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- Mishra, A., et al.
(författare)
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Stroke genetics informs drug discovery and risk prediction across ancestries
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 611, s. 115-123
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Tidskriftsartikel (refereegranskat)abstract
- Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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| 2. |
- Hageman, Steven H. J., et al.
(författare)
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Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease : the updated SMART2 algorithm
- 2022
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Ingår i: European Heart Journal. - : Oxford University Press. - 0195-668X .- 1522-9645. ; 43:18, s. 1715-1727
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Tidskriftsartikel (refereegranskat)abstract
- Aims The 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations.Methods and results Individuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2-12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] in BACS/BAMI to 0.772 (95% CI 0.659-0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options.Conclusion The SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk.
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| 3. |
- Varmdal, T, et al.
(författare)
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Comparison of the validity of stroke diagnoses in a medical quality register and an administrative health register
- 2016
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Ingår i: Scandinavian journal of public health. - : SAGE Publications. - 1651-1905 .- 1403-4948. ; 44:2, s. 143-149
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Tidskriftsartikel (refereegranskat)abstract
- Aims: Health registers are essential sources of data used in a wide range of stroke research, including epidemiological, clinical and healthcare studies. Regardless of the type of register, the data must be of high quality to be useful. In this study, we investigated and compared the correctness and completeness of the Norwegian Patient Register (an administrative health register) and the Norwegian Stroke Register (a medical quality register for acute stroke). Methods: We reviewed the medical records for 5192 admissions to hospital in 2012 and defined cases of stroke in the two registers as true positive, false positive, true negative or false negative. We calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value with 95% confidence intervals assuming a normal approximation of the binomial distribution. Results: The Norwegian Stroke Register was highly correct and relatively complete (sensitivity 88.1%, specificity 100% and PPV 98.6%). The Norwegian Patient Register was more complete, but less correct, when we included both the main and secondary diagnoses of stroke (sensitivity 96.8%, specificity 99.6% and PPV 79.7%); restricting the analyses to the main diagnoses of stroke resulted in less complete and more correct registrations (sensitivity 86.1%, specificity 99.9% and PPV 93.5%). Conclusions: The Norwegian Stroke Register and the Norwegian Patient Register are adequately complete and correct to serve as valuable sources of data for epidemiological, clinical and healthcare studies, as well as for administrative purposes.
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