Mutations in<i>C8ORF37</i>cause Bardet Biedl syndrome (BBS21)
Bibliographic record
Abstract
Bardet Biedl syndrome (BBS) is a multisystem genetically heterogeneous ciliopathy that most commonly leads to obesity, photoreceptor degeneration, digit anomalies, genito-urinary abnormalities, as well as cognitive impairment with autism, among other features. Sequencing of a DNA sample from a 17-year-old female affected with BBS did not identify any mutation in the known BBS genes. Whole-genome sequencing identified a novel loss-of-function disease-causing homozygous mutation (K102*) in C8ORF37, a gene coding for a cilia protein. The proband was overweight (body mass index 29.1) with a slowly progressive rod-cone dystrophy, a mild learning difficulty, high myopia, three limb post-axial polydactyly, horseshoe kidney, abnormally positioned uterus and elevated liver enzymes. Mutations in C8ORF37 were previously associated with severe autosomal recessive retinal dystrophies (retinitis pigmentosa RP64 and cone-rod dystrophy CORD16) but not BBS. To elucidate the functional role of C8ORF37 in a vertebrate system, we performed gene knockdown in Danio rerio and assessed the cardinal features of BBS and visual function. Knockdown of c8orf37 resulted in impaired visual behavior and BBS-related phenotypes, specifically, defects in the formation of Kupffer's vesicle and delays in retrograde transport. Specificity of these phenotypes to BBS knockdown was shown with rescue experiments. Over-expression of human missense mutations in zebrafish also resulted in impaired visual behavior and BBS-related phenotypes. This is the first functional validation and association of C8ORF37 mutations with the BBS phenotype, which identifies BBS21. The zebrafish studies hereby show that C8ORF37 variants underlie clinically diagnosed BBS-related phenotypes as well as isolated retinal degeneration.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".