provide additional tools in this often challenging process.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".