Abstract 14629: Rare Variants for Electrocardiographic Traits Identify Arrhythmia Susceptibility Genes

Abstract

Introduction: Electrocardiogram (ECG) intervals are quantitative and heritable endophenotypes for arrhythmias and sudden cardiac death (SCD). Studying rare sequence variation related to ECG intervals may help identify the genetic underpinnings of cardiac conduction and SCD. Methods: Using a discovery sample of 29,000 individuals with whole-genome sequences from TOPMed and a replication sample of about 100,000 individuals with whole-exome sequence data from the UK Biobank and MyCode, we examined associations between low-frequency (MAF<1%) and rare (MAF<0.1%) coding variants with 5 routinely ascertained ECG intervals (RR, P-wave, PR, QRS, and QTc intervals). We further assessed pathogenic variants in identified genes using ClinVar. Results: In low-frequency single variant analysis, we observed associations for PR interval in PAM ( P =2x10 -7 ) and MFGE8 ( P =5x10 -8 ). In gene-based tests, we identified rare coding variation associated with marked effects in established SCD genes KCNQ1, KCNH2, SCN5A and KCNE1 . For example, loss-of-function or pathogenic variants in KCNQ1 and KCNH2 were carried in 0.2% of individuals, were associated with 29 ms longer QTc intervals ( P =2x10 -82 ) and conferred up to 23-fold increased odds of marked QTc prolongation ( P =4x10 -25 ). Nevertheless, over 75% of carriers had normal QTc intervals. Similarly, loss-of-function or pathogenic variants in SCN5A , carried by 0.1% of individuals, conferred marked PR prolongation (31 ms), yet less than 30% of carriers had first-degree atrioventricular block. Discussion: This study demonstrates the value of studying ECGs in large sequenced biobanks for identifying rare variants predisposing to cardiac arrhythmias. Results define the frequency of pathogenic variation in SCD genes in the population and document incomplete penetrance of such variation. Our findings may serve as a benchmark for future population-based analyses aimed at discovering clinically actionable variants and genes.