Shared Genetic Predisposition in Peripartum and Dilated Cardiomyopathies
Bibliographic record
Abstract
Background Peripartum cardiomyopathy shares some clinical features with idiopathic dilated cardiomyopathy, a disorder caused by mutations in more than 40 genes, including TTN, which encodes the sarcomere protein titin. Methods In 172 women with peripartum cardiomyopathy, we sequenced 43 genes with variants that have been associated with dilated cardiomyopathy. We compared the prevalence of different variant types (nonsense, frameshift, and splicing) in these women with the prevalence of such variants in persons with dilated cardiomyopathy and with population controls. Results We identified 26 distinct, rare truncating variants in eight genes among women with peripartum cardiomyopathy. The prevalence of truncating variants (26 in 172 [15%]) was significantly higher than that in a reference population of 60,706 persons (4.7%, P=1.3×10(-7)) but was similar to that in a cohort of patients with dilated cardiomyopathy (55 of 332 patients [17%], P=0.81). Two thirds of identified truncating variants were in TTN, as seen in 10% of the patients and in 1.4% of the reference population (P=2.7×10(-10)); almost all TTN variants were located in the titin A-band. Seven of the TTN truncating variants were previously reported in patients with idiopathic dilated cardiomyopathy. In a clinically well-characterized cohort of 83 women with peripartum cardiomyopathy, the presence of TTN truncating variants was significantly correlated with a lower ejection fraction at 1-year follow-up (P=0.005). Conclusions The distribution of truncating variants in a large series of women with peripartum cardiomyopathy was remarkably similar to that found in patients with idiopathic dilated cardiomyopathy. TTN truncating variants were the most prevalent genetic predisposition in each disorder.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".