Identification of potential candidate genes and pathways in atrioventricular nodal reentry tachycardia by whole‐exome sequencing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Atrioventricular nodal reentry tachycardia (AVNRT) is the most common manifestation of paroxysmal supraventricular tachycardia (PSVT). Increasing data have indicated familial clustering and participation of genetic factors in AVNRT, and no pathogenic genes related to AVNRT have been reported. METHODS: Whole-exome sequencing (WES) was performed in 82 patients with AVNRT and 100 controls. Reference genes, genome-wide association analysis, gene-based collapsing, and pathway enrichment analysis were performed. A protein-protein interaction (PPI) network was then established; WES database in the UK Biobank and one only genetic study of AVNRT in Denmark were used for external data validation. RESULTS: Among 95 reference genes, 126 rare variants in 48 genes were identified in the cases (minor allele frequency < 0.001). Gene-based collapsing analysis and pathway enrichment analysis revealed six functional pathways related to AVNRT as with neuronal system/neurotransmitter release cycles and ion channel/cardiac conduction among the top 30 enriched pathways, and then 36 candidate pathogenic genes were selected. By combining with PPI analysis, 10 candidate genes were identified, including RYR2, NOS1, SCN1A, CFTR, EPHB4, ROBO1, PRKAG2, MMP2, ASPH, and ABCC8. From the UK Biobank database, 18 genes from candidate genes including SCN1A, PRKAG2, NOS1, and CFTR had rare variants in arrhythmias, and the rare variants in PIK3CB, GAD2, and HIP1R were in patients with PSVT. Moreover, one rare variant of RYR2 (c.4652A > G, p.Asn1551Ser) in our study was also detected in the Danish study. Considering the gene functional roles and external data validation, the most likely candidate genes were SCN1A, PRKAG2, RYR2, CFTR, NOS1, PIK3CB, GAD2, and HIP1R. CONCLUSION: The preliminary results first revealed potential candidate genes such as SCN1A, PRKAG2, RYR2, CFTR, NOS1, PIK3CB, GAD2, and HIP1R, and the pathways mediated by these genes, including neuronal system/neurotransmitter release cycles or ion channels/cardiac conduction, might be involved in AVNRT.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it