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Genetic Risk Prediction of Atrial Fibrillation

  • Steven A Lubitz
  • Xiaoyan Yin
  • Henry J. Lin
  • Matthew Kolek
  • Gustav G. Smith
  • Stella Trompet
  • Michiel Rienstra
  • Natalia S. Rost
  • Pedro L. Teixeira
  • Peter Almgren
  • Christopher D. Anderson
  • Lin Y. Chen
  • Gunnar Engström
  • Ian Ford
  • Karen L. Furie
  • Xiuqing Guo
  • Martin G. Larson
  • Kathryn L. Lunetta
  • Peter W Macfarlane
  • Bruce M. Psaty
  • Elsayed Z Soliman
  • Nona Sotoodehnia
  • David J. Stott
  • Kent D Taylor
  • Lu Chen Weng
  • Jie Yao
  • Bastiaan Geelhoed
  • Niek Verweij
  • Joylene E. Siland
  • Sekar Kathiresan
  • Carolina Roselli
  • Dan M Roden
  • Pim van der Harst
  • Dawood Darbar
  • J. Wouter Jukema
  • Olle Melander
  • Jonathan Rosand
  • Jerome I. Rotter
  • Susan R Heckbert
  • Patrick T Ellinor
  • Alvaro Alonso
  • Emelia J Benjamin
Publishing year: 2017-03-02
Language: English
Pages: 1311-1320
Publication/Series: Circulation
Volume: 135
Issue: 14
Document type: Journal article
Publisher: Lippincott Williams and Wilkins

Abstract english

BACKGROUND—: Atrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke. METHODS—: To determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in five prospective studies comprising 18,919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3,028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P-values ranging from <1x10 to <1x10 in a prior independent genetic association study. RESULTS—: Incident AF occurred in 1,032 (5.5%) individuals. AF genetic risk scores were associated with new-onset AF after adjusting for clinical risk factors. The pooled hazard ratio for incident AF for the highest versus lowest quartile of genetic risk scores ranged from 1.28 (719 variants; 95%CI, 1.13-1.46; P=1.5x10) to 1.67 (25 variants; 95%CI, 1.47-1.90; P=9.3x10). Discrimination of combined clinical and genetic risk scores varied across studies and scores (maximum C statistic, 0.629-0.811; maximum ΔC statistic from clinical score alone, 0.009-0.017). AF genetic risk was associated with stroke in age- and sex-adjusted models. For example, individuals in the highest versus lowest quartile of a 127-variant score had a 2.49-fold increased odds of cardioembolic stroke (95%CI, 1.39-4.58; P=2.7x10). The effect persisted after excluding individuals (n=70) with known AF (odds ratio, 2.25; 95%CI, 1.20-4.40; P=0.01). CONCLUSIONS—: Comprehensive AF genetic risk scores were associated with incident AF beyond associations for clinical AF risk factors, though offered small improvements in discrimination. AF genetic risk was also associated with cardioembolic stroke in age- and sex-adjusted analyses. Efforts are warranted to determine whether AF genetic risk may improve identification of subclinical AF or help distinguish between stroke mechanisms.


  • Medical Genetics
  • Neurology


  • Diabetes and Endocrinology
  • Cardio-vascular Epidemiology
  • Hypertension and Cardiovascular Disease
  • ISSN: 0009-7322
E-mail: gustav [dot] smith [at] med [dot] lu [dot] se

Associate professor


+46 46 17 26 33



Research project participant

Cardiovascular Epigenetics


Research project participant

Heart Failure and Mechanical Support


Project manager

Molecular Epidemiology and Cardiology

+46 46 17 26 33


Lund University Diabetes Centre, CRC, SUS Malmö, Entrance 72, House 91:12. SE-205 02 Malmö. Telephone: +46 40 39 10 00