The ClinGen Syndromic Disorders Gene Curation Expert Panel: Assessing the clinical validity of 111 gene-disease relationships
Bibliographic record
Abstract
Purpose: The Clinical Genome Resource (ClinGen) Gene Curation Expert Panels have historically focused on specific organ systems or phenotypes; thus, the ClinGen Syndromic Disorders Gene Curation Expert Panel (SD-GCEP) was formed to address an unmet need. Methods: The SD-GCEP applied ClinGen's framework to evaluate the clinical validity of genes associated with rare syndromic disorders. A total of 111 gene-disease relationships (GDRs) associated with 100 genes spanning the clinical spectrum of syndromic disorders were curated. Results: From April 2020 through March 2024, 38 precurations were performed on genes with multiple disease relationships and were reviewed to determine if the disorders were part of a spectrum or distinct entities. A total of 14 genes were lumped into a single disease entity, and 24 were split into separate entities, of which 11 were curated by the SD-GCEP. A full review of 111 GDRs for 100 genes followed, with 78 classified as Definitive, 9 as Strong, 15 as Moderate, and 9 as Limited, highlighting cases in which further data are needed. All diseases involved 2 or more organ systems, whereas the majority (88/111 GDRs, 79.2%) had 5 or more organ systems affected. Conclusion: The SD-GCEP addresses a critical gap in gene curation efforts, enabling inclusion of genes for syndromic disorders in clinical testing and contributing to keeping pace with the rapid discovery of new genetic syndromes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".