Novel <i>BBS1</i> deletion and <i>BBS9</i> nonsense pathogenic variant in Bardet-Biedl syndrome
Bibliographic record
Abstract
Background Bardet‐Biedl syndrome (BBS) is a rare syndromic ciliopathy characterized with retinal degeneration and a broad range of systemic features. Twenty-six BBS-associated genes have been identified to date and clinical genetic testing resolves around 80% of the cases. Two BBS cases unsolved by clinical genetic testing were recruited to identify causative variants using next-generation sequencing.Methods Genomic DNA of the probands from both families was extracted from peripheral blood. Whole genome or exome sequencing results were analyzed with comprehensive variant filtering on structural variants, single nucleotide variants (SNVs), insertions/deletions (indels).Results Family 1: A novel rare deletion NM_024649.5(BBS1): c.830 + 554_1110 + 1052del; p.(Asp278Metfs*3) was identified in the female proband in trans with a known pathogenic missense variant p.(Met390Arg). This 3k base pair (bp) deletion was predicted to cause a loss in exons 10–11, resulting in a premature stop codon. Family 2: Variant filtering in the male proband identified two rare (gnomAD AF < 0.01%) nonsense SNVs in trans in BBS9, NM_198428.3: c.724 G>T; p.(Gly242*) and c.966 G>A; p.(Trp322*), one of them being a novel pathogenic variant.Conclusion All the novel variants identified fell into the pathogenic variant classification following ACMG/AMP criteria. This report highlights the role of whole exome and genome sequencing in unsolved cases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".