» Articles » PMID: 34688810

Aberrant Large-scale Brain Modules in Deficit and Non-deficit Schizophrenia

Overview
Specialty Psychiatry
Date 2021 Oct 24
PMID 34688810
Citations 7
Authors
Affiliations
Soon will be listed here.
Abstract

Objective: Schizophrenia is a heterogenous psychiatric disease, and deficit schizophrenia (DS) is a clinical subgroup with primary and enduring negative symptoms. Although previous neuroimaging studies have identified functional connectome alterations in schizophrenia, the modular organizations in DS and nondeficit schizophrenia (NDS) remain poorly understood. Therefore, this study aimed to investigate the modular-level alterations in DS patients compared with the NDS and healthy control (HC) groups.

Methods: A previously collected dataset was re-analyzed, in which 74 chronic male schizophrenia patients (33 DS and 41 NDS) and 40 HC underwent resting-state functional magnetic resonance imaging with eyes closed in a Siemens 3 T scanner (scanning duration = 8 min). Modular- (intramodule and intermodule connectivity) and nodal- [normalized within-module degree (Z) and participation coefficient (PC)] level graph theory properties were computed and compared among the three groups. Receiver operating characteristic curve (ROC) analyses were performed to examine the classification ability of these measures, and partial correlations were conducted between network measures and symptom severity. Validation analyses on head motion, network sparsity, and parcellation scheme were also performed.

Results: Both schizophrenia subgroups showed decreased intramodule connectivity in salience network (SN), somatosensory-motor network (SMN), and visual network (VN), and increased intermodule connectivity in SMN-default mode network (DMN) and SMN-frontoparietal network (FPN). Compared with NDS patients, DS patients showed weaker intramodule connectivity in SN and stronger intermodule connectivity in SMN-FPN and SMN-VN. At the nodal level, the schizophrenia-related alterations were distributed in SN, SMN, VN, and DMN, and 7 DS-specific nodal alterations were identified. Intramodule connectivity of SN, intermodule connectivity of SMN-VN, and Z of left precuneus successfully distinguished the three groups. Partial correlational analyses revealed that these measures were related to negative symptoms, general psychiatric symptoms, and neurocognitive function.

Conclusion: Our findings suggest that functional connectomes, especially SN, SMN, and VN, may capture the distinct and common disruptions of DS and NDS. These findings may help to understand the neuropathology of negative symptoms of schizophrenia and inform targets for treating different schizophrenia subtypes.

Citing Articles

Stress-induced cortisol response predicts empathy for pain: The role of task-based connectivity between the insula and sensorimotor cortex during acute stress.

Tang Z, Liu Y, Zhao X, Hu W, Zhang M, Ren Y Neurobiol Stress. 2024; 33:100682.

PMID: 39502834 PMC: 11536065. DOI: 10.1016/j.ynstr.2024.100682.


Analysis of the status quo and clinical influencing factors of the social cognitive impairment in deficit schizophrenia.

Chengbing H, Jia W, Lirong Z, Tingting Z, Yanling S, Taipeng S Front Psychiatry. 2024; 15:1470159.

PMID: 39415884 PMC: 11479924. DOI: 10.3389/fpsyt.2024.1470159.


Topological Perturbations in the Functional Connectome Support the Deficit/Non-deficit Distinction in Antipsychotic Medication-Naïve First Episode Psychosis Patients.

Teles M, Maximo J, Lahti A, Kraguljac N Schizophr Bull. 2024; 50(4):839-847.

PMID: 38666705 PMC: 11283198. DOI: 10.1093/schbul/sbae054.


Altered patterns of dynamic functional connectivity of brain networks in deficit and non-deficit schizophrenia.

Ye B, Wu Y, Cao M, Xu C, Zhou C, Zhang X Eur Arch Psychiatry Clin Neurosci. 2024; .

PMID: 38662092 DOI: 10.1007/s00406-024-01803-1.


Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume.

Zhu W, Wang Z, Yu M, Zhang X, Zhang Z Front Neurosci. 2023; 17:1132607.

PMID: 37051145 PMC: 10083255. DOI: 10.3389/fnins.2023.1132607.