Type 8 long QT syndrome: pathogenic variants in CACNA1C-encoded Cav1.2 cluster in STAC protein binding site
Bibliographic record
Abstract
AIMS: Pathogenic gain-of-function variants in CACAN1C cause type-8 long QT syndrome (LQT8). We sought to describe the electrocardiographic features in LQT8 and utilize molecular modelling to gain mechanistic insights into its genetic culprits. METHODS AND RESULTS: Rare variants in CACNA1C were identified from genetic testing laboratories. Treating physicians provided clinical information. Variant pathogenicity was independently assessed according to recent guidelines. Pathogenic (P) and likely pathogenic (LP) variants were mapped onto a 3D modelled structure of the Cav1.2 protein. Nine P/LP variants, identified in 23 patients from 19 families with non-syndromic LQTS were identified. Six variants, found in 79% of families, clustered to a 4-residue section in the cytosolic II-III loop region which forms a region capable of binding STAC SH3 domains. Therefore, variants may affect binding of SH3-domain containing proteins. Arrhythmic events occurred in similar proportions of patients with II-III loop variants and with other P/LP variants (53% vs. 48%, P = 0.41) despite shorter QTc intervals (477 ± 31 ms vs. 515 ± 37 ms, P = 0.03). A history of sudden death was reported only in families with II-III loop variants (60% vs. 0%, P = 0.03). The predominant T-wave morphology was a late peaking T wave with a steep descending limb. Exercise testing demonstrated QTc prolongation on standing and at 4 min recovery after exercise. CONCLUSION: The majority of P/LP variants in patients with CACNA1C-mediated LQT8 cluster in an SH3-binding domain of the cytosolic II-III loop. This represents a 'mutation hotspot' in LQT8. A late-peaking T wave with a steep descending limb and QT prolongation on exercise are commonly seen.
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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 | 0.000 | 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".