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Disentangling age- and disease-related alterations in schizophrenia brain network using structural equation modeling: A graph theoretical study based on minimum spanning tree.

ABSTRACT: Functional brain networks have been shown to undergo fundamental changes associated with aging or schizophrenia. However, the mechanism of how these factors exert influences jointly or interactively on brain networks remains elusive. A unified recognition of connectomic alteration patterns was also hampered by heterogeneities in network construction and thresholding methods. Recently, an unbiased network representation method regardless of network thresholding, so called minimal spanning tree algorithm, has been applied to study the critical skeleton of the brain network. In this study, we aimed to use minimum spanning tree (MST) as an unbiased network reconstruction and employed structural equation modeling (SEM) to unravel intertwined relationships among multiple phenotypic and connectomic variables in schizophrenia. First, we examined global and local brain network properties in 40 healthy subjects and 40 schizophrenic patients aged 21-55 using resting-state functional magnetic resonance imaging (rs-fMRI). Global network alterations are measured by graph theoretical metrics of MSTs and a connectivity-transitivity two-dimensional approach was proposed to characterize nodal roles. We found that networks of schizophrenic patients exhibited a more star-like global structure compared to controls, indicating excessive integration, and a loss of regional transitivity in the dorsal frontal cortex (corrected p <.05). Regional analysis of MST network topology revealed that schizophrenia patients had more network hubs in frontal regions, which may be linked to the "overloading" hypothesis. Furthermore, using SEM, we found that the level of MST integration mediated the influence of age on negative symptom severity (indirect effect 95% CI [0.026, 0.449]). These findings highlighted an altered network skeleton in schizophrenia and suggested that aging-related enhancement of network integration may undermine functional specialization of distinct neural systems and result in aggravated schizophrenic symptoms.

SUBMITTER: Liu X

PROVIDER: S-EPMC8193510 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Identifying early and non-invasive biomarkers to detect individuals in the earliest stages of the Alzheimer's disease continuum is crucial. As a result, electrophysiology and plasma biomarkers are emerging as great candidates in this pursuit due to their low invasiveness. This is the first magnetoencephalography study to assess the relationship between minimum spanning tree parameters, an alternative to overcome the comparability and thresholding problem issues characteristic of conventional brain network analyses, and plasma phosphorylated tau231 levels in unimpaired individuals, with different risk levels of Alzheimer's disease. Seventy-six individuals with available magnetoencephalography recordings and phosphorylated tau231 plasma determination were included. The minimum spanning tree for the theta, alpha and beta bands for each subject was obtained, and the leaf fraction, tree hierarchy and diameter were calculated. To study the relationship between these topological parameters and phosphorylated tau231, we performed correlation analyses, for the whole sample and considering the two risk sub-groups separately. Increasing concentrations of phosphorylated tau231 were associated with greater leaf fraction and tree hierarchy values, along with lower diameter values, for the alpha and theta frequency bands. These results emerged for the whole sample and the higher risk group, but not for the lower risk group. Our results indicate that the network topology of cognitively unimpaired individuals with elevated plasma phosphorylated tau231 levels, a marker of Alzheimer's disease pathology and amyloid-β accumulation, is already altered, shifting towards a more integrated network increasing its vulnerability and hub-dependency, mostly in the alpha band. This is indicated by increases in leaf fraction and tree hierarchy, along with reductions in diameter. These results match the initial trajectory proposed by theoretical models of disease progression and network disruption and suggest that changes in brain function and organization begin early on.

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Disentangling age- and disease-related alterations in schizophrenia brain network using structural equation modeling: A graph theoretical study based on minimum spanning tree.

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