Crosstalk between oxidative stress and neutrophil response in early ischemic stroke: a comprehensive transcriptome analysis

中性粒细胞胞外陷阱 基因 转录组 计算生物学 生物信息学 生物 候选基因 基因调控网络 免疫学 遗传学 基因表达 炎症
作者
Changqing Mu,Yanzhi Wang,Chen Han,Hui Song,Qian Wu,Junyi Yang,Na Guo,Yumei Ma,Chenguang Zhang,Jian Zhang,Xu Liu
出处
期刊:Frontiers in Immunology [Frontiers Media]
卷期号:14 被引量:3
标识
DOI:10.3389/fimmu.2023.1134956
摘要

Background Ischemic stroke (IS) is the second leading cause of mortality worldwide, continuing to be a serious health concern. It is well known that oxidative stress and neutrophil response play vital roles in the pathophysiology of early IS. However, the complex interactions and critical genes associated with them have not been fully understood. Methods Two datasets (GSE37587 and GSE16561) from the Gene Expression Omnibus database were extracted and integrated as the discovery dataset. Subsequent GSVA and WGCNA approaches were used to investigate IS-specific oxidative stress-related genes (ISOSGS). Then, we explored IS-specific neutrophil-associated genes (ISNGS) using CIBERSORT analysis. Next, the protein-protein interaction network was established to ascertain candidate critical genes related with oxidative stress and neutrophil response. Furthermore, these candidate genes were validated using GSE58294 dataset and our clinical samples by RT-qPCR method. Finally, functional annotation, diagnostic capability evaluation and drug-gene interactions were performed by using GSEA analysis, ROC curves and DGIDB database. Result In our analysis of discovery dataset, 155 genes were determined as ISOSGS and 559 genes were defined as ISNGS. Afterward, 9 candidate genes were identified through the intersection of ISOSGS and ISNGS, PPI network construction, and filtration by degree algorithm. Then, six real critical genes, including STAT3, MMP9, AQP9, SELL, FPR1, and IRAK3, passed the validation using the GSE58294 dataset and our clinical samples. Further functional annotation analysis indicated these critical genes were associated with neutrophil response, especially neutrophil extracellular trap. Meanwhile, they had a good diagnostic performance. Lastly, 53 potential drugs targeting these genes were predicted by DGIDB database. Conclusion We identified 6 critical genes, STAT3, FPR1, AQP9, SELL, MMP9 and IRAK3, related to oxidative stress and neutrophil response in early IS, which may provide new insights into understanding the pathophysiological mechanism of IS. We hope our analysis could help develop novel diagnostic biomarkers and therapeutic strategies for IS.
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