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A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia

Authors :
Heng Shao
Na Li
Meiling Chen
Jie Zhang
Hui Chen
Minjun Zhao
Jingjing Yang
Jian Xia
Source :
Frontiers in Psychiatry, Vol 14 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

BackgroundLate-life depression (LLD) is linked to various medical conditions and influenced by aging-related processes. Sleep disturbances and insomnia symptoms may be early indicators or risk factors for depression. Neuroimaging studies have attempted to understand the neural mechanisms underlying LLD, focusing on different brain networks. This study aims to further delineate discriminative brain structural profiles for LLD with insomnia using MRI.MethodsWe analyzed 24 cases in the LLD with insomnia group, 26 cases in the LLD group, and 26 in the healthy control (HC) group. Patients were evaluated using the Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Rating Scale (HAMA), Mini-Mental State Examination (MMSE), and Pittsburgh Sleep Quality Index (PSQI). Structural MRI data were gathered and analyzed using voxel-based morphometry (VBM) to identify differences in gray matter volume (GMV) among the groups. Correlation analyses were conducted to explore the relationships between GMV and clinical characteristics.ResultsSignificant difference in sex distribution was observed across the groups (p = 0.029). However, no significant differences were detected in age and MMSE scores among the groups. LLD with insomnia group exhibited significantly higher HAMA (p = 0.041) and PSQI scores (p

Details

Language :
English
ISSN :
16640640
Volume :
14
Database :
Directory of Open Access Journals
Journal :
Frontiers in Psychiatry
Publication Type :
Academic Journal
Accession number :
edsdoj.bc4b617bee844aff963530bb7bb0adf1
Document Type :
article
Full Text :
https://doi.org/10.3389/fpsyt.2023.1201256