2022
DOI: 10.1038/s41586-022-05492-5
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Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries

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Cited by 7 publications
(2 citation statements)
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“…3 Similar to other complex traits, PRSs for ischemic stroke and intracerebral hemorrhage are strongly associated with risk of incident events in populationbased settings and independently of clinical risk factors, such as hypertension. 2,4 However, despite innovations in PRS construction and improvements in their predictive ability, there has been to date no strong evidentiary support for their use in clinical and public health practice. 5 Whereas PRSs have been extensively studied in population-based research settings, covering this translational gap would require testing PRSs in prospective clinical studies and randomized trials.…”
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confidence: 99%
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“…3 Similar to other complex traits, PRSs for ischemic stroke and intracerebral hemorrhage are strongly associated with risk of incident events in populationbased settings and independently of clinical risk factors, such as hypertension. 2,4 However, despite innovations in PRS construction and improvements in their predictive ability, there has been to date no strong evidentiary support for their use in clinical and public health practice. 5 Whereas PRSs have been extensively studied in population-based research settings, covering this translational gap would require testing PRSs in prospective clinical studies and randomized trials.…”
mentioning
confidence: 99%
“…1 By accumulating power with increasing sample sizes and increasing representation across ancestries, GWASs have detected thousands of loci across the genome associated with complex vascular diseases including stroke. 2 Polygenic risk scores (PRSs) aggregate this information at an individual level by adding the number of genetic risk variants a person carries, weighted by the effect sizes from GWASs. Since their first description, PRSs were considered a means toward the clinical implementation of GWAS-derived data by consolidating complicated genomic data into a simple numerical biomarker representing an individual's genetic risk for a disease.…”
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confidence: 99%