综合多机器学习和孟德尔随机化发现LTF基因是非特异性眼窝炎症的预后生物标志物。

IF 2.7 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Zixuan Wu, Jinfeng Xu, Yuan Gao, Kang Tan, Xiaolei Yao, Qinghua Peng
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引用次数: 0

摘要

背景:非特异性眼眶炎症(NSOI),也称为特发性眼眶炎症,包括影响眼眶组织的异质免疫介导的疾病,由于缺乏明确的病因而统一。乳转铁蛋白(LTF)是一种铁结合糖蛋白,通过隔离微生物生长所必需的铁来发挥有效的抗菌活性,并具有广谱抗菌、抗病毒和抗真菌特性。方法:使用多重机器学习和WGCNA分析,通过对GEO数据库中GSE58331和GSE105149数据集中的公共deg以及import数据库中的免疫相关基因列表进行交叉分析,确定LTF。GSEA和GSVA用与LTF共表达的基因集进行。为了进一步研究LTF与免疫相关生物过程的相关性,采用CIBERSORT算法和ESTIMATE方法对每个样本的免疫微环境特征进行评估。随后使用GSE105149验证LTF的表达水平。结果:Lasso和SVM-RFE算法确定了28个轮毂基因。富集分析显示,与LTF正相关的基因集在免疫相关通路中富集。在LTF的生物学功能分析中,强调了视网膜稳态、苦味感官知觉和组织稳态。免疫浸润分析表明,浆细胞和B细胞naive与LTF呈正相关(即当LTF表达水平升高时,这些免疫细胞也相应升高),而B细胞记忆、巨噬细胞M2、肥大细胞静息、单核细胞、NK细胞活化、T细胞调节(Tregs)与LTF呈负相关。LTF在鉴别非soi方面具有重要的诊断潜力。结论:本研究确定LTF是与NSOI相关的潜在生物标志物,为其发病机制提供了新的见解,并为跟踪疾病进展提供了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation.

Background: Nonspecific orbital inflammation (NSOI), also known as idiopathic orbital inflammation, comprises a heterogeneous group of immune-mediated disorders affecting orbital tissues, unified by the absence of a defined etiology. Lactotransferrin (LTF), an iron-binding glycoprotein, exerts potent antimicrobial activity by sequestering iron essential for microbial growth, and demonstrates broad-spectrum antibacterial, antiviral, and antifungal properties.

Methods: LTF was identified through the intersection analysis of common DEGs from datasets GSE58331 and GSE105149 from the GEO database, alongside immune-related gene lists from the ImmPort database, using Multiple Machine learning and WGCNA analysis. GSEA and GSVA were conducted with gene sets co-expressed with LTF. To further investigate the correlation between LTF and immune-related biological processes, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate immune microenvironment characteristics of each sample. The expression levels of LTF were subsequently validated using GSE105149.

Results: Lasso and SVM-RFE algorithms pinpointed 28 hub genes. Enrichment analysis revealed that gene sets positively correlated with LTF were enriched in immune-related pathways. For biological function analysis in LTF, retina homeostasis, sensory perception of bitter taste, and tissue homeostasis were emphasized. Immune infiltration analysis indicated that Plasma cells and B cells naive were positively associated (That is, when the expression level of LTF increases, these immune cells also increase accordingly) with LTF, whereas B cells memory, Macrophages M2, Mast cells resting, Monocytes, NK cells activated, T cells regulatory (Tregs) were negatively associated with LTF. LTF demonstrated significant diagnostic potential in differentiating NSOI.

Conclusions: This study identifies LTF as a potential biomarker linked to NSOI, providing insights into its pathogenesis and offering new avenues for tracking disease progression.

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来源期刊
BMC Pharmacology & Toxicology
BMC Pharmacology & Toxicology PHARMACOLOGY & PHARMACYTOXICOLOGY&nb-TOXICOLOGY
CiteScore
4.80
自引率
0.00%
发文量
87
审稿时长
12 weeks
期刊介绍: BMC Pharmacology and Toxicology is an open access, peer-reviewed journal that considers articles on all aspects of chemically defined therapeutic and toxic agents. The journal welcomes submissions from all fields of experimental and clinical pharmacology including clinical trials and toxicology.
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