Macroscale Gradient Dysfunction in Alzheimer's Disease: Patterns With Cognition Terms and Gene Expression Profiles.

Kun Zhao, Yongbin Wei, Dawei Wang, Jie Lu, Yuqi Chen, Yong Liu, Bo Zhou, Xi Zhang, Ying Han, Pan Wang, Fan Yang, Zhuangzhuang Li, Pindong Chen, Hongxiang Yao

Journal: Human brain mapping 2024;45(15):e70046

PMID: 39449114

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Abstract

Macroscale functional gradient techniques provide a continuous coordinate system that extends from unimodal regions to transmodal higher-order networks. However, the alterations of these functional gradients in AD and their correlations with cognitive terms and gene expression profiles remain to be established. In the present study, we directly studied the functional gradients with functional MRI data from seven scanners. We adopted data-driven meta-analytic techniques to unveil AD-associated changes in the functional gradients. The principal primary-to-transmodal gradient was suppressed in AD. Compared to NCs, AD patients exhibited global connectome gradient alterations, including reduced gradient range and gradient variation, increased gradient scores in the somatomotor, ventral attention, and frontoparietal regions, and decreased in the default mode network. More importantly, the Gene Ontology terms of biological processes were significantly enriched in the potassium ion transport and protein-containing complex remodeling. Our compelling evidence provides a new perspective in understanding the connectome alterations in AD.

Address: Department of Radiology, Qilu Hospital of Shandong University; Qilu Medical Imaging Institute of Shandong University, Jinan, China.; Research Institute of Shandong University, Magnetic Field-Free Medicine & Functional Imaging, Jinan, China.; Shandong Key Laboratory: Magnetic Field-Free Medicine & Functional Imaging (MF), Jinan, China.; Queen Mary School Hainan, Beijing University of Posts and Telecommunications, Hainan, China.; Queen Mary School Hainan, Beijing University of Posts and Telecommunications, Hainan, China.; School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.; School of Artificial Intelligence, University of Chinese Academy of Sciences, & Institute of Automation, Chinese Academy of Sciences, Beijing, China.; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China.; Department of Radiology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.; Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.; Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China.; Affiliated Hospital, Beijing University of Posts and Telecommunications, Beijing, China.; Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.; School of Biomedical Engineering, Hainan University, Haikou, China.; Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.; Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China.

DOI: 10.1002/hbm.70046

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MeSH Terms: Humans, Alzheimer Disease, Brain, Connectome, Default Mode Network, Magnetic Resonance Imaging, Nerve Net, Transcriptome