Unraveling High‐Risk Cell‐Cell Interactions in Alzheimer's Disease Using an Integrative Single Cell Analysis
Year: 2025
Type: article
Abstract: BACKGROUND: Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by cognitive decline and disruptions in neurovascular integrity, inflammation, immune signaling, and synaptic connectivity. While single-cell and bulk RNA-seq have revealed cell-type-specific changes in AD, the intercellular communication networks driving these processes remain unclear. This study introduces a novel integrative pipeline to systematically identify and prioritize robust cell-cell interactions contributing to AD pathology. METHOD: We developed an advanced computational pipeline (Figure 1) that, to our knowledge, is the first to integrate cell prioritization tools with cell-cell interactions to identify AD-associated interactions. To achieve this, we integrated RNA-seq from the Mount Sinai Brain Bank (MSBB) and single-cell RNA-seq (scRNA-seq) from Grubman, Mathys, and MIT datasets, totaling over 2.4 million cells. The pipeline combined Diagnostic Evidence GAuge of Single cells (DEGAS), a transfer learning framework for identifying AD-associated cellular states, with CellChat, which infers intercellular communication networks by mapping ligand-receptor interactions across cell types. To ensure robustness, correlation analysis validated ligand-receptor co-expression, while differential gene expression (DEG) and gene ontology (GO) analyses identified pathways linked to AD-associated states. Consistent interactions across datasets will be experimentally validated via colocalization using immunofluorescence (IF) and binding via co-immunoprecipitation (Co-IP). RESULT: Our pipeline consistently identified cell-cell interactions underlying AD pathology across datasets (Figure 2). FN1-SDC4 interactions between endothelial cells and astrocytes were associated with blood-brain barrier dysfunction (Figure 3). CADM1-CADM1 interactions, observed between oligodendrocytes and oligodendrocyte progenitor cells (Figure 3), highlighted their role in synaptic organization and connectivity deficits. The BSG-PPIA interaction, specific to endothelial cells, was linked to vascular inflammation (Figure 3). Additional interactions, JAM3-JAM3 and PTPRM-PTPRM, were consistently identified in control contexts, suggesting roles in synaptic maintenance and axonal guidance. Correlation analysis further validated ligand-receptor co-expression, while DEG and GO analyses highlighted enriched pathways, including extracellular matrix organization, cell adhesion, and synaptic signaling. These results are now being further validated via IF and Co-IP. CONCLUSION: This study highlights the novelty of our pipeline in integrating RNA-seq data to identify robust intercellular communication networks in AD. By prioritizing consistent interactions across datasets, we provide insights into AD pathology that inform experimental validation and therapeutic development.
Source: Alzheimer s & Dementia
Authors: Jiahui Liu, Jie Zhang, Kun Huang, Travis S Johnson
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,200
OpenAlex ID: W7117115102
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