A Research of Voxel-Based Amygdala Genetic Network Based on Improved Label Propagation Algorithm
- Resource Type
- Conference
- Authors
- Wang, Lingfei; Li, Yuxin; Li, Jin; Liu, Wenjie
- Source
- 2023 IEEE International Conference on Mechatronics and Automation (ICMA) Mechatronics and Automation (ICMA), 2023 IEEE International Conference on. :67-72 Aug, 2023
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Knowledge engineering
Brain
Correlation
Mechatronics
Automation
Databases
Imaging
Alzheimer Disease
Amygdala
Voxel-Based Genetic Network
Label Propagation Algorithm
- Language
- ISSN
- 2152-744X
Currently, the amygdala is often treated as a single entity in research, which may overlook valuable information from each amygdala subregion. There have been few studies examining the amygdala at the voxel level. In this paper, we propose an amygdala voxel-based genetic correlation network to explore the relationship between the amygdala subregions and Alzheimer's disease (AD). We conducted GWAS analysis using data from the ADNI Database and combined Single nucleotide polymorphism (SNP) results highly correlated with AD with amygdala voxel-based imaging data to construct a genetic correlation network for the left and right amygdala. We used an improved label propagation algorithm to conduct a more thorough analysis of the network and explore the potential relationship between AD and the amygdala subregions at the voxel level. We verified the pathways found by this method using KEGG and GO analysis and found that they have a significant impact on the pathogenesis of AD.