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- Debette, Stéphanie, et al.
(författare)
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Common variation in PHACTR1 is associated with susceptibility to cervical artery dissection
- 2015
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 47, s. 78-83
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Tidskriftsartikel (refereegranskat)abstract
- Cervical artery dissection (CeAD), a mural hematoma in a carotid or vertebral artery, is a major cause of ischemic stroke in young adults although relatively uncommon in the general population (incidence of 2.6/100,000 per year)1. Minor cervical traumas, infection, migraine and hypertension are putative risk factors1–3, and inverse associations with obesity and hypercholesterolemia are described3,4. No confirmed genetic susceptibility factors have been identified using candidate gene approaches5. We performed genome-wide association studies (GWAS) in 1 1,393 CeAD cases and 1 14,416 controls. The rs9349379[G] allele (PHACTR1) was associated with lower CeAD risk (odds ratio (OR) = 0.75, 95% confidence interval (CI) = 0.69–0.82; P = 4.46 × 1 10−10), with confirmation in independent follow-up samples (659 CeAD cases and 2,648 controls; P = 3.91 1 × 1 10−3; combined P = 1 1.00 × 1 10−1111). The rs9349379[G] allele was previously shown to be associated with lower risk of migraine and increased risk of myocardial infarction6–9. Deciphering the mechanisms underlying this pleiotropy might provide important information on the biological underpinnings of these disabling conditions.
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| 2. |
- Parmar, Priya, et al.
(författare)
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The Stroke Riskometer (TM) App: Validation of a data collection tool and stroke risk predictor
- 2015
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Ingår i: International Journal of Stroke. - : SAGE Publications. - 1747-4949 .- 1747-4930. ; 10:2, s. 231-244
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the mass' approach), the high risk' approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer(TM), has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods. Methods752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction tool algorithm (Stroke Riskometer(TM)) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R-2 statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm. ResultsThe Stroke Riskometer(TM) performed well against the FSRS five-year AUROC for both males (FSRS=750% (95% CI 723%-776%), Stroke Riskometer(TM)=740(95% CI 713%-767%) and females [FSRS=703% (95% CI 679%-728%, Stroke Riskometer(TM)=715% (95% CI 690%-739%)], and better than QStroke [males - 597% (95% CI 573%-620%) and comparable to females=711% (95% CI 690%-731%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 051-056, D-statistic ranging from 001-012). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event data (P<0006). ConclusionsThe Stroke Riskometer(TM) is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer(TM) will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors.
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