Lack of Phenotypic Differences by Cardiovascular Magnetic Resonance Imaging in MYH7 (β-Myosin Heavy Chain)- Versus MYBPC3 (Myosin-Binding Protein C)-Related Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Background— The 2 most commonly affected genes in hypertrophic cardiomyopathy (HCM) are MYH7 (β-myosin heavy chain) and MYBPC3 (β-myosin-binding protein C). Phenotypic differences between patients with mutations in these 2 genes have been inconsistent. Scarce data exist on the genotype–phenotype association as assessed by tomographic imaging using cardiac magnetic resonance imaging. Methods and Results— Cardiac magnetic resonance imaging was performed on 358 consecutive genotyped hypertrophic cardiomyopathy probands at 5 tertiary hypertrophic cardiomyopathy centers. Genetic testing revealed a pathogenic mutation in 159 patients (44.4%). The most common genes identified were MYH7 (n=53) and MYBPC3 (n=75); 33.1% and 47% of genopositive patients, respectively. Phenotypic characteristics by cardiac magnetic resonance imaging of these 2 groups were similar, including left ventricular volumes, mass, maximal wall thickness, morphology, left atrial volume, and mitral valve leaflet lengths (all P =non-significant). The presence of late gadolinium enhancement (65% versus 64%; P =0.99) and the proportion of total left ventricular mass (%late gadolinium enhancement; 10.4±13.2% versus 8.5±8.5%; P =0.44) were also similar. Conclusions— This multicenter multinational study shows lack of phenotypic differences between MYH7- and MYBPC3-associated hypertrophic cardiomyopathy when assessed by cardiac magnetic resonance imaging. Postmutational mechanisms appear more relevant to thick-filament disease expression and outcome than the disease-causing variant per se.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".