Exome survey of individuals affected by <scp>VATER</scp>/<scp>VACTERL</scp> with renal phenotypes identifies phenocopies and novel candidate genes
Bibliographic record
Abstract
The acronym VATER/VACTERL refers to the rare nonrandom association of the following component features (CFs): vertebral defects (V), anorectal malformations (ARM) (A), cardiac anomalies (C), tracheoesophageal fistula with or without esophageal atresia (TE), renal malformations (R), and limb anomalies (L). For the clinical diagnosis, the presence of at least three CFs is required, individuals presenting with only two CFs have been categorized as VATER/VACTERL-like. The majority of VATER/VACTERL individuals displays a renal phenotype. Hitherto, variants in FGF8, FOXF1, HOXD13, LPP, TRAP1, PTEN, and ZIC3 have been associated with the VATER/VACTERL association; however, large-scale re-sequencing could only confirm TRAP1 and ZIC3 as VATER/VACTERL disease genes, both associated with a renal phenotype. In this study, we performed exome sequencing in 21 individuals and their families with a renal VATER/VACTERL or VATER/VACTERL-like phenotype to identify potentially novel genetic causes. Exome analysis identified biallelic and X-chromosomal hemizygous potentially pathogenic variants in six individuals (29%) in B9D1, FREM1, ZNF157, SP8, ACOT9, and TTLL11, respectively. The online tool GeneMatcher revealed another individual with a variant in ZNF157. Our study suggests six biallelic and X-chromosomal hemizygous VATER/VACTERL disease genes implicating all six genes in the expression of human renal malformations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".