Clinical exome sequencing efficacy and phenotypic expansions involving anomalous pulmonary venous return
Bibliographic record
Abstract
Anomalous pulmonary venous return (APVR) frequently occurs with other congenital heart defects (CHDs) or extra-cardiac anomalies. While some genetic causes have been identified, the optimal approach to genetic testing in individuals with APVR remains uncertain, and the etiology of most cases of APVR is unclear. Here, we analyzed molecular data from 49 individuals to determine the diagnostic yield of clinical exome sequencing (ES) for non-isolated APVR. A definitive or probable diagnosis was made for 8 of those individuals yielding a diagnostic efficacy rate of 16.3%. We then analyzed molecular data from 62 individuals with APVR accrued from three databases to identify novel APVR genes. Based on data from this analysis, published case reports, mouse models, and/or similarity to known APVR genes as revealed by a machine learning algorithm, we identified 3 genes-EFTUD2, NAA15, and NKX2-1-for which there is sufficient evidence to support phenotypic expansion to include APVR. We also provide evidence that 3 recurrent copy number variants contribute to the development of APVR: proximal 1q21.1 microdeletions involving RBM8A and PDZK1, recurrent BP1-BP2 15q11.2 deletions, and central 22q11.2 deletions involving CRKL. Our results suggest that ES and chromosomal microarray analysis (or genome sequencing) should be considered for individuals with non-isolated APVR for whom a genetic etiology has not been identified, and that genetic testing to identify an independent genetic etiology of APVR is not warranted in individuals with EFTUD2-, NAA15-, and NKX2-1-related disorders.
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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 | 0.000 |
| 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 | 0.000 | 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".