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Updated: May 22, 2025

A Thrombotic Stroke Model Based On Transient Cerebral Hypoxia-ischemia
Published on: August 18, 2015
Genetic Risk Scores in Stroke Research and Care
Nicola Luigi Bragazzi1, Lanyue Zhang1, Murad Omarov1
1Institute for Stroke and Dementia Research, Ludwig Maximilian University (LMU) University Hospital, LMU Munich, Germany (N.L.B., L.Z., M.O., M.K.G.).
Abstract:
Stroke remains a leading cause of death and disability worldwide. While well-established risk factors play a major role, genetic predisposition is a crucial determinant of stroke susceptibility, with heritability estimates up to 39% for ischemic stroke and 29% for intracerebral hemorrhage. Advances in next-generation sequencing and genome-wide association studies have identified numerous genetic loci associated with stroke risk, paving the way for the development of genetic risk scores. These scores aggregate information from multiple genetic variants to estimate an individual's stroke risk, offering a promising tool for personalized risk stratification that complements traditional clinical models. While GRSs have demonstrated strong predictive potential for primary stroke events in population-based settings, their integration into clinical practice remains limited. Emerging evidence suggests that GRSs could add value in clinical decision-making, for instance, for stratifying ischemic stroke risk in patients with atrial fibrillation, assessing intracerebral hemorrhage risk in anticoagulant users, and predicting vascular risk factor control in stroke survivors. The incorporation of GRSs with multiomics data and machine learning may further refine risk assessment, driving personalized prevention strategies for both primary and secondary stroke prevention. A major challenge is the limited applicability of GRS across diverse populations, as most genome-wide association studies have been conducted in individuals of European ancestry. Addressing this limitation is critical for ensuring equitable and effective implementation of GRSs in clinical settings. As methodologies continue to evolve, integrating GRS into stroke research could significantly enhance risk assessment and support precision medicine approaches tailored to individual patients.
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