Year: 2021
Type: article
Abstract: BACKGROUND: Atrial fibrillation (AF) risk estimation using clinical factors with or without genetic information may identify AF screening candidates more accurately than the guideline-based age threshold of ≥65 years. METHODS: We analyzed 4 samples across the United States and Europe (derivation: UK Biobank; validation: FINRISK, Geisinger MyCode Initiative, and Framingham Heart Study). We estimated AF risk using the CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology AF) score and a combination of CHARGE-AF and a 1168-variant polygenic score (Predict-AF). We compared the utility of age, CHARGE-AF, and Predict-AF for predicting 5-year AF by quantifying discrimination and calibration. RESULTS: Among 543 093 individuals, 8940 developed AF within 5 years. In the validation sets, CHARGE-AF (C index range, 0.720-0.824) and Predict-AF (0.749-0.831) had largely comparable discrimination, both favorable to continuous age (0.675-0.801). Calibration was similar using CHARGE-AF (slope range, 0.67-0.87) and Predict-AF (0.65-0.83). Net reclassification improvement using Predict-AF versus CHARGE-AF was modest (net reclassification improvement range, 0.024-0.057) but more favorable among individuals aged <65 years (0.062-0.11). Using Predict-AF among 99 530 individuals aged ≥65 years across each sample, 70 849 had AF risk <5%, of whom 69 067 (97.5%) did not develop AF, whereas 28 681 had AF risk ≥5%, of whom 2264 (7.9%) developed AF. Of 11 379 individuals aged <65 years with AF risk ≥5%, 435 (3.8%) developed AF before age 65 years, with roughly half (46.9%) meeting anticoagulation criteria. CONCLUSIONS: AF risk estimation using clinical factors may prioritize individuals for AF screening more precisely than the age threshold endorsed in current guidelines. The additional value of genetic predisposition is modest but greatest among younger individuals.
Authors: Shaan Khurshid, Nina Mars, Christopher M. Haggerty, Qiuxi Huang, Lu-Chen Weng, Dustin N. Hartzel, Kathryn L. Lunetta, Jeffrey M. Ashburner, Christopher D. Anderson, Emelia J. Benjamin, Veikko Salomaa, Patrick T. Ellinor, Brandon K. Fornwalt, Samuli Ripatti, Ludovic Trinquart, Steven A. Lubitz
Institutions: Broad Institute, Harvard University, Massachusetts General Hospital, Massachusetts Institute of Technology, University of Helsinki, Institute for Molecular Medicine Finland, HiLIFE – Elämäntieteiden Instituutti, Geisinger Health System, Boston University, Framingham Heart Study, Geisinger Medical Center, National Heart, Lung, and Blood Institute, Regeneron (United States), Finnish Institute for Health and Welfare
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Awards: FHS-NEXT - Framingham Novel EXam using Technology, Precision Medicine in Ischemic Stroke and Atrial Fibrillation (PreMISe-AF), ERICH-GENE, G2628120876, G278200998, G3405256882, Sequencing Annotation and Functional Analysis in Risk of Intracerebral Hemorrhage, AFGen Consortium: Atrial Fibrillation Genomics to Functional Analyses, Clinical and genetic prediction of lifetime risk of atrial fibrillation and its complications, Determining the Role of the Potassium Channel, KCNN3, in Atrial Fibrillation, G4976486911, G5164707915, G5850737185, The Framingham Heart Study, Mentoring in Arrhythmia Research, IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVAL, Integrated, Multidisciplinary Training in Cardiovascular Research, Genomics of Cardiac Arrhythmias, American Heart Association Tobacco Center for Regulatory Science (A-TRAC) 2.0
OpenAlex ID: W3197999035