Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke

Abraham, G.; Malik, Rainer; Yonova-Doing, E.; Salim, Agus; Wang, T.; Danesh, John; Butterworth, Adam S.; Howson, Joanna M. M.; Inouye, M. und Dichgans, Martin (20. Dezember 2019): Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke. In: Nature Communications, 5819

Abstract

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.

• Dokumententyp: Zeitschriftenartikel
• EU Funded Grant Agreement Number: 666881
• EU-Projekte: Horizon 2020 > RIA - Research and Innovation action > SVDs-at-target - Small Vessel Diseases from a therapeutic perspective: Targets for intervention. Affected pathways and mechanistic exploitation for prevention of stroke dementia ; Horizon 2020 > RIA - Research and Innovation action > CoSTREAM - Common mechanisms and pathways in stroke and Alzheimer's disease
• Publikationsform: Publisher's Version
• Fakultät: Medizin > Institut für Schlaganfall- und Demenzforschung (ISD) ; Medizin > Munich Cluster for Systems Neurology (SyNergy)
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 2041-1723
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198