Changes in Functional Brain Networks in Coronary Heart Disease Patients: Independent Component Analysis and Graph Theory Analysis

This article, published in the 229th volume of “Brain Structure and Function” in 2024, explores the changes in functional connectivity (FC) and brain network topology in patients with coronary heart disease (CHD). The study, conducted by scientists from several institutions including the Cardiovascular Hospital of Xiamen University and Xiamen University School of Medicine, lists Simin Lin, Puyeh Wu, Shaoyin Duan, and others as primary authors.

Background and Motivation

Coronary heart disease is one of the leading causes of death globally, and patients face an increased risk of cognitive and psychological impairment. Previous studies have indicated that the pathogenesis of CHD is closely related to inflammatory factors (Li et al. 2017). CHD is not just a cardiovascular condition but is also associated with a series of risk factors such as hypertension, diabetes, obesity, and smoking, which can adversely affect cognitive function (Arntzen et al. 2011; Grodstein 2007). It has been found that CHD patients perform poorly in neuropsychological tests, especially in attention, executive function, and psychomotor speed (Roberts et al. 2010). However, the potential link between CHD and higher-order cognitive processing has not been thoroughly studied.

Source

This study was published on November 9, 2023, in the journal “Brain Structure and Function,” under Springer-Verlag GmbH Germany. The research team primarily comes from the Cardiovascular Hospital of Xiamen University, Xiamen University School of Medicine, GE Healthcare, and other institutions, and was funded by the Fujian Provincial Natural Science Fund.

Research Methods

This study utilized resting-state functional magnetic resonance imaging (rs-fMRI), independent component analysis (ICA), and graph theoretical analysis (GTA) to investigate the changes in brain functional networks in CHD patients.

Experimental Procedures

The study included 27 CHD patients and 44 age, gender, and education-matched healthy controls. All participants underwent resting-state functional magnetic resonance imaging scans. The experimental procedures involved the following steps:

1. Data Collection and Preprocessing: All structural and functional MRI data were obtained using a GE Healthcare 3.0T MRI scanner. Data were preprocessed using SPM12 and DPABI tools.
2. Independent Component Analysis (ICA): ICA analysis was conducted using the GIFT tool, identifying 36 independent components. Through temporal correlation analysis, 12 functional networks were ultimately identified.
3. Graph Theory Analysis (GTA): The GRETNA tool was used to construct whole-brain functional networks by dividing the entire brain into 90 regions of interest (ROIs). Pearson correlation coefficients between these regions were calculated, creating a 90×90 correlation matrix. Further analysis of global and regional network metrics was conducted.

Sample Processing and Data Analysis

Samples were divided into CHD and healthy control groups, and functional connectivity analysis was performed both within and between groups. Pearson correlation coefficients were used to calculate the time series among various functional networks, and Fisher’s z transformation was used to convert them into z-values. Graph theory analysis measured small-world network topology and network efficiency to explore differences between the two groups.

Key Findings

Independent Component Analysis Results

The study identified 12 functional networks, including anterior and posterior default mode networks (aDMN and pDMN), left and right frontoparietal networks (LFPN and RFPN), dorsal and ventral sensorimotor networks (dSMN and vSMN), dorsal attention network (DAN), ventral attention network (VAN), salience network (SN), auditory network (AN), and medial and posterior visual networks (MVN and PVN).

Compared to the healthy control group, CHD patients exhibited the following functional connectivity changes: - Increased functional connectivity: Between the pDMN and MVN. - Decreased functional connectivity: Between the LFPN and AN, and between the DAN and PVN.

Graph Theory Analysis Results

Graph theory analysis found that both groups demonstrated small-world properties in their functional brain networks, indicating a good balance between network integration and segregation. However, CHD patients showed less optimized topological organization, with significantly reduced local efficiency in the left putamen.

Discussion

This study observed significant changes in the functional brain network connectivity and topology in CHD patients. The increased connectivity between the default mode and visual networks might be related to higher-order cognitive and visual processing. Decreased connectivity between the frontoparietal and auditory networks, and between the dorsal attention and posterior visual networks, could be associated with declines in executive function, attention, and auditory verbal learning ability.

In terms of small-world network topology, although both CHD patients and healthy controls exhibited small-world properties, the CHD patients’ topological organization was less optimized, with the left putamen showing reduced local efficiency, which may be related to motor control.

Conclusion and Application Value

The study highlights the impact of CHD on functional brain networks, particularly those associated with higher-order cognitive functions. These findings enhance our understanding of CHD-related brain functional changes and potential neural mechanisms, suggesting that CHD patients require additional brain protective measures.

Research Highlights

1. Increased Functional Connectivity: The hyperconnectivity between the default mode and visual networks may explain the cognitive impairments in CHD patients.
2. Decreased Functional Connectivity: Reduced functional connectivity between the frontoparietal and auditory networks, and between the dorsal attention and posterior visual networks, may be related to declines in executive function, attention, and auditory verbal learning ability.
3. Topological Changes: Although CHD patients exhibited small-world network properties, the left putamen’s local efficiency was significantly reduced.

This study preliminarily reveals changes in the functional brain networks of CHD patients, providing new insights for future research in this field. Larger sample sizes and more comprehensive studies, including cognitive function assessments, are necessary to validate these findings.