Work

Stroke risk, gray matter network, and cognitive performance in stroke-free individuals with atrial fibrillation

Year: 2026

Type: article

Abstract: Atrial fibrillation (AF) is associated with an elevated risk of cognitive impairment (CI), but its mechanisms remain incompletely understood. The study aims to investigate alterations in GM network in stroke-free patients with AF and to explore the mechanistic role of brain network changes in linking stroke risk to cognitive function. Sixty-three stroke-free individuals with AF and forty-five healthy controls underwent structural magnetic resonance imaging, and cognitive function was assessed using the Montreal Cognitive Assessment and the Mini-Mental State Examination. Single-subject GM similarity networks were constructed based on regional similarity metrics of GM, computed via the Kullback-Leibler similarity method, and subsequent analyses of network topological properties were conducted using graph theory. Results revealed significant alterations in the GM network of stroke-free individuals with AF, primarily manifested as impaired local segregation. Concurrently, changes in nodal centrality were detected in brain regions implicated in executive function, sensory processing, motor control, and cognition. Notably, the CHA 2 DS 2 -VASc score, an established clinical metric for guiding antithrombotic therapy and predicting stroke risk, was associated with both cognitive performance outcomes and GM network alterations. Mediation analysis further indicated that local efficiency within GM network served as a key mediating pathway linking the CHA 2 DS 2 -VASc score to cognitive function. These findings demonstrate disrupted GM network organization in stroke-free AF, with reduced local efficiency closely associated with stroke risk and CI. They not only enhance understanding of the neurobiological mechanisms underlying CI in stroke-free AF individuals but may also inform the development of novel clinical approaches for targeted cognitive interventions.

Source: Brain Research Bulletin

DOI: 10.1016/j.brainresbull.2026.111861