Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease

Zhenrong Fu; Mingyan Zhao; Yirong He; Xuetong Wang; Jiadong Lu; Shaoxian Li; Xin Li; Guixia Kang; Ying Han; Shuyu Li

doi:10.3389/fnagi.2021.686598

Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease

Front Aging Neurosci. 2021 Aug 16:13:686598. doi: 10.3389/fnagi.2021.686598. eCollection 2021.

Authors

Zhenrong Fu¹, Mingyan Zhao^{2

3}, Yirong He¹, Xuetong Wang¹, Jiadong Lu¹, Shaoxian Li¹, Xin Li^{4

5}, Guixia Kang⁶, Ying Han^{3

7

8

9}, Shuyu Li¹

Affiliations

¹ School of Biological Science and Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China.
² Department of Neurology, Tangshan Gongren Hospital, Tangshan, China.
³ Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.
⁴ School of Electrical Engineering, Yanshan University, Qinhuangdao, China.
⁵ Measurement Technology and Instrumentation Key Laboratory of Hebei Province, Qinhuangdao, China.
⁶ School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China.
⁷ Biomedical Engineering Institute, Hainan University, Haikou, China.
⁸ Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
⁹ National Clinical Research Center for Geriatric Disorders, Beijing, China.

Abstract

Alzheimer's disease (AD) has a long preclinical stage that can last for decades prior to progressing toward amnestic mild cognitive impairment (aMCI) and/or dementia. Subjective cognitive decline (SCD) is characterized by self-experienced memory decline without any evidence of objective cognitive decline and is regarded as the later stage of preclinical AD. It has been reported that the changes in structural covariance patterns are affected by AD pathology in the patients with AD and aMCI within the specific large-scale brain networks. However, the changes in structural covariance patterns including normal control (NC), SCD, aMCI, and AD are still poorly understood. In this study, we recruited 42 NCs, 35 individuals with SCD, 43 patients with aMCI, and 41 patients with AD. Gray matter (GM) volumes were extracted from 10 readily identifiable regions of interest involved in high-order cognitive function and AD-related dysfunctional structures. The volume values were used to predict the regional densities in the whole brain by using voxel-based statistical and multiple linear regression models. Decreased structural covariance and weakened connectivity strength were observed in individuals with SCD compared with NCs. Structural covariance networks (SCNs) seeding from the default mode network (DMN), salience network, subfields of the hippocampus, and cholinergic basal forebrain showed increased structural covariance at the early stage of AD (referring to aMCI) and decreased structural covariance at the dementia stage (referring to AD). Moreover, the SCN seeding from the executive control network (ECN) showed a linearly increased extent of the structural covariance during the early and dementia stages. The results suggest that changes in structural covariance patterns as the order of NC-SCD-aMCI-AD are divergent and dynamic, and support the structural disconnection hypothesis in individuals with SCD.

Keywords: Alzheimer’s disease; amnestic mild cognitive impairment; default mode network; structural MRI; structural covariance network; subjective cognitive decline.