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

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...

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Main Authors: Heng Shao, Na Li, Meiling Chen, Jie Zhang, Hui Chen, Minjun Zhao, Jingjing Yang, Jian Xia
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Psychiatry
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1201256/full
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author Heng Shao
Na Li
Meiling Chen
Meiling Chen
Jie Zhang
Jie Zhang
Hui Chen
Hui Chen
Minjun Zhao
Minjun Zhao
Jingjing Yang
Jingjing Yang
Jian Xia
author_facet Heng Shao
Na Li
Meiling Chen
Meiling Chen
Jie Zhang
Jie Zhang
Hui Chen
Hui Chen
Minjun Zhao
Minjun Zhao
Jingjing Yang
Jingjing Yang
Jian Xia
author_sort Heng Shao
collection DOAJ
description 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 < 0.05) compared to the LLD group. ANOVA identified significant difference in GMV of anterior lobe of cerebellum (peak MNI coordinate: x = 52, y = −40, z = −30) among HC, LLD, and LLD with insomnia. Post-hoc two-sample t-tests revealed that the significant difference in GMV was only found between the LLD group and the HC group (p < 0.05). The mean GMV in the cerebellum was positively correlated with HAMA scale in LLD patients (r = 0.47, p < 0.05).ConclusionThere is significant difference in GMV in the LLD group, the association between late-life depression and insomnia may be linked to anxiety. This study provides insights into the discriminative brain structural profiles of LLD and LLD with insomnia, advancing the understanding of the underlying neural mechanisms and potential targets for intervention.
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spelling doaj.art-bc4b617bee844aff963530bb7bb0adf12023-05-18T06:52:19ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402023-05-011410.3389/fpsyt.2023.12012561201256A voxel-based morphometry investigation of brain structure variations in late-life depression with insomniaHeng Shao0Na Li1Meiling Chen2Meiling Chen3Jie Zhang4Jie Zhang5Hui Chen6Hui Chen7Minjun Zhao8Minjun Zhao9Jingjing Yang10Jingjing Yang11Jian Xia12Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, ChinaDepartment of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, ChinaDepartment of Clinical Psychology, The First People’s Hospital of Yunnan Province, Kunming, ChinaThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, ChinaThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, ChinaDepartment of MRI, The First People’s Hospital of Yunnan Province, Kunming, ChinaDepartment of Clinical Psychology, The First People’s Hospital of Yunnan Province, Kunming, ChinaThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, ChinaThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, ChinaDepartment of Geriatrics, The First People’s Hospital of Yunnan Province, Kunming, ChinaThe Affiliated Hospital of Kunming University of Science and Technology, Kunming, ChinaDepartment of Geriatrics, The First People’s Hospital of Yunnan Province, Kunming, ChinaSchool of Medicine, Kunming University of Science and Technology, Kunming, ChinaBackgroundLate-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 < 0.05) compared to the LLD group. ANOVA identified significant difference in GMV of anterior lobe of cerebellum (peak MNI coordinate: x = 52, y = −40, z = −30) among HC, LLD, and LLD with insomnia. Post-hoc two-sample t-tests revealed that the significant difference in GMV was only found between the LLD group and the HC group (p < 0.05). The mean GMV in the cerebellum was positively correlated with HAMA scale in LLD patients (r = 0.47, p < 0.05).ConclusionThere is significant difference in GMV in the LLD group, the association between late-life depression and insomnia may be linked to anxiety. This study provides insights into the discriminative brain structural profiles of LLD and LLD with insomnia, advancing the understanding of the underlying neural mechanisms and potential targets for intervention.https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1201256/fullvoxel-based morphometrylate-life depressioninsomniaanxietycerebellum
spellingShingle Heng Shao
Na Li
Meiling Chen
Meiling Chen
Jie Zhang
Jie Zhang
Hui Chen
Hui Chen
Minjun Zhao
Minjun Zhao
Jingjing Yang
Jingjing Yang
Jian Xia
A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia
Frontiers in Psychiatry
voxel-based morphometry
late-life depression
insomnia
anxiety
cerebellum
title A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia
title_full A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia
title_fullStr A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia
title_full_unstemmed A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia
title_short A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia
title_sort voxel based morphometry investigation of brain structure variations in late life depression with insomnia
topic voxel-based morphometry
late-life depression
insomnia
anxiety
cerebellum
url https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1201256/full
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