Is Immune Suppression Involved in the Ischemic Stroke? A Study Based on Computational Biology.

Xin Wang,Zhiqiang Su,Hu Li,Kun Wang,Qian Wang,Yuzhen Xu,Qingbin Ni

doi:10.3389/fnagi.2022.830494

Abstract

ObjectiveTo identify the genetic mechanisms of immunosuppression-related genes implicated in ischemic stroke.BackgroundA better understanding of immune-related genes (IGs) involved in the pathophysiology of ischemic stroke may help identify drug targets beneficial for immunomodulatory approaches and reducing stroke-induced immunosuppression complications.MethodsTwo datasets related to ischemic stroke were downloaded from the GEO database. Immunosuppression-associated genes were obtained from three databases (i.e., DisGeNET, HisgAtlas, and Drugbank). The CIBERSORT algorithm was used to calculate the mean proportions of 22 immune-infiltrating cells in the stroke samples. Differential gene expression analysis was performed to identify the differentially expressed genes (DEGs) involved in stroke. Immunosuppression-related crosstalk genes were identified as the overlapping genes between ischemic stroke-DEGs and IGs. Feature selection was performed using the Boruta algorithm and a classifier model was constructed to evaluate the prediction accuracy of the obtained immunosuppression-related crosstalk genes. Functional enrichment analysis, gene-transcriptional factor and gene-drug interaction networks were constructed.ResultsTwenty two immune cell subsets were identified in stroke, where resting CD4 T memory cells were significantly downregulated while M0 macrophages were significantly upregulated. By overlapping the 54 crosstalk genes obtained by feature selection with ischemic stroke-related genes obtained from the DisGenet database, 17 potentially most valuable immunosuppression-related crosstalk genes were obtained, ARG1, CD36, FCN1, GRN, IL7R, JAK2, MAFB, MMP9, PTEN, STAT3, STAT5A, THBS1, TLR2, TLR4, TLR7, TNFSF10, and VASP. Regulatory transcriptional factors targeting key immunosuppression-related crosstalk genes in stroke included STAT3, SPI1, CEPBD, SP1, TP53, NFIL3, STAT1, HIF1A, and JUN. In addition, signaling pathways enriched by the crosstalk genes, including PD-L1 expression and PD-1 checkpoint pathway, NF-kappa B signaling, IL-17 signaling, TNF signaling, and NOD-like receptor signaling, were also identified.ConclusionPutative crosstalk genes that link immunosuppression and ischemic stroke were identified using bioinformatics analysis and machine learning approaches. These may be regarded as potential therapeutic targets for ischemic stroke.

Highlights

Ischemic stroke is the second most common cause of mortality worldwide and imposes a tremendous healthcare burden owing to significant disability
The derived cellular component subsets in the samples are displayed as heatmaps and volcano plots (Figure 1) and significant differences were noted in the immune cell components between the stroke and normal samples
Two subtypes of immune cells, resting CD4 memory T cells and M0 Macrophages were significantly different between the cases and controls

Summary

Introduction

Ischemic stroke is the second most common cause of mortality worldwide and imposes a tremendous healthcare burden owing to significant disability. Stroke is frequently followed by post-stroke infection, which results from systemic immunosuppression that occurs after stroke and is associated with a worse prognosis (Shi et al, 2018) This occurs as a bi-directional brain-immune system interaction, when catecholamines and glucocorticoids are produced by an activated HPA-axis in attempts to limit local inflammation, which leads to natural killer T-cell (NKT) and T-cell activation, alongside reactive oxygen species production (Shim and Wong, 2016). Immunomodulatory approaches that target multiple elements of the immune system are recognized as the most promising directions in stroke and its complication management (Fu et al, 2015) Several established drugs such as Azithromycin and Metformin have shown neuroprotective action in stroke via modulation of innate immune responses (Amantea and Giacinto, 2016) and the repurposing of such drugs may offer therapeutic potential, underscoring the importance of uncovering immunosuppression mechanisms in stroke. A better understanding of immune-related genes (IGs) involved in the pathophysiology of ischemic stroke may help identify drug targets beneficial for immunomodulatory approaches and reducing stroke-induced immunosuppression complications

Methods

Results

Conclusion