Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease

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  • William J Young
  • Jeffrey Haessler
  • Jan-Walter Benjamins
  • Linda Repetto
  • Jie Yao
  • Aaron Isaacs
  • Andrew R Harper
  • Julia Ramirez
  • Sophie Garnier
  • Stefan van Duijvenboden
  • Antoine R Baldassari
  • Maria Pina Concas
  • ThuyVy Duong
  • Luisa Foco
  • Hao Mei
  • Raymond Noordam
  • Anne Richmond
  • Meddly L Santolalla
  • Colleen M Sitlani
  • Negin Soroush
  • Sébastien Thériault
  • Stella Trompet
  • Stefanie Aeschbacher
  • Fariba Ahmadizar
  • Alvaro Alonso
  • Jennifer A Brody
  • Archie Campbell
  • Adolfo Correa
  • Dawood Darbar
  • Antonio De Luca
  • Jean-François Deleuze
  • Christian Fuchsberger
  • Anuj Goel
  • Christopher Grace
  • Xiuqing Guo
  • Susan R Heckbert
  • Rebecca D. Jackson
  • Jan A Kors
  • Maria Fernanda Lima-Costa
  • Peter W Macfarlane
  • Alanna C Morrison
  • Pau Navarro
  • David J Porteous
  • Peter P Pramstaller
  • Alexander P Reiner
  • Lorenz Risch
  • Ulrich Schotten
  • Xia Shen
  • Gianfranco Sinagra
  • Elsayed Z Soliman
  • Monika Stoll
  • Eduardo Tarazona-Santos
  • Andrew Tinker
  • Katerina Trajanoska
  • Eric Villard
  • Helen R Warren
  • Eric A Whitsel
  • Kerri L Wiggins
  • Dan E Arking
  • Christy L Avery
  • David Conen
  • Giorgia Girotto
  • Caroline Hayward
  • J Wouter Jukema
  • Dennis O Mook-Kanamori
  • Sandosh Padmanabhan
  • Bruce M Psaty
  • Cristian Pattaro
  • Antonio Luiz P Ribeiro
  • Jerome I Rotter
  • Bruno H Stricker
  • Pim van der Harst
  • Cornelia M van Duijn
  • Niek Verweij
  • James G Wilson
  • Michele Orini
  • Philippe Charron
  • Hugh Watkins
  • Charles Kooperberg
  • Henry J Lin
  • James F Wilson
  • Nona Sotoodehnia
  • Borbala Mifsud
  • Pier D Lambiase
  • Larisa G Tereshchenko
  • Patricia B Munroe

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

Original languageEnglish
Article number1411
JournalNature Communications
Issue number1
Number of pages16
Publication statusPublished - 14 Mar 2023

Bibliographical note

© 2023. The Author(s).

    Research areas

  • Humans, Cardiovascular Diseases/genetics, Atrioventricular Block, Genome-Wide Association Study, Risk Factors, Arrhythmias, Cardiac/genetics, Electrocardiography/methods, Biomarkers

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