Disruptive and complementary effects of depression symptoms on spontaneous brain activity in the subcortical vascular mild cognitive impairment.

depression symptoms fractions of amplitude of low-frequency fluctuations resting-state functional connectivity subcortical vascular mild cognitive impairment support vector machine

Journal

Frontiers in aging neuroscience
ISSN: 1663-4365
Titre abrégé: Front Aging Neurosci
Pays: Switzerland
ID NLM: 101525824

Informations de publication

Date de publication:
2024
Historique:
received: 14 11 2023
accepted: 26 08 2024
medline: 2 10 2024
pubmed: 2 10 2024
entrez: 2 10 2024
Statut: epublish

Résumé

Although depression symptoms are commonly reported in patients with subcortical vascular mild cognitive impairment (svMCI), their impact on brain functions remains largely unknown, with diagnoses mainly dependent on behavioral assessments. In this study, we analyzed resting-state fMRI data from a cohort of 34 svMCI patients, comprising 18 patients with depression symptoms (svMCI+D) and 16 patients without (svMCI-D), along with 34 normal controls (NC). The study used the fraction of the amplitude of low-frequency fluctuations (fALFF), resting-state functional connectivity, correlation analyses, and support vector machine (SVM) techniques. The fALFF of the right cerebellum (CERE.R) differed among the svMCI+D, svMCI-D, and NC groups. Specifically, the regional mean fALFF of CERE. R was lower in svMCI-D patients compared to NC but higher in svMCI+D patients compared to svMCI-D patients. Moreover, the adjusted fALFF of CERE. R showed a significant correlation with Montreal Cognitive Assessment (MOCA) scores in svMCI-D patients. The fALFF of the right orbital part of the superior frontal gyrus was significantly correlated with Hamilton Depression Scale scores in svMCI+D patients, whereas the fALFF of the right postcingulate cortex (PCC.R) showed a significant correlation with MOCA scores in svMCI-D patients. Furthermore, RSFC between PCC. R and right precuneus, as well as between CERE. R and the right lingual gyrus (LING.R), was significantly reduced in svMCI-D patients compared to NC. In regional analyses, the adjusted RSFC between PCC. R and PreCUN. R, as well as between CERE. R and LING. R, was decreased in svMCI-D patients compared to NC but increased in svMCI+D patients compared to svMCI-D. Further SVM analyses achieved good performances, with an area under the curve (AUC) of 0.82 for classifying svMCI+D, svMCI-D, and NC; 0.96 for classifying svMCI+D and svMCI-D; 0.82 for classifying svMCI+D and NC; and 0.92 for classifying svMCI-D and NC. The study revealed disruptive effects of cognitive impairment, along with both disruptive and complementary effects of depression symptoms on spontaneous brain activity in svMCI. Moreover, these findings suggest that the identified features might serve as potential biomarkers for distinguishing between svMCI+D, svMCI-D, and NC, thereby guiding clinical treatments such as transcranial magnetic stimulation for svMCI.

Sections du résumé

Background UNASSIGNED
Although depression symptoms are commonly reported in patients with subcortical vascular mild cognitive impairment (svMCI), their impact on brain functions remains largely unknown, with diagnoses mainly dependent on behavioral assessments.
Methods UNASSIGNED
In this study, we analyzed resting-state fMRI data from a cohort of 34 svMCI patients, comprising 18 patients with depression symptoms (svMCI+D) and 16 patients without (svMCI-D), along with 34 normal controls (NC). The study used the fraction of the amplitude of low-frequency fluctuations (fALFF), resting-state functional connectivity, correlation analyses, and support vector machine (SVM) techniques.
Results UNASSIGNED
The fALFF of the right cerebellum (CERE.R) differed among the svMCI+D, svMCI-D, and NC groups. Specifically, the regional mean fALFF of CERE. R was lower in svMCI-D patients compared to NC but higher in svMCI+D patients compared to svMCI-D patients. Moreover, the adjusted fALFF of CERE. R showed a significant correlation with Montreal Cognitive Assessment (MOCA) scores in svMCI-D patients. The fALFF of the right orbital part of the superior frontal gyrus was significantly correlated with Hamilton Depression Scale scores in svMCI+D patients, whereas the fALFF of the right postcingulate cortex (PCC.R) showed a significant correlation with MOCA scores in svMCI-D patients. Furthermore, RSFC between PCC. R and right precuneus, as well as between CERE. R and the right lingual gyrus (LING.R), was significantly reduced in svMCI-D patients compared to NC. In regional analyses, the adjusted RSFC between PCC. R and PreCUN. R, as well as between CERE. R and LING. R, was decreased in svMCI-D patients compared to NC but increased in svMCI+D patients compared to svMCI-D. Further SVM analyses achieved good performances, with an area under the curve (AUC) of 0.82 for classifying svMCI+D, svMCI-D, and NC; 0.96 for classifying svMCI+D and svMCI-D; 0.82 for classifying svMCI+D and NC; and 0.92 for classifying svMCI-D and NC.
Conclusion UNASSIGNED
The study revealed disruptive effects of cognitive impairment, along with both disruptive and complementary effects of depression symptoms on spontaneous brain activity in svMCI. Moreover, these findings suggest that the identified features might serve as potential biomarkers for distinguishing between svMCI+D, svMCI-D, and NC, thereby guiding clinical treatments such as transcranial magnetic stimulation for svMCI.

Identifiants

pubmed: 39355540
doi: 10.3389/fnagi.2024.1338179
pmc: PMC11442267
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1338179

Informations de copyright

Copyright © 2024 Hu, Chen, Li, Zhang, Zhang, Lu, Lian, Yu, Yang, Wang, Lyu and Xu.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Liyu Hu (L)

Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China.
Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Jianxiang Chen (J)

Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China.

Xinbei Li (X)

Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China.

Haoran Zhang (H)

Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Jinhuan Zhang (J)

Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China.

Yingqi Lu (Y)

Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Jie Lian (J)

Department of Neurology and Psychiatry, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China, 5Hospital of Traditional Chinese Medicine of Zhongshan, Shenzhen, China.

Haibo Yu (H)

Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China.

Nan Yang (N)

Hospital of Traditional Chinese Medicine of Zhongshan, Zhongshan, China.

Jianjun Wang (J)

Department of Neurology and Psychiatry, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China, 5Hospital of Traditional Chinese Medicine of Zhongshan, Shenzhen, China.

Hanqing Lyu (H)

Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China.

Jinping Xu (J)

Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Classifications MeSH