Coffin-Siris Syndrome and the BAF Complex: Genotype-Phenotype Study in 63 Patients
Bibliographic record
Abstract
De novo germline variants in several components of the SWI/SNF-like BAF complex can cause Coffin-Siris syndrome (CSS), Nicolaides-Baraitser syndrome (NCBRS), and nonsyndromic intellectual disability. We screened 63 patients with a clinical diagnosis of CSS for these genes (ARID1A, ARID1B, SMARCA2, SMARCA4, SMARCB1, and SMARCE1) and identified pathogenic variants in 45 (71%) patients. We found a high proportion of variants in ARID1B (68%). All four pathogenic variants in ARID1A appeared to be mosaic. By using all variants from the Exome Variant Server as test data, we were able to classify variants in ARID1A, ARID1B, and SMARCB1 reliably as being pathogenic or nonpathogenic. For SMARCA2, SMARCA4, and SMARCE1 several variants in the EVS remained unclassified, underlining the importance of parental testing. We have entered all variant and clinical information in LOVD-powered databases to facilitate further genotype-phenotype correlations, as these will become increasingly important because of the uptake of targeted and untargeted next generation sequencing in diagnostics. The emerging phenotype-genotype correlation is that SMARCB1 patients have the most marked physical phenotype and severe cognitive and growth delay. The variability in phenotype seems most marked in ARID1A and ARID1B patients. Distal limbs anomalies are most marked in ARID1A patients and least in SMARCB1 patients. Numbers are small however, and larger series are needed to confirm this correlation.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".