Abstract 4144528: The Polygenic Mechanisms of Dilated Cardiomyopathy Contribute to The Development of Tachycardia-Associated Cardiomyopathy in Patients With Atrial Tachyarrhythmias
Bibliographic record
Abstract
Background Longstanding tachycardia can lead to reversible left ventricular (LV) systolic dysfunction called tachycardia-associated cardiomyopathy (TAC). It is unknown if there is a genetic predisposition to the development of TAC or whether there is overlap between the genetic pathways of TAC and dilated cardiomyopathy (DCM). Research Questions Is there a genetic predisposition towards the development of TAC in individuals with arrhythmia? If so, do these genetic pathways overlap with those of DCM? Methods/Approach The study is a single-center case control study performed at the Montreal Heart Institute (MHI). Inclusion criteria for TAC cases are shown in Table 1. All cases underwent array genotyping and exome sequencing. Previously genotyped controls with arrhythmia but no documented LV dysfunction were included from the MHI Biobank. Following imputation using the TOPMed imputation server, a polygenic score for DCM (PGS DCM ; PGS000666) was calculated for cases and controls. The rate of (likely) pathogenic variants in known cardiomyopathy genes was reported in cases. Results/Data (descriptive and inferential statistics) The study included 107 cases and 878 controls. Case characteristics are shown in Table 1. The average PGS DCM for cases was significantly higher than that of controls (p-value <10 -10 ; Figure 1). Logistic regression with correction for age, sex, and ancestry (principal components) showed a strong association of PGS DCM with TAC (OR 1.99, 95% CI 1.54-2.58; p-value <10 -6 ). Notably, among patients with atrial tachyarrhythmias, those with a PGS DCM above the 95 th percentile had a 3.53-fold increased risk of TAC (p-value 4.5 -4 ). Exome sequencing in TAC cases identified only 2/107 (2%) carriers of (likely) pathogenic variants (in cardiomyopathy genes TNNT2 and MYH7 ). Conclusions Pathogenic variants account for a small minority of TAC cases. In contrast, a significant association between PGS DCM and TAC is suggestive of a shared polygenic pathway between TAC and DCM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".