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Research Paper|Volume 16, Issue 8|pp 6852—6867

ITGAM is a critical gene in ischemic stroke

Lei Hou1,2, Zhongchen Li2, Xiaoli Guo3, Jiatao Lv2, Zonglei Chong2, Yilei Xiao2, Liyong Zhang2, Zefu Li1,4
  • 1Department of Neurosurgery, Qilu Hospital of Shandong University, Jinan 250012, Shandong Province, P.R. China
  • 2Department of Neurosurgery, Liaocheng People’s Hospital, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Liaocheng 252000, Shandong Province, P.R. China
  • 3Department of Pediatrics, Liaocheng People’s Hospital, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Liaocheng 252000, Shandong Province, P.R. China
  • 4Department of Neurosurgery, Binzhou Medical University Hospital, Binzhou Medical University, Binzhou 256603, Shandong Province, P.R. China
* Equal contribution
Received: November 22, 2023Accepted: March 4, 2024Published: April 17, 2024
https://doi.org/10.18632/aging.205729

Copyright: © 2024 Hou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Globally, ischemic stroke (IS) is ranked as the second most prevailing cause of mortality and is considered lethal to human health. This study aimed to identify genes and pathways involved in the onset and progression of IS.

Methods: GSE16561 and GSE22255 were downloaded from the Gene Expression Omnibus (GEO) database, merged, and subjected to batch effect removal using the ComBat method. The limma package was employed to identify the differentially expressed genes (DEGs), followed by enrichment analysis and protein-protein interaction (PPI) network construction. Afterward, the cytoHubba plugin was utilized to screen the hub genes. Finally, a ROC curve was generated to investigate the diagnostic value of hub genes. Validation analysis through a series of experiments including qPCR, Western blotting, TUNEL, and flow cytometry was performed.

Results: The analysis incorporated 59 IS samples and 44 control samples, revealing 226 DEGs, of which 152 were up-regulated and 74 were down-regulated. These DEGs were revealed to be linked with the inflammatory and immune responses through enrichment analyses. Overall, the ROC analysis revealed the remarkable diagnostic potential of ITGAM and MMP9 for IS. Quantitative assessment of these genes showed significant overexpression in IS patients. ITGAM modulation influenced the secretion of critical inflammatory cytokines, such as IL-1β, IL-6, and TNF-α, and had a distinct impact on neuronal apoptosis.

Conclusions: The inflammation and immune response were identified as potential pathological mechanisms of IS by bioinformatics and experiments. In addition, ITGAM may be considered a potential therapeutic target for IS.