Exosome-related genes influence the progression of stroke through neuroinflammatory responses

Ischemic stroke (IS) ranks among the top causes of mortality and disability globally. Exosomes exert a crucial effect on maintaining a complex regulatory balance with neuroinflammation in IS. Hence, this research aimed to elucidate the roles of exosome-related genes IS. We integrated data from five IS-related datasets from the Gene Expression Omnibus (GEO) database and exosome-related genes from ExoCarta. The least absolute shrinkage and selection operator regression and random forest models were performed to detect feature genes. Search Tool for the Retrieval of Interacting Genes and Cytoscape were employed to recognize the hub genes. Enrichment analyses were conducted to examine biological processes. CIBERSORT and MCPcounter were applied to assess immune infiltration, and Principal Component Analysis was utilized to explore the associations of feature genes and hub genes with immune cells. After identified different cell types, we analyzed differentiation, developmental trajectory, and interactions of the cell populations. Middle cerebral artery occlusion models were conducted on mice, followed by quantitative polymerase chain reaction to assess the expression levels of each hub gene. We identified 13 feature genes and 10 hub genes. Through qPCR, LGALS3, CD36, TLR2, ICAM1, and CD14 were significantly upregulated after Middle Cerebral Artery Occlusion surgery. Hub genes were significantly involved in inflammatory responses, as well as chemokine signaling and JAK-STAT signaling. Immuno-infiltration analysis revealed significant differences in immune cell populations between IS and controls. Additionally, neutrophils and monocytes/macrophages were positively correlated with CD14 and LGALS3, respectively. Single-cell analysis revealed 19 cell subpopulations with detailed pseudo-time trajectory predictions, highlighting the developmental importance of MG2 microglial cells. In conclusion, our results illuminate exosomal genes, including LGALS3 and CD14, participate in the progression of IS through neuroinflammation, as well as highlight potential therapeutics to mitigate IS injury.

Authors

Institutions

Publication Details

Journal
Frontiers in Neurology
Published
2025-05-19
DOI
https://doi.org/10.3389/fneur.2025.1517588
Citations
1
Primary Topic
Neuroinflammation and Neurodegeneration Mechanisms
Type
article
Field-Weighted Citation Impact
0.84

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exosome-related genes influence the progression of stroke through neuroinflammatory responses

Shiguang Zhao, Boyan Zhao, Ruotian Zhang, Jianing Wu et al.
1 citations
Frontiers in Neurology
Neuroinflammation and Neurodegeneration Mechanisms
0.84
article

Exosome-related genes influence the progression of stroke through neuroinflammatory responses

Shiguang Zhao, Boyan Zhao, Ruotian Zhang, Jianing Wu, Rong Xuan, Mingyang Han, Fei Peng, Cheng Zhang, Jin Jin, Xingli Dong, Shiya Liu, Xin Chen
article en
1 citations

Abstract

Ischemic stroke (IS) ranks among the top causes of mortality and disability globally. Exosomes exert a crucial effect on maintaining a complex regulatory balance with neuroinflammation in IS. Hence, this research aimed to elucidate the roles of exosome-related genes IS. We integrated data from five IS-related datasets from the Gene Expression Omnibus (GEO) database and exosome-related genes from ExoCarta. The least absolute shrinkage and selection operator regression and random forest models were performed to detect feature genes. Search Tool for the Retrieval of Interacting Genes and Cytoscape were employed to recognize the hub genes. Enrichment analyses were conducted to examine biological processes. CIBERSORT and MCPcounter were applied to assess immune infiltration, and Principal Component Analysis was utilized to explore the associations of feature genes and hub genes with immune cells. After identified different cell types, we analyzed differentiation, developmental trajectory, and interactions of the cell populations. Middle cerebral artery occlusion models were conducted on mice, followed by quantitative polymerase chain reaction to assess the expression levels of each hub gene. We identified 13 feature genes and 10 hub genes. Through qPCR, LGALS3, CD36, TLR2, ICAM1, and CD14 were significantly upregulated after Middle Cerebral Artery Occlusion surgery. Hub genes were significantly involved in inflammatory responses, as well as chemokine signaling and JAK-STAT signaling. Immuno-infiltration analysis revealed significant differences in immune cell populations between IS and controls. Additionally, neutrophils and monocytes/macrophages were positively correlated with CD14 and LGALS3, respectively. Single-cell analysis revealed 19 cell subpopulations with detailed pseudo-time trajectory predictions, highlighting the developmental importance of MG2 microglial cells. In conclusion, our results illuminate exosomal genes, including LGALS3 and CD14, participate in the progression of IS through neuroinflammation, as well as highlight potential therapeutics to mitigate IS injury.

Frontiers in NeurologyVol. 16
Harbin Medical University (CN), Shenzhen University (CN), University of Toronto (CA), Scarborough Health Network (CA), Second Affiliated Hospital of Guangzhou Medical University (CN), Longgang Central Hospital (CN), First Affiliated Hospital of Harbin Medical University (CN), Guangzhou Medical University (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 26%
Neuroinflammation and Neurodegeneration Mechanisms
0.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.