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

Thursday,2014-02-06 09:35 America/Los_Angeles — poolea2
TitlePredicting stroke through genetic risk functions: the CHARGE Risk Score Project.
Publication TypeJournal Article
Year of Publication2014
AuthorsIbrahim-Verbaas, CA, Fornage, M, Bis, JC, Choi, SHoan, 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, AM, Seshadri, S, Mosley, TH, Longstreth, WT, van Duijn, CM, Launer, LJ
JournalStroke
Volume45
Issue2
Pagination403-12
Date Published2014 Feb
ISSN1524-4628
KeywordsAge 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, Regression Analysis, Risk Factors, ROC Curve, Sex Factors, Stroke
Abstract<p><b>BACKGROUND AND PURPOSE: </b>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.</p><p><b>METHODS: </b>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.</p><p><b>RESULTS: </b>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)).</p><p><b>CONCLUSIONS: </b>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.</p>
DOI10.1161/STROKEAHA.113.003044
Alternate JournalStroke
PubMed ID24436238
PubMed Central IDPMC3955258
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