PO100 Genetic analysis and electrocardiographic patterns in Brugada syndrome: a comprehensive multi-tiered approach

Abstract Background Brugada syndrome is a complex cardiac channelopathy characterised by significant genotype-phenotype heterogeneity¹. Whilst SCN5A is established as the primary gene², the underlying genetic architecture explaining clinical variability remains incompletely understood³,4. Purpose To characterise the genetic landscape of patients with suspected Brugada syndrome, analysing variant distribution across different electrocardiographic patterns using novel methodological approaches. Methods We characterised 284 consecutive patients with suspected Brugada syndrome referred between 2008-2025. Patients (191 males, 67.3%; median age 45.5 years) were stratified into four ECG pattern groups: non-diagnostic (n=49, 17.3%), drug-induced (n=95, 33.5%), spontaneous intermittent (n=103, 36.3%), and spontaneous persistent (n=37, 13.0%). Multi-tiered genetic testing included Sanger sequencing (n=74), NGS cardio panel (n=158), and whole exome sequencing (n=52). Variants were classified according to ACMG/AMP guidelines5. Following our previously validated approach6, we sub-classified variants of uncertain significance with strong pathogenic evidence for exploratory analysis. Results Overall genetic yield was 29.2% (83/284 patients), with SCN5A variants in 49 patients (17.3%). Using standard ACMG criteria, we observed a significant gradient from 0% in non-diagnostic to 8.1% in spontaneous persistent patterns (p=0.04). Enhanced criteria strengthened this gradient: 2.0% to 24.3% respectively (p=0.02). NGS analysis revealed ion channel genes in 31% of variants, structural proteins 13.3%, other genes 10%. Ion channel genes maintained similar gradient trends though not significant (p=0.072), whilst structural proteins and other genes showed uniform distribution. Clinical correlations included higher male prevalence in spontaneous intermittent patterns (76.7% vs 56.8%, p=0.03) and more frequent palpitations (36.9% vs 16.2%, p=0.02). Electrophysiological studies showed low-voltage areas more frequent in spontaneous intermittent patterns (61.9%, p=0.001). Conclusions This study introduces novel methodological innovations including four-class ECG pattern stratification and enhanced VUS subclassification that significantly improve genotype-phenotype correlation analysis. Sodium channel genetics represents the primary determinant of Brugada syndrome phenotypic complexity, with ion channels maintaining gradient trends unlike other gene categories. These approaches advance personalised risk stratification and support refined variant reclassification in cardiac channelopathies.