Generalization of Variants Identified by Genome‐Wide Association Studies for Electrocardiographic Traits in African Americans. (28th March 2013)

• Record Type: Journal Article
• Authors: Jeff, Janina M.; Ritchie, Marylyn D.; Denny, Joshua C.; Kho, Abel N.; Ramirez, Andrea H.; Crosslin, David; Armstrong, Loren; Basford, Melissa A.; Wolf, Wendy A.; Pacheco, Jennifer A.; Chisholm, Rex L.; Roden, Dan M.; Hayes, M. Geoffrey; Crawford, Dana C.
• Is Part Of: Annals of human genetics. Volume 77:Number 4(2013:Jul.)
• Page Start: 321
• Page End: 332
• Publication Date: 2013-03-28
• Subjects: Electrocardiography -- African Americans -- GWAS -- generalization -- electronic medical records; Human genetics -- Periodicals; 599.935
• DOI: 10.1111/ahg.12023
• Languages: English
• ISSNs: 0003-4800

Abstract

Summary: Electrocardiographic (ECG) measurements vary by ancestry. Genome‐wide association studies (GWAS) have identified loci that contribute to ECG measurements; however, most are performed in Europeans collected from population‐based cohorts or surveys. The strongest associations reported are in NOS1AP with QT interval and SCN10A with PR and QRS durations. The extent to which these associations can be generalized to African Americans has yet to be determined. Using electronic medical records, PR and QT intervals, QRS duration, and heart rate were determined in 455 African Americans as part of the Vanderbilt Genome‐Electronic Records Project and Northwestern University NUgene Project. We tested for an association between these ECG traits and >930K SNPs. We identified a total 36 novel associations with PR interval, QRS duration, QT interval, and heart rate at p < 1.0 × 10 −6 . Using published GWAS data, we compared our results with those previously identified in other populations. Five associations originally identified in other populations generalized with respect to statistical significance and direction of effect. A total of 43 associations have a consistent direction of effect with European and/or Asian populations. This work provides a catalogue of generalized versus nongeneralized associations, a necessary step in prioritizing GWAS‐identified regions for further fine‐mapping in diverse populations.