Identification and Validation of Potential Immune-Related Genes for Endometriosis

IF 2.5 3区医学 Q3 IMMUNOLOGY

American Journal of Reproductive Immunology Pub Date : 2025-05-14 DOI:10.1111/aji.70091

Yi Zhang, Lulu Wu, Wanjing Yuan, Zhen Ren, Li Tang, Jilin Kuang, Lin Li, Yingying Liang

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引用次数: 0

Abstract

Objective

This study aimed to identify and validate potential immune-related genes in endometriosis (Ems) through comprehensive bioinformatics analysis and immunohistochemistry (IHC) verification.

Design

Using data from the GEO database, single-cell RNA sequencing (scRNA) data and traditional bulk RNA sequencing data were analyzed to identify differentially expressed genes related to the immune system. Immunological analysis confirmed alterations in immune cells associated with Ems. Machine learning techniques were employed to identify characteristic immune genes of eutopic and ectopic endometria, which were then validated through IHC experiments.

Main Outcome Measures

Immunological analysis revealed distinct variations in the enrichment of macrophages and NK cells in Ems. Functional enrichment analysis revealed a decrease in NK cell toxicity in both ectopic and eutopic endometria, activation of M2 macrophages in the ectopic endometrium supporting the survival of ectopic endothelial cells, and the presence of lipid antigens and signaling between immune cells facilitating the development of Ems. Machine learning algorithms revealed that TGFBR1 is a characteristic immune gene associated with the eutopic endometrium and that GIMAP4 is associated with the ectopic endometrium; this conclusion was also confirmed by IHC.

Results

Macrophage and NK cell enrichment was significantly increased in endometria from patients with Ems. TGFBR1 is a characteristic immune gene associated with the eutopic endometrium, whereas GIMAP4 is associated with the ectopic endometrium.

Conclusion

These findings provide new insights for the clinical diagnosis and selection of immune-related targets for Ems.

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子宫内膜异位症潜在免疫相关基因的鉴定和验证

目的通过综合生物信息学分析和免疫组化（IHC）验证，鉴定和验证子宫内膜异位症（Ems）中潜在的免疫相关基因。利用GEO数据库的数据，分析单细胞RNA测序（scRNA）数据和传统的批量RNA测序数据，以鉴定与免疫系统相关的差异表达基因。免疫学分析证实了与Ems相关的免疫细胞改变。利用机器学习技术识别异位和异位子宫内膜的特征免疫基因，然后通过免疫组化实验验证。免疫学分析显示，em中巨噬细胞和NK细胞的富集有明显的变化。功能富集分析显示，异位和异位子宫内膜中NK细胞毒性降低，M2巨噬细胞在异位子宫内膜中的活化支持异位内皮细胞的存活，以及免疫细胞之间脂质抗原和信号传导的存在促进了Ems的发展。机器学习算法显示TGFBR1是与异位子宫内膜相关的特征性免疫基因，GIMAP4与异位子宫内膜相关；免疫组化也证实了这一结论。结果Ems患者子宫内膜中巨噬细胞和NK细胞的富集明显增加。TGFBR1是与异位子宫内膜相关的特征性免疫基因，而GIMAP4与异位子宫内膜相关。结论本研究结果为临床诊断和选择Ems的免疫相关靶点提供了新的思路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

American Journal of Reproductive Immunology 医学-免疫学

CiteScore

6.20

自引率

5.60%

发文量

314

审稿时长

2 months

期刊介绍： The American Journal of Reproductive Immunology is an international journal devoted to the presentation of current information in all areas relating to Reproductive Immunology. The journal is directed toward both the basic scientist and the clinician, covering the whole process of reproduction as affected by immunological processes. The journal covers a variety of subspecialty topics, including fertility immunology, pregnancy immunology, immunogenetics, mucosal immunology, immunocontraception, endometriosis, abortion, tumor immunology of the reproductive tract, autoantibodies, infectious disease of the reproductive tract, and technical news.