Jiu Chen1, Hao Shu1, Zan Wang1, Yafeng Zhan2, Duan Liu1, Wenxiang Liao1, Lin Xu3, Yong Liu4, Zhijun Zhang5. 1. Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China. 2. Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China. 3. Key Laboratory of Animal Models and Human Disease Mechanisms, Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; Graduate School of Chinese Academy of Sciences, Beijing, China. 4. Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China. Electronic address: yliu@nlpr.ia.ac.cn. 5. Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China; Department of Psychology, Xinxiang Medical University, Xinxiang, Henan, China. Electronic address: janemengzhang@vip.163.com.
Abstract
INTRODUCTION: Both remitted late-life depression (rLLD) and amnesiac mild cognitive impairment (aMCI) alter brain functions in specific regions of the brain. They are also disconnection syndromes that are associated with a high risk of developing Alzheimer's disease (AD). OBJECTIVES: Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) was performed to define the shared and distinct aberrant patterns in intranetwork and internetwork connectivity between rLLD and aMCI and to determine how knowledge of these differences might contribute to our essential understanding of the altered sequences involved in functional systems both inside and outside of resting-state networks. METHODS: We used rs-fcMRI to investigate in five functionally well-defined brain networks in two large cohorts of subjects at high risk for AD (55 rLLD and 87 aMCI) and 114 healthy controls (HC). RESULTS: A reduced degree of functional connectivity was observed in the bilateral inferior temporal cortex and supplemental motor area, and reduced correlations were observed within the sensory-motor network (SMN) and in the default mode network (DMN)-control network (CON) pair in the rLLD group than the HC group. The aMCI group showed only focal functional changes in regions of interest pairs, a trend toward increased correlations within the salience network and SMN, and a trend toward a reduced correlation in the DMN-CON pair. Furthermore, the rLLD group exhibited more severely altered functional connectivity than the aMCI group. Interestingly, these altered connectivities were associated with specific multi-domain cognitive and behavioral functions in both rLLD and aMCI. The degree of functional connectivity in the right primary auditory areas was negatively correlated with Hamilton Depression Scale scores in rLLD. Notably, altered connectivity between the right middle temporal cortex and the posterior cerebellum was negatively correlated with Mattis Dementia Rating Scale scores in both rLLD and aMCI. CONCLUSIONS: These results demonstrate that rLLD and aMCI may share convergent and divergent aberrant intranetwork and internetwork connectivity patterns as a potential continuous spectrum of the same disease. They further suggest that dysfunctions in the right specific temporal-cerebellum neural circuit may contribute to the similarities observed in rLLD and aMCI conversion to AD.
INTRODUCTION: Both remitted late-life depression (rLLD) and amnesiac mild cognitive impairment (aMCI) alter brain functions in specific regions of the brain. They are also disconnection syndromes that are associated with a high risk of developing Alzheimer's disease (AD). OBJECTIVES: Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) was performed to define the shared and distinct aberrant patterns in intranetwork and internetwork connectivity between rLLD and aMCI and to determine how knowledge of these differences might contribute to our essential understanding of the altered sequences involved in functional systems both inside and outside of resting-state networks. METHODS: We used rs-fcMRI to investigate in five functionally well-defined brain networks in two large cohorts of subjects at high risk for AD (55 rLLD and 87 aMCI) and 114 healthy controls (HC). RESULTS: A reduced degree of functional connectivity was observed in the bilateral inferior temporal cortex and supplemental motor area, and reduced correlations were observed within the sensory-motor network (SMN) and in the default mode network (DMN)-control network (CON) pair in the rLLD group than the HC group. The aMCI group showed only focal functional changes in regions of interest pairs, a trend toward increased correlations within the salience network and SMN, and a trend toward a reduced correlation in the DMN-CON pair. Furthermore, the rLLD group exhibited more severely altered functional connectivity than the aMCI group. Interestingly, these altered connectivities were associated with specific multi-domain cognitive and behavioral functions in both rLLD and aMCI. The degree of functional connectivity in the right primary auditory areas was negatively correlated with Hamilton Depression Scale scores in rLLD. Notably, altered connectivity between the right middle temporal cortex and the posterior cerebellum was negatively correlated with Mattis Dementia Rating Scale scores in both rLLD and aMCI. CONCLUSIONS: These results demonstrate that rLLD and aMCI may share convergent and divergent aberrant intranetwork and internetwork connectivity patterns as a potential continuous spectrum of the same disease. They further suggest that dysfunctions in the right specific temporal-cerebellum neural circuit may contribute to the similarities observed in rLLD and aMCI conversion to AD.
Authors: Benoit H Mulsant; Aristotle N Voineskos; Neda Rashidi-Ranjbar; Tarek K Rajji; Colin Hawco; Sanjeev Kumar; Nathan Herrmann; Linda Mah; Alastair J Flint; Corinne E Fischer; Meryl A Butters; Bruce G Pollock; Erin W Dickie; Christopher R Bowie; Matan Soffer Journal: Neuropsychopharmacology Date: 2022-04-11 Impact factor: 7.853