Nexilin Mutations Are Associated with Left Ventricular Noncompaction Cardiomyopathy
Bibliographic record
Abstract
Introduction: Left Ventricular Noncompaction Cardiomyopathy (LVNC) is a very rare congenital heart disease. LVNC is a form of cardiomyopathy in which the fetal myocardium fails to „compact” during cardiac development and it may be associated with impairment of LV function and LV dilatation. Mutations in several sarcomere genes have been described in LVNC. Nexilin, encoded by NEXN , is a cardiac Z-disc protein that stabilizes the sarcomere. We evaluated nexilin as a disease gene for LVNC. Methods: Ninety-two LVNC patients and 254 controls were screened and NEXN was sequenced by Sanger sequencing. Results: We found a missense mutation (c.1408 G>C, p.Glu470Gln) in one patient and a nonsense mutation in another patient (c.1723G>T, p.Glu575*). None of these mutations were detected in the healthy controls. In addition, we identified one single nucleotide polymorphismus (c.733G>A, p.Gly245Arg) homozygous in two and heterozygous in three LVNC patients. This polymorphism was also found in 78 controls (homozygous in 12 and heterozygous in 64 controls). Conclusion: Mutations in genes encoding Z-disc proteins such as nexilin have been shown to cause different forms of cardiomyopathy. Therefore, the two mutations we identified in NEXN may further increase our knowledge of Z-disc genes in the pathogenesis of LVNC. To establish the disease causality, it is necessary to investigate the effect of the mutations on protein function in further in vitro studies.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".