The yield on re-interpretation of genetic variants in pediatric cardiomyopathy
Bibliographic record
Abstract
ABSTRACT Background Variant interpretation can change over time as new knowledge emerges. Our aim was to determine the frequency and causes of variant reinterpretation on systematic re-evaluation in pediatric patients with cardiomyopathy. Methods Overall, 227 unrelated pediatric patients with cardiomyopathy enrolled in the Heart Centre Biobank harbored a pathogenic/likely pathogenic (P/LP) variant and/or a variant of uncertain significance (VUS) on clinical genetic testing (2005-2022). Variant pathogenicity was re-evaluated using the American College of Medical Genetics and Genomics (ACMG) guidelines. Additional extension cohorts (n=4547, cases) were analyzed to assess variant burden in cases versus controls (gnomAD 4.1.0). Results 382 variants (110 P/LP, 272 VUS) in 227 patients were re-evaluated. Forty-nine variants in 49 patients (21.6%) changed classification. Twelve (10.9%) P/LP variants were downgraded to VUS in 14 patients. Leading criteria were high population allele frequency and variant not located in mutational hotspot or critical functional gene domain. Thirty-seven (13.6%) VUS were upgraded to P/LP in 35 patients. Leading criteria were variant location in mutational hotspot for gene, and deleteriousness on in silico prediction. Only 8 reclassified variants had been reported back by the clinical genetic testing laboratory at the time of the study. Ten of the 37 VUS upgraded to P/LP were significantly enriched in cardiomyopathy cases (n=4796) versus controls. Conclusions One in five patients with cardiomyopathy had a clinically relevant change in variant pathogenicity on systematic re-evaluation that would require modifying family clinical screening and cascade genetic testing. These findings underscore the clinical importance of regular variant re-interpretation on follow-up.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".