Identification of a Gene Responsible for Familial Wolff–Parkinson–White Syndrome
Bibliographic record
Abstract
BACKGROUND: The Wolff-Parkinson-White syndrome, with a prevalence in Western countries of 1.5 to 3.1 per 1000 persons, causes considerable morbidity and may cause sudden death. We identified two families in which the Wolff-Parkinson-White syndrome segregated as an autosomal dominant disorder. METHODS: We studied 70 members of the two families (57 in Family 1 and 13 in Family 2). The subjects underwent 12-lead electrocardiography and two-dimensional echocardiography. Genotyping mapped the gene responsible to 7q34-q36, a locus previously identified to be responsible for an inherited form of Wolff-Parkinson-White syndrome. Candidate genes were identified, sequenced, and analyzed in normal and affected family members to identify the disease-causing gene. RESULTS: A total of 31 members (23 from Family 1 and 8 from Family 2) had the Wolff-Parkinson-White syndrome. Affected members of both families had ventricular preexcitation with conduction abnormalities and cardiac hypertrophy. The maximal combined two-point lod score was 9.82 at a distance of 5 cM from marker D7S636, which confirmed the linkage of the gene in both families to 7q34-q36. Haplotype analysis indicated that there were no alleles in common in the two families at this locus, suggesting that the two families do not have a common founder. We identified a missense mutation in the gene that encodes the gamma2 regulatory subunit of AMP-activated protein kinase (PRKAG2). The mutation results in the substitution of glutamine for arginine at residue 302 in the protein. CONCLUSIONS: The identification of this genetic defect has important implications for elucidating the pathogenesis of ventricular preexcitation. Further understanding of how this molecular defect leads to supraventricular arrhythmias could influence the development of specific therapies for other forms of supraventricular arrhythmia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".