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Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine

Ischemic stroke (IS), the leading cause of death and disability worldwide, is caused by many modifiable and non-modifiable risk factors. This complex disease is also known for its multiple etiologies with moderate heritability. Polygenic risk scores (PRSs), which have been used to establish a common...

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Autores principales: Li, Jiang, Abedi, Vida, Zand, Ramin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9604604/
https://www.ncbi.nlm.nih.gov/pubmed/36294301
http://dx.doi.org/10.3390/jcm11205980
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author Li, Jiang
Abedi, Vida
Zand, Ramin
author_facet Li, Jiang
Abedi, Vida
Zand, Ramin
author_sort Li, Jiang
collection PubMed
description Ischemic stroke (IS), the leading cause of death and disability worldwide, is caused by many modifiable and non-modifiable risk factors. This complex disease is also known for its multiple etiologies with moderate heritability. Polygenic risk scores (PRSs), which have been used to establish a common genetic basis for IS, may contribute to IS risk stratification for disease/outcome prediction and personalized management. Statistical modeling and machine learning algorithms have contributed significantly to this field. For instance, multiple algorithms have been successfully applied to PRS construction and integration of genetic and non-genetic features for outcome prediction to aid in risk stratification for personalized management and prevention measures. PRS derived from variants with effect size estimated based on the summary statistics of a specific subtype shows a stronger association with the matched subtype. The disruption of the extracellular matrix and amyloidosis account for the pathogenesis of cerebral small vessel disease (CSVD). Pathway-specific PRS analyses confirm known and identify novel etiologies related to IS. Some of these specific PRSs (e.g., derived from endothelial cell apoptosis pathway) individually contribute to post-IS mortality and, together with clinical risk factors, better predict post-IS mortality. In this review, we summarize the genetic basis of IS, emphasizing the application of methodologies and algorithms used to construct PRSs and integrate genetics into risk models.
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spelling pubmed-96046042022-10-27 Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine Li, Jiang Abedi, Vida Zand, Ramin J Clin Med Review Ischemic stroke (IS), the leading cause of death and disability worldwide, is caused by many modifiable and non-modifiable risk factors. This complex disease is also known for its multiple etiologies with moderate heritability. Polygenic risk scores (PRSs), which have been used to establish a common genetic basis for IS, may contribute to IS risk stratification for disease/outcome prediction and personalized management. Statistical modeling and machine learning algorithms have contributed significantly to this field. For instance, multiple algorithms have been successfully applied to PRS construction and integration of genetic and non-genetic features for outcome prediction to aid in risk stratification for personalized management and prevention measures. PRS derived from variants with effect size estimated based on the summary statistics of a specific subtype shows a stronger association with the matched subtype. The disruption of the extracellular matrix and amyloidosis account for the pathogenesis of cerebral small vessel disease (CSVD). Pathway-specific PRS analyses confirm known and identify novel etiologies related to IS. Some of these specific PRSs (e.g., derived from endothelial cell apoptosis pathway) individually contribute to post-IS mortality and, together with clinical risk factors, better predict post-IS mortality. In this review, we summarize the genetic basis of IS, emphasizing the application of methodologies and algorithms used to construct PRSs and integrate genetics into risk models. MDPI 2022-10-11 /pmc/articles/PMC9604604/ /pubmed/36294301 http://dx.doi.org/10.3390/jcm11205980 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Li, Jiang
Abedi, Vida
Zand, Ramin
Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine
title Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine
title_full Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine
title_fullStr Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine
title_full_unstemmed Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine
title_short Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine
title_sort dissecting polygenic etiology of ischemic stroke in the era of precision medicine
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9604604/
https://www.ncbi.nlm.nih.gov/pubmed/36294301
http://dx.doi.org/10.3390/jcm11205980
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