Exploring the bidirectional relationships between MRI resting-state functional connectivity networks and...

Area of Science:

• Neuroimaging
• Cardiovascular Medicine
• Genetics

Background:

• Alterations in brain functional connectivity are observed in cardiovascular diseases (CVDs).
• The causal relationship between brain resting-state functional connectivity networks and CVDs is not fully understood.
• Investigating the cardio-cerebral axis is crucial for understanding disease mechanisms.

Purpose of the Study:

• To investigate the bidirectional causality between brain network connectivity and major CVDs using Mendelian randomization (MR).
• To identify specific brain functional networks associated with hypertension, atrial fibrillation (AF), heart failure (HF), and coronary artery disease (CAD).

Main Methods:

• Utilized genome-wide association study (GWAS) data from the UK Biobank (n=34,691).
• Conducted bidirectional two-sample MR analyses between 191 resting-state functional MRI phenotypes and four major CVDs.
• Performed sensitivity analyses (MR-Egger, weighted median) to ensure robustness and test for pleiotropy.

Main Results:

• Hypertension showed negative causal associations with motor, subcortical-cerebellar, default mode, and visual networks.
• Atrial fibrillation (AF) was linked to increased connectivity in salience/default mode networks and decreased connectivity in visual-motor networks.
• Heart failure (HF) showed decreased connectivity in visual/temporal networks and increased connectivity in motor networks.
• Coronary artery disease (CAD) was associated with increased connectivity in default mode and central executive networks.

Conclusions:

• Established novel bidirectional causal relationships between specific brain functional networks and CVDs.
• Identified distinct network involvement patterns for different CVDs, suggesting disease-specific cardio-cerebral mechanisms.
• Highlighted potential neuroimaging biomarkers for early detection and monitoring of cardiovascular diseases.