Rare Coding Variants Associated With Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-Ancestry Analysis
Author(s) -
Seung Hoan Choi,
Sean J. Jurgens,
Christopher M. Haggerty,
Amelia Weber Hall,
Jennifer L. Halford,
Valerie N. Morrill,
LuChen Weng,
Braxton Lagerman,
Tooraj Mirshahi,
Mary Pettinger,
Xiuqing Guo,
Henry J. Lin,
Álvaro Alonso,
Elsayed Z. Soliman,
Jelena Kornej,
Honghuang Lin,
Arden Moscati,
Girish N. Nadkarni,
Jennifer A. Brody,
Kerri L. Wiggins,
Brian E. Cade,
Jiwon Lee,
Christina AustinTse,
Tom Blackwell,
Mark Chaffin,
Christina JiYoung Lee,
Heidi L. Rehm,
Carolina Roselli,
Susan Redline,
Braxton D. Mitchell,
a Sotoodehnia,
Bruce M. Psaty,
Susan R. Heckbert,
Ruth J. F. Loos,
Ramachandran S. Vasan,
Emelia J. Benjamin,
Adolfo Correa,
Eric Boerwinkle,
Dan E. Arking,
Jerome I. Rotter,
Stephen S. Rich,
Eric A. Whitsel,
Marco Pérez,
Charles Kooperberg,
Brandon K. Fornwalt,
Kathryn L. Lunetta,
Patrick T. Ellinor,
Steven A. Lubitz
Publication year - 2021
Publication title -
circulation genomic and precision medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.795
H-Index - 607
ISSN - 2574-8300
DOI - 10.1161/circgen.120.003300
Subject(s) - penetrance , exome sequencing , qt interval , odds ratio , sudden cardiac death , genetics , medicine , exome , cardiac arrhythmia , genotyping , biology , genotype , gene , mutation , phenotype , atrial fibrillation
Background: Alterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between electrocardiographic intervals and rare genetic variation at a population level are poorly understood. Methods: Using a discovery sample of 29 000 individuals with whole-genome sequencing from Trans-Omics in Precision Medicine and replication in nearly 100 000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured electrocardiographic traits (RR, P-wave, PR, and QRS intervals and corrected QT interval). Results: We found that rare variants associated with population-based electrocardiographic intervals identify established monogenic SCD genes (KCNQ1 ,KCNH2 , andSCN5A ), a controversial monogenic SCD gene (KCNE1 ), and novel genes (PAM andMFGE8 ) involved in cardiac conduction. Loss-of-function and pathogenicSCN5A variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of the first-degree atrioventricular block (P =8.4×10−5 ). Similar variants inKCNQ1 andKCNH2 (0.2% of individuals) were associated with a 23-fold increased odds of marked corrected QT interval prolongation (P =4×10−25 ), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal electrocardiographic intervals.Conclusions: Our findings indicate that large-scale high-depth sequence data and electrocardiographic analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked electrocardiographic interval prolongation.
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