Abstract #3126
Stage-dependent differential influence of metabolic and structural networks on memory across Alzheimer’s disease continuum
Xing Qian1, Kok Pin Ng2,3,4, Kwun Kei Ng1, Fang Ji1, Pedro Rosa-Neto 5,6, Serge Gauthier 6, Nagaendran Kandiah 2,3,4, and Juan Helen Zhou 1,3,7,8
1Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore, Singapore, Singapore, 2Department of Neurology, National Neuroscience Institute, Singapore, Singapore, Singapore, 3Duke-NUS Medical School, Singapore, Singapore, Singapore, 4Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Singapore, Singapore, Singapore, 5Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada, Montreal, QC, Canada, 6Alzheimer’s Disease Research Unit, The McGill University Research Centre for Studies in Aging, McGill University, Montreal, Canada, Montreal, QC, Canada, 7Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore, Singapore, Singapore, 8Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore, Singapore, Singapore
Synopsis
While emerging evidence suggests the association between network neurodegeneration and memory varies with pathology in Alzheimer’s disease (AD), the trajectory of this relationship remains elusive. We stratified 708 participants into non-amyloid/non-tau, tau-only, and AD pathology groups and examined the associations between individual-level structural and metabolic network integrity and memory across cognitive stages (cognitively normal, mild cognitive impairment, and probable AD) in each pathology group. The associations of hippocampal and default mode networks with memory exhibited differential pathology-dependent trajectories across cognitive stages. Our findings pave the way for early interventions and stage-dependent remedies to modify disease trajectory and improve clinical outcomes.
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