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recent acc/aha/aapa/abc/acpm/ags/apha/ash/aspc/nma/pcna guidelines34 2017 acc/aha/aapa/abc/acpm/ags/apha/ash/aspc/nma/pcna guideline nature portfolio open access resource privacy policy nature communications advertising social media genome-wide association studies east-west coordinates reprints genome-wide polygenic scores standardised socio-demographic questionnaire nature 518 nature 562 nature genome-wide association analyses genome-wide association study early-onset myocardial infarction transplant research unit 44 successful development body mass index ludwig-maximilians-universität lmu british heart foundation trans-ethnic association study low-density lipoprotein cholesterol uk/showcase/docs/alg_outcome_stroke national disability-adjusted life-years thin-plate regression spline east coordinates high-density lipoprotein cholesterol french-canadian cohorts43 suggests receiving-operating characteristic curve elastic-net logistic regression aha/asa guidelines deep-learning-based approaches health research blood elastic-net cross-validation highest cross-validated auc geographical north-south coordinates developing subtype-specific scores permissions highest c-index stroke-related risk factors8 coronary heart disease greater c-index improve risk prediction additional information provided examine subtype-specific outcomes meeting guideline targets

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         headline:Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke
         description:Recent genome-wide association studies in stroke have enabled the generation of genomic risk scores (GRS) but their predictive power has been modest compared to established stroke risk factors. Here, using a meta-scoring approach, we develop a metaGRS for ischaemic stroke (IS) and analyse this score in the UK Biobank (n = 395,393; 3075 IS events by age 75). The metaGRS hazard ratio for IS (1.26, 95% CI 1.22–1.31 per metaGRS standard deviation) doubles that of a previous GRS, identifying a subset of individuals at monogenic levels of risk: the top 0.25% of metaGRS have three-fold risk of IS. The metaGRS is similarly or more predictive compared to several risk factors, such as family history, blood pressure, body mass index, and smoking. We estimate the reductions needed in modifiable risk factors for individuals with different levels of genomic risk and suggest that, for individuals with high metaGRS, achieving risk factor levels recommended by current guidelines may be insufficient to mitigate risk. Stroke risk is influenced by genetic and lifestyle factors and previously a genomic risk score (GRS) for stroke was proposed, albeit with limited predictive power. Here, Abraham et al. develop a metaGRS that is composed of several stroke-related GRSs and demonstrate improved predictive power compared with individual GRS or classic risk factors.
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      headline:Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke
      description:Recent genome-wide association studies in stroke have enabled the generation of genomic risk scores (GRS) but their predictive power has been modest compared to established stroke risk factors. Here, using a meta-scoring approach, we develop a metaGRS for ischaemic stroke (IS) and analyse this score in the UK Biobank (n = 395,393; 3075 IS events by age 75). The metaGRS hazard ratio for IS (1.26, 95% CI 1.22–1.31 per metaGRS standard deviation) doubles that of a previous GRS, identifying a subset of individuals at monogenic levels of risk: the top 0.25% of metaGRS have three-fold risk of IS. The metaGRS is similarly or more predictive compared to several risk factors, such as family history, blood pressure, body mass index, and smoking. We estimate the reductions needed in modifiable risk factors for individuals with different levels of genomic risk and suggest that, for individuals with high metaGRS, achieving risk factor levels recommended by current guidelines may be insufficient to mitigate risk. Stroke risk is influenced by genetic and lifestyle factors and previously a genomic risk score (GRS) for stroke was proposed, albeit with limited predictive power. Here, Abraham et al. develop a metaGRS that is composed of several stroke-related GRSs and demonstrate improved predictive power compared with individual GRS or classic risk factors.
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      name:Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany
      name:British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
      name:Baker Heart and Diabetes Institute, Melbourne, Australia
      name:Department of Mathematics and Statistics, La Trobe University, Melbourne, Australia
      name:Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia
      name:British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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      name:National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
      name:National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
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      name:National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
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      name:Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
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      name:Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
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      name:Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany
      name:German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
      name:Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

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