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Monday, July 20 • 7:00pm - 8:00pm
P73: Effects of transneuronal spreading in the logistic diffusion model of Aβ protein with longitudinal PET scans

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Byeong Chang Jeong, Myungwon Choi, Daegyeom Kim, Xue Chen, Marcus Kaiser, Cheol E Han

Alzheimer’s disease (AD) is a neuro-degenerative disease which causes severe loss of cognitive functions and deteriorates the quality of daily life of elders. One hypothesis of AD development and progression is deposition of amyloid-beta protein which is known to cause neuronal cell death in the gray matter and to degrade the cognitive function of the affected regions. Recently, it is reported that the toxic protein can move through connectivity between neurons, which is called transneuronal projection, besides the local diffusion through the non-neuronal tissues. In this study, we investigated the effects of the transneuronal projection on the amyloid deposition pattern over the brain through simulation of a mathematical model based on the actual neuroimage data. The model consists of two components: transneuronal spreading, and local spreading. The transneuronal spreading captures propagation of the toxic protein in the white matter while the local spreading captures its local diffusion through the gray matter. Each component has its own parameter to balance between components. We estimated all parameters in the model through the Bayesian inference method that best describe the longitudinal data from Alzheimer’s disease neuroimaging initiative (ADNI) dataset, by comparing the results of simulation data with the actual dataset. We modelled our brain as a high-resolution graph whose nodes are a small volume of the cerebral cortices, and whose edges are the structure of adjacency between them, delineating spreading pathways. We transformed the cerebral cortices into a triangular lattice of prism-like volumes from structural magnetic resonance (MR) images. From the topology of the lattice we extracted local adjacency between the nodes. On the contrary, for the long- range connection through the neuronal fibers, we obtained the connectivity between the nodes from the diffusion-weighted MR imaging (DWI). Each node has the level of the amyloid deposition, obtained through the 18F-Florbetapir positron emission tomography (PET) images with partial volume effect correction. This high-resolution graph model can enable to simulate more granularly and accurately. To investigate the effect of transneuronal spreading, we compared results of two conditions: simulation 1) with only the local spreading, and 2) with both the local and transneuronal spreading. Both models showed the spread of the amyloid from the regions where the initial protein accumulation is high, also known as epicenters. The result of the former condition may explain gradual spread from the epicenters to their nearby regions while it could not explain remote spread from the epicenters to their distant regions. On the other hand, the latter results illustrated not only local spread, but also remote spread. Thus, the model with both local and transneuronal spreading components is more feasible to explain the deposition of amyloid-beta in AD. The purpose of this study is to investigate the effect of transneuronal spread of the amyloid beta over AD’s progression using the actual neuroimage data. Our results support the previous research of transmission of amyloid through the neuronal pathways.

**Acknowledgement:** This work was supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) that was funded by the Ministry of Health & Welfare, Republic of Korea (HI19C0645), and Medical Research Council, UK (MR/T004347/1).


Byeong Chang Jeong

Electronic information engineering, Korea University

Monday July 20, 2020 7:00pm - 8:00pm CEST
Slot 06