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Neuropsychiatric symptoms associated multimodal brain networks in Alzheimer's disease |
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| Authors: | Kaicheng Li Qingze Zeng Xiao Luo Shile Qi Xiaopei Xu Zening Fu Luwei Hong Xiaocao Liu Zheyu Li Yanv Fu Yanxing Chen Zhirong Liu Vince D Calhoun Peiyu Huang Minming Zhang |
| Institution: | 1. Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA;2. Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China;3. Department of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China;4. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA;5. Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China;6. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA Department of Psychology, Computer Science, Neuroscience Institute, and Physics, Georgia State University, Atlanta, Georgia, USA Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA |
| Abstract: | Concomitant neuropsychiatric symptoms (NPS) are associated with accelerated Alzheimer's disease (AD) progression. Identifying multimodal brain imaging patterns associated with NPS may help understand pathophysiology correlates AD. Based on the AD continuum, a supervised learning strategy was used to guide four-way multimodal neuroimaging fusion (Amyloid, Tau, gray matter volume, brain function) by using NPS total score as the reference. Loadings of the identified multimodal patterns were compared across the AD continuum. Then, regression analyses were performed to investigate its predictability of longitudinal cognition performance. Furthermore, the fusion analysis was repeated in the four NPS subsyndromes. Here, an NPS-associated pathological–structural–functional covaried pattern was observed in the frontal-subcortical limbic circuit, occipital, and sensor-motor region. Loading of this multimodal pattern showed a progressive increase with the development of AD. The pattern significantly correlates with multiple cognitive domains and could also predict longitudinal cognitive decline. Notably, repeated fusion analysis using subsyndromes as references identified similar patterns with some unique variations associated with different syndromes. Conclusively, NPS was associated with a multimodal imaging pattern involving complex neuropathologies, which could effectively predict longitudinal cognitive decline. These results highlight the possible neural substrate of NPS in AD, which may provide guidance for clinical management. |
| Keywords: | Alzheimer's disease cognitive decline frontal-subcortical limbic circuit neuropsychiatric symptoms supervised multimodal fusion |