Key result
Multi-ethnic GWAS identifies 6 novel genetic loci linked to specific ECG traits.
Why the study?
The authors sought to examine how including ancestrally diverse populations, prioritizing more precise phenotypic measures, and evaluating shared genetic effects enables the detection and characterization of electrocardiographic loci.
Observational (n=34,668)
Yes
Expanding GWAS to include ancestrally diverse populations and more precisely decomposed ECG traits enabled the discovery of novel genetic determinants of cardiac electrophysiology.
Should not yet alter ECG interpretation; extends GWAS by uncovering ancestry-specific loci via trait decomposition in diverse cohorts.
BACKGROUND: We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci. METHODS: We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test. RESULTS: was common in Blacks (minor allele frequency=10%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci. CONCLUSIONS: Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies.
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Baldassari et al. (2020) conducted an observational in Electrocardiographic (ECG) traits (n=34,668). Single-nucleotide polymorphisms vs. Reference alleles was evaluated on Novel genetic loci associated with 6 contiguous and 2 composite electrocardiographic traits. A multi-ethnic genome-wide association study identified 6 novel genetic loci associated with specific electrocardiographic traits, including a CD36 variant common in Black populations.
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