AUTHOR=Jia Kejuan , Xia Wenbo , Su Qian , Yang Shiqi , Zhang Yanli , Ni Xunran , Su Zhiqiang , Meng Delong TITLE=RNA methylation pattern and immune microenvironment characteristics mediated by m6A regulator in ischemic stroke JOURNAL=Frontiers in Genetics VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1148510 DOI=10.3389/fgene.2023.1148510 ISSN=1664-8021 ABSTRACT=

Background: Ischemic stroke (IS) is a highly heterogeneous disease. Recent studies have shown that epigenetic variables affect the immune response. However, only a few studies have examined the relationship between IS and m6A immunoregulation. Therefore, we aim to explore the methylation of RNA mediated by m6A regulatory factor and the immune microenvironment characteristics of IS.

Methods: Differentially expressed m6A regulators were detected in IS microarray datasets GSE22255 and GSE58294. We used a series of machine learning algorithms to identify key IS-related m6A regulators and validated them on blood samples of IS patients, oxygen-glucose deprivation/reoxygenation (OGD/R) microglia and GSE198710 independent data sets. Different m6A modification modes were determined and the patients were classified. In addition, we systematically associate these modification patterns with the characteristics of immune microenvironment, including infiltrating immune cells, immune function genes and immune response genes. Then we developed a model of m6A score to quantify the m6A modification in IS samples.

Results: Through the analysis of the differences between the control group and IS patients, METTL16, LRPPRC, and RBM15 showed strong diagnostic significance in three independent data sets. In addition, qRT-PCR and Western blotting also confirmed that the expression of METTL16 and LRPPRC was downregulated and the expression of RBM15 was upregulated after ischemia. Two m6A modification modes and two m6A gene modification modes were also identified. m6A gene cluster A (high m6A value group) was positively correlated with acquired immunity, while m6A gene cluster B (low m6A value group) was positively correlated with innate immunity. Similarly, five immune-related hub genes were significantly associated with m6Acore (CD28, IFNG, LTF, LCN2, and MMP9).

Conclusion: The modification of m6A is closely related to the immune microenvironment. The evaluation of individual m6A modification pattern may be helpful for future immunomodulatory therapy of anti-ischemic response.