The contribution of <i>RBM20</i> truncating variants to human cardiomyopathy
Bibliographic record
Abstract
Abstract Background Genetic diagnosis has become increasingly important to guide clinical decision making for patients with dilated cardiomyopathy (DCM). Disease-causing (P/LP) missense variants in the gene RBM20 cause a highly penetrant arrhythmogenic dilated cardiomyopathy (DCM), but the role of truncating RBM20 variants ( RBM20tvs ) is unclear. Objective Assess the contribution of RBM20tvs to DCM. Methods We assembled an international cohort of DCM patients with RBM20 variants and used data from the genome-first UK Biobank (UKB) to assess the etiologic fraction, natural history and penetrance of RBM20tvs . Results The etiologic fraction of RBM20tvs in arrhythmogenic DCM was modest (0.53[0.32,0.67], p=7.5×10 -5 ). RBM20tv DCM patients presented to referral centers later in life than RBM20 P/LP DCM patients (53±10 vs. 34±18 years, p=4×10 -3 ), and were less likely to have a family history of sudden cardiac arrest (20% vs. 65%, p= 0.046) or cardiomyopathy (20% vs. 78% p=5.4×10 -3 ). There was no significant difference in age- and sex-adjusted incident major heart failure or arrhythmia events between RBM20tv and RBM20 P/LP DCM patients, though sex-adjusted lifetime hazard was reduced in RBM20tv DCM (HR 0.15[0.03,0.66],p=0.009). In UKB, lifetime incidence of cardiomyopathy, heart failure, or major ventricular arrhythmia diagnosis was lower in participants with RBM20tvs than in those with TTNtvs (HR 0.55 [0.36,0.84], p=5.9×10 -3 ). Conclusions RBM20tvs contribute to arrhythmogenic DCM phenotypes, but confer milder disease severity alone than RBM20 P/LP variants, and reduced lifetime disease penetrance compared to TTNtvs . Their potential for additive interactions with other damaging variants should be considered in DCM patients and families.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".