Ontology highlight
ABSTRACT:
SUBMITTER: Ibrahim-Verbaas CA
PROVIDER: S-EPMC3955258 | biostudies-literature | 2014 Feb
REPOSITORIES: biostudies-literature
Ibrahim-Verbaas Carla A CA Fornage Myriam M Bis Joshua C JC Choi Seung Hoan SH Psaty Bruce M BM Meigs James B JB Rao Madhu M Nalls Mike M Fontes Joao D JD O'Donnell Christopher J CJ Kathiresan Sekar S Ehret Georg B GB Fox Caroline S CS Malik Rainer R Dichgans Martin M Schmidt Helena H Lahti Jari J Heckbert Susan R SR Lumley Thomas T Rice Kenneth K Rotter Jerome I JI Taylor Kent D KD Folsom Aaron R AR Boerwinkle Eric E Rosamond Wayne D WD Shahar Eyal E Gottesman Rebecca F RF Koudstaal Peter J PJ Amin Najaf N Wieberdink Renske G RG Dehghan Abbas A Hofman Albert A Uitterlinden André G AG Destefano Anita L AL Debette Stephanie S Xue Luting L Beiser Alexa A Wolf Philip A PA Decarli Charles C Ikram M Arfan MA Seshadri Sudha S Mosley Thomas H TH Longstreth W T WT van Duijn Cornelia M CM Launer Lenore J LJ
Stroke 20140116 2
<h4>Background and purpose</h4>Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors.<h4>Methods</h4>The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphi ...[more]