Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

C.A. Ibrahim-Verbaas; M. Fornage; J.C. Bis; S.H. Choi; B.M. Psaty; J.B. Meigs; M. Rao; M. Nalls; J.D. Fontes; O'Donnell C.J.; S. Kathiresan; G.B. Ehret; C.S. Fox; R. Malik; M. Dichgans; H. Schmidt; J. Lahti; S.R. Heckbert; T. Lumley; K. Rice; J.I. Rotter; K.D. Taylor; A.R. Folsom; E. Boerwinkle; W.D. Rosamond; E. Shahar; R.F. Gottesman; P.J. Koudstaal; N. Amin; R.G. Wieberdink; A. Dehghan; A. Hofman; A.G. Uitterlinden; A.L. Destefano; S. Debette; L. Xue; A. Beiser; P.A. Wolf; C. Decarli; M.A. Ikram; S. Seshadri; T.H. Mosley; W.T. Longstreth; C.M. van Duijn; L.J. Launer

Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

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Auteurs

Date

2014

Discipline

Psychologie

Type de document

Articles

Périmètre

Publications

Langue

Anglais

Identifiants

doi: 10.1161/STROKEAHA.113.003044
issn: 0039-2499

Source

Serveur académique Lausannois

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Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1161/STROKEAHA.113.003044

Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/24436238

Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/1524-4628

Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_87DD4E4DB47A4

Collection

Serveur Académique Lausannois

Organisation

Université de Lausanne et CHUV

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info:eu-repo/semantics/openAccess , Copying allowed only for non-profit organizations , https://serval.unil.ch/disclaimer

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Age Factors; Aged; Aged, 80 and over; Area Under Curve; Case-Control Studies; Cohort Studies; European Continental Ancestry Group; Female; Genetic Predisposition to Disease; Genome-Wide Association Study; Genotype; Humans; Male; Middle Aged; Polymorphism, Single Nucleotide/genetics; ROC Curve; Regression Analysis; Risk Factors; Sex Factors; Stroke/epidemiology; Stroke/genetics

Sujets proches En

Apoplexy Cerebrovascular disorders Cerebrovascular syndrome Brain--Blood-vessels--Diseases Cerebral circulation disorders Stroke CVA (Disease) Cerebral vascular accident Cerebrovascular accident

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C.A. Ibrahim-Verbaas et al., « Predicting stroke through genetic risk functions: the CHARGE Risk Score Project. », Serveur académique Lausannois, ID : 10.1161/STROKEAHA.113.003044

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BACKGROUND AND PURPOSE: 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. METHODS: 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 polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke. RESULTS: In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P

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Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

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