Variant R94C in <i>TNNT2</i> ‐Encoded Troponin T Predisposes to Pediatric Restrictive Cardiomyopathy and Sudden Death Through Impaired Thin Filament Relaxation Resulting in Myocardial Diastolic Dysfunction
Bibliographic record
Abstract
-encoded cardiac troponin T (TNNT2) is poorly described. Methods and Results Genetic analysis of a proband and kindred with RCM identified TNNT2-R94C, which cosegregated in a family with 2 generations of RCM, ventricular arrhythmias, and sudden death. TNNT2-R94C was absent among large, population-based cohorts Genome Aggregation Database (gnomAD) and predicted to be pathologic by in silico modeling. Biophysical experiments using recombinant human TNNT2-R94C demonstrated impaired cardiac regulation at the molecular level attributed to reduced calcium-dependent blocking of myosin's interaction with the thin filament. Computational modeling predicted a shift in the force-calcium curve for the R94C mutant toward submaximal calcium activation compared within the wild type, suggesting low levels of muscle activation even at resting calcium concentrations and hypercontractility following activation by calcium. Conclusions The pathogenic TNNT2-R94C variant activates thin-filament-mediated sarcomeric contraction at submaximal calcium concentrations, likely resulting in increased muscle tension during diastole and hypercontractility during systole. This describes the proximal biophysical mechanism for development of RCM in this family.
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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) | 0.003 | 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".