Sarcomere Gene Mutations in Isolated Left Ventricular Noncompaction Cardiomyopathy Do Not Predict Clinical Phenotype
Bibliographic record
Abstract
BACKGROUND: Left ventricular noncompaction of the myocardium (LVNC) has been recognized as a cardiomyopathy with a genetic etiology. Mutations in genes encoding sarcomere proteins were shown to be associated with LVNC. We evaluated the potential clinical impact of genetic analysis of sarcomere genes in patients with LVNC. METHODS AND RESULTS: We identified 5 mutations in cardiac myosin-binding protein C (MYBPC3) and 2 mutations in α-tropomyosin (TPM1) in a cohort of unrelated adult probands with isolated LVNC. The mutations in MYBPC3 and TPM1 and in 6 other previously reported sarcomere genes in this cohort resulted in a total of 18 (29%) heterozygous mutations in 63 probands. β-myosin heavy chain (MYH7) was the most prevalent disease gene and accounts for 13% of cases, followed by MYBPC3 (8%). Comparing sarcomere mutation-positive and mutation-negative LVNC probands showed no significant differences in terms of average age, myocardial function, and presence of heart failure or tachyarrhythmias at initial presentation or at follow-up. Familial disease was found in 16 probands of whom 8 were sarcomere mutation positive. Nonpenetrance was detected in 2 of 8 mutation-positive families with LVNC. CONCLUSIONS: Mutations in sarcomere genes account for a significant (29%) proportion of cases of isolated LVNC in this cohort. The distribution of disease genes confirms genetic heterogeneity and opens new perspectives in genetic testing in patients with LVNC and their relatives at high risk of inheriting the cardiomyopathy. The presence or absence of a sarcomere gene mutation in LVNC cannot be related to the clinical phenotype.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".