title: Novel genetic markers improve measures of atrial fibrillation risk prediction.
abstract: OBJECTIVE
  Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown.
  
  
  RESULTS
  We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684-0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709-0.774); P = 0.001], the category-less net reclassification [0.490 (0.301-0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033-0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1-5, and 5+% [0.041 (-0.044-0.12); P = 0.33].
  
  
  CONCLUSIONS
  Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categories.
authors: Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. beverett@partners.org
authors: Brendan M
authors: BM
authors: Everett
authors: Nancy R
authors: NR
authors: Cook
authors: David
authors: D
authors: Conen
authors: Daniel I
authors: DI
authors: Chasman
authors: Paul M
authors: PM
authors: Ridker
authors: Christine M
authors: CM
authors: Albert
mesh_terms: D000367:Age Factors; D000428:Alcohol Drinking / Q000009:adverse effects; D000465:Algorithms; D001281:Atrial Fibrillation / Q000235:genetics* / Q000517:prevention & control*; D001827:Body Height; D001835:Body Weight; D005260:Female; D005819:Genetic Markers / Q000235:genetics; D006801:Humans; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects
chemical_list: D005819:Genetic Markers
keywords: Atrial fibrillation; Epidemiology; Genetics; Risk prediction; Women