4.7 Article

Brain Network Topology in Deficit and Non-Deficit Schizophrenia: Application of Graph Theory to Local and Global Indices

Journal

JOURNAL OF PERSONALIZED MEDICINE
Volume 13, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/jpm13050799

Keywords

neuroimaging; clinical neuroscience; brain structural covariance; mental diseases; psychiatric disorders

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This study compared the brain network topology features of deficit schizophrenia (SZD) and non-deficit schizophrenia (SZND) patients with a healthy control group using graph theory analysis for the first time. The results showed significant alterations in both local and global networks in SZD patients, while SZND patients exhibited differences in centrality and integration measures in specific brain regions. These findings contribute to a better understanding of the neurobiology of SZD.
Patients with deficit schizophrenia (SZD) suffer from primary and enduring negative symptoms. Limited pieces of evidence and neuroimaging studies indicate they differ from patients with non-deficit schizophrenia (SZND) in neurobiological aspects, but the results are far from conclusive. We applied for the first time, graph theory analyses to discriminate local and global indices of brain network topology in SZD and SZND patients compared with healthy controls (HC). High-resolution T1-weighted images were acquired for 21 SZD patients, 21 SZND patients, and 21 HC to measure cortical thickness from 68 brain regions. Graph-based metrics (i.e., centrality, segregation, and integration) were computed and compared among groups, at both global and regional networks. When compared to HC, at the regional level, SZND were characterized by temporoparietal segregation and integration differences, while SZD showed widespread alterations in all network measures. SZD also showed less segregated network topology at the global level in comparison to HC. SZD and SZND differed in terms of centrality and integration measures in nodes belonging to the left temporoparietal cortex and to the limbic system. SZD is characterized by topological features in the network architecture of brain regions involved in negative symptomatology. Such results help to better define the neurobiology of SZD (SZD: Deficit Schizophrenia; SZND: Non-Deficit Schizophrenia; SZ: Schizophrenia; HC: healthy controls; CC: clustering coefficient; L: characteristic path length; E: efficiency; D: degree; CCnode: CC of a node; CCglob: the global CC of the network; E-loc: efficiency of the information transfer flow either within segregated subgraphs or neighborhoods nodes; E-glob: efficiency of the information transfer flow among the global network; FDA: Functional Data Analysis; and D-min: estimated minimum densities).

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