Characterizing the propagation pattern of neurodegeneration in alzheimer's disease by longitudinal network analysis.

CHARACTERIZING THE PROPAGATION PATTERN OF NEURODEGENERATION IN ALZHEIMER'S DISEASE BY LONGITUDINAL NETWORK ANALYSIS. Proc IEEE Int Symp Biomed Imaging. 2020 Apr;2020:292-295 Authors: Wang Y, Yang D, Li Q, Kaufer D, Styner M, Wu G Abstract Converging evidence shows that Alzheimer's disease (AD) is a neurodegenerative disease that represents a disconnection syndrome, whereby a large-scale brain network is progressively disrupted by one or more neuropathological processes. However, the mechanism by which pathological entities spread across a brain network is largely unknown. Since pathological burden may propagate trans-neuronally, we propose to characterize the propagation pattern of neuropathological events spreading across relevant brain networks that are regulated by the organization of the network. Specifically, we present a novel mixed-effect model to quantify the relationship between longitudinal network alterations and neuropathological events observed at specific brain regions, whereby the topological distance to hub nodes, high-risk AD genetics, and environmental factors (such as education) are considered as predictor variables. Similar to many cross-section studies, we find that AD-related neuropathology preferentially affects hub nodes. Furthermore, our statistical model provides strong evidence that abnormal neuropathological burden diffuses from hub nodes to non-hub nodes in a prion-like manner, whereby the propagation pat...
Source: Proceedings - International Symposium on Biomedical Imaging - Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research