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Updated: Nov 13, 2025

The Mouse Stroke Unit Protocol with Standardized Neurological Scoring for Translational Mouse Stroke Studies
Published on: February 7, 2025
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.
Objective:
To determine whether the polygenic risk score (PRS) derived from MEGASTROKE is associated with ischemic stroke (IS) and its subtypes in an independent tertiary health care system and to identify the PRS derived from gene sets of known biological pathways associated with IS.
Methods:
Controls (n = 19,806/7,484, age ≥69/79 years) and cases (n = 1,184/951 for discovery/replication) of acute IS with European ancestry and clinical risk factors were identified by leveraging the Geisinger Electronic Health Record and chart review confirmation. All Geisinger MyCode patients with age ≥69/79 years and without any stroke-related diagnostic codes were included as low risk control. Genetic heritability and genetic correlation between Geisinger and MEGASTROKE (EUR) were calculated using the summary statistics of the genome-wide association study by linkage disequilibrium score regression. All PRS for any stroke (AS), any ischemic stroke (AIS), large artery stroke (LAS), cardioembolic stroke (CES), and small vessel stroke (SVS) were constructed by PRSice-2.
Results:
A moderate heritability (10%-20%) for Geisinger sample as well as the genetic correlation between MEGASTROKE and the Geisinger cohort was identified. Variation of all 5 PRS significantly explained some of the phenotypic variations of Geisinger IS, and the R 2 increased by raising the cutoff for the age of controls. PRSLAS, PRSCES, and PRSSVS derived from low-frequency common variants provided the best fit for modeling (R 2 = 0.015 for PRSLAS). Gene sets analyses highlighted the association of PRS with Gene Ontology terms (vascular endothelial growth factor, amyloid precursor protein, and atherosclerosis). The PRSLAS, PRSCES, and PRSSVS explained the most variance of the corresponding subtypes of Geisinger IS suggesting shared etiologies and corroborated Geisinger TOAST subtyping.
Conclusions:
We provide the first evidence that PRSs derived from MEGASTROKE have value in identifying shared etiologies and determining stroke subtypes.
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