Gene interactions analysis of brain spatial transcriptome for Alzheimer's disease
Shengran Wang1,2,3, Jonathan Greenbaum3, Chuan Qiu3
1Reproductive Medicine Center, The Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510120, China.
Genes & Diseases
|September 16, 2024
Summary
This study reveals spatial gene interaction dynamics during Alzheimer's disease (AD) progression using spatial transcriptomics. It identifies key ligand-receptor pairs and transcription factors, offering new insights into AD etiology.
Area of Science:
- Neuroscience
- Genomics
- Molecular Biology
Background:
- Alzheimer's disease (AD) research increasingly uses spatial transcriptomics to map brain gene expression.
- Understanding gene interaction dynamics during amyloid-β (Aβ) accumulation in AD is crucial but remains limited.
Purpose of the Study:
- To investigate the spatial and temporal dynamics of gene interactions during Aβ accumulation in Alzheimer's disease.
- To identify key ligand-receptor pairs and transcription factors involved in AD pathogenesis.
Main Methods:
- Analysis of spatial transcriptomics datasets from AD mouse models and human brain data.
- Examination of ligand-receptor communication, transcription factor regulatory networks, and spot-specific networks.
- Validation using independent datasets and human single-nuclei RNA-seq data.
Main Results:
- Identified 17 ligand-receptor pairs exhibiting opposite trends during Aβ accumulation.
- Characterized specific ligand-receptor interactions within hippocampal layers across varying pathological stages.
- Discovered nerve function-related transcription factors and differentially associated genes in AD versus wild-type mice.
Conclusions:
- This study provides the first comprehensive analysis of spatio-temporal gene associations in Alzheimer's disease using spatial transcriptomics.
- Establishes a foundation for understanding AD etiology through the lens of complex, spatially dependent gene interactions.
- Highlights the potential of spatial transcriptomics for novel AD research perspectives.


