The Cardiac Genome Clinic: implementing genome sequencing in pediatric heart disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: This study investigated the diagnostic utility of nontargeted genomic testing in patients with pediatric heart disease. METHODS: We analyzed genome sequencing data of 111 families with cardiac lesions for rare, disease-associated variation. RESULTS: In 14 families (12.6%), we identified causative variants: seven were de novo (ANKRD11, KMT2D, NR2F2, POGZ, PTPN11, PURA, SALL1) and six were inherited from parents with no or subclinical heart phenotypes (FLT4, DNAH9, MYH11, NEXMIF, NIPBL, PTPN11). Outcome of the testing was associated with the presence of extracardiac features (p = 0.02), but not a positive family history for cardiac lesions (p = 0.67). We also report novel plausible gene-disease associations for tetralogy of Fallot/pulmonary stenosis (CDC42BPA, FGD5), hypoplastic left or right heart (SMARCC1, TLN2, TRPM4, VASP), congenitally corrected transposition of the great arteries (UBXN10), and early-onset cardiomyopathy (TPCN1). The identified candidate genes have critical functions in heart development, such as angiogenesis, mechanotransduction, regulation of heart size, chromatin remodeling, or ciliogenesis. CONCLUSION: This data set demonstrates the diagnostic and scientific value of genome sequencing in pediatric heart disease, anticipating its role as a first-tier diagnostic test. The genetic heterogeneity will necessitate large-scale genomic initiatives for delineating novel gene-disease associations.
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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 it