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GWAS Study

The Genetic Makeup of the Electrocardiogram.

Verweij N, Benjamins JW, Morley MP et al.

32916098 PubMed ID
GWAS Study Type
63706 Participants
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

VN
Verweij N
BJ
Benjamins JW
MM
Morley MP
VD
van de Vegte YJ
TA
Teumer A
TT
Trenkwalder T
RW
Reinhard W
CT
Cappola TP
VD
van der Harst P
Chapter II

Abstract

Summary of the research findings

The electrocardiogram (ECG) is one of the most useful non-invasive diagnostic tests for a wide array of cardiac disorders. Traditional approaches to analyzing ECGs focus on individual segments. Here, we performed comprehensive deep phenotyping of 77,190 ECGs in the UK Biobank across the complete cycle of cardiac conduction, resulting in 500 spatial-temporal datapoints, across 10 million genetic variants. In addition to characterizing polygenic risk scores for the traditional ECG segments, we identified over 300 genetic loci that are statistically associated with the high-dimensional representation of the ECG. We established the genetic ECG signature for dilated cardiomyopathy, associated the BAG3, HSPB7/CLCNKA, PRKCA, TMEM43, and OBSCN loci with disease risk and confirmed this association in an independent cohort. In total, our work demonstrates that a high-dimensional analysis of the entire ECG provides unique opportunities for studying cardiac biology and disease and furthering drug development. A record of this paper's transparent peer review process is included in the Supplemental Information.

63,706 European and unknown ancestry individuals

Chapter III

Study Statistics

Key metrics and study information

63706
Total Participants
GWAS
Study Type
No
Replicated
European, NR
Ancestry
U.K.
Recruitment Country
Chapter IV

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