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Updated: Jun 16, 2026
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Isolation and Flow Cytometric Assessment of Neuroimmune Interactions in a Mini-Stroke Murine Model
Published on: June 20, 2025
Combining Machine Learning, Single-Cell Sequencing Data, and Mendelian Randomization Studies to Explore the
Si Wang1, Yan Xu1, Meilei Wang2
1Department of Cardiology, Xishan People's Hospital of Wuxi City, Wuxi, Jiangsu, China.
International Journal of Genomics
|June 15, 2026
Summary
This study identifies key inflammatory genes linked to ischemic stroke (IS) progression. Findings highlight inflammation
Area of Science:
- Neuroscience
- Immunology
- Genetics
Background:
- Ischemic stroke (IS) is a severe neurological disorder where inflammation plays a critical role.
- Understanding the genetic basis of inflammation in IS is crucial for disease management.
Purpose of the Study:
- To investigate gene expression profiles related to inflammation in IS patients.
- To identify key inflammatory pathway-related genes (IPRGs) associated with IS.
- To explore the association between these genes and IS progression.
Main Methods:
- Analysis of public gene expression datasets comparing IS patients and healthy controls.
- Differential expression analysis and machine learning to identify IPRGs.
- Consensus clustering, single-cell sequencing, and Mendelian randomization studies (including tumor necrosis factor - TNF).
Main Results:
- Four genes (HLA-DRA, IL1A, IL15, TNF) were upregulated in IS patients and correlated with inflammation.
- A diagnostic nomogram model was developed and validated.
- Single-cell sequencing revealed distinct inflammatory roles for macrophages and monocytes; TNF may negatively regulate IS risk.
Conclusions:
- Identified key IPRGs and gene expression profiles in IS patients.
- Provided insights into IS pathogenesis and the role of inflammation.
- Highlighted potential therapeutic targets and predictive tools for IS.