Genomic insights into stroke recovery: cross-phenotype associations

Clicks: 6
ID: 326496
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #59 of 120 articles by views in Brain communications

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Stroke is a major cause of long-term disability with variable recovery. While clinical factors such as initial severity play a role, genetic factors are increasingly recognized as important contributors to stroke recovery. Genotype studies are generally focused on a single post-stroke behavioral domain, but some genes might relate to broad mechanisms of plasticity. This study therefore aimed to identify cross-phenotypic genetic variants associated across two or more stroke recovery domains. DNA from Stroke, Stress, Rehabilitation, and Genetics study participants was genotyped, resulting in 9,814,610 variants. In order to examine cross-phenotypic results, we first conducted genome-wide association studies on the six recovery domains: motor (grip force), cognition (telephone Montreal Cognitive Assessment), depression (Patient Health Questionnaire-8), stress (Primary Care Post-Traumatic Stress Disorder Screen), functional status (Stroke Impact Scale-Activities of Daily Living), and disability (modified Rankin Scale 0-2 vs 3-6), some of which were tested longitudinally, yielding nine phenotypes. Models were adjusted for age, sex, initial severity (NIH Stroke Scale score), and ancestry. Cross-phenotype associations were identified by evaluating single nucleotide polymorphisms associated (p<5e-5) with multiple phenotypes. To determine how these genetic variants may relate to biological mechanisms of recovery, we conducted gene enrichment analyses. Participants (n=565, 59% male) had mild-moderate initial stroke severity (median acute NIH Stroke Scale score=4). After accounting for the correlation structure among the nine phenotypes, we observed 319 cross-phenotypic single nucleotide polymorphisms (SNPs), 3.45 times the expected number. Five of the cross-phenotypic SNPs were linked to genes relevant to neural development, function, and plasticity, e.g., ERICH1 (rs11778883-C), FOX3 (rs55726768-G), LIFR-AS1 (rs76401391-T), RPS6KA2 (rs113518460-C), and TUBGCP2 (rs147150392-C), as were enrichments in RAB5-EEA1, CTNNA1-CTNNB1, CIN85-SH3GL2, and ELMO1-DOCK2 complexes. Multiple gene enrichments were found, e.g., Stroke Impact Scale-Activities of Daily Living and Patient Health Questionnaire 8 at 3 months were enriched for CREB phosphorylation, which is important for long-term potentiation. We identified cross-phenotypic single nucleotide polymorphisms associated with multiple behavioral domains of stroke recovery. Some of these genes encode, or regulate, druggable proteins. These genetic factors are not well captured by clinical or neuroimaging assessments and so provide a unique window into stroke recovery. These findings, if validated, suggest that some genes may be broadly important to stroke recovery.
Reference Key
openalex_W7204225448 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Chad Aldridge, Robynne Braun, Livia Parodi, Keith R. Lohse, Matthew A. Edwardson, John W. Cole, Arne Lindgren, Fang‐Chi Hsu, Keith Keene, Bradford Worrall, Jonathan Rosand, E Alison Holman, Steven C. Cramer
Journal Brain communications
Year 2026
DOI
10.1093/braincomms/fcag322
URL
https://doi.org/10.1093/braincomms/fcag322
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.