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.

Extracting interpretable signatures of whole-brain dynamics through systematic comparison

“…Head movement in the scanner was evaluated using framewise displacement (FD) calculated from the six framewise head-motion parameters (corresponding to rotation and translation in the x , y , and z planes) using the method of Power et al [162]. We found that SCZ, BP, and ASD—but not ADHD—cases exhibited significantly higher mean FD relative to control participants, consistent with prior studies [163–165] (all p < 0.05, Wilcoxon rank-sum test). Head movement (mean FD) alone significantly distinguished cases from controls for SCZ (74.0 ± 12.5%), BP (60.7 ± 11.4%), and ASD (55.5 ± 4.3%), though not for ADHD (44.0 ± 11.5%; Fig.…”

Neurobehavioral indices of gaze perception are associated with social cognition across schizophrenia patients and healthy controls.

“…Such an approach would be consistent with frameworks such as the NIMH RDoC (Insel et al, 2010) and the Hierarchical Taxonomy of Psychopathology (Kotov et al, 2017), which seek to understand psychopathology in terms of underlying mechanisms and dimensions rather than diagnosis. Finally, although our sample size was comparable to or larger than those used in several previous studies using latent variable modeling/multivariate analyses to investigate brain function in SZ (Lincoln et al, 2020; Liu et al, 2021; Plis et al, 2014), future research with even larger samples should be undertaken to confirm results from the current study.…”

Involvement of cerebellar and subcortical connector hubs in schizophrenia

“…Previous studies have also reported hub abnormalities in schizophrenia using resting-state functional MRI ( Hummer et al, 2020 , Li et al, 2019 , Liu et al, 2021 , Rubinov and Bullmore, 2013 ). The main findings of these studies were lower global efficiency and fewer hubs in the cerebellum network ( Hummer et al, 2020 ), reduced nodal efficiency and strength in the hippocampal formation ( Li et al, 2019 ), and a shift in hub locations with more hubs in frontal and occipital regions ( Liu et al, 2021 ) in patients with schizophrenia compared to healthy controls. These different findings may be due to the differences in methodology (such as sample characteristics and analytic methods).…”