IRF8在非特异性眼眶炎症中的作用:生物信息学和机器学习的综合分析。

IF 2.9 Q1 OPHTHALMOLOGY
Zixuan Wu, Jinfeng Xu, Yi Hu, Xin Peng, Zheyuan Zhang, Xiaolei Yao, Qinghua Peng
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引用次数: 0

摘要

背景:非特异性眼眶炎(NSOI)是一种以眼眶内多形性淋巴细胞浸润为特征的持续性特发性增生性炎症。转录因子干扰素调节因子8(IRF8)是IRF蛋白家族的组成部分,最初被认为是髓系细胞系承诺和分化的关键因素。作为先天性免疫受体信号传导的核心调节因子,IRF8 在造血细胞发育过程中发挥着多种功能。然而,IRF8产生的复杂机制仍有待阐明,其作为NSOI生物标志物的潜在作用也有待解决:使用 The Lasso 回归和 SVM-RFE 分析方法,从 GEO 的 GSE58331 和 GSE105149 的常见 DEGs 交集分析中以及 ImmPort 数据库的免疫相关基因列表中提取 IRF8。我们对与IRF8共表达的基因集进行了GSEA和GSVA,观察到与IRF8正相关的基因集在免疫相关通路中富集。为了进一步探讨IRF8与免疫相关生物学过程的相关性,我们采用了CIBERSORT算法和ESTIMATE方法来评估每个样本的TME特征,结果证实IRF8的高表达可能导致免疫细胞的高浸润。最后,利用GSE58331确认了IRF8的表达水平:结果:在 314 个差异表达基因(DEGs)中,一些 DEGs 存在显著差异。通过LASSO和SVM-RFE算法,我们得到了15个中心基因。在 IRF8 的生物功能分析中,重点分析了白细胞介导的免疫、白细胞的细胞间粘附、免疫系统过程的负调控。B 细胞幼稚型、巨噬细胞 M0、巨噬细胞 M1、T 细胞 CD4 记忆激活型、T 细胞 CD4 记忆静息型、T 细胞 CD4 幼稚型和 T 细胞 gamma delta 与 IRF8 呈正相关。而静息的肥大细胞、单核细胞、激活的 NK 细胞、浆细胞、CD8 T 细胞和调节性 T 细胞(Tregs)则与 IRF8 呈负相关。IRF8在区分NSOI方面具有良好的诊断能力:本研究发现了与 NSOI 相关的 IRF8。结论:这项研究发现了与 NSOI 相关的 IRF8,IRF8 为 NSOI 的潜在新生物标记物和追踪其进展提供了启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The roles of IRF8 in nonspecific orbital inflammation: an integrated analysis by bioinformatics and machine learning.

Background: Nonspecific Orbital Inflammation (NSOI) represents a persistent and idiopathic proliferative inflammatory disorder, characterized by polymorphous lymphoid infiltration within the orbit. The transcription factor Interferon Regulatory Factor 8 (IRF8), integral to the IRF protein family, was initially identified as a pivotal element for the commitment and differentiation of myeloid cell lineage. Serving as a central regulator of innate immune receptor signaling, IRF8 orchestrates a myriad of functions in hematopoietic cell development. However, the intricate mechanisms underlying IRF8 production remain to be elucidated, and its potential role as a biomarker for NSOI is yet to be resolved.

Methods: IRF8 was extracted from the intersection analysis of common DEGs of GSE58331 and GSE105149 from the GEO and immune- related gene lists in the ImmPort database using The Lasso regression and SVM-RFE analysis. We performed GSEA and GSVA with gene sets coexpressed with IRF8, and observed that gene sets positively related to IRF8 were enriched in immune-related pathways. To further explore the correlation between IRF8 and immune-related biological process, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate TME characteristics of each sample and confirmed that high IRF8 expression might give rise to high immune cell infiltration. Finally, the GSE58331 was utilized to confirm the levels of expression of IRF8.

Results: Among the 314 differentially expressed genes (DEGs), some DEGs were found to be significantly different. With LASSO and SVM-RFE algorithms, we obtained 15 hub genes. For biological function analysis in IRF8, leukocyte mediated immunity, leukocyte cell-cell adhesion, negative regulation of immune system process were emphasized. B cells naive, Macrophages M0, Macrophages M1, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD4 naive, and T cells gamma delta were shown to be positively associated with IRF8. While, Mast cells resting, Monocytes, NK cells activated, Plasma cells, T cells CD8, and T cells regulatory (Tregs) were shown to be negatively linked with IRF8. The diagnostic ability of the IRF8 in differentiating NSOI exhibited a good value.

Conclusions: This study discovered IRF8 that are linked to NSOI. IRF8 shed light on potential new biomarkers for NSOI and tracking its progression.

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来源期刊
CiteScore
3.80
自引率
3.40%
发文量
39
审稿时长
13 weeks
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