ArticleFrontiers in neurology2025
Cortical morphometric similarity patterns and molecular signatures across ischemic stroke recovery.
Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Ischemic stroke is associated with widespread and dynamic brain structural alterations, but the relationship between these changes and underlying molecular signatures across different post-stroke stages remains unclear. Therefore, we examined the brain structural difference of patients with 3 T high resolution magnetic resonance, further explored special molecular signatures across ischemic stroke recovery stages. Methods: Among 170 participants were recruited, including 60 acute/subacute ischemic stroke patients, 59 chronic ischemic stroke patients, and 51 healthy controls. Morphometric similarity networks (MSNs) were constructed by calculating Pearson correlations between cortical morphometric feature vectors across 308 regions. Group differences in MSN strength were assessed using covariate-adjusted linear regression. We further applied partial least squares regression to link regional MSN differences with gene expression data from the Allen Human Brain Atlas, identifying molecular signatures across ischemic stroke recovery stages. Results: Regional MSN differences differed by stroke stage, predominantly involving frontal-temporal cortices in acute/subacute ischemic stroke and widespread cortical areas in chronic ischemic stroke. Regional MSN differences were associated with cortical transcriptional gradients, identifying key stroke-related genes (e.g., KIF5B, C4orf3, APMAP, STOML1). Functional analysis highlighted molecular signatures linked to neuronal changing, axonal transport, and protein homeostasis. Conclusion: Our findings demonstrate stage-specific morphometric differences and molecular signatures associated with different stages of ischemic stroke, highlighting regionally distinct structural and transcriptomic associations. These insights may facilitate targeted interventions aimed at improving functional outcomes across different stages of stroke.
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