Genetic Risk Prediction of Atrial Fibrillation

• Type of Material: Article
• Authors: Steven A. Lubitz, Massachusetts General Hospital; Xiaoyan Yin Yin, Boston University; Henry J. Lin, Harbor-UCLA Medical Center; Matthew Kolek, Vanderbilt University; J. Gustav Smith, Lund University; Stella Trompet, Leiden University; Michiel Rienstra, University of Groningen; Natalia S. Rost, Massachusetts General Hospital; Pedro L. Teixeira, Vanderbilt University; Peter Almgren, Lund University; Christopher D. Anderson, Massachusetts General Hospital; Lin Y Chen, University of Minnesota; Gunnar Engstrom, Lund University; Ian Ford, University of Glasgow; Karen L Furie, Brown University; Xiuqng Guo, Harbor-UCLA Medical Center; Martin G. Larson, Boston University; Kathryn L. Lunetta, Boston University; Peter W. Macfarlane, University of Glasgow; Bruce M. Psaty, University of Washington; Elsayed Z. Soliman, Wake Forest School of Medicine; Nona Sotoodehnia, University of Washington; David J. Stott, University of Glasgow; Kent D. Taylor, Harbor-UCLA Medical Center; Lu-Chen Weng, Massachusetts General Hospital; Jie Yao, Harbor-UCLA Medical Center; Bastiaan Geelhoed, University of Groningen; Niek Verweij, University of Groningen; Joylene Siland, University of Groningen; Sekar Kathiresan, Massachusetts General Hospital; Carolina Roselli, The Broad Insitute of Harvard and MIT; Dan Roden, Vanderbilt University; Pim van der Harst, University of Groningen; Dawood Darbar, Vanderbilt University; J. Wouter Jukema, Leiden University; Olle Melander, Lund University; Jonathan Rosand, Massachusetts General Hospital; Jerome I. Rotter, Harbor-UCLA Medical Center; Susan R. Heckbert, University of Washington; Patrick T. Ellinor, Massachusetts General Hospital; Alvaro Alonso, Emory University; Emelia J. Benjamin, Boston University
• Language: English
• Date: 2017-04-04
• Publisher: American Heart Association
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: ©2016 American Heart Association, Inc.
• Final Published Version (URL): http://dx.doi.org/10.1161/CIRCULATIONAHA.116.024143
• Title of Journal or Parent Work: Circulation
• ISSN: 0009-7322
• Volume: 135
• Issue: 14
• Start Page: 1311
• End Page: +
• Grant/Funding Information: Please see supplemental material for funding information.
• Keywords: COMMON VARIANTS; Peripheral Vascular Disease; CHROMOSOME 4Q25; stroke; atrial fibrillation; ISCHEMIC-STROKE; SEQUENCE; METAANALYSIS; GENOME-WIDE ASSOCIATION; COMMUNITY-BASED COHORT; INDIVIDUALS; Life Sciences & Biomedicine; forecasting; Cardiovascular System & Cardiology; HEART; Science & Technology; atrial flutter; Cardiac & Cardiovascular Systems; genetic association studies; AFRICAN-AMERICANS
• Research Categories: Health Sciences, Epidemiology; Health Sciences, Public Health

Abstract

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 5 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 3028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P values ranging from < 1×10 -3 to < 1×10 -8 in a prior independent genetic association study. RESULTS: Incident AF occurred in 1032 individuals (5.5%). AF genetic risk scores were associated with new-onset AF after adjustment 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% confidence interval, 1.13-1.46; P=1.5×10 -4 ) to 1.67 (25 variants; 95% confidence interval, 1.47-1.90; P=9.3×10 -15 ). 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 ageand 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% confidence interval, 1.39-4.58; P=2.7×10 -3 ). The effect persisted after the exclusion of individuals (n=70) with known AF (odds ratio, 2.25; 95% confidence interval, 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 but 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.