ORCID: https://orcid.org/0000-0002-0654-387X; Pulit, Sara L. und Rosand, Jonathan
(1. June 2019):
Stroke genetics: discovery, biology, and clinical applications.
In: The Lancet Neurology, Vol. 18, No. 6: pp. 587-599
[PDF, 2MB]

Abstract
Stroke, a leading cause of long-term disability and death worldwide, has a heritable component. Recent gene discovery efforts have expanded the number of known single-gene disorders associated with stroke and have linked common variants at approximately 35 genetic loci to stroke risk. These discoveries have highlighted novel mechanisms and pathways implicated in stroke related to large artery atherosclerosis, cardioembolism, and small vessel disease, and defined shared genetic influences with related vascular traits. Genetics has also successfully established causal relationships with risk factors and holds promise for prioritising targets for exploration in clinical trials. Genome-wide polygenic scores enable the identification of high-risk individuals before the emergence of vascular risk factors. Challenges ahead include a better understanding of rare variants and ancestral differences for integration of genetics into precision medicine, integration with other omics data, uncovering the genetic factors that govern stroke recurrence and stroke outcome, and the conversion of genetic discoveries to novel therapies.
Item Type: | Journal article |
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EU Funded Grant Agreement Number: | 666881 |
EU Projects: | 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 |
Faculties: | Medicine > Institute for Stroke and Dementia Research (ISD) Medicine > Munich Cluster for Systems Neurology (SyNergy) |
Subjects: | 600 Technology > 610 Medicine and health |
URN: | urn:nbn:de:bvb:19-epub-72667-9 |
ISSN: | 1474-4422 |
Language: | English |
Item ID: | 72667 |
Date Deposited: | 14. Jul 2020 10:38 |
Last Modified: | 06. Jun 2024 13:32 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198 |