Common and Rare Variant Contributions to Bradyarrhythmias from Multi-Ancestry Meta-Analyses
Bibliographic record
Abstract
ABSTRACT To broaden our understanding of bradyarrhythmias and diseases of the cardiac conduction system, we performed cross-sectional multi-ancestry genome-wide association study meta-analyses in up to 1.3 million individuals for sinus node dysfunction (SND), distal conduction disease (DCD), and pacemaker implantation (PM). We evaluated the biological relevance of bradyarrhythmia loci by analyses of transcriptomes, pleiotropy, and partitioned heritability based on cardiac single cell RNA sequencing data. Finally, we performed rare variant burden testing in 460,000 whole exome sequenced individuals from two biobanks. We identified 13, 28, and 21 common variant loci for SND, DCD, and PM, respectively. Four well-known common variant arrhythmia loci ( SCN5A/SCN10A , CCDC141, TBX20 , and CAMK2D) were shared for SND and DCD, while other loci were more specific for either SND or DCD. Cardiomyocyte-expressed genes were strongly enriched for contributions to DCD heritability, while SND and PM were more heterogeneous. Rare variant analyses implicated LMNA for all bradyarrhythmia subtypes; SMAD6 and SCN5A for DCD; and TTN , MYBPC3 , and SCN5A for PM. The genetic architectures of SND and DCD are both overlapping and distinct. Multiple genetic mechanisms involving ion channels, sarcomeric components, cellular homeostasis, and cardiac development may influence the development of bradyarrhythmias.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.022 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".