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Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Genetic Risk Prediction of Atrial Fibrillation
Steven A Lubitz1, Xiaoyan Yin2, Henry J Lin2
1From Cardiac Arrhythmia Service (S.A.L., P.T.E.), Cardiovascular Research Center (S.A.L., L.-C.W., S.K., P.T.E.), J. Philip Kistler Stroke Research Center, Department of Neurology (N.S.R., C.D.A., J.R.), and Center for Human Genetic Research (C.D.A., S.K., J.R.), Massachusetts General Hospital, Boston; Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge (S.A.L., C.D.A., L.-C.W., S.K., C.R., J.R., P.T.E.); Boston University and National Heart, Lung, and Blood Institute's Framingham Heart Study, MA (X.Y., M.G.L., K.L.L., E.J.B.); Department of Pediatrics (H.J.L., X.G., K.D.T., J.I.R.) and Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute (H.J.L., X.G., K.D.T., J.Y., J.I.R.), Harbor-UCLA Medical Center, Torrance, CA; Vanderbilt University, Nashville, TN (M.K., P.L.T., D.D.); Department of Cardiology, Clinical Sciences, Lund University, Sweden (J.G.S.); Skåne University Hospital, Lund, Sweden (J.G.S.); Departments of Cardiology (S.T., J.W.J.) and Gerontology and Geriatrics (S.T.), Leiden University Medical Center, the Netherlands; University of Groningen, University Medical Center Groningen, the Netherlands (M.R., B.G., N.V., J.E.S., P.v.d.H.); Department of Clinical Sciences, Lund University, Malmö, Sweden (P.A., G.E., O.M.); Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis (L.Y.C.); Robertson Center for Biostatistics (I.F.) and Institute of Cardiovascular and Medical Sciences (P.W.M., D.J.S.), University of Glasgow, UK; Department of Neurology, Rhode Island Hospital, Alpert Medical School of Brown University, Providence (K.L.F.); Department of Mathematics and Statistics, Boston University, Boston, MA (M.G.L.); Department of Biostatistics (M.G.L., K.L.L.), Department of Epidemiology (E.J.B.), Section of Cardiovascular Medicine, Department of Medicine (E.J.B.), and Preventive Medicine Section, Department of Medicine (E.J.B.), Boston University School of Public Health, MA; Cardiovascular Health Research Unit, Departments of Medicine (B.M.P., N.S., S.R.H.), Epidemiology (B.M.P., N.S., S.R.H.), and Health Services (B.M.P.), University of Washington, Seattle; Kaiser Permanente Health Research Institute, Kaiser Permanente, Seattle, WA (B.M.P., S.R.H.); Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston-Salem, NC (E.Z.S.); Department of Medicine and Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN (D.R.); University of Illinois, Chicago (D.D.); Interuniversity Cardiology Institute of the Netherlands, Utrecht (J.W.J.); Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden (O.M.); and Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA (A.A.). slubitz@mgh.harvard.edu.
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 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% 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.
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