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Gewählte Publikation:

SHR Neuro Krebs Kardio Lipid

Ibrahim-Verbaas, CA; Fornage, M; Bis, JC; Choi, SH; Psaty, BM; Meigs, JB; Rao, M; Nalls, M; Fontes, JD; O'Donnell, CJ; Kathiresan, S; Ehret, GB; Fox, CS; Malik, R; Dichgans, M; Schmidt, H; Lahti, J; Heckbert, SR; Lumley, T; Rice, K; Rotter, JI; Taylor, KD; Folsom, AR; Boerwinkle, E; Rosamond, WD; Shahar, E; Gottesman, RF; Koudstaal, PJ; Amin, N; Wieberdink, RG; Dehghan, A; Hofman, A; Uitterlinden, AG; Destefano, AL; Debette, S; Xue, L; Beiser, A; Wolf, PA; Decarli, C; Ikram, MA; Seshadri, S; Mosley, TH; Longstreth, WT; van Duijn, CM; Launer, LJ.
Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.
Stroke. 2014; 45(2):403-412 [OPEN ACCESS]
Web of Science PubMed PUBMED Central FullText FullText_MUG


Autor/innen der Med Uni Graz:
Schmidt Helena

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Plum Analytics:
Number of Figures: 3
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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. 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. 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<10(-4)). The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.
Find related publications in this database (using NLM MeSH Indexing)
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

Find related publications in this database (Keywords)
genetic epidemiology
risk factors
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