Polygenic risk modulates myocardial repolarization and T-wave geometry in congenital long-QT syndrome type 1:...

Congenital long-QT syndrome type 1 (LQT1), one of the major LQTS subtypes caused by pathogenic variants in the KCNQ1 gene, exhibits marked phenotypic variability, including incomplete penetrance and differences in myocardial repolarization. This variability suggests that additional genetic factors, particularly the additive effects of common single nucleotide polymorphisms (SNPs) captured by polygenic risk scores (PRS), may modulate disease expression.

We analyzed digital 12-lead ECGs from 273 LQT1 patients carrying pathogenic KCNQ1 variants from a German national registry. Sixty quantitative descriptors of myocardial repolarization were derived using a validated, automated ECG-analysis algorithm. A PRS was calculated from 169 genome-wide SNPs recently known to affect QT interval duration in the general population. Associations between PRS and ECG parameters were tested using multivariable linear regression, including interaction terms and heart-rate correction of the QT interval and subsegments.

Higher PRS values were modestly but significantly associated with longer Bazett-corrected QTc intervals (β = 0.24, p = 0.00008) and longer T-peak to T-end (TPE) intervals (β = 0.16, p = 0.008). A novel finding was a significant negative interaction between T-wave area and T-wave duration, both measured and confirmed using Rautaharju-corrected parameters (β = -0.14, p = 0.006), suggesting that the polygenic burden modulates both timing and geometry of ventricular repolarization. The overall model explained a modest proportion of variance (R² = 0.09).

Our findings demonstrate that a polygenic background modestly modulates not only QTc duration but also T-wave parameters in LQT1 patients, revealing rate-independent influences on repolarization dynamics. Despite the limited variance explained, these associations were statistically robust and trait-specific, suggesting biologically meaningful modulation of repolarization phenotypes. Quantitative ECG phenotyping combined with PRS may offer a scalable framework for dissecting genotype-ECG phenotype relationships in inherited arrhythmia syndromes, particularly when digital ECG data are used.