Abstract
Dysfunction in the brain's resting-state functional networks is strongly connected with mental illness and cognitive impairment, while cardiovascular disease (CVD) is accepted as a risk factor for cognitive dysfunction. Growing interest exists in the correlation between brain and heart diseases. However, the causality between resting-state functional networks and CVD remains uncertain. In this research, a two-sample Mendelian randomization (MR) approach was applied to explore the causal association between 191 resting-state functional magnetic resonance imaging (rsfMRI) traits and 10 CVDs. This MR study employed single nucleotide polymorphisms that are strongly associated with rsfMRI phenotypes, which were sourced from the Zenodo database. We aimed to determine the causal relationship between rsfMRI phenotypes, considered as the exposure, and CVD, defined as the outcome. We engaged inverse variance weighting as our primary analytical method and executed a comprehensive sensitivity analysis to assess the heterogeneity and dependability of the results. Additionally, to validate the robustness of the findings, the test thresholds were recalibrated using the Bonferroni correction method. Functional connectivity among the angular gyrus, precuneus, cingulate gyrus, and parietal lobe also increased the hazards of atrial fibrillation (ORIVW = 0.644, 95% CI: 0.527-0.788, P = 1.83 × 10-5). Moreover, MR analyses of brain network connectivity concerning other CVDs did not meet the Bonferroni-corrected P-value threshold. Changes in functional connectivity of brain networks may be an indicator of risk for the development of atrial fibrillation but are not associated with the development of other CVDs.