A Rare Noncoding Enhancer Variant in <i>SCN5A</i> Contributes to the High Prevalence of Brugada Syndrome in Thailand
Bibliographic record
Abstract
BACKGROUND: Brugada syndrome (BrS) is a cardiac arrhythmia disorder that causes sudden death in young adults. Rare genetic variants in the SCN5A gene encoding the Na v 1.5 sodium channel and common noncoding variants at this locus are robustly associated with the condition. BrS is particularly prevalent in Southeast Asia but the underlying ancestry-specific factors remain largely unknown. METHODS: Genome sequencing of BrS probands and population-matched controls from Thailand was performed to identify rare noncoding variants at the SCN5A-SCN10A locus that were enriched in patients with BrS. A likely causal variant was prioritized by computational methods and introduced into human induced pluripotent stem cell (hiPSC) lines using CRISPR-Cas9. The effect of the variant on SCN5A expression and Na v 1.5 sodium channel current was then assessed in hiPSC-derived cardiomyocytes (hiPSC-CMs). RESULTS: A rare noncoding variant in an SCN5A intronic enhancer region was highly enriched in patients with BrS (detected in 3.9% of cases with a case-control odds ratio of 45.2). The variant affects a nucleotide conserved across all mammalian species and predicted to disrupt a Mef2 transcription factor binding site. Heterozygous introduction of the enhancer variant in hiPSC-CMs caused significantly reduced SCN5A expression from the variant-containing allele and a 30% reduction in Na v 1.5-mediated sodium current density compared with isogenic controls, confirming its pathogenicity. Patients with the variant had severe phenotypes, with 89% experiencing cardiac arrest. CONCLUSIONS: This is the first example of a functionally validated rare noncoding variant at the SCN5A locus and highlights how genome sequencing in understudied populations can identify novel disease mechanisms. The variant partly explains the increased prevalence of BrS in this region and enables the identification of at-risk variant carriers to reduce the burden of sudden cardiac death in Thailand.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".