Altered global signal topography in Alzheimer's diseaseResearch in context
Pindong Chen,
Kun Zhao,
Han Zhang,
Yongbin Wei,
Pan Wang,
Dawei Wang,
Chengyuan Song,
Hongwei Yang,
Zengqiang Zhang,
Hongxiang Yao,
Yida Qu,
Xiaopeng Kang,
Kai Du,
Lingzhong Fan,
Tong Han,
Chunshui Yu,
Bo Zhou,
Tianzi Jiang,
Yuying Zhou,
Jie Lu,
Ying Han,
Xi Zhang,
Bing Liu,
Yong Liu
Affiliations
Pindong Chen
Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
Kun Zhao
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China; Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing, China
Han Zhang
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
Yongbin Wei
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
Pan Wang
Department of Neurology, Tianjin Huanhu Hospital Tianjin University, Tianjin, China
Dawei Wang
Department of Radiology, Qilu Hospital of Shandong University, Ji'nan, China
Chengyuan Song
Department of Neurology, Qilu Hospital of Shandong University, Ji'nan, China
Hongwei Yang
Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
Zengqiang Zhang
Branch of Chinese PLA General Hospital, Sanya, China
Hongxiang Yao
Department of Radiology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
Yida Qu
Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
Xiaopeng Kang
Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
Kai Du
Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
Lingzhong Fan
Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Tong Han
Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
Chunshui Yu
Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
Bo Zhou
Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
Tianzi Jiang
Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
Yuying Zhou
Department of Neurology, Tianjin Huanhu Hospital Tianjin University, Tianjin, China
Jie Lu
Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
Ying Han
Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China; Beijing Institute of Geriatrics, Beijing, China; National Clinical Research Center for Geriatric Disorders, Beijing, China
Xi Zhang
Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
Bing Liu
State Key Laboratory of Cognition Neuroscience & Learning, Beijing Normal University, Beijing, China
Yong Liu
Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China; Corresponding author. School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
Summary: Background: Alzheimer's disease (AD) is a neurodegenerative disease associated with widespread disruptions in intrinsic local specialization and global integration in the functional system of the brain. These changes in integration may further disrupt the global signal (GS) distribution, which might represent the local relative contribution to global activity in functional magnetic resonance imaging (fMRI). Methods: fMRI scans from a discovery dataset (n = 809) and a validated dataset (n = 542) were used in the analysis. We investigated the alteration of GS topography using the GS correlation (GSCORR) in patients with mild cognitive impairment (MCI) and AD. The association between GS alterations and functional network properties was also investigated based on network theory. The underlying mechanism of GSCORR alterations was elucidated using imaging-transcriptomics. Findings: Significantly increased GS topography in the frontal lobe and decreased GS topography in the hippocampus, cingulate gyrus, caudate, and middle temporal gyrus were observed in patients with AD (Padj < 0.05). Notably, topographical GS changes in these regions correlated with cognitive ability (P < 0.05). The changes in GS topography also correlated with the changes in functional network segregation (ρ = 0.5). Moreover, the genes identified based on GS topographical changes were enriched in pathways associated with AD and neurodegenerative diseases. Interpretation: Our findings revealed significant changes in GS topography and its molecular basis, confirming the informative role of GS in AD and further contributing to the understanding of the relationship between global and local neuronal activities in patients with AD. Funding: Beijing Natural Science Funds for Distinguished Young Scholars, China; Fundamental Research Funds for the Central Universities, China; National Natural Science Foundation, China.
