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Polygenic Risk Scores Augment Stroke Subtyping.

Jiang Li1, Durgesh P Chaudhary1, Ayesha Khan1

  • 1Department of Molecular and Functional Genomics (J.L., D.J.C., V.A.), Weis Center for Research, Geisinger Health System; Neuroscience Institute (D.P.C., A.K., C.G., R.Z.), Geisinger Health System, Danville, PA; Biocomplexity Institute (V.A.), Virginia Tech, Blacksburg, VA; and Research Institute of Neurointervention (C.G.), Paracelsus Medical University, Salzburg, Austria.

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Summary
This summary is machine-generated.

Polygenic risk scores (PRS) from MEGASTROKE effectively identify shared causes and subtypes of ischemic stroke (IS) in a new population. These genetic risk scores demonstrate value in understanding stroke etiology and classification.

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Area of Science:

  • Genetics
  • Neurology
  • Epidemiology

Background:

  • Ischemic stroke (IS) is a leading cause of disability and death.
  • Understanding the genetic underpinnings of IS and its subtypes is crucial for risk stratification and targeted interventions.
  • Previous genome-wide association studies (GWAS) have identified genetic variants associated with IS, but their clinical utility requires validation in independent cohorts.

Purpose of the Study:

  • To assess the association of polygenic risk scores (PRS) derived from the MEGASTROKE GWAS with IS and its subtypes in an independent healthcare system.
  • To identify PRS derived from gene sets linked to known biological pathways relevant to IS.
  • To evaluate the performance of PRS in predicting IS subtypes based on clinical risk factors and genetic ancestry.

Main Methods:

  • Utilized a large electronic health record (EHR) database (Geisinger MyCode) with European ancestry individuals, including IS cases and controls.
  • Calculated genetic heritability and genetic correlation between the MEGASTROKE and Geisinger cohorts using GWAS summary statistics.
  • Constructed PRS for various stroke types (any stroke, any IS, large artery stroke, cardioembolic stroke, small vessel stroke) using PRSice-2 and evaluated their predictive ability.

Main Results:

  • A moderate genetic heritability (10%-20%) and significant genetic correlation were found between the MEGASTROKE and Geisinger cohorts.
  • All five PRS significantly explained phenotypic variations in Geisinger IS cases, with improved prediction by increasing the age cutoff for controls.
  • PRS for specific subtypes (large artery stroke, cardioembolic stroke, small vessel stroke) showed the best modeling fit, indicating shared etiologies and corroborating clinical subtyping (TOAST).

Conclusions:

  • This study provides the first evidence that PRS derived from the MEGASTROKE resource are valuable for identifying shared etiologies of IS.
  • PRS can aid in determining stroke subtypes, offering potential for improved clinical risk assessment and personalized medicine approaches.
  • The findings highlight the utility of large-scale genetic studies in understanding complex diseases like ischemic stroke.