Twelve–Single Nucleotide Polymorphism Genetic Risk Score Identifies Individuals at Increased Risk for Future Atrial Fibrillation and Stroke

Background and Purpose— Atrial fibrillation (AF) is prevalent and there is a clinical need for biomarkers to identify individuals at higher risk for AF. Fixed throughout a life course and assayable early in life, genetic biomarkers may meet this need. Here, we investigate whether multiple single nucleotide polymorphisms together as an AF genetic risk score (AF-GRS) can improve prediction of one’s risk for AF. Methods— In 27 471 participants of the Malmö Diet and Cancer Study, a prospective, community-based cohort, we used Cox models that adjusted for established AF risk factors to assess the association of AF-GRS with incident AF and ischemic stroke. Median follow-up was 14.4 years for incident AF and 14.5 years for ischemic stroke. The AF-GRS comprised 12 single nucleotide polymorphisms that had been previously shown to be associated with AF at genome-wide significance. Results— During follow-up, 2160 participants experienced a first AF event and 1495 had a first ischemic stroke event. Participants in the top AF-GRS quintile were at increased risk for incident AF (hazard ratio, 2.00; 95% confidence interval, 1.73–2.31; P=2.7×10–21) and ischemic stroke (hazard ratio, 1.23; 95% confidence interval, 1.04–1.46; P=0.02) when compared with the bottom quintile. Addition of the AF-GRS to established AF risk factors modestly improved both discrimination and reclassification (P<0.0001 for both). Conclusions— An AF-GRS can identify 20% of individuals who are at ≈2-fold increased risk for incident AF and at 23% increased risk for ischemic stroke. Targeting diagnostic or therapeutic interventions to this subset may prove clinically useful.

[1]  B. Ohlsson,et al.  PT05.1: Intake of Different Types of Red Meat, Poultry and Fish and Incident Colorectal Cancer in Women and Men - Results from the Malmö Diet and Cancer Study , 2016 .

[2]  Helmut Pürerfellner,et al.  Clinical classifications of atrial fibrillation poorly reflect its temporal persistence: insights from 1,195 patients continuously monitored with implantable devices. , 2014, Journal of the American College of Cardiology.

[3]  K. Lunetta,et al.  Novel genetic markers associate with atrial fibrillation risk in Europeans and Japanese. , 2014, Journal of the American College of Cardiology.

[4]  Benjamin F. J. Verhaaren,et al.  Multilocus Genetic Risk Score Associates With Ischemic Stroke in Case–Control and Prospective Cohort Studies , 2014, Stroke.

[5]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[6]  Nancy R. Cook,et al.  Novel genetic markers improve measures of atrial fibrillation risk prediction , 2013, European heart journal.

[7]  Bernadette A. Thomas,et al.  Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010 , 2012, The Lancet.

[8]  A. Donald,et al.  Supplemental Material to , 2013 .

[9]  K. Lunetta,et al.  Meta-analysis identifies six new susceptibility loci for atrial fibrillation , 2012, Nature Genetics.

[10]  David D. McManus,et al.  Atrial Fibrillation Atrial Fibrillation Current Knowledge and Future Directions in Epidemiology and Genomics , 2011 .

[11]  S. Johnston,et al.  Estimation of Total Incremental Health Care Costs in Patients With Atrial Fibrillation in the United States , 2011, Circulation. Cardiovascular quality and outcomes.

[12]  Sunil K. Agarwal,et al.  Absolute and Attributable Risks of Atrial Fibrillation in Relation to Optimal and Borderline Risk Factors: The Atherosclerosis Risk in Communities (ARIC) Study , 2011, Circulation.

[13]  Ewout W Steyerberg,et al.  Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers , 2011, Statistics in medicine.

[14]  V. Basevi.  Diagnosis and Classification of Diabetes Mellitus , 2011, Diabetes Care.

[15]  Michael J Pencina,et al.  Association between familial atrial fibrillation and risk of new-onset atrial fibrillation. , 2010, JAMA.

[16]  Olle Melander,et al.  Assessment of conventional cardiovascular risk factors and multiple biomarkers for the prediction of incident heart failure and atrial fibrillation. , 2010, Journal of the American College of Cardiology.

[17]  L. Groop,et al.  Plasma Copeptin and the Risk of Diabetes Mellitus , 2010, Circulation.

[18]  Thomas Meitinger,et al.  Common Variants in KCNN3 are Associated with Lone Atrial Fibrillation , 2010, Nature Genetics.

[19]  P. O S I T I O N S T A T E M E N T,et al.  Diagnosis and Classification of Diabetes Mellitus , 2011, Diabetes Care.

[20]  Eric Boerwinkle,et al.  Independent Susceptibility Markers for Atrial Fibrillation on Chromosome 4q25 , 2010, Circulation.

[21]  O. Melander,et al.  Atrial fibrillation in the Malmö diet and cancer study: a study of occurrence, risk factors and diagnostic validity , 2010, European Journal of Epidemiology.

[22]  G. Naccarelli,et al.  Increasing prevalence of atrial fibrillation and flutter in the United States. , 2009, The American journal of cardiology.

[23]  C. Gieger,et al.  A sequence variant in ZFHX3 on 16q22 associates with atrial fibrillation and ischemic stroke , 2009, Nature Genetics.

[24]  Jesper Hastrup Svendsen,et al.  Familial Aggregation of Atrial Fibrillation: A Study in Danish Twins , 2009, Circulation. Arrhythmia and electrophysiology.

[25]  Eric Boerwinkle,et al.  Variants in ZFHX3 are associated with atrial fibrillation in individuals of European ancestry , 2009, Nature Genetics.

[26]  D. Levy,et al.  Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort study , 2009, The Lancet.

[27]  Randall J. Lee,et al.  A first-degree family history in lone atrial fibrillation patients. , 2008, Heart rhythm.

[28]  Thomas Lumley,et al.  Association of Gene Variants With Incident Myocardial Infarction in the Cardiovascular Health Study , 2007, Arteriosclerosis, thrombosis, and vascular biology.

[29]  E. Benjamin,et al.  Status of the epidemiology of atrial fibrillation. , 2008, The Medical clinics of North America.

[30]  P. Ridker,et al.  Effects of Random Allocation to Vitamin E Supplementation on the Occurrence of Venous Thromboembolism: Report From the Women’s Health Study , 2007, Circulation.

[31]  Eric E. Smith,et al.  Variants conferring risk of atrial fibrillation on chromosome 4q25 , 2007, Nature.

[32]  A. Hofman,et al.  Prevalence, incidence and lifetime risk of atrial fibrillation: the Rotterdam study. , 2006, European heart journal.

[33]  K. Stefánsson,et al.  Familial aggregation of atrial fibrillation in Iceland. , 2006, European heart journal.

[34]  M. Gonen,et al.  Concordance probability and discriminatory power in proportional hazards regression , 2005 .

[35]  J. Ruskin,et al.  Familial aggregation in lone atrial fibrillation , 2005, Human Genetics.

[36]  D. Levy,et al.  Lifetime Risk for Development of Atrial Fibrillation: The Framingham Heart Study , 2004, Circulation.

[37]  Ralph B D'Agostino,et al.  Parental atrial fibrillation as a risk factor for atrial fibrillation in offspring. , 2004, JAMA.

[38]  Alan D. Lopez,et al.  The Global Burden of Disease Study , 2003 .

[39]  M. Rich,et al.  Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. , 2001, JAMA.

[40]  D. Singer,et al.  Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the AnTicoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. , 2001, JAMA.

[41]  D. Levy,et al.  Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. , 1998, Circulation.

[42]  G. Berglund,et al.  Design and feasibility , 1993 .

[43]  G. Berglund,et al.  Stroke Registry in Malmö, Sweden , 1992, Stroke.

[44]  P. Wolf,et al.  Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. , 1991, Stroke.