Uncovering the connectomic and functional components of neurodegenerative disease spread using dynamic network modeling
Abstract/Contents
- Abstract
- An emerging view regarding neurodegenerative diseases is that discreet seeding of misfolded proteins leads to widespread pathology. However, the mechanisms by which misfolded proteins seed distinct brain regions and cause differential whole-brain pathology remain elusive. Using whole-brain tissue clearing and high-resolution imaging, I longitudinally mapped pathology in an α-synuclein preformed fibril injection model of Parkinson's disease. Cleared brains at different time points of disease progression were quantitatively segmented and registered to a standardized atlas, revealing distinct phases of spreading and decline. I then developed a computational network model with parameters that represent α-synuclein pathological spreading, aggregation, decay, and gene expression pattern to this longitudinal dataset. This model generalized to predicting α-synuclein spreading patterns from several distinct brain regions and could also estimate their origins. Altogether, these results empower a more mechanistic understanding and accurate prediction of neurodegenerative disease progression.
Description
Type of resource | text |
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Form | electronic resource; remote; computer; online resource |
Extent | 1 online resource. |
Place | California |
Place | [Stanford, California] |
Publisher | [Stanford University] |
Copyright date | 2023; ©2023 |
Publication date | 2023; 2023 |
Issuance | monographic |
Language | English |
Creators/Contributors
Author | Dadgar-Kiani, Ehsan |
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Degree supervisor | Lee, Jin Hyung |
Thesis advisor | Lee, Jin Hyung |
Thesis advisor | Ding, Jun (Jun B.) |
Thesis advisor | Lin, Michael Z |
Degree committee member | Ding, Jun (Jun B.) |
Degree committee member | Lin, Michael Z |
Associated with | Stanford University, Department of Bioengineering |
Subjects
Genre | Theses |
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Genre | Text |
Bibliographic information
Statement of responsibility | Ehsan Dadgar-Kiani. |
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Note | Submitted to the Department of Bioengineering. |
Thesis | Thesis Ph.D. Stanford University 2023. |
Location | https://purl.stanford.edu/nm719hy6952 |
Access conditions
- Copyright
- © 2023 by Ehsan Dadgar-Kiani
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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